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Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

types of research papers in social sciences

Anol Bhattacherjee, University of South Florida

Copyright Year: 2019

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

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Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance... read more

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

types of research papers in social sciences

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize this literature, and how to write a literature review.

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project... read more

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science... read more

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix.... read more

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the... read more

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional... read more

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have liked to see more practical examples. For instance, what type of problem is unresearchable? (p. 24)

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so... read more

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version of this text that I plan to produce.

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how... read more

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise... read more

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading assignments (as he provides in his sample syllabus), this book could be a great base for further usage.

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text says it is written for a doctoral and graduate students.

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be... read more

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long... read more

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on quantitative research. Towards the end, there are three chapters with a qualitative focus, but they are brief.

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in... read more

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to... read more

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The... read more

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as... read more

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory... read more

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science,... read more

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic understanding of social science research.

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and... read more

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The... read more

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social... read more

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short... read more

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later... read more

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text... read more

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and... read more

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could... read more

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research... read more

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient... read more

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types... read more

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on... read more

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract... read more

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often... read more

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including... read more

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

Table of Contents

About the book.

Part I. Main Body

  • Science and scientific research
  • Thinking like a researcher
  • The research process
  • Theories in scientific research
  • Research design
  • Measurement of constructs
  • Scale reliability and validity
  • Survey research
  • Experimental research
  • Case research
  • Interpretive research
  • Qualitative analysis
  • Quantitative analysis: Descriptive statistics
  • Quantitative analysis: Inferential statistics
  • Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline,  MIS Quarterly  and  Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of  MIS Quarterly  for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at  http://ab2020.weebly.com .

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Reference management. Clean and simple.

Types of research papers

types of research papers in social sciences

Analytical research paper

Argumentative or persuasive paper, definition paper, compare and contrast paper, cause and effect paper, interpretative paper, experimental research paper, survey research paper, frequently asked questions about the different types of research papers, related articles.

There are multiple different types of research papers. It is important to know which type of research paper is required for your assignment, as each type of research paper requires different preparation. Below is a list of the most common types of research papers.

➡️ Read more:  What is a research paper?

In an analytical research paper you:

  • pose a question
  • collect relevant data from other researchers
  • analyze their different viewpoints

You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic. It is important to stay neutral and not show your own negative or positive position on the matter.

The argumentative paper presents two sides of a controversial issue in one paper. It is aimed at getting the reader on the side of your point of view.

You should include and cite findings and arguments of different researchers on both sides of the issue, but then favor one side over the other and try to persuade the reader of your side. Your arguments should not be too emotional though, they still need to be supported with logical facts and statistical data.

Tip: Avoid expressing too much emotion in a persuasive paper.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information. You should include facts from a variety of sources, but leave those facts unanalyzed.

Compare and contrast papers are used to analyze the difference between two:

Make sure to sufficiently describe both sides in the paper, and then move on to comparing and contrasting both thesis and supporting one.

Cause and effect papers are usually the first types of research papers that high school and college students write. They trace probable or expected results from a specific action and answer the main questions "Why?" and "What?", which reflect effects and causes.

In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

An interpretative paper requires you to use knowledge that you have gained from a particular case study, for example a legal situation in law studies. You need to write the paper based on an established theoretical framework and use valid supporting data to back up your statement and conclusion.

This type of research paper basically describes a particular experiment in detail. It is common in fields like:

Experiments are aimed to explain a certain outcome or phenomenon with certain actions. You need to describe your experiment with supporting data and then analyze it sufficiently.

This research paper demands the conduction of a survey that includes asking questions to respondents. The conductor of the survey then collects all the information from the survey and analyzes it to present it in the research paper.

➡️ Ready to start your research paper? Take a look at our guide on how to start a research paper .

In an analytical research paper, you pose a question and then collect relevant data from other researchers to analyze their different viewpoints. You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information.

Cause and effect papers are usually the first types of research papers that high school and college students are confronted with. The answer questions like "Why?" and "What?", which reflect effects and causes. In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

This type of research paper describes a particular experiment in detail. It is common in fields like biology, chemistry or physics. Experiments are aimed to explain a certain outcome or phenomenon with certain actions.

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Literature Reviews in the Social Sciences: Home

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Literature Reviews in the Social Sciences

  This guide is designed to help you as you get started on a literature review in the social sciences.  It contains search tips, advice on where to look for sources, and information on how to organize and evaluate the sources you find.   

Doing a Literature Review

What's a Literature Review?

A literature review is the systematic written analysis of previously published research on a specific topic or subject. A literature review is not merely a summary of another scholar's articles or books. Instead, it provides a contextual analysis of the data, ideas, or theoretical concepts presented in the article, book, or other publication.

Why is a literature review important?

All scholars recognize the importance of the literature review. It provides the foundation for all scholarly research papers, theses, and dissertations. You can't write intelligently about a subject if you are unfamiliar with the existing literature. Therefore, the literature review is meant to showcase what has already been discussed or discovered in your topical area.

What types of resources should be used for a literature review?

 A literature review should be written using "credible" academic sources of information. This means using peer-reviewed, scholarly articles, books, and other publications in your subject area. You should avoid using popular magazines, unpublished works, blogs, or other resources deemed non-scholarly.

What other things should I consider while reading the source material?

Take careful notes of important ideas, concepts, or facts you find that are relevant to your overall topic or thesis. Most importantly, keep track of all the sources used. This will keep you from needing to relocate them later. If your paper is large in scope, use electronic bibliographic tools such as Endnote or RefWorks to keep track of all your citations while you write.

What about writing the literature review itself?

When you are prepared to begin writing your literature review, you should not simply summarize the articles and books you find. You should carefully consider the research and the author's interpretation of the subject matter. Then show how their research relates to your specific topic, from your unique point of view.

Annual Reviews / Dissertations & Theses

Many scholarly journals, dissertations, and theses also publish long and extremely detailed literature reviews. 

The Annual Reviews series of publications offer articles that analyze the most significant scholarly research published within the preceding year. Written by leading scholars and academics, the articles cover over 40 different subject disciplines in the social and hard sciences.

To search directly for a literature review, go to a library database and search for:

    "literature review" AND [your research topic] .

  • Annual Reviews This link opens in a new window Annual Reviews offers comprehensive, timely collections of critical reviews written by leading scientists. Annual Reviews volumes are published each year for 29 focused disciplines within the Biomedical, Physical, and Social Sciences.
  • Dissertations & Theses Global This link opens in a new window Dissertations and Theses Global contains indexes, dissertations and some theses. Full-text is available for many dissertations and theses, including those from NYU.

Books on Writing Literature Reviews

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Sage Research Methods - Videos on Doing Literature Reviews

  • Sage Research Methods - Literature Reviews Professor Eric Jensen and Dr. Charles Laurie explain how to write a literature review, and why researchers need to do so. Literature reviews can be stand-alone research or part of a larger project. They communicate the state of academic knowledge on a given topic, specifically detailing what is still unknown.
  • How to Conduct an Effective Literature Review Claire White, an Associate professor from California State University Northridge, explains how to conduct an effective literature review using a literature review sketch.
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Organizing Your Social Sciences Research Paper: Writing a Case Study

  • Purpose of Guide
  • Design Flaws to Avoid
  • Independent and Dependent Variables
  • Glossary of Research Terms
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
  • Extending the Timeliness of a Topic Idea
  • Academic Writing Style
  • Choosing a Title
  • Making an Outline
  • Paragraph Development
  • Executive Summary
  • The C.A.R.S. Model
  • Background Information
  • The Research Problem/Question
  • Theoretical Framework
  • Citation Tracking
  • Content Alert Services
  • Evaluating Sources
  • Reading Research Effectively
  • Primary Sources
  • Secondary Sources
  • Tiertiary Sources
  • What Is Scholarly vs. Popular?
  • Qualitative Methods
  • Quantitative Methods
  • Using Non-Textual Elements
  • Limitations of the Study
  • Common Grammar Mistakes
  • Writing Concisely
  • Avoiding Plagiarism
  • Footnotes or Endnotes?
  • Further Readings
  • Annotated Bibliography
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • Types of Structured Group Activities
  • Group Project Survival Skills
  • Multiple Book Review Essay
  • Reviewing Collected Essays
  • Writing a Case Study
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Research Proposal
  • Bibliography

The term case study refers to both a method of analysis and a specific research design for examining a problem, both of which are used in most circumstances to generalize across populations. This tab focuses on the latter--how to design and organize a research paper in the social sciences that analyzes a specific case.

A case study research paper examines a person, place, event, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or among more than two subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies . Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in this writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a single case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

  • Does the case represent an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
  • Does the case provide important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
  • Does the case challenge and offer a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in practice. A case may offer you an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to the study a case in order to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
  • Does the case provide an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings in order to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
  • Does the case offer a new direction in future research? A case study can be used as a tool for exploratory research that points to a need for further examination of the research problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of Uganda. A case study of how women contribute to saving water in a particular village can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community throughout rural regions of east Africa. The case could also point to the need for scholars to apply feminist theories of work and family to the issue of water conservation.

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work. In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

  • What was I studying? Describe the research problem and describe the subject of analysis you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
  • Why was this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
  • What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the research problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
  • How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

  • Place relevant works in the context of their contribution to understanding the case study being investigated . This would include summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
  • Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to study the research problem and the underlying research questions.
  • Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
  • Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
  • Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
  • Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
  • Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in the context of explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular subject of analysis to study and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that frames your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; c) what were the consequences of the event.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experience he or she has had that provides an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of his/her experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using him or her as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem.

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, cultural, economic, political, etc.], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, why study Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research reveals Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut? How might knowing the suppliers of these trucks from overseas reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should be linked to the findings from the literature review. Be sure to cite any prior studies that helped you determine that the case you chose was appropriate for investigating the research problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is more common to combine a description of the findings with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings It is important to remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations for the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and needs for further research.

The function of your paper's conclusion is to: 1)  restate the main argument supported by the findings from the analysis of your case; 2) clearly state the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place for you to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

  • If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
  • If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
  • Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in and your professor's preferences, the concluding paragraph may contain your final reflections on the evidence presented applied to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were on social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood differently than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis.

Case Studies . Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent knowledge is more valuable than concrete, practical (context-dependent) knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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This book is designed to introduce students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This text will introduce you to the fascinating and important study of the methods of inquiry in the Social Sciences. You will learn both the logic behind – and the procedures for – a wide variety of research methods, including correlational and experimental designs. If you are the curious type, and if you like to think rationally, I believe you will enjoy this course.

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Data science can be valuable tool for analyzing social determinants of health, uncovering causes of health inequities

by NYU Tandon School of Engineering

Data science can be a valuable tool for analyzing social determinants of health and uncover causes of health inequities

Data science methods can help overcome challenges in measuring and analyzing social determinants of health (SDoH), according to a paper published in The Lancet Digital Health , helping mitigate the root causes of health inequities that are not fully addressed through health care spending or lifestyle choices.

The paper came out of the NYU-Moi Data Science Social Determinants Training Program (DSSD), a collaboration between New York University, the NYU Grossman School of Medicine, Moi University, and Brown University. Through interdisciplinary training at NYU, DSSD aims to build a cohort of data science trainees from Kenya.

Rumi Chunara, associate professor at both NYU Tandon School of Engineering and NYU School of Global Public Health, is a DSSD Program Principal Investigator and wrote the paper with colleagues from DSSD's collaborating institutions and the NIH.

SDoH are the diverse conditions in people's environments that affect their health, such as racism and climate. These conditions can negatively impact quality of life and health outcomes by shaping economic policies, social norms , and other environmental factors that consequently influence individual behaviors.

According to the researchers, the three main challenges—and potential solutions—in studying SDoH are:

  • SDoH data is hard to measure, especially at multiple levels like individual, community, and national, with racism being one notable example. Data science methods can help capture social determinants of health not easily quantified, like racism or climate impacts, from unstructured data sources including social media , notes, or imagery. For example, natural language processing can extract housing insecurity from medical notes, and deep learning can parse environmental factors from satellite imagery. These unstructured sources provide diverse insights compared to tabular, structured data, but also may contain biases requiring careful inspection. Incorporating social determinants from flexible, unstructured sources into analyses can better capture the heterogeneity of health effects across different populations.
  • SDoH impact health through complex, nonlinear pathways over time. Social factors like income or education are farther removed from health outcomes than medical factors. They affect health through complicated chains of intermediate factors that can also flow back to influence the social factors. For instance, income provides resources for healthy behaviors that improve health, while poor health hinders income. Advanced modeling techniques like machine learning can handle these tangled relationships between many variables better than simpler statistical models. Models that simulate individuals' behaviors and interactions allow studying how health patterns emerge from social factors. This captures the real-world complexity traditional models may miss between broad social conditions and individual health.
  • It takes a long time, sometimes decades, to observe how SDoH ultimately affect health outcomes . For example, lack of fresh produce and recreation options leads to poor nutrition, but chronic diseases take decades to develop. Longitudinal data over such time spans is rare, especially globally. Collecting representative surveys is resource-intensive. But novel digital data like mobile usage, purchases, or satellite imagery can provide longitudinal views at granular place and time scales. With proper privacy protections and population considerations, these new data managed with data science methods can help model social determinants ' long-term health impacts.

Fully leveraging data science for SDoH research requires diverse experts working collaboratively across disciplines, according to the researchers. Training more data scientists, especially from underrepresented backgrounds, in SDoH is pivotal. Developing local data science skills grounded in community knowledge and values is also vital.

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Structural efficiency evaluation of humanities and social sciences research based on MEA model: a case of universities in Jiangsu, China

  • Original Paper
  • Published: 25 March 2024
  • Volume 4 , article number  83 , ( 2024 )

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  • Zhen Zhen 2 &
  • Rong Cai 2  

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Understanding the research efficiency is crucial for optimizing the allocation of research resources among universities and different departments, improving the innovation capability of universities, and accomplishing high-quality development. This work applies the multi-directional efficiency analysis to the data between 2015 and 2020 from 46 universities in the Jiangsu Province of China. We evaluate the research efficiency of humanities and social sciences. We also compare the research efficiency differences between the capital and non-capital cities. Results show that the overall efficiency of humanities and social sciences research in universities in Jiangsu has declined over the years. The insufficient number of published monographs and papers in international journals is the main reason for the relatively low efficiency of universities. A clear gap in structural efficiency exists between the universities in the capital and non-capital cities. Therefore, we suggest the following methods for universities to improve their structural efficiency of the humanities and social sciences research: strengthen international exchanges and cooperation, increase the level of internationalization, optimize the research evaluation mechanism, develop incentives for research, boost the interdisciplinary cooperation, build the dynamic adjustment mechanism, and share resources and promote the partnerships among universities.

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The data used in this study are all from the “Compilation Statistics of Social Science of Higher Education Institutions in Jiangsu Province,” with a time span between 2015 and 2020.

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This paper was supported by Postgraduate Education Reform Project of Nanjing University of Finance and Economics (Y21004), Higher Education Reform and Development Project of Nanjing University of Finance and Economics (GJGF202010).

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Ouya and Zhenzhen. The first draft of the manuscript was written by Ouya and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Ou, Y., Zhen, Z. & Cai, R. Structural efficiency evaluation of humanities and social sciences research based on MEA model: a case of universities in Jiangsu, China. SN Soc Sci 4 , 83 (2024). https://doi.org/10.1007/s43545-024-00880-2

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Organizing Your Social Sciences Research Paper: Quantitative Methods

  • Purpose of Guide
  • Writing a Research Proposal
  • Design Flaws to Avoid
  • Independent and Dependent Variables
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs may or may not establish causality. Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

  • The data is usually gathered using structured research instruments.
  • The results are based on larger sample sizes that are representative of the population.
  • The research study can usually be replicated or repeated, given its high reliability.
  • Researcher has a clearly defined research question to which objective answers are sought.
  • All aspects of the study are carefully designed before data is collected.
  • Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
  • Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
  • Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods . Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

  • Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
  • Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
  • Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

  • Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
  • Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
  • Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

  • Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
  • Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
  • Applying well establshed standards means that the research can be replicated, and then analyzed and compared with similar studies;
  • You can summarize vast sources of information and make comparisons across categories and over time; and,
  • Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantiative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

  • Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
  • Uses a static and rigid approach and so employs an inflexible process of discovery;
  • The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
  • Results provide less detail on behavior, attitudes, and motivation;
  • Researcher may collect a much narrower and sometimes superficial dataset;
  • Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
  • The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
  • Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

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Statistics & Data Research Guide

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

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Abstract: In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training data choices, we identified several crucial design lessons. For example, we demonstrate that for large-scale multimodal pre-training using a careful mix of image-caption, interleaved image-text, and text-only data is crucial for achieving state-of-the-art (SOTA) few-shot results across multiple benchmarks, compared to other published pre-training results. Further, we show that the image encoder together with image resolution and the image token count has substantial impact, while the vision-language connector design is of comparatively negligible importance. By scaling up the presented recipe, we build MM1, a family of multimodal models up to 30B parameters, including both dense models and mixture-of-experts (MoE) variants, that are SOTA in pre-training metrics and achieve competitive performance after supervised fine-tuning on a range of established multimodal benchmarks. Thanks to large-scale pre-training, MM1 enjoys appealing properties such as enhanced in-context learning, and multi-image reasoning, enabling few-shot chain-of-thought prompting.

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Organizing Your Social Sciences Research Paper

  • 4. The Introduction
  • Purpose of Guide
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  • Narrowing a Topic Idea
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  • Scholarly vs. Popular Publications
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The introduction leads the reader from a general subject area to a particular topic of inquiry. It establishes the scope, context, and significance of the research being conducted by summarizing current understanding and background information about the topic, stating the purpose of the work in the form of the research problem supported by a hypothesis or a set of questions, explaining briefly the methodological approach used to examine the research problem, highlighting the potential outcomes your study can reveal, and outlining the remaining structure and organization of the paper.

Key Elements of the Research Proposal. Prepared under the direction of the Superintendent and by the 2010 Curriculum Design and Writing Team. Baltimore County Public Schools.

Importance of a Good Introduction

Think of the introduction as a mental road map that must answer for the reader these four questions:

  • What was I studying?
  • Why was this topic important to investigate?
  • What did we know about this topic before I did this study?
  • How will this study advance new knowledge or new ways of understanding?

According to Reyes, there are three overarching goals of a good introduction: 1) ensure that you summarize prior studies about the topic in a manner that lays a foundation for understanding the research problem; 2) explain how your study specifically addresses gaps in the literature, insufficient consideration of the topic, or other deficiency in the literature; and, 3) note the broader theoretical, empirical, and/or policy contributions and implications of your research.

A well-written introduction is important because, quite simply, you never get a second chance to make a good first impression. The opening paragraphs of your paper will provide your readers with their initial impressions about the logic of your argument, your writing style, the overall quality of your research, and, ultimately, the validity of your findings and conclusions. A vague, disorganized, or error-filled introduction will create a negative impression, whereas, a concise, engaging, and well-written introduction will lead your readers to think highly of your analytical skills, your writing style, and your research approach. All introductions should conclude with a brief paragraph that describes the organization of the rest of the paper.

Hirano, Eliana. “Research Article Introductions in English for Specific Purposes: A Comparison between Brazilian, Portuguese, and English.” English for Specific Purposes 28 (October 2009): 240-250; Samraj, B. “Introductions in Research Articles: Variations Across Disciplines.” English for Specific Purposes 21 (2002): 1–17; Introductions. The Writing Center. University of North Carolina; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide. Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70; Reyes, Victoria. Demystifying the Journal Article. Inside Higher Education.

Structure and Writing Style

I.  Structure and Approach

The introduction is the broad beginning of the paper that answers three important questions for the reader:

  • What is this?
  • Why should I read it?
  • What do you want me to think about / consider doing / react to?

Think of the structure of the introduction as an inverted triangle of information that lays a foundation for understanding the research problem. Organize the information so as to present the more general aspects of the topic early in the introduction, then narrow your analysis to more specific topical information that provides context, finally arriving at your research problem and the rationale for studying it [often written as a series of key questions to be addressed or framed as a hypothesis or set of assumptions to be tested] and, whenever possible, a description of the potential outcomes your study can reveal.

These are general phases associated with writing an introduction: 1.  Establish an area to research by:

  • Highlighting the importance of the topic, and/or
  • Making general statements about the topic, and/or
  • Presenting an overview on current research on the subject.

2.  Identify a research niche by:

  • Opposing an existing assumption, and/or
  • Revealing a gap in existing research, and/or
  • Formulating a research question or problem, and/or
  • Continuing a disciplinary tradition.

3.  Place your research within the research niche by:

  • Stating the intent of your study,
  • Outlining the key characteristics of your study,
  • Describing important results, and
  • Giving a brief overview of the structure of the paper.

NOTE:   It is often useful to review the introduction late in the writing process. This is appropriate because outcomes are unknown until you've completed the study. After you complete writing the body of the paper, go back and review introductory descriptions of the structure of the paper, the method of data gathering, the reporting and analysis of results, and the conclusion. Reviewing and, if necessary, rewriting the introduction ensures that it correctly matches the overall structure of your final paper.

II.  Delimitations of the Study

Delimitations refer to those characteristics that limit the scope and define the conceptual boundaries of your research . This is determined by the conscious exclusionary and inclusionary decisions you make about how to investigate the research problem. In other words, not only should you tell the reader what it is you are studying and why, but you must also acknowledge why you rejected alternative approaches that could have been used to examine the topic.

Obviously, the first limiting step was the choice of research problem itself. However, implicit are other, related problems that could have been chosen but were rejected. These should be noted in the conclusion of your introduction. For example, a delimitating statement could read, "Although many factors can be understood to impact the likelihood young people will vote, this study will focus on socioeconomic factors related to the need to work full-time while in school." The point is not to document every possible delimiting factor, but to highlight why previously researched issues related to the topic were not addressed.

Examples of delimitating choices would be:

  • The key aims and objectives of your study,
  • The research questions that you address,
  • The variables of interest [i.e., the various factors and features of the phenomenon being studied],
  • The method(s) of investigation,
  • The time period your study covers, and
  • Any relevant alternative theoretical frameworks that could have been adopted.

Review each of these decisions. Not only do you clearly establish what you intend to accomplish in your research, but you should also include a declaration of what the study does not intend to cover. In the latter case, your exclusionary decisions should be based upon criteria understood as, "not interesting"; "not directly relevant"; “too problematic because..."; "not feasible," and the like. Make this reasoning explicit!

NOTE:   Delimitations refer to the initial choices made about the broader, overall design of your study and should not be confused with documenting the limitations of your study discovered after the research has been completed.

ANOTHER NOTE : Do not view delimitating statements as admitting to an inherent failing or shortcoming in your research. They are an accepted element of academic writing intended to keep the reader focused on the research problem by explicitly defining the conceptual boundaries and scope of your study. It addresses any critical questions in the reader's mind of, "Why the hell didn't the author examine this?"

III.  The Narrative Flow

Issues to keep in mind that will help the narrative flow in your introduction :

  • Your introduction should clearly identify the subject area of interest . A simple strategy to follow is to use key words from your title in the first few sentences of the introduction. This will help focus the introduction on the topic at the appropriate level and ensures that you get to the subject matter quickly without losing focus, or discussing information that is too general.
  • Establish context by providing a brief and balanced review of the pertinent published literature that is available on the subject. The key is to summarize for the reader what is known about the specific research problem before you did your analysis. This part of your introduction should not represent a comprehensive literature review--that comes next. It consists of a general review of the important, foundational research literature [with citations] that establishes a foundation for understanding key elements of the research problem. See the drop-down menu under this tab for " Background Information " regarding types of contexts.
  • Clearly state the hypothesis that you investigated . When you are first learning to write in this format it is okay, and actually preferable, to use a past statement like, "The purpose of this study was to...." or "We investigated three possible mechanisms to explain the...."
  • Why did you choose this kind of research study or design? Provide a clear statement of the rationale for your approach to the problem studied. This will usually follow your statement of purpose in the last paragraph of the introduction.

IV.  Engaging the Reader

A research problem in the social sciences can come across as dry and uninteresting to anyone unfamiliar with the topic . Therefore, one of the goals of your introduction is to make readers want to read your paper. Here are several strategies you can use to grab the reader's attention:

  • Open with a compelling story . Almost all research problems in the social sciences, no matter how obscure or esoteric , are really about the lives of people. Telling a story that humanizes an issue can help illuminate the significance of the problem and help the reader empathize with those affected by the condition being studied.
  • Include a strong quotation or a vivid, perhaps unexpected, anecdote . During your review of the literature, make note of any quotes or anecdotes that grab your attention because they can used in your introduction to highlight the research problem in a captivating way.
  • Pose a provocative or thought-provoking question . Your research problem should be framed by a set of questions to be addressed or hypotheses to be tested. However, a provocative question can be presented in the beginning of your introduction that challenges an existing assumption or compels the reader to consider an alternative viewpoint that helps establish the significance of your study. 
  • Describe a puzzling scenario or incongruity . This involves highlighting an interesting quandary concerning the research problem or describing contradictory findings from prior studies about a topic. Posing what is essentially an unresolved intellectual riddle about the problem can engage the reader's interest in the study.
  • Cite a stirring example or case study that illustrates why the research problem is important . Draw upon the findings of others to demonstrate the significance of the problem and to describe how your study builds upon or offers alternatives ways of investigating this prior research.

NOTE:   It is important that you choose only one of the suggested strategies for engaging your readers. This avoids giving an impression that your paper is more flash than substance and does not distract from the substance of your study.

Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. University College Writing Centre. University of Toronto; Introduction. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Introductions. The Writing Center. University of North Carolina; Introductions. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Introductions, Body Paragraphs, and Conclusions for an Argument Paper. The Writing Lab and The OWL. Purdue University; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide . Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70; Resources for Writers: Introduction Strategies. Program in Writing and Humanistic Studies. Massachusetts Institute of Technology; Sharpling, Gerald. Writing an Introduction. Centre for Applied Linguistics, University of Warwick; Samraj, B. “Introductions in Research Articles: Variations Across Disciplines.” English for Specific Purposes 21 (2002): 1–17; Swales, John and Christine B. Feak. Academic Writing for Graduate Students: Essential Skills and Tasks . 2nd edition. Ann Arbor, MI: University of Michigan Press, 2004 ; Writing Your Introduction. Department of English Writing Guide. George Mason University.

Writing Tip

Avoid the "Dictionary" Introduction

Giving the dictionary definition of words related to the research problem may appear appropriate because it is important to define specific terminology that readers may be unfamiliar with. However, anyone can look a word up in the dictionary and a general dictionary is not a particularly authoritative source because it doesn't take into account the context of your topic and doesn't offer particularly detailed information. Also, placed in the context of a particular discipline, a term or concept may have a different meaning than what is found in a general dictionary. If you feel that you must seek out an authoritative definition, use a subject specific dictionary or encyclopedia [e.g., if you are a sociology student, search for dictionaries of sociology]. A good database for obtaining definitive definitions of concepts or terms is Credo Reference .

Saba, Robert. The College Research Paper. Florida International University; Introductions. The Writing Center. University of North Carolina.

Another Writing Tip

When Do I Begin?

A common question asked at the start of any paper is, "Where should I begin?" An equally important question to ask yourself is, "When do I begin?" Research problems in the social sciences rarely rest in isolation from history. Therefore, it is important to lay a foundation for understanding the historical context underpinning the research problem. However, this information should be brief and succinct and begin at a point in time that illustrates the study's overall importance. For example, a study that investigates coffee cultivation and export in West Africa as a key stimulus for local economic growth needs to describe the beginning of exporting coffee in the region and establishing why economic growth is important. You do not need to give a long historical explanation about coffee exports in Africa. If a research problem requires a substantial exploration of the historical context, do this in the literature review section. In your introduction, make note of this as part of the "roadmap" [see below] that you use to describe the organization of your paper.

Introductions. The Writing Center. University of North Carolina; “Writing Introductions.” In Good Essay Writing: A Social Sciences Guide . Peter Redman. 4th edition. (London: Sage, 2011), pp. 63-70.

Yet Another Writing Tip

Always End with a Roadmap

The final paragraph or sentences of your introduction should forecast your main arguments and conclusions and provide a brief description of the rest of the paper [the "roadmap"] that let's the reader know where you are going and what to expect. A roadmap is important because it helps the reader place the research problem within the context of their own perspectives about the topic. In addition, concluding your introduction with an explicit roadmap tells the reader that you have a clear understanding of the structural purpose of your paper. In this way, the roadmap acts as a type of promise to yourself and to your readers that you will follow a consistent and coherent approach to addressing the topic of inquiry. Refer to it often to help keep your writing focused and organized.

Cassuto, Leonard. “On the Dissertation: How to Write the Introduction.” The Chronicle of Higher Education , May 28, 2018; Radich, Michael. A Student's Guide to Writing in East Asian Studies . (Cambridge, MA: Harvard University Writing n. d.), pp. 35-37.

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  • Published: 21 March 2024

Expert review of the science underlying nature-based climate solutions

  • B. Buma   ORCID: orcid.org/0000-0003-2402-7737 1 , 2   na1 ,
  • D. R. Gordon   ORCID: orcid.org/0000-0001-6398-2345 1 , 3   na1 ,
  • K. M. Kleisner 1 ,
  • A. Bartuska 1 , 4 ,
  • A. Bidlack 5 ,
  • R. DeFries   ORCID: orcid.org/0000-0002-3332-4621 6 ,
  • P. Ellis   ORCID: orcid.org/0000-0001-7933-8298 7 ,
  • P. Friedlingstein   ORCID: orcid.org/0000-0003-3309-4739 8 , 9 ,
  • S. Metzger 10   nAff15   nAff16 ,
  • G. Morgan 11 ,
  • K. Novick   ORCID: orcid.org/0000-0002-8431-0879 12 ,
  • J. N. Sanchirico 13 ,
  • J. R. Collins   ORCID: orcid.org/0000-0002-5705-9682 1 , 14 ,
  • A. J. Eagle   ORCID: orcid.org/0000-0003-0841-2379 1 ,
  • R. Fujita 1 ,
  • E. Holst 1 ,
  • J. M. Lavallee   ORCID: orcid.org/0000-0002-3028-7087 1 ,
  • R. N. Lubowski 1   nAff17 ,
  • C. Melikov 1   nAff18 ,
  • L. A. Moore   ORCID: orcid.org/0000-0003-0239-6080 1   nAff19 ,
  • E. E. Oldfield   ORCID: orcid.org/0000-0002-6181-1267 1 ,
  • J. Paltseva 1   nAff20 ,
  • A. M. Raffeld   ORCID: orcid.org/0000-0002-5036-6460 1 ,
  • N. A. Randazzo 1   nAff21   nAff22 ,
  • C. Schneider 1 ,
  • N. Uludere Aragon 1   nAff23 &
  • S. P. Hamburg 1  

Nature Climate Change ( 2024 ) Cite this article

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  • Climate-change ecology
  • Climate-change mitigation
  • Environmental impact

Viable nature-based climate solutions (NbCS) are needed to achieve climate goals expressed in international agreements like the Paris Accord. Many NbCS pathways have strong scientific foundations and can deliver meaningful climate benefits but effective mitigation is undermined by pathways with less scientific certainty. Here we couple an extensive literature review with an expert elicitation on 43 pathways and find that at present the most used pathways, such as tropical forest conservation, have a solid scientific basis for mitigation. However, the experts suggested that some pathways, many with carbon credit eligibility and market activity, remain uncertain in terms of their climate mitigation efficacy. Sources of uncertainty include incomplete GHG measurement and accounting. We recommend focusing on resolving those uncertainties before broadly scaling implementation of those pathways in quantitative emission or sequestration mitigation plans. If appropriate, those pathways should be supported for their cobenefits, such as biodiversity and food security.

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Nature-based climate solutions (NbCS) are conservation, restoration and improved management strategies (pathways) in natural and working ecosystems with the primary motivation to mitigate GHG emissions and remove CO 2 from the atmosphere 1 (similar to ecosystem-based mitigation 2 ). GHG mitigation through ecosystem stewardship is integral to meeting global climate goals, with the greatest benefit coming from near-term maximization of emission reductions, followed by CO 2 removal 3 . Many countries (for example, Indonesia, China and Colombia) use NbCS to demonstrate progress toward national climate commitments.

The scope of NbCS is narrower than that of nature-based solutions (NbS) which include interventions that prioritize non-climate benefits alongside climate (for example, biodiversity, food provisioning and water quality improvement) 4 . In many cases, GHG mitigation is considered a cobenefit that results from NbS actions focused on these other challenges 2 . In contrast, NbCS are broader than natural climate solutions, which are primarily focused on climate mitigation through conservation, restoration and improved land management, generally not moving ecosystems beyond their unmodified structure, function or composition 5 . NbCS may involve moving systems beyond their original function, for example by cultivating macroalgae in water deeper than their natural habitat.

The promise of NbCS has generated a proliferation of interest in using them in GHG mitigation plans 6 , 7 ; 104 of the 168 signatories to the Paris Accord included nature-based actions as part of their mitigation plans 8 . Success in long-term GHG management requires an accurate accounting of inputs and outputs to the atmosphere at scale, so NbCS credits must have robust, comprehensive and transparent scientific underpinnings 9 . Given the urgency of the climate problem, our goal is to identify NbCS pathways with a sufficient scientific foundation to provide broad confidence in their potential GHG mitigation impact, provide resources for confident implementation and identify priority research areas in more uncertain pathways. Evaluating implementation of mitigation projects is beyond our scope; this effort focuses on understanding the underlying science. The purpose is not evaluating any specific carbon crediting protocol or implementation framework but rather the current state of scientific understanding necessary to provide confidence in any NbCS.

In service of this goal, we first investigated nine biomes (boreal forests, coastal marine (salt marsh, mangrove, seagrass and coral reef), freshwater wetlands, grasslands, open ocean (large marine animal and mesopelagic zone biomass, seabed), peatlands, shrublands, temperate forests and tropical forests) and three cultivation types (agroforestry, croplands and macroalgae aquaculture); these were chosen because of their identified potential scale of global impact. In this context, impact is assessed as net GHG mitigation: the CO 2 sequestered or emissions reduced, for example, discounted by understood simultaneous emissions of other GHG (as when N 2 O is released simultaneously with carbon sequestration in cropland soils). From there, we identified 43 NbCS pathways which have been formally implemented (with or without market action) or informally proposed. We estimated the scale of mitigation impact for each pathway on the basis of this literature and, as a proxy measure of NbCS implementation, determined eligibility and activity under existing carbon crediting protocols. Eligibility means that the pathway is addressed by an existing GHG mitigation protocol; market activity means that credits are actively being bought under those eligibility requirements. We considered pathways across a spectrum from protection to improved management to restoration to manipulated systems, but some boundaries were necessary. We excluded primarily abiotically driven pathways (for example, ocean alkalinity enhancement) or where major land use or land-use trade-offs exist (for example, afforestation) 10 , 11 , 12 . Of the 43 pathways, 79% are at present eligible for carbon crediting (sometimes under several methodologies) and at least 65% of those have been implemented (Supplementary Table 1 ). This review was then appraised by 30 independent scholars (at least three per pathway; a complete review synthesis is given in the Supplementary Data ).

Consolidation of a broad body of scientific knowledge, with inherent variance, requires expert judgement. We used an expert elicitation process 13 , 14 , 15 with ten experts to place each proposed NbCS pathway into one of three readiness categories following their own assessment of the scientific literature, categorized by general sources of potential uncertainty: category 1, sufficient scientific basis to support a high-quality carbon accounting system or to support the development of such a system today; category 2, a >25% chance that focused research and reasonable funding would support development of high-quality carbon accounting (that is, move to category 1) within 5 years; or category 3, a <25% chance of development of high-quality carbon accounting within 5 years (for example, due to measurement challenges, unconstrained leakage, external factors which constrain viability).

If an expert ranked a pathway as category 2, they were also asked to rank general research needs to resolve: leakage/displacement (spillover to other areas), measuring, reporting and verification (the ability to quantify all salient stocks and fluxes), basic mechanisms of action (fundamental science), durability (ability to predict or compensate for uncertainty in timescale of effectiveness due to disturbances, climate change, human activity or other factors), geographic uncertainty (place-to-place variation), scaling potential (ability to estimate impact) and setting of a baseline (ability to estimate additionality over non-action; a counterfactual). To avoid biasing towards a particular a priori framework for evaluation of the scientific literature, reviewers could use their own framework for evaluating the NbCS literature about potential climate impact and so could choose to ignore or add relevant categorizations as well. Any pathway in category 1 would not need fundamental research for implementation; research gaps were considered too extensive for useful guidance on reducing uncertainty in category 3 pathways. Estimates of the global scale of likely potential impact (PgCO 2 e yr −1 ) and cobenefits were also collected from expert elicitors. See Methods and Supplementary Information for the survey instrument.

Four pathways with the highest current carbon market activity and high mitigation potential (tropical and temperate forest conservation and reforestation; Table 1 and Supplementary Data ), were consistently rated as high-confidence pathways in the expert elicitation survey. Other NbCS pathways, especially in the forestry sector, were rated relatively strongly by the experts for both confidence in scientific basis and scale of potential impact, with some spread across the experts (upper right quadrant, Fig. 1 ). Conversely, 13 pathways were consistently marked by experts as currently highly uncertain/low confidence (median score across experts: 2.5–3.0) and placed in category 3 (for example, cropland microbial amendments and coral reef restoration; Supplementary Tables 1 and 2 ). For the full review, including crediting protocols currently used, literature estimates of scale and details of sub-pathways, see Supplementary Data .

figure 1

Pathways in the upper right quadrant have both high confidence in the scientific foundations and the largest potential scale of global impact; pathways in the lower left have the lowest confidence in our present scientific body of knowledge and an estimated smaller potential scale of impact. Designations of carbon credit eligibility under existing protocols and market activity at the present time are noted. Grassland enhanced mineral weathering (EMW) is not shown (mean category rating 2.9) as no scale of impact was estimated. See Supplementary Table 1 for specific pathway data. Bars represent 20th to 80th percentiles of individual estimates, if there was variability in estimates. A small amount of random noise was added to avoid overlap.

The experts assessed 26 pathways as having average confidence scores between 1.5 and 2.4, suggesting the potential for near-term resolution of uncertainties. This categorization arose from either consensus amongst experts on the uncertain potential (for example, boreal forest reforestation consistently rated category 2, with primary concerns about durability) or because experts disagreed, with some ranking category 1 and others category 3 (for example, pasture management). We note that where expert disagreement exists (seen as the spread of responses in Fig. 1 and Supplementary Table 1 ; also see Data availability for link to original data), this suggests caution against overconfidence in statements about these pathways. These results also suggest that confidence may be increased by targeted research on the identified sources of uncertainty (Supplementary Table 3 ).

Sources of uncertainty

Durability and baseline-setting were rated as high sources of uncertainty across all pathways ranked as category 2 by the experts (mean ratings of 3.6 and 3.4 out of 5, respectively; Supplementary Table 3 ). Understanding of mechanisms and geographic spread had the lowest uncertainty ratings (2.1 and 2.3, respectively), showing confidence in the basic science. Different subsets of pathways had different prioritizations, however, suggesting different research needs: forest-centric pathways were most uncertain in their durability and additionality (3.8 and 3.4, respectively), suggesting concerns about long-term climate and disturbance trajectories. Agricultural and grassland systems, however, had higher uncertainty in measurement methods and additionality (3.9 and 3.5 respectively). Although there were concerns about durability from some experts (for example, due to sea-level rise), some coastal blue carbon pathways such as mangrove restoration (mean category ranking: 1.7 (20th to 80th percentile 1.0–2.0)) have higher confidence than others (for example, seagrass restoration: mean category ranking 2.8, 20th to 80th percentile 2.6–3.0)), which are relatively poorly constrained in terms of net radiative forcing potential despite a potentially large carbon impact (seagrass median: 1.60 PgCO 2 e yr −1 ; see Supplementary Data for more scientific literature estimates).

Scale of impact

For those pathways with lower categorization by the expert elicitation (category 2 or 3) at the present time, scale of global impact is a potential heuristic for prioritizing further research. High variability, often two orders of magnitude, was evident in the mean estimated potential PgCO 2 e yr −1 impacts for the different pathways (Fig. 1 and Supplementary Table 2 ) and the review of the literature found even larger ranges produced by individual studies (Supplementary Data ). A probable cause of this wide range was different constraints on the estimated potential, with some studies focusing on potential maximum impact and others on more constrained realizable impacts. Only avoided loss of tropical forest and cropland biochar amendment were consistently estimated as having the likely potential to mitigate >2 PgCO 2 e yr −1 , although biochar was considered more uncertain by experts due to other factors germane to its overall viability as a climate solution, averaging a categorization of 2.2. The next four highest potential impact pathways, ranging from 1.6 to 1.7 PgCO 2 e yr −1 , spanned the spectrum from high readiness (temperate forest restoration) to moderate (cropland conversion from annual to perennial vegetation and grassland restoration) to low (seagrass restoration, with main uncertainties around scale of potential impact and durability).

There was high variability in the elicitors’ estimated potential scale of impact, even in pathways with strong support, such as tropical forest avoided loss (20th to 80th percentile confidence interval: 1–8 PgCO 2 e yr −1 ), again emphasizing the importance of consistent definitions and constraints on how NbCS are measured, evaluated and then used in broad-scale climate change mitigation planning and budgeting. Generally, as pathway readiness decreased (moving from category 1 to 3), the elicitor-estimated estimates of GHG mitigation potential decreased (Supplementary Fig. 1 ). Note that individual studies from the scientific literature may have higher or lower estimates (Supplementary Data ).

Expert elicitation meta-analyses suggest that 6–12 responses are sufficient for a robust and stable quantification of responses 15 . We tested that assumption via a Monte Carlo-based sensitivity assessment. Readiness categorizations by the ten experts were robust to a Monte Carlo simulation test, where further samples were randomly drawn from the observed distribution of responses: mean difference between the original and the boot-strapped data was 0.02 (s.d. = 0.05) with an absolute difference average of 0.06 (s.d. = 0.06). The maximum difference in readiness categorization means across all pathways was 0.20 (s.d. = 0.20) (Supplementary Table 2 ). The full dataset of responses is available online (see ʻData availabilityʼ).

These results highlight opportunities to accelerate implementation of NbCS in well-supported pathways and identify critical research needs in others (Fig. 1 ). We suggest focusing future efforts on resolving identified uncertainties for pathways at the intersection between moderate average readiness (for example, mean categorizations between ~1.5 and 2.0) and high potential impact (for example, median >0.5 PgCO 2 e yr −1 ; Supplementary Table 1 ): agroforestry, improved tropical and temperate forest management, tropical and boreal peatlands avoided loss and peatland restoration. Many, although not all, experts identified durability and baseline/additionality as key concerns to resolve in those systems; research explicitly targeted at those specific uncertainties (Supplementary Table 3 ) could rapidly improve confidence in those pathways.

We recommend a secondary research focus on the lower ranked (mean category 2.0 to 3.0) pathways with estimated potential impacts >1 PgCO 2 e yr −1 (Supplementary Fig. 2 ). For these pathways, explicit, quantitative incorporation into broad-scale GHG management plans will require further focus on systems-level carbon/GHG understandings to inspire confidence at all stages of action and/or identifying locations likely to support durable GHG mitigation, for example ref. 16 . Examples of this group include avoided loss and degradation of boreal forests (for example, fire, pests and pathogens and albedo 16 ) and effective mesopelagic fishery management, which some individual studies estimate would avoid future reductions of the currently sequestered 1.5–2.0 PgC yr −1 (refs. 17 , 18 ). These pathways may turn out to have higher or lower potential than the expert review suggests, on the basis of individual studies (Supplementary Data ) but strong support will require further, independent verification of that potential.

We note that category 3 rankings by expert elicitation do not necessarily imply non-viability but simply that much more research is needed to confidently incorporate actions into quantitative GHG mitigation plans. We found an unsurprising trend of lower readiness categorization with lower pathway familiarity (Supplementary Fig. 3 ). This correlation may result from two, non-exclusive potential causes: (1) lower elicitor expertise in some pathways (inevitable, although the panel was explicitly chosen for global perspectives, connections and diverse specialties) and (2) an actual lack of scientific evidence in the literature, which leads to that self-reported lack of familiarity, a common finding in the literature review (Supplementary Data ). Both explanations suggest a need to better consolidate, develop and disseminate the science in each pathway for global utility and recognition.

Our focus on GHG-related benefits in no way diminishes the substantial conservation, environmental and social cobenefits of these pathways (Supplementary Table 4 ), which often exceed their perceived climate benefits 1 , 19 , 20 , 21 . Where experts found climate impacts to remain highly uncertain but other NbS benefits are clear (for example, biodiversity and water quality; Supplementary Table 4 ), other incentives or financing mechanisms independent of carbon crediting should be pursued. While the goals here directly relate to using NbCS as a reliably quantifiable part of global climate action planning and thus strong GHG-related scientific foundations, non-climate NbS projects may provide climate benefits that are less well constrained (and thus less useful from a GHG budgeting standpoint) but also valuable. Potential trade-offs, if any, between ecosystem services and management actions, such as biodiversity and positive GHG outcomes, should be explored to ensure the best realization of desired goals 2 .

Finally, our focus in this study was on broad-scale NbCS potential in quantitative mitigation planning because of the principal and necessary role of NbCS in overall global warming targets. We recognize the range of project conditions that may increase, or decrease, the rigour of any pathway outside the global-scale focus here. We did not specifically evaluate the large and increasing number of crediting concepts (by pathway: Supplementary Data ), focusing rather on the underlying scientific body of knowledge within those pathways. Some broad pathways may have better defined sub-pathways within them, with a smaller potential scale of impact but potentially lower uncertainty (for example, macroalgae harvest cycling). Poorly enacted NbCS actions and/or crediting methodologies at project scales may result in loss of benefits even from high-ranking pathways 22 , 23 , 24 and attention to implementation should be paramount. Conversely, strong, careful project-scale methodologies may make lower readiness pathways beneficial for a given site.

Viable NbCS are vital to global climate change mitigation but NbCS pathways that lack strong scientific underpinnings threaten global accounting by potentially overestimating future climate benefits and eroding public trust in rigorous natural solutions. Both the review of the scientific literature and the expert elicitation survey identified high potential ready-to-implement pathways (for example, tropical reforestation), reinforcing present use of NbCS in planning.

However, uncertainty remains about the quantifiable GHG mitigation of some active and nascent NbCS pathways. On the basis of the expert elicitation survey and review of the scientific literature, we are concerned that large-scale implementation of less scientifically well-founded NbCS pathways in mitigation plans may undermine net GHG budget planning; those pathways require more study before they can be confidently promoted at broad scales and life-cycle analyses to integrate system-level emissions when calculating totals. The expert elicitation judgements suggest a precautionary approach to scaling lower confidence pathways until the scientific foundations are strengthened, especially for NbCS pathways with insufficient measurement and monitoring 10 , 24 , 25 or poorly understood or measured net GHG mitigation potentials 16 , 26 , 27 , 28 . While the need to implement more NbCS pathways for reducing GHG emissions and removing carbon from the atmosphere is urgent, advancing the implementation of poorly quantified pathways (in relation to their GHG mitigation efficacy) could give the false impression that they can balance ongoing, fossil emissions, thereby undermining overall support for more viable NbCS pathways. Explicitly targeting research to resolve these uncertainties in the baseline science could greatly bolster confidence in the less-established NbCS pathways, benefiting efforts to reduce GHG concentrations 29 .

The results of this study should inform both market-based mechanisms and non-market approaches to NbCS pathway management. Research and action that elucidates and advances pathways to ensure a solid scientific basis will provide confidence in the foundation for successfully implementing NbCS as a core component of global GHG management.

NbCS pathway selection

We synthesized scientific publications for nine biomes (boreal forests, coastal blue carbon, freshwater wetlands, grasslands, open ocean blue carbon, peatlands, shrublands, temperate forests and tropical forests) and three cultivation types (agroforestry, croplands and macroalgae aquaculture) (hereafter, systems) and the different pathways through which they may be able to remove carbon or reduce GHG emissions. Shrublands and grasslands were considered as independent ecosystems; nonetheless, we acknowledge that there is overlap in the numbers presented here because shrublands are often included with grasslands 5 , 30 , 31 , 32 , 33 .

The 12 systems were chosen because they have each been identified as having potential for emissions reductions or carbon removal at globally relevant scales. Within these systems, we identified 43 pathways which either have carbon credit protocols formally established or informally proposed for review (non-carbon associated credits were not evaluated). We obtained data on carbon crediting protocols from international, national and regional organizations and registries, such as Verra, American Carbon Registry, Climate Action Reserve, Gold Standard, Clean Development Mechanism, FAO and Nori. We also obtained data from the Voluntary Registry Offsets Database developed by the Berkeley Carbon Trading Project and Carbon Direct company 34 . While we found evidence of more Chinese carbon crediting protocols, we were not able to review these because of limited publicly available information. To maintain clarity and avoid misrepresentation, we used the language as written in each protocol. A full list of the organizations and registries for each system can be found in the Supplementary Data .

Literature searches and synthesis

We reviewed scientific literature and reviews (for example, IPCC special reports) to identify studies reporting data on carbon stocks, GHG dynamics and sequestration potential of each system. Peer-reviewed studies and meta-analyses were identified on Scopus, Web of Science and Google Scholar using simple queries combining the specific practice or pathway names or synonyms (for example, no-tillage, soil amendments, reduced stocking rates, improved forest management, avoided forest conversion and degradation, avoided mangrove conversion and degradation) and the following search terms: ‘carbon storage’, ‘carbon stocks’, ‘carbon sequestration’, ‘carbon sequestration potential’, ‘additional carbon storage’, ‘carbon dynamics’, ‘areal extent’ or ‘global’.

The full literature review was conducted between January and October 2021. We solicited an independent, external review of the syntheses (obtaining from at least three external reviewers per natural or working system; see p. 2 of the Supplementary Data ) as a second check against missing key papers or misinterpretation of data. The review was generally completed in March 2022. Data from additional relevant citations were added through October 2022 as they were discovered. For a complete list of all literature cited, see pp. 217–249 of the Supplementary Data .

From candidate papers, the papers were considered if their results/data could be applied to the following central questions:

How much carbon is stored (globally) at present in the system (total and on average per hectare) and what is the confidence?

At the global level, is the system a carbon source or sink at this time? What is the business-as-usual projection for its carbon dynamics?

Is it possible, through active management, to either increase net carbon sequestration in the system or prevent carbon emissions from that system? (Note that other GHG emissions and forcings were included here as well.)

What is the range of estimates for how much extra carbon could be sequestered globally?

How much confidence do we have in the present methods to detect any net increases in carbon sequestration in a system or net changes in areal extent of that?

From each paper, quantitative estimates for the above questions were extracted for each pathway, including any descriptive information/metadata necessary to understand the estimate. In addition, information on sample size, sampling scheme, geographic coverage, timeline of study, timeline of projections (if applicable) and specific study contexts (for example, wind-break agroforestry) were recorded.

We also tracked where the literature identified trade-offs between carbon sequestered or CO 2 emissions reduced and emissions of other GHG (for example, N 2 O or methane) for questions three and five above. For example, wetland restoration can result in increased CO 2 uptake from the atmosphere. However, it can also increase methane and N 2 O emissions to the atmosphere. Experts were asked to consider the uncertainty in assessing net GHG mitigation as they categorized the NbCS pathways.

Inclusion of each pathway in mitigation protocols and the specific carbon registries involved were also identified. These results are reported (grouped or individually as appropriate) in the Supplementary Data , organized by the central questions and including textual information for interpretation. The data and protocol summaries for each of the 12 systems were reviewed by at least three scientists each and accordingly revised.

These summaries were provided to the expert elicitation group as optional background information.

Unit conversions

Since this synthesis draws on literature from several sources that use different methods and units, all carbon measurements were standardized to the International System of Units (SI units). When referring to total stocks for each system, numbers are reported in SI units of elemental carbon (that is, PgC). When referring to mitigation potential, elemental carbon was converted to CO 2 by multiplying by 3.67. Differences in methodology, such as soil sampling depth, make it difficult to standardize across studies. Where applicable, the specific measurement used to develop each stock estimate is reported.

Expert elicitation process

To assess conclusions brought about by the initial review process described above, we conducted an expert elicitation survey to consolidate and add further, independent assessments to the original literature review. The expert elicitation survey design followed best practice recommendations 14 , with a focus on participant selection, explicitly defining uncertainty, minimizing cognitive and overconfidence biases and clarity of focus. Research on expert elicitation suggests that 6–12 responses are sufficient for a stable quantification of responses 15 . We identified >40 potential experts via a broad survey of leading academics, science-oriented NGO and government agency publications and products. These individuals have published on several NbCS pathways or could represent larger research efforts that spanned the NbCS under consideration. Careful attention was paid to the gender and sectoral breakdown of respondents to ensure equitable representation. Of the invitees, ten completed the full elicitation effort. Experts were offered compensation for their time.

Implementation of the expert elicitation process followed the IDEA protocol 15 . Briefly, after a short introductory interview, the survey was sent to the participants. Results were anonymized and standardized (methods below) and a meeting held with the entire group to discuss the initial results and calibrate understanding of questions. The purpose of this meeting was not to develop consensus on a singular answer but to discuss and ensure that all questions are being considered in the same way (for example, clarifying any potentially confusing language, discussing any questions that emerged as part of the process). The experts then revisited their initial rankings to provide final, anonymous rankings which were compiled in the same way. These final rankings are the results presented here and may be the same or different from the initial rankings, which were discarded.

Survey questions

The expert elicitation survey comprised five questions for each pathway. The data were collected via Google Forms and collated anonymously at the level of pathways, with each respondent contributing one datapoint for each pathway. The experts reported their familiarity (or the familiarity of the organization whose work they were representing) with the pathway and other cobenefits for the pathways.

The initial question ranked the NbCS pathway by category, from one to three.

Category 1 was defined as a pathway with sufficient scientific knowledge to support a high-quality carbon accounting system today (for example, meets the scientific criteria identified in the WWF-EDF-Oeko Institut and ICAO TAB) or to support the development of such a system today. The intended interpretation is that sufficient science is available for quantifying and verifying net GHG mitigation. Note that experts were not required to reference any given ‘high-quality’ crediting framework, which were provided only as examples. In other words, the evaluation was not intended to rank a given framework (for example, ref. 35 ) but rather expert confidence in the fundamental scientific understandings that underpin potential for carbon accounting overall. To this end, no categorization of uncertainty was required (reviewers could skip categorizations they felt were not necessary) and space was available to fill in new categories by individual reviewers (if they felt a category was missing or needed). Uncertainties at this category 1 level are deemed ‘acceptable’, for example, not precluding accounting now, although more research may further substantiate high-quality credits.

Category 2 pathways have a good chance (>25%) that with more research and within the next 5 years, the pathway could be developed into a high-quality pathway for carbon accounting and as a nature-based climate solution pathway. For these pathways, further understanding is needed for factors such as baseline processes, long-term stability, unconstrained fluxes, possible leakage or other before labelling as category 1 but the expert is confident that information can be developed, in 5 years or less, with more work. The >25% chance threshold and 5-year timeframe were determined a priori to reflect and identify pathways that experts identified as having the potential to meet the Paris Accord 2030 goal. Other thresholds (for example, longer timeframes) could have been chosen, which would impact the relative distribution of pathways in categories 2 and 3 (for example, a longer timeframe allowed could move some pathways from category 3 into category 2, for some reviewers). We emphasize that category 3 pathways do not necessarily mean non-valuable approaches but longer timeframes required for research than the one set here.

Category 3 responses denoted pathways that the expert thought had little chance (<25%) that with more research and within the next 5 years, this pathway could be developed into a suitable pathway for managing as a natural solutions pathway, either because present evidence already suggests GHG reduction is not likely to be viable, co-emissions or other biophysical feedbacks may offset those gains or because understanding of key factors is lacking and unlikely to be developed within the next 5 years. Notably, the last does not mean that the NbCS pathway is not valid or viable in the long-term, simply that physical and biological understandings are probably not established enough to enable scientific rigorous and valid NbCS activity in the near term.

The second question asked the experts to identify research gaps associated with those that they ranked as category 2 pathways to determine focal areas for further research. The experts were asked to rank concerns about durability (ability to predict or compensate for uncertainty in timescale of effectiveness due to disturbances, climate change, human activity or other factors), geographic uncertainty (place-to-place variation), leakage or displacement (spillover of activities to other areas), measuring, reporting and verification (MRV, referring to the ability to quantify all salient stocks and fluxes to fully assess climate impacts), basic mechanisms of action (fundamental science), scaling potential (ability to estimate potential growth) and setting of a baseline (ability to reasonably quantify additionality over non-action, a counterfactual). Respondents could also enter a different category if desired. For complete definitions of these categories, see the survey instrument ( Supplementary Information ). This question was not asked if the expert ranked the pathway as category 1, as those were deemed acceptable, or for category 3, respecting the substantial uncertainty in that rating. Note that responses were individual and so the same NbCS pathway could receive (for example) several individual category 1 rankings, which would indicate reasonable confidence from those experts, and several category 2 rankings from others, which would indicate that those reviewers have lingering concerns about the scientific basis, along with their rankings of the remaining key uncertainties in those pathways. These are important considerations, as they reflect the diversity of opinions and research priorities; individual responses are publicly available (anonymized: https://doi.org/10.5281/zenodo.7859146 ).

The third question involved quantification of the potential for moving from category 2 to 1 explicitly. Following ref. 14 , the respondents first reported the lowest plausible value for the potential likelihood of movement (representing the lower end of a 95% confidence interval), then the upper likelihood and then their best guess for the median/most likely probability. They were also asked for the odds that their chosen interval contained the true value, which was used to scale responses to standard 80% credible intervals and limit overconfidence bias 13 , 15 . This question was not asked if the expert ranked the pathway as category 3, respecting the substantial uncertainty in that rating.

The fourth question involved the scale of potential impact from the NbCS, given the range of uncertainties associated with effectiveness, area of applicability and other factors. The question followed the same pattern as the third, first asking about lowest, then highest, then best estimate for potential scale of impact (in PgCO 2 e yr −1 ). Experts were again asked to express their confidence in their own range, which was used to scale to a standard 80% credible interval. This estimate represents a consolidation of the best-available science by the reviewers. For a complete review including individual studies and their respective findings, see the Supplementary Data . This question was not asked if the expert ranked the pathway as category 3, respecting the substantial uncertainty in that rating.

Final results

After collection of the final survey responses, results were anonymized and compiled by pathway. For overall visualization and discussion purposes, responses were combined into a mean and 20th to 80th percentile range. The strength of the expert elicitation process lies in the collection of several independent assessments. Those different responses represent real differences in data interpretation and synthesis ascribed by experts. This can have meaningful impacts on decision-making by different individuals and organizations (for example, those that are more optimistic or pessimistic about any given pathway). Therefore, individual anonymous responses were retained by pathway to show the diversity of responses for any given pathway. The experts surveyed, despite their broad range of expertise, ranked themselves as less familiar with category 3 pathways than category 1 or 2 (linear regression, P  < 0.001, F  = 59.6 2, 394 ); this could be because of a lack of appropriate experts—although they represented all principal fields—or simply because the data are limited in those areas.

Sensitivity

To check for robustness against sample size variation, we conducted a Monte Carlo sensitivity analysis of the data on each pathway to generate responses of a further ten hypothetical experts. Briefly, the extra samples were randomly drawn from the observed category ranking mean and standard deviations for each individual pathway and appended to the original list; values <1 or >3 were truncated to those values. This analysis resulted in only minor differences in the mean categorization across all pathways: the mean difference between the original and the boot-strapped data was 0.02 (s.d. = 0.05) with an absolute difference average of 0.06 (s.d. = 0.06). The maximum difference in means across all pathways was 0.20 (s.d. = 0.20) (Supplementary Table 2 ). The results suggest that the response values are stable to additional responses.

All processing was done in R 36 , with packages including fmsb 37 and forcats 38 .

Data availability

Anonymized expert elicitation responses are available on Zenodo 39 : https://doi.org/10.5281/zenodo.7859146 .

Code availability

R code for analysis available on Zenodo 39 : https://doi.org/10.5281/zenodo.7859146 .

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Acknowledgements

This research was supported through gifts to the Environmental Defense Fund from the Bezos Earth Fund, King Philanthropies and Arcadia, a charitable fund of L. Rausing and P. Baldwin. We thank J. Rudek for help assembling the review and 30 experts who reviewed some or all of those data and protocol summaries (Supplementary Data ). S.M. was supported by a cooperative agreement between the National Science Foundation and Battelle that sponsors the National Ecological Observatory Network programme.

Author information

Present address: Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, USA

Present address: AtmoFacts, Longmont, CO, USA

R. N. Lubowski

Present address: Lombard Odier Investment Managers, New York, NY, USA

Present address: Ecological Carbon Offset Partners LLC, dba EP Carbon, Minneapolis, MN, USA

L. A. Moore

Present address: , San Francisco, CA, USA

J. Paltseva

Present address: ART, Arlington, VA, USA

N. A. Randazzo

Present address: NASA/GSFC, Greenbelt, MD, USA

Present address: University of Maryland, College Park, MD, USA

N. Uludere Aragon

Present address: Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA

These authors contributed equally: B. Buma, D. R. Gordon.

Authors and Affiliations

Environmental Defense Fund, New York, NY, USA

B. Buma, D. R. Gordon, K. M. Kleisner, A. Bartuska, J. R. Collins, A. J. Eagle, R. Fujita, E. Holst, J. M. Lavallee, R. N. Lubowski, C. Melikov, L. A. Moore, E. E. Oldfield, J. Paltseva, A. M. Raffeld, N. A. Randazzo, C. Schneider, N. Uludere Aragon & S. P. Hamburg

Department of Integrative Biology, University of Colorado, Denver, CO, USA

Department of Biology, University of Florida, Gainesville, FL, USA

D. R. Gordon

Resources for the Future, Washington, DC, USA

A. Bartuska

International Arctic Research Center, University of Alaska, Fairbanks, AK, USA

Department of Ecology Evolution and Environmental Biology and the Climate School, Columbia University, New York, NY, USA

The Nature Conservancy, Arlington, VA, USA

Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK

P. Friedlingstein

Laboratoire de Météorologie Dynamique/Institut Pierre-Simon Laplace, CNRS, Ecole Normale Supérieure/Université PSL, Sorbonne Université, Ecole Polytechnique, Palaiseau, France

National Ecological Observatory Network, Battelle, Boulder, CO, USA

Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

O’Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN, USA

Department of Environmental Science and Policy, University of California, Davis, CA, USA

J. N. Sanchirico

Department of Marine Chemistry & Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

J. R. Collins

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Contributions

D.R.G. and B.B. conceived of and executed the study design. D.R.G., K.M.K., J.R.C., A.J.E., R.F., E.H., J.M.L., R.N.L., C.M., L.A.M., E.E.O., J.P., A.M.R., N.A.R., C.S. and N.U.A. coordinated and conducted the literature review. G.M. and B.B. primarily designed the survey. A. Bartuska, A. Bidlack, B.B., J.N.S., K.N., P.E., P.F., R.D. and S.M. contributed to the elicitation. B.B. conducted the analysis and coding. S.P.H. coordinated funding. B.B. and D.R.G. were primary writers; all authors were invited to contribute to the initial drafting.

Corresponding author

Correspondence to B. Buma .

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Competing interests.

The authors declare no competing interests. In the interest of full transparency, we note that while B.B., D.R.G., K.M.K., A.B., J.R.C., A.J.E., R.F., E.H., J.M.L., R.N.L., C.M., L.A.M., E.E.O., J.P., A.M.R., N.A.R., C.S., N.U.A., S.P.H. and P.E. are employed by organizations that have taken positions on specific NbCS frameworks or carbon crediting pathways (not the focus of this work), none have financial or other competing interest in any of the pathways and all relied on independent science in their contributions to the work.

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Nature Climate Change thanks Camila Donatti, Connor Nolan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary information.

Supplementary Tables 1–4, Figs. 1–3 and survey instrument.

Supplementary Data

Literature review and list of reviewers.

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Buma, B., Gordon, D.R., Kleisner, K.M. et al. Expert review of the science underlying nature-based climate solutions. Nat. Clim. Chang. (2024). https://doi.org/10.1038/s41558-024-01960-0

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DOI : https://doi.org/10.1038/s41558-024-01960-0

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A first-ever complete map for elastic strain engineering

types of research papers in social sciences

Without a map, it can be just about impossible to know not just where you are, but where you’re going, and that’s especially true when it comes to materials properties.

For decades, scientists have understood that while bulk materials behave in certain ways, those rules can break down for materials at the micro- and nano-scales, and often in surprising ways. One of those surprises was the finding that, for some materials, applying even modest strains — a concept known as elastic strain engineering — on materials can dramatically improve certain properties, provided those strains stay elastic and do not relax away by plasticity, fracture, or phase transformations. Micro- and nano-scale materials are especially good at holding applied strains in the elastic form.

Precisely how to apply those elastic strains (or equivalently, residual stress) to achieve certain material properties, however, had been less clear — until recently.

Using a combination of first principles calculations and machine learning, a team of MIT researchers has developed the first-ever map of how to tune crystalline materials to produce specific thermal and electronic properties.

Led by  Ju Li , the Battelle Energy Alliance Professor in Nuclear Engineering and professor of materials science and engineering, the team described a framework for understanding precisely how changing the elastic strains on a material can fine-tune properties like thermal and electrical conductivity. The work is described in an open-access paper published in  PNAS .

“For the first time, by using machine learning, we’ve been able to delineate the complete six-dimensional boundary of ideal strength, which is the upper limit to elastic strain engineering, and create a map for these electronic and phononic properties,” Li says. “We can now use this approach to explore many other materials. Traditionally, people create new materials by changing the chemistry.”

“For example, with a ternary alloy, you can change the percentage of two elements, so you have two degrees of freedom,” he continues. “What we’ve shown is that diamond, with just one element, is equivalent to a six-component alloy, because you have six degrees of elastic strain freedom you can tune independently.”

Small strains, big material benefits

The paper builds on a foundation laid as far back as the 1980s, when researchers first discovered that the performance of semiconductor materials doubled when a small — just 1 percent — elastic strain was applied to the material.

While that discovery was quickly commercialized by the semiconductor industry and today is used to increase the performance of microchips in everything from laptops to cellphones, that level of strain is very small compared to what we can achieve now, says Subra Suresh, the Vannevar Bush Professor of Engineering Emeritus.

In a 2018  Science  paper, Suresh, Dao, and colleagues demonstrated that 1 percent strain was just the tip of the iceberg.

As part of a 2018 study, Suresh and colleagues demonstrated for the first time that diamond nanoneedles could withstand elastic strains of as much as 9 percent and still return to their original state. Later on, several groups independently confirmed that microscale diamond can indeed elastically deform by approximately 7 percent in tension reversibly.

“Once we showed we could bend nanoscale diamonds and create strains on the order of 9 or 10 percent, the question was, what do you do with it,” Suresh says. “It turns out diamond is a very good semiconductor material … and one of our questions was, if we can mechanically strain diamond, can we reduce the band gap from 5.6 electron-volts to two or three? Or can we get it all the way down to zero, where it begins to conduct like a metal?”

To answer those questions, the team first turned to machine learning in an effort to get a more precise picture of exactly how strain altered material properties.

“Strain is a big space,” Li explains. “You can have tensile strain, you can have shear strain in multiple directions, so it’s a six-dimensional space, and the phonon band is three-dimensional, so in total there are nine tunable parameters. So, we’re using machine learning, for the first time, to create a complete map for navigating the electronic and phononic properties and identify the boundaries.”

Armed with that map, the team subsequently demonstrated how strain could be used to dramatically alter diamond’s semiconductor properties.

“Diamond is like the Mt. Everest of electronic materials,” Li says, “because it has very high thermal conductivity, very high dielectric breakdown strengths, a very big carrier mobility. What we have shown is we can controllably squish Mt. Everest down … so we show that by strain engineering you can either improve diamond’s thermal conductivity by a factor of two, or make it much worse by a factor of 20.”

New map, new applications

Going forward, the findings could be used to explore a host of exotic material properties, Li says, from dramatically reduced thermal conductivity to superconductivity.

“Experimentally, these properties are already accessible with nanoneedles and even microbridges,” he says. “And we have seen exotic properties, like reducing diamond’s (thermal conductivity) to only a few hundred watts per meter-Kelvin. Recently, people have shown that you can produce room-temperature superconductors with hydrides if you squeeze them to a few hundred gigapascals, so we have found all kinds of exotic behavior once we have the map.”

The results could also influence the design of next-generation computer chips capable of running much faster and cooler than today’s processors, as well as quantum sensors and communication devices. As the semiconductor manufacturing industry moves to denser and denser architectures, Suresh says the ability to tune a material’s thermal conductivity will be particularly important for heat dissipation.

While the paper could inform the design of future generations of microchips, Zhe Shi, a postdoc in Li’s lab and first author of the paper, says more work will be needed before those chips find their way into the average laptop or cellphone.

“We know that 1 percent strain can give you an order of magnitude increase in the clock speed of your CPU,” Shi says. “There are a lot of manufacturing and device problems that need to be solved in order for this to become realistic, but I think it’s definitely a great start. It’s an exciting beginning to what could lead to significant strides in technology.”

This work was supported with funding from the Defense Threat Reduction Agency, an NSF Graduate Research Fellowship, the Nanyang Technological University School of Biological Sciences, the National Science Foundation (NSF), the MIT Vannevar Bush Professorship, and a Nanyang Technological University Distinguished University Professorship.

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types of research papers in social sciences

types of research papers in social sciences

Catalysis Science & Technology

Reaction rate and thermal effects of hydrogen peroxide decomposition in microfluidic chips containing channel-type silver catalysts.

As an important application of microfluidic chips, liquid chemical microthrusters need to introduce a structured catalyst block in the design process. In this paper, a structured silver catalyst is used to promote the decomposition of hydrogen peroxide in microfluidic chips. The planar electric heating plate is used to control the temperature of the microfluidic channel on the microfluidic chip in real time, and the temperature of the catalytic reaction of hydrogen peroxide fluid is measured in real time with an infrared thermal imaging camera. The decomposition reaction rate of hydrogen peroxide was indirectly detected online by UV-Vis spectrophotometer. The experimental results show that when the temperature of the microfluidic chip exceeds 70°C, the thermal decomposition rate of hydrogen peroxide in the microchannel on the preheating region gradually dominates and can not be ignored. When the quadratic regression orthogonal experiment was used to study the influence of 1/T, lnt and lnc0 on lnr, it was found that lnc0 had a significant effect on lnr, and (1/T)*lnt and (lnt)2 had a significant effect on lnr. And within the experimental study range, when T=333.16 K, t=0.02ms and c0=3mol· L-1, the maximum value of lnr was obtained, and it was 454.5±8.2 mol·L-1·s-1. In the single factor study, it can be seen that the temperature of the hot plate and the initial concentration of hydrogen peroxide have a positive correlation with the reaction rate of catalytic decomposition of hydrogen peroxide. The reaction rate of catalytic decomposition of hydrogen peroxide decreases first and then increases with the increase of flow rate. This law is consistent with the trend of quadratic regression orthogonal equations. The thermal effect and catalytic performance of microfluidic chips are emphatically studied, which provides a reference value for the design and application of microfluidic chips in microthrusters.

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Y. Yang, Y. Ye, P. Zhu, W. Zhang and R. Shen, Catal. Sci. Technol. , 2024, Accepted Manuscript , DOI: 10.1039/D4CY00278D

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Hawaii International Conference on System Sciences 2023

Permanent uri for this community.

We are so pleased to release the proceedings of the 56th Hawaii International Conference on System Sciences (HICSS).

The pandemic has at least three positive effects on the shaping of the research at HICSS. Overall, judging from the massive amount of reviews of the 1,429 papers submitted for the conference, the quality of papers have significantly increased, and the overall total score of the accepted papers have jumped to an all-time high. With a target acceptance rate set at 47%, HICSS welcomes 678 papers to its 2023 Proceedings.

As HICSS records an increase in the number of paper submissions in all tracks, and if the number of submitted papers is a relevant indicator of research interests, the following tracks have attracted a significant amount of attention:

  • Organizational Systems and Technology (278)
  • Internet and the Digital Economy (237)
  • Decision Analytics and Service Sciences (191)
  • Collaboration Systems and Technologies (140)
  • Digital and Social Media (127)
  • Information Technology in Healthcare (122)

HICSS continues to promote a new area of MIS research – Location intelligence. In a nutshell, location intelligence brings the context of location to business analytics and problem solving. By analyzing and visualizing spatial data on maps, dashboards, and business models, location intelligence has become an integral part of today’s decision-making and planning paradigms.

We have seen a high number of research papers on the effect of COVID-19 pandemic on a wide spectrum of MIS topics from technology-supported collaboration to the future of work. We also notice an increasing number of research on the pandemic effect on the “dark side of technology” – negative impacts on people’s health and the dissemination of misinformation. As a consequence, various aspects of cyber security are another key feature of this year’s research at HICSS.

As HICSS has returned to the island of Maui to host its annual event, we welcome more than 1,100 scientists at the Hyatt Regency Resort in the pristine Kaanapali Beach area, HICSS welcomes a host of Symposia, Workshops and Tutorials.

As you are downloading the papers in this year’s proceedings, we invite you to cite them in your research work, and we encourage you to submit your work to future HICSS.

Finally, I would like to acknowledge the co-creation of HICSS-56 by the HICSS community.

  • 2,012 Authors of 678 research papers;
  • 2,523 Reviewers ;
  • 457 Minitrack Chairs;
  • 20 Track Chairs; and
  • Our sponsors including University of Hawaii at Manoa’s Shidler College of Business, National Security Agency, Association for Information Systems, University of Redlands and ESRI’s Joint Spatial Business Initiative, and University of Arkansas Sam M. Walton College of Business.

We are looking forward to continuing working with the community of researchers to advance the mission of HICSS – that is to provide a venue where ideas meet and science speaks.

Tung Bui Conference Chair Click here to download front matter and preface

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  • Digital and Social Media
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  • Location Intelligence
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  1. Research Guides: Organizing Your Social Sciences Research Paper: Types

    Before beginning your paper, you need to decide how you plan to design the study.. The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection ...

  2. Organizing Your Social Sciences Research Paper

    The accepted form of academic writing in the social sciences can vary considerable depending on the methodological framework and the intended audience. However, most college-level research papers require careful attention to the following stylistic elements: I. The Big Picture

  3. PDF Writing a Formal Research Paper in the Social Sciences

    For a social science research paper, APA format is typically expected. APA format was developed for the social sciences, so it is followed fairly strictly in these types of papers in both formatting the paper and citing sources. When in doubt, follow APA guidelines. Use peer-reviewed sources for research.

  4. Social Science Research: Principles, Methods and Practices

    This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any ...

  5. Organizing Your Social Sciences Research Paper: Types of Research Designs

    Before beginning your paper, you need to decide how you plan to design the study.. The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data.

  6. PDF How to Write a Social Science Research Paper

    What follows is a general guide to writing a research paper in the social sciences (e.g., an undergraduate honors thesis, MA thesis). In particular, we review common sections in such papers and what they generally entail. Please note that the format of a particular paper may vary by discipline and/or class, so

  7. PDF Style Guidelines for Writing Academic Papers in the Social Sciences

    This document offers several forms of guidance to students writing academic in the social sciences. First, it sets forth basic style guidelines in the current edition of the American Psychological Association's (2010 Publication Manual. Second, it provides special guidelines, some of which are different from those in the current Publication ...

  8. What are the different types of research papers?

    Experimental research paper. This type of research paper basically describes a particular experiment in detail. It is common in fields like: biology. chemistry. physics. Experiments are aimed to explain a certain outcome or phenomenon with certain actions. You need to describe your experiment with supporting data and then analyze it sufficiently.

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    A literature review is the systematic written analysis of previously published research on a specific topic or subject. A literature review is not merely a summary of another scholar's articles or books. Instead, it provides a contextual analysis of the data, ideas, or theoretical concepts presented in the article, book, or other publication.

  10. PDF Social Science Research: Principles, Methods and Practices (Revised

    This work, Social Science Research: Principles, Methods and Practices (Revised edition), is a derivative of Social Science Research: Principles, Methods and Practice by Anol Bhattacherjee [University of South Florida], used under a Creative Commons Attribution NonCommercial ShareAlike 3.0 Unported Licence. Social Science Research: Principles ...

  11. Writing a Case Study

    Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is more common to combine a description of the findings with the discussion about their implications. ... Robert K. Case Study Research: Design and Methods. 6th edition. Los Angeles, CA, SAGE ...

  12. The Literature Review

    A literature review may consist of simply a summary of key sources, but in the social sciences, a literature review usually has an organizational pattern and combines both summary and synthesis, often within specific conceptual categories.A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that ...

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  15. Research Methods for the Social Sciences (Pelz)

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    The Course Book contains abstracts of resource persons on different topics of Research Methodology in Social Sciences for MPhil, PhD, and PDF scholars. Indian Council of Social Science Research ...

  18. Data science can be valuable tool for analyzing social determinants of

    Data science methods can help overcome challenges in measuring and analyzing social determinants of health (SDoH), according to a paper published in The Lancet Digital Health, helping mitigate the ...

  19. A conceptual-empirical typology of social science research methods pedagogy

    Introduction: research methods pedagogy. This paper reports on the findings and outcome of a five-year study with the purpose of examining the pedagogic practices of research methods teachers in the social sciences, opening them up for discussion with a view to building the pedagogic culture in research methods training.

  20. Structural efficiency evaluation of humanities and social sciences

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  23. MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

    In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training data choices, we identified several crucial design lessons. For example, we demonstrate that ...

  24. Organizing Your Social Sciences Research Paper

    The introduction leads the reader from a general subject area to a particular topic of inquiry. It establishes the scope, context, and significance of the research being conducted by summarizing current understanding and background information about the topic, stating the purpose of the work in the form of the research problem supported by a hypothesis or a set of questions, explaining briefly ...

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    Pathways in the upper right quadrant have both high confidence in the scientific foundations and the largest potential scale of global impact; pathways in the lower left have the lowest confidence ...

  26. A first-ever complete map for elastic strain engineering

    In a 2018 Science paper, Suresh, Dao, and colleagues demonstrated that 1 percent strain was just the tip of the iceberg. As part of a 2018 study, Suresh and colleagues demonstrated for the first time that diamond nanoneedles could withstand elastic strains of as much as 9 percent and still return to their original state.

  27. Reaction rate and thermal effects of hydrogen peroxide decomposition in

    As an important application of microfluidic chips, liquid chemical microthrusters need to introduce a structured catalyst block in the design process. In this paper, a structured silver catalyst is used to promote the decomposition of hydrogen peroxide in microfluidic chips. The planar electric heating plate

  28. Hawaii International Conference on System Sciences 2023

    The pandemic has at least three positive effects on the shaping of the research at HICSS. Overall, judging from the massive amount of reviews of the 1,429 papers submitted for the conference, the quality of papers have significantly increased, and the overall total score of the accepted papers have jumped to an all-time high.