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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

  • Your overall aims and approach
  • The type of research design you’ll use
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods
  • The procedures you’ll follow to collect data
  • Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

  • Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

  • How much time do you have to collect data and write up the research?
  • Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
  • Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
  • Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.


Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

  • How many participants do you need for an adequate sample size?
  • What inclusion and exclusion criteria will you use to identify eligible participants?
  • How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

  • The distribution of the data (e.g., the frequency of each score on a test)
  • The central tendency of the data (e.g., the mean to describe the average score)
  • The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

  • Make estimates about the population based on your sample data.
  • Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
  • If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Shona McCombes

Shona McCombes

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2 Considerations in Designing Your Research Approach

Once you’ve identified your area of interest, sorted through and analyzed the literature to identify the problem you’d like to address, and developed both a purpose and a question; the next step is to design your study. This chapter will provide a basic overview of the considerations any researcher must think about as they design a research study.

Chapter 2: Learning Objectives

As you work to identify the best approach to identify an answer to your research question, you will be able to:

  • Compare the conceptualization and operational activities of the process
  • Discuss the difference between an independent and dependent variable
  • Discuss the importance of sampling
  • Contrast research approaches
  • Demonstrate a systematic approach to selecting a research design

Understanding the Language of Research

As you work to determine which approach you will consider in order to best answer your question, you’ll need to consider how to address both the conceptual and operational components of your inquiry. As we discussed in Chapter 1; theory often informs practice (deductive approaches). Theory is often discussed in terms of abstract, or immeasurable, constructs. Because of the ambiguous nature of theory, it is important to conceptualize the parameters of your investigation. Conceptualizing is the process of defining what is or is not included in your description of a specific construct.

Understanding Theoretical and Contextual Framework

You may consider the theoretical or contextual framework for your study as the ‘lens’ through which you want your reader to view the work from. That is, this is your opportunity frame their experience with this information through your educated perspective on the material.

How Will You Determine the Subjective Aspects of Your Work?

Consider exploring one’s motivation to advance their education:

  • That is if you’re determining whether clinicians who have advanced credentials are more motivated at work; you’ll need to create a clear delineation between motivation and effort and work out how to measure each of these independently

Operationalization is the process of defining concepts or constructs in a measurable way. As you dive into the ‘HOW’ you will go about your research, you will need to understand the terminology related to study design

As we discussed in Chapter 1, there are several kinds of Variables. As a reminder, a variable is an objective and measurable representation of a theoretical construct. An independent variable is a variable which causes an effect on the dependent, or outcome variable. Note that there may be more than one independent variable in your study. Therefore, the dependent variable is the variable which you are measuring as an effect of an intervention or influence; you can think of this as the outcome variable. Identifying at least these two variables is an essential first step in designing your study. This is because how you explore the relationship between your effect (independent variable) and outcome (dependent variable) with help guide your methodology. Other variables to consider include mediating variables , which are variables that are explained by both the independent and dependent variables. Moderating variables influence the relationship between the independent and dependent variables and control variables which may have an impact on the dependent variable but does not help to explain the dependent variable.

Assigning Dependent and Independent Variables

You would like to determine the relationship between weight and tidal volume:

  • Dependent Variable : Which variable DEPENDS on the other? Or, which variable will define the OUTCOME? ( Tidal volume)
  • Independent Variable : Does the variable INFLUENCE, HELP EXPLAIN, or have an IMPACT on the dependent variable? (Weight)

You would like to determine whether the number of hours spent in clinical training influences post training test scores :

  • Dependent Variable : Score on post training test
  • Independent Variable : Number of hours in clinical training

Identifying and assigning the dependent and independent variable(s) is one of the most important research activities as this will help guide you toward the type of information you’ll be collecting and what you will do with that information. However, as you consider both the outcome (dependent) variable and the impact (independent) variable, it is also important to consider what other variables may influence the relationship between these two primary variables.

Representing the relationship among variables which impact the association of intelligence and earning potential. Intelligence is the independent variable and earning potential, the dependent variable. However, something like effort, which would impact the relationship between intelligence and earning potential, is considered a moderating variable. Academic achievement is considered a mediating variable as it can be explained by both the independent variable (intelligence) as well as the dependent variable (earning potential).

There are very few instances wherein you can control EVERY variable. However, it is your job as a researcher to plan for, acknowledge, and attempt to address anything that may influence the results you present.

levels of measurement can be thought of as values within each variable. For example, traditionally, the variable ‘Gender’ had two values: male or female. The modern variable of ‘Gender’ may have several values which are used to delineate each potential designation within the variable. Each value represents a specific designation of measure.

Values of measures may be considered quantitative (numeric); in our example of traditional gender you may assign a numeric (quantitative) value to male and female as either ‘1’ and ‘2’, respectively. Values may also be assigned non-numerically; meaning they are qualitative. It is important to note that if you want to analyze non-numeric data, it must be coded first.

Understanding and Assigning Value

You may create a question asking respondents to rank their agreement with a statement on a scale ranging from strongly disagree to strongly agree. Although qualitative in nature, we can assign a numeric value to each level of measurement as a ‘code’.

  • 1= Strongly Disagree
  • 2= Somewhat Disagree
  • 3= Neither Disagree nor Agree
  • 4= Somewhat Agree
  • 5= Strongly Agree

By doing this, we can explore relationships between the attributes and variables using quantitative statistical methods.

Levels of measurement

One of the most important aspects of operationalizing a theoretical construct is to determine the level(s) of measurement. This is done by assessing the types of variables and values:

  • Nominal : also called categorical. This level of measurement is used to describe a variable with two or more values BUT there is no intrinsic ordering to the categories

Example of a Nominal Variable

You would like to collect information about the gender (variable) of individuals participating in your study. Your level of measures may be:

You may then assign these measures a numeric value:

  • Non-Binary=3
  • Ordinal : This level of measurement is used to describe variable values that have a specific rank order. BUT that order does not indicate a specificity between ranks.

Example of an Ordinal Variable

You provide a scale of agreement for respondents to indicate their level of agreement with the use of a current policy within the hospital:

  • Strongly Agree
  • Strongly Disagree

Note: Those who strongly disagree with the use of this policy disapprove MORE than do those who disagree; however, there is no quantifiable value for how much more.

  • Interval : You’ll use this level of measurement for variable values which are rank ordered AND have specified intervals between ranks and can tell you ‘how much more’.

Example of an Interval Variable

You classify the ages of the participants in your study:

  • 18-24 years old
  • 25-30 years old
  • 31-35 years old
  • >35 years old

NOTE: 35 is 5 more than 30. The quantifiable ‘how much more’ is what distinguishes age as an interval variable.

  • Ratio : Ratio values have all of the qualities of a nominal, ordinal, and/or interval scale BUT ALSO have a ‘true zero’. In this case true zero indicates a lack of the underlying construct (i.e. it does not exist). Additionally, there is a ratio between points on this particular scale. That is, in this case, 10 IS twice that of 5.

Example of a Ratio Variable

You are doing a pre and post bronchodilator treatment trial for a new drug. You must establish baseline heart rate in your treatment group:

  • Pulse rate is a ratio variable because the scale has an absolute zero (asystole) and there is a ratio between the number of times the heart beats (i.e. a change in heart rate of 10 beats per minute)

Identification of variable and values is essential to a successful project. Not only will doing this early in the process allow you to predict factors that may affect your research question, but it will also guide you toward the type of data you will collect and determine what kind of statistical analyses you will likely be performing in order to understand and present the results of your work.

Table differentiating the types of variable classifications as well as describing the types of statistical analyses inherent to the classifications.

Scales are used to glean insight into a situation or phenomenon and can be used to help quantify information that would otherwise be difficult to understand or convey. Although there are several types of scales used by researchers, we’ll focus on the two of the most common:

  • Binary scale : Nominal scale that offers two possible outcomes, or values. Questions that force a respondent to answer either ‘yes’ or ‘no’ utilize a binary scale. IF you offer more than two options, your scale is no longer binary, but is still a nominal scaled item

Table illustrating binary scale wherein questions are asked and respondents are given two options to answer. In this case, 'yes' or 'no'.

  • Likert scales : Likert scales are popular for measuring ordinal data and include indications from respondents. Data can be quantified using codes assigned to responses and an overall summation for each attribute can be associated with each respondent

Likert Scale indicating scaled responses between 1 and 5 to questions. A selection of 1 indicates strongly disagree and a selection of 5 indicates strongly agree

Sampling is the statistical process of selecting a subset (called a “sample”) of a population of interest for purposes of making observations and statistical inferences about that population. We cannot study entire populations because of feasibility and cost constraints, and hence, we must select a representative sample from the population of interest for observation and analysis. It is extremely important to choose a sample that is truly representative of the population so that the inferences derived from the sample can be generalized back to the population of interest. Probability sampling is a technique in which every unit in the population has a chance (non-zero probability) of being selected in the sample, and this chance can be accurately determined. An example of probability sampling is simple random sampling wherein you include ALL possible participants in a population and utilize a method to randomly select a sample that is representative of that population. Nonprobability Sampling is a sampling technique in which some units of the population have zero chance of selection or where the probability of selection cannot be accurately determined. Typically, units are selected based on certain non-random criteria, such as quota or convenience. Because selection is non-random, nonprobability sampling does not allow the estimation of sampling errors, and may be subjected to a sampling bias. Therefore, information from a sample cannot be generalized back to the population. An example of nonprobability sampling is utilizing a convenience sample of participants due to your close proximity or access to them.

Why does sampling matter?

When you measure a certain observation from a given unit, such as a person’s response to a Likert-scaled item, that observation is called a response. In other words, a response is a measurement value provided by a sampled unit. Each respondent will give you different responses to different items in an instrument. Responses from different respondents to the same item or observation can be graphed into a frequency distribution based on their frequency of occurrences. For a large number of responses in a sample, this frequency distribution tends to resemble a bell-shaped curve called a normal distribution, which can be used to estimate overall characteristics of the entire sample, such as sample mean (average of all observations in a sample) or standard deviation (variability or spread of observations in a sample). These sample estimates are called sample statistics (a “statistic” is a value that is estimated from observed data). Populations also have means and standard deviations that could be obtained if we could sample the entire population. However, since the entire population can never be sampled, population characteristics are always unknown, and are called population parameters (and not “statistic” because they are not statistically estimated from data). Sample statistics may differ from population parameters if the sample is not perfectly representative of the population; the difference between the two is called sampling error. Theoretically, if we could gradually increase the sample size so that the sample approaches closer and closer to the population, then sampling error will decrease and a sample statistic will increasingly approximate the corresponding population parameter.

If a sample is truly representative of the population, then the estimated sample statistics should be identical to corresponding theoretical population parameters. How do we know if the sample statistics are at least reasonably close to the population parameters? Here, we need to understand the concept of a sampling distribution . Imagine that you took three different random samples from a given population, as shown below, and for each sample, you derived sample statistics such as sample mean and standard deviation. If each random sample was truly representative of the population, then your three sample means from the three random samples will be identical (and equal to the population parameter), and the variability in sample means will be zero. But this is extremely unlikely, given that each random sample will likely constitute a different subset of the population, and hence, their means may be slightly different from each other. However, you can take these three sample means and plot a frequency histogram of sample means. If the number of such samples increases from three to 10 to 100, the frequency histogram becomes a sampling distribution. Hence, a sampling distribution is a frequency distribution of a sample statistic (like sample mean) from a set of samples, while the commonly referenced frequency distribution is the distribution of a response (observation) from a single sample. Just like a frequency distribution, the sampling distribution will also tend to have more sample statistics clustered around the mean (which presumably is an estimate of a population parameter), with fewer values scattered around the mean. With an infinitely large number of samples, this distribution will approach a normal distribution. The variability or spread of a sample statistic in a sampling distribution (i.e., the standard deviation of a sampling statistic) is called its standard error. In contrast, the term standard deviation is reserved for variability of an observed response from a single sample.

Representation of sample statistics for a data set of responses. Graphic indicates item names, individual responses, missing data, and mean for a specific set of responses.

The mean value of a sample statistic in a sampling distribution is presumed to be an estimate of the unknown population parameter. Based on the spread of this sampling distribution (i.e., based on standard error), it is also possible to estimate confidence intervals for that prediction population parameter. Confidence interval is the estimated probability that a population parameter lies within a specific interval of sample statistic values. All normal distributions tend to follow a 68-95-99 percent rule (see below), which says that over 68% of the cases in the distribution lie within one standard deviation of the mean value (μ 1σ), over 95% of the cases in the distribution lie within two standard deviations of the mean (μ 2σ), and over 99% of the cases in the distribution lie within three standard deviations of the mean value (μ 3σ). Since a sampling distribution with an infinite number of samples will approach a normal distribution, the same 68-95-99 rule applies, and it can be said that:

  • (Sample statistic one standard error) represents a 68% confidence interval for the population parameter.
  • (Sample statistic two standard errors) represents a 95% confidence interval for the population parameter.
  • (Sample statistic three standard errors) represents a 99% confidence interval for the population parameter.

Describes the frequency distribution for random sampling

A sample is “biased” (i.e., not representative of the population) if its sampling distribution cannot be estimated or if the sampling distribution violates the 68-95-99 percent rule. As an aside, note that in most regression analysis where we examine the significance of regression coefficients with p<0.05, we are attempting to see if the sampling statistic (regression coefficient) predicts the corresponding population parameter (true effect size) with a 95% confidence interval. Interestingly, the “six sigma” standard attempts to identify manufacturing defects outside the 99% confidence interval or six standard deviations (standard deviation is represented using the Greek letter sigma), representing significance testing at p<0.01.

Deliniates the 68-95-99 percent rule for confidence intervals. The bell curve indicates the percentage of chance that exists that the researcher made an error

Types of Research Designs

There are many different approaches to research. The list provided here is not exhaustive by any means; rather, this is a brief list of the most common approaches you may identify as you review the literature related to your interest.


Experimental research is typically performed in a controlled environment so that the researcher can manipulate an independent variable and measure the outcome (dependent variable) between a group of subjects who received the manipulated variable (intervention) and a group of subjects who did not receive the intervention. This type of design typically adheres to the scientific method in order to test a hypothesis. A hypothesis is a proposed explanation for a phenomenon and serves as the starting point for the investigation.  You may see a hypothesis indicated as (H O ), also called the null hypothesis. This is to differentiate it from an alternative hypothesis (H 1 or H A ), which is any hypothesis other than the null.

Development of the Hypothesis

There are two types of hypotheses, the null (HO) and an alternative (H 1 or H A )

  • H O = There is no significant difference between length of stay for patients diagnosed with COPD and those diagnosed with CHF.
  • H 1 or H A = There is a significant difference between length of stay for patients diagnosed with COPD and those diagnosed with CHF

NOTE: Accepting the null hypothesis would mean that your data confirm that there is no difference. Rejecting the null would mean that your data indicated that there is a significant difference in patient outcomes for these groups; therefore, rejecting the null means accepting an alternative hypothesis.

Randomized Experimental : Participants are randomly assigned to either a treatment (intervention) or a control group. Typically, the treatment group receives an intervention (independent variable) and the outcome of each group is considered dependent variables and compared for effect. Independent variables in this case are considered active in that this variable can be manipulated.

Example of Randomized Experimental Approach

You would like to assess outcomes as they relate to the post delivery resuscitation of  very low birthweight infants in the delivery room. You have decided that one group will receive direct intubation and surfactant (intervention group) in the delivery room and the other will receive the standard care of CPAP (control group). Participants will be randomly assigned to groups and as a bonus, the assignment to groups will be blinded. You will then compare the difference between participants in each group regarding need for oxygen at 36 weeks adjusted gestational age.

  • Dependent Variable: Need for oxygen at 36 weeks adjusted gestational age
  • Independent Variable (Active) : Administration of surfactant

Quasi Experimental : Similar to the randomized experimental approach aside from the random assignment. In quasi-experimental approaches, participants are NOT randomly assigned; however, one group does receive an intervention while the control group does not and outcomes are still compared. The independent variable is also active.

Example of Quasi Experimental Approach

You would like to assess outcomes as they relate to the post delivery resuscitation of  very low birthweight infants in the delivery room. You have decided that one group will receive direct intubation and surfactant (intervention group) in the delivery room and the other will receive the standard care of CPAP (control group). Participants will be assigned to groups based on administration of maternal steroids. You will then compare the difference between participants in each group regarding need for oxygen at 36 weeks adjusted gestational age.

Non Experimental

Non-experimental approaches include a wide variety of approaches; therefore, it is difficult to list them all in a succinct way here. However, it is safe to say that a study approach is considered non-experimental when there lacks intentional manipulation of the independent variable.

Comparative approach : Groups are compared to reveal differences in outcome (dependent variable). Groups are typically formed based on independent variables that cannot be manipulated but are important to the study. This type of independent variable is known as an attribute independent variable. In this approach there are a few categories (2-4 levels) of attribute independent variables that are then compared.

Example of Comparative Approach

You would like to investigate the perceptions of first and second year student-instructor engagement and student learning and instructor motivation in the clinical environment.

  • Dependent Variable : Student perception of experience (2 levels: First and second year)
  • Independent Variable : Student-instructor engagement in learning and motivation

Associational or Correlational approach : Two or more variables for the same group of participants are explored for relationships. Independent variables are also attributive in this approach; meaning, they can be manipulated to impact the dependent variable. Variables included in this approach are typically continuous or have at least five ordered categories.

Example of Associational or Correlational Approach

You would like to conduct a study to better understand practitioner attitudes about the future of the profession.

  • Dependent Variable: Attitude about the future of the profession
  • Independent Variable(s): Age, gender, autonomy

Descriptive research : Projects which only gather data which can be described, not inferred. That is, results and data collected cannot be inferred back to the population nor can comparisons or associations be made. Many qualitative studies are considered descriptive. This is done by considering only one variable at a time and there is no independent variable.

Example of Descriptive Research

You would like to describe the development of a protocol to implement high flow nasal cannula as an intermediate therapy for acute respiratory failure to be used in the Emergency Department at your institution. You plan to compare rates of intubation before and after implementation of the protocol.

  • You are DESCRIBING a process
  • You may collect and compare data using descriptive statistics

It is important to note that it is possible to have more than one approach in one research project. This is because the approach selected is specific to the question that has been asked. If there is more than one question asked, it is reasonable to assume that more than one approach may be used.

There are a few areas of research that although fit under the category of non-experimental; do not quite fit within the classifications presented here. Two of these areas are quality improvement (QI) projects and protocol development.

Quality improvement (QI) projects: The purpose of a QI project is to evaluate the performance of systems, processes, or practices to determine whether either function or operational improvements are needed. Using tools such as the SQUIRE explanation and elaboration guidelines , is extremely helpful in developing, conducting, and analyzing a thorough and impactful QI project.

The SQUIRE guidelines focus on the following four questions:

  • Why did you start?
  • What did you do?
  • What did you find?
  • What does it mean?

These four questions are then expanded upon to help develop the systematic approach to your inquiry and presentation of your findings. An extended investigation of this method is covered in Chapter 6.

Protocol Development

Before we dig too deep into the development of protocols, a clarification needs to be made regarding vocabulary relating to projects of this nature. Although frequently used interchangeably, the terms protocol and guideline are not synonymous. A protocol is described as an official procedure or system of rules governing a process. A guideline is a suggested course of action, policy, or conduct. In healthcare, this is an important distinction; a protocol is a course of action to which treatment must follow without deviation whereas a guideline, although firmly rooted in evidence, allows for deviation based on best judgment of a clinician or presentation of a specific case. Through a research lens, this distinction is important because the process by which these two objectives are realized are very different. The complete process for the development of guidelines which are generalizable beyond a specific situation is best outlined by the World Health Organization Handbook

The development of both guidelines often involves a team of people who are charged with first evaluating the existing evidence and then contributing an interpretation of that evidence toward the consensus of best practice. This is why guidelines are typically issued by federal or state agencies or professional organization. Protocols are generally less generalizable due to contextual constraints. However, even organizational protocols are not developed by a single individual. This does not mean, however, that you cannot begin the process of developing a guideline or protocol for your organization on you own; rather, it is important to frame the work you contribute as the foundation upon which a group can work toward the consensus of best practice. Typically, this initial work is referred to as a narrative review. A narrative review can be described as a broad perspective on a topic which may or may not be impacted by bias. This type of review differs from a systematic review in that it is understood that a narrative review may not encompass all relevant literature on a relevant topic as might a systematic review. Another note; the development of both guidelines and protocols is often an iterative process requiring several cycles of evaluation and revision.  A systematic review is described as exhaustive review of the literature relevant to a specific topic. In addition to being exhaustive, a systematic review includes methodology which is both explicit and reproducible to select, evaluate, and synthesize ALL available evidence. A meta-analysis is a systematic approach to evaluating the data from independent studies of the same subject to evaluate overall trends. Often, a meta-analysis is part of a systematic review.

Selecting your approach

As we’ve discussed, there are several factors which will guide your approach selection. Emphasis should be placed on the development of your purpose and problem statements as well as your research question. Ambiguity in these areas may cause some confusion as you begin to consider what approach you will take to answer your question.  Here we will work to narrow the scope of your approach using a systematic process and answering a few specific questions:

Step 1: Outlining your general purpose

Understanding the overarching goal of your study will help direct the rest of your approach. Here, you will ask yourself “What am I trying to do?”.

Table presenting the question, "What am I trying do do?". The logic is then branched for the reader to decide either the purpose is to understand more about the relationships either among or between OR to describe a process, phenomenon, or practice.

Step 2: Identifying your general approach

Earlier we discussed the difference between experimental and non-experimental approaches. As we mentioned, these are two broad categories of approaches. Your general purpose will determine which of these two general approaches you take. The determination here will point you toward a more focused, or specific, approach.

  • Experimental: Experimental research is typically performed in a controlled environment so that the researcher can manipulate an independent variable and measure the outcome (dependent variable) between a group of subjects who received the manipulated variable (intervention) and a group of subjects who did not receive the intervention. A true experimental approach means that you have random selection or assignment of participants. All other elements aside, if you do NOT have randomization incorporated into your approach, your approach becomes quasi-experimental.
  • Non-experimental: Nonexperimental research is an extremely broad category of approaches. Therefore, the simplest way to explain non-experimental research is to simply state that this approach lacks the manipulation of an independent variable. That is, you are not imposing an intervention on one group and comparing the outcome with a control group. Rather, you may have attribute independent variables which influence, or impact, the dependent variable, but the purpose of the research is not the direct manipulation of that variable. There are several different types of non-experimental research approaches, as we will soon see; however, it is important to understand that descriptive research is always classified as nonexperimental.

Table continuing the logic from step 1 to step two in identifying general approach. General approaches are usually classified as either experimental, in that they are manipulating an independent variable to measure an outcome, or non-experimental wherein they are not directly manipulating an independent variable.

Step 3: Narrowing down your specific purpose

Now that you’ve decided what the general purpose and approach, you can begin to really narrow down the ‘how’ of your research. I find that this is best done by again asking yourself what you are really trying to do. Now that you understand the boundaries of your purpose and approach, you can work to understand the fine points about what types of interactions between variables you’re looking to explore and determine.

A continuation of the stepwise approach to identifying the best study approach. In step 3, you are asked to consider what it is you are trying to determine by exploring the interactions between or among variables. Most people either want to investigate causality, compare groups, find associations, or describe a process, phenomenon, or practice.

Step 4 : Selecting your specific approach

As you can see, there are specific words you should pay attention to when you’re describing your purpose. Given these key words, like ‘determine causality’, or ‘compare groups’, you’ll have a bit more direction as to what approach is most appropriate to identify the best answer to your question. Once we know what it is we really want to do with the information we’re planning to gather (variables), we can select an approach. Selecting your specific approach

Final step in the process of identifying the most appropriate approach is added to the figure. Depending on how you answered the question in step 3, your approach would either be experimental, quasi-experimental, comparative, associational, or descriptive.

Key Takeaways

There are several important concepts presented in this chapter:

  • The theoretical/conceptual framework is the frame, or lens, that YOU build for your reader. It is the perspective through which you would like them to view your work.
  • Constructs represent abstract theory
  • Variables are the concrete measures of constructs
  • There are several different types of variables; however, understanding the relationship between the independent variable (impact variable) and the dependent variable (outcome variable) is extremely important
  • Attributes are levels within variables
  • Attributes and variables must be classified in terms of measurement: Nominal, ordinal, interval, and ratio variables each represent different information and must be assessed correctly to have meaning
  • Sampling is very important because whether your sample represents the larger population is an important factor in how your research is presented and interpreted
  • There are A LOT of different approaches to research. Systematically approaching the selection of your approach by first defining your problem and purpose statements and your research question will be helpful as you narrow your focus on the which approach best captures the interaction between or among variables

Crawford, L.M., Burkholder, G.J., Cox, K.A. (2020). Writing the Research Proposal. In G.J. Burkholder, K.A Cox, L.M. Crawford, and J.H. Hitchcock (Eds.), Research design and methods: An applied guide for the scholar-practitioner (pp. 309-334). Sage Publications

Gliner, J.A., Morgan, G.A., & Leech, N.L. (2017). Research methods in applied settings: An integrated approach to design and analysis. Routledge

  • This section can be attributed to Bhattacherjee, A. (2012) published under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License ↵

Defining a construct through your lens as a researcher. How you are choosing to describe the boundaries associated with your work

A measurable representation of an abstract construct

A variable that can explain another variable. A variable which may be manipulated (active) or describes (attribute) to affect an outcome

The variable which is measured as an outcome and is affected by the independent variable(s)

Variables that are explained by both the independent and dependent variables

Influence the relationship between the independent and dependent variable

A variable which has an impact on the dependent variable, but does not explain the outcome (dependent variable)

values within each variable.

The assignment of a number to an attribute to describe a variable

Variable with two or more layers but without a specific order

A variable which has a specific rank order but no specificity between the ranks

Rank ordered variable with specified intervals between ranks

Has a true zero within the scale against which it is measured

A tool, or measure, used to quantify material that may be difficult to do so otherwise

Nominal scale with two potential outcomes

Used to measure ordinal data with a ranking system

Method of selecting a subset of the population to study.

Method of sampling wherein potential for sampling is equally likely for the entire population

Method of sampling where in the likelihood of being selected into a sample is not equal across the population

Visual representation of how a sample falls around a mean

A proposed explanation for the observed phenomenon

A form of experimental study design were participants are randomly assigned to either an intervention or control group

A form of experimental design involving both intervention and control groups but lacks randomization

Groups of participants are compared to identify differences in outcome

Two or more variables for the SAME group of participants are explored for relationships

Research projects wherein data gathered and described, but no relationships are inferred

A subset of nonexperimental research wherein the performance of systems, processes, or practices are evaluated for either efficiency or effectiveness

An official procedure or system

A suggested course of action

A broad perspective on a topic, typically from the perspective of a single author

An exhaustive review of literature relevant to a specific topic; typically performed by a group of people

Systematic approach to evaluating data from independent studies on a topic to evaluate or identify trends

Research performed in a controlled environment in which a researcher can manipulate an independent variable and measure a dependent variable (outcome)

Broad category of research approaches which lack the manipulation of an independent variable

Practical Research: A Basic Guide to Planning, Doing, and Writing Copyright © by megankoster. All Rights Reserved.

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Designing research projects

How to design better research projects, and how to develop your skill as someone who generates research projects.

Eleanor C Sayre

Designing good research studies is an important part of becoming a researcher, no matter what your field is. The exercises on this page are aimed at junior researchers who are designing their first studies in education research. If you’ve already done one or two projects, these exercises will help you get better at seeking funding and developing more projects. If you’ve never done research before, these exercises will help your first project be more successful.

If you are looking to design an education research project, the exercises on this page will help you. If you’re looking for advice on how to plan research projects is a good choice. You might also look at research process models to help you think about how research projects progress, or Iterative Design to think about to structure them for maximum likelihood of success.

If you’re doing video-based observational research, here’s a good companion piece to consider. If you’re thinking about Design-based research, check out this article .

More broadly, check out all articles tagged with “ doing research ”.

What does my project need?

Every project in education research needs to address four areas. While the details of these areas can be (should be) emergent, well-formed and successful research projects identify as much as possible ahead of time.

Every project needs:

Additionally, when you present your work for publication or funding, you will need to consider two more areas:

We’re going to leave these two aside for now because they reference a broader sense of where the research community is, what societal needs are, and how your project fits into a much larger narrative. Those considerations are outside the scope of this guide, though you might consider reading ahead to other guides on writing. Let’s work on the four primary areas.

In a good research project, the four areas are all tightly related and supportive of each other. You should develop them in concert with each other. The exercises on this page will help you design a research study, and they will also help you develop your design skills in general.

Details of the four areas

Research questions.

Your research question(s) tie together your theoretical frameworks, methods, and access. They give purpose to your data collection and analysis. Answering them generates new knowledge about human behavior. In the ordinary process of doing research or thinking about the world, you will ask lots of questions. As you pursue some of them, you’ll develop follow-up questions and related lines of inquiry.

Research Question templates

If you’re in the very beginning stages of thinking about your project, you might need help brainstorming some possible research questions. Here are some templates to get you started. It’s not an exhaustive list.

  • Theory X says A, but theory Y says B. How can they be made commensurate?
  • This paper used population A, but I have population B. How can I apply their findings to my population?
  • Surveys shows that students can do X. What is the actual process of learning to do X?
  • What are the moderating factors which control success at task X?
  • Our previous work shows X happens sometimes. Why does X occur?
  • What’s better at teaching X, curriculum A or curriculum B?
  • How do teachers make sense of X in light of Y?

Making your research question better

When you have an idea about what you’d like to investigate, you need to refine your ideas into a research question that suggests how you will answer it and how you will know when it is answered.

A good research question has the following properties:

  • It is phrased a question, not a statement of problem
  • Specific enough to be answerable
  • Open to complicated, robust answers
  • Interesting to investigate

You will want to have two versions of your research question: one that uses regular language, and a longer one (possibly with subquestions!) that uses specific, technical language.

This exercise helps you refine your ideas into a research question.

Write your question in the form of a question. Use regular language.

Make it specific. Your research question needs to be answerable in principle, and your research design needs to have a high likelihood of answering it.

  • If your research question uses comparison language, what are you comparing? For example, if your research question is about whether a new curriculum is “better” or if students are learning “more”, what will you be comparing it to? Do you need to collect baseline data? Will you be able to run a treatment group and a control group at the same time?
  • If your research question uses development language (e.g. “learning”), over what time are your subjects changing? An hour? Four years? Their lives? How will you know if change is durable? how will you know if it occurs at all?

Open it up to complicated, robust answers.

  • If your research question has a binary answer (“does X happen?”), revise it to permit a more subtle answer (“to what extent does X happen?”; “how much does Y mediate X happening?”; “under what conditions can X be optimized to happen?”)
  • If your research question is too specific (“what is the correlation coefficient of X with Y?”), you are too specific. Revise your question to have more robust answers (“how do X and Y relate?”; “what factors affect X and by how much?”)

Check: does answering this question sound like fun to you?

  • If you refined your question so much that finding the answer sounds boring, trivial, or insurmountably hard, try new ways to refine it so that it really captures your interest in this topic.

In the process of refining your research question, you might realize that there are a bunch of interesting sub-questions to pursue. Go ahead and list them out, and follow this same process to refine them. Your refinements probably also include technical language and reserved words that mean something specific to the research project. Define each reserved word and link it to specific theoretical frameworks, methods, or data streams.

A good research question is a living question. As you interact with theories and data , it will necessarily change. The more specific you can make it in the beginning, the better you will be able to see it change and adjust your future work in an intentional way. You may find it useful to read Engle et al’s “ Progressive Refinement of Hypotheses in Video-Supported Research ” to understand how research questions can change and in response to repeated engagement with data, and Iterative Design to think about how to design for this feature.

The Access area is about practical constraints on your project: what populations do you have access to, and in which modalities? how much time do you have, and which analysis resources can you marshal? Of all the areas, Access is the one which is usually fixed earliest in the project, because the kinds and amounts of data you have access to are usually determined before you can collect any data at all, and the scope of your project is usually outside your control.

Questions that detail your access to data:

  • What kinds of people will you measure? Some examples: introductory students, pre-service teachers, graduate teaching assistants, third graders in a specific elementary school.
  • In what modalities can you collect data from them? Some examples: I can talk to them individually in interviews once per person, I can video them in class every day, I can put a problem on their final exam, I have three years of archival data but cannot collect new data, etc.
  • How many people / how much data? One or two significant figures are ok here: about 10 students, about 300 students, about 20 hours of video, about 100 matched pre-post tests, etc

You probably can’t answer all of these questions alone. Get specific guidance from your collaborators, advisor, and people who control your access to research subjects (their instructors, their principals, the registrar, the data librarian, etc) – the members of your Advisory Board . At early design stages, you don’t need to seek IRB approval yet, and you don’t need written permission from every stakeholder. When your study is more fully designed , you will talk to these people again to firm up the details of your access and adjust your research questions and methods.

Questions that detail your access to resources:

  • How long can you spend collecting data? How long analyzing it?
  • How many researchers will be involved in data collection and analysis? What are their skill levels?
  • How much data (and what kinds) can you reasonably expect to collect / analyze in the amount of time and effort that are available to you?

It is entirely possible that you have access to more data and analysis resources than you will need or use in your project. That’s great! You don’t need to collect (or use) everything. Alternately, you might not have enough access (or the right kind of access) to do the study you really want to do. That’s disappointing. You will need to adjust your research questions and methods in light of how much (and what kinds) of data you can collect or analyze with your resources.

On rare occasions, you can use your research questions to argue for access to more resources or different modalities. For example, suppose your research question is about student epistemology and persistence, and you already have access to students’ attitude survey scores. You might be able to ask the registrar for students’ demographics and final grades to enhance your analysis.

Theoretical frameworks

The role of your theoretical frameworks is to tell you why your observations are meaningful and in what ways your analyses generate new knowledge. Without a theoretical framework, your observations are meaningless and your work is unpublishable.

The primer on theory covers what you need theory for, an organizing framework for deciding which theory or theories to use, some theory options in education research, and some other common considerations.

The best theoretical frameworks are a) explicit; b) well-matched to your research question and methods; and c) intentionally chosen. There isn’t a “best framework” for everyone, or even every research question, and there are a lot of options available.

I’m using “Theoretical framework” in a loose sense to include things like knowledge-in-pieces , communities of practice, speech genres, models of institutional change, error-based learning, etc. (I’ve used all of these, and there are a lot more out there.) Some people use the phrase “theoretical-methodological framework” to acknowledge that good frameworks must tie theory, methods, and data together.

In this article, I’m not going to explore those subtleties.


The role of your methodology is to tell you how to generate observations to answer your research question, how to convert those observations into data , and how to analyze that data. While theoretical frameworks are mostly concerned with why those observations and analyses are meaningful or interesting, methodologies are mostly concerned with the practicality of converting observations into analyses and the reasons for those analyses.

It is becoming a lot more common in discipline-based education research to be explicit about the methods that you choose and why. While it used to be sufficient in papers to outline what you did, now you also need to discuss why you did it and how it fits into a broader research tradition.

Many projects – especially large projects – coordinate multiple kinds of data and multiple kinds of analyses in order to make robust conclusions. This is (broadly) called “mixed-methods” or “multi-methods” design. There are lots of ways to mix methods well (and some ways to do it badly). If your research questions demand multi- or mixed-methods, you will need to write sub-research questions and choose theoretical frameworks for each method, and you will need to think about how the analyses from each method will interact to generate new knowledge. Before you jump into a mixed-methods design, ask yourself carefully if your research questions really warrant it, and if your access really allows it.

Sources for theoretical frameworks and methodologies:

There are books and papers written on this subject. Some of them are textbook-style for students; others are monograph style for researchers. To find them, you will have to step outside your particular discipline and look at the broader educational research literature, the learning sciences, or psychology (depending on your research questions).

  • The Journal of the Learning Sciences has an excellent series on methodology and many beautiful papers on theory.
  • Reviews in PER has a few papers with brief overviews of some kinds of methods and theories.
  • Probably the most highly-cited book on methods is Creswell’s book on research design. It is not comprehensive, but it is extensive.
  • There’s a quick overview of coding qualitative data (aimed at UX researchers) on Delve
  • Shayan Doroudi wrote an excellent primer on learning theories.
  • When you read papers , make note of their frameworks and methods (and their citations!).

You can also talk to other humans!

  • Talk to your advisor or collaborators about what they would use (or require you to use).
  • Write a one-page prospectus that outlines what you want to do and why you think it’s interesting or important, and send it to someone who does similar work. Ask them (nicely) for suggestions.

Develop the four areas in concert for a specific research project

In this exercise, you’re going to iteratively refine each of the four areas so that they are tightly integrated with each other.

On a whiteboard, write down a preliminary research question. If you don’t have a preliminary research question, start with one of the research question templates or do the exercise on making better research questions.

Write down what kind of access you have. Be specific about what populations, what kind of resources you have to undertake this research and how long it will take, and what kind of data modalities are available to you.

If you’re structurally constrained (by your funder, or your advisor, or your equipment) to use particular methods or theories, write them down as well.

Return to your research question, and update it so that it is constrained to the populations you have access to (as well as other structural constraints). It will get longer and more detailed. That’s great.

Which theories support your research question? Write them down. Amend your research question to explicitly reference at least one theoretical framework. If your question is about how individuals develop, you might look at the Resource Framework . If it’s about how communities form, try Communities of Practice. If you don’t know any theories, what have you read that makes you think this would be an interesting research question? You might need to use two or three frameworks in concert with each other to fully answer your research question.

What kind of data will you collect? Here’s a quick overview of the common kinds of data .

  • Make sure that your access permits this kind of data, that your theoretical framework will be able to use the data from it, and that it will be able to answer your research question.
  • Amend your research question and theoretical framework(s) to reflect the kind of observations you will collect. You might triangulate across several different data streams: preliminary surveys will identify participants for in depth interviews , and you ask them for their homework, for example.

How much data will you need to collect or analyze to show the effects you are looking for? Part of the answer to this question is about where you plan to publish your results at the end of your study: if you want to exhaustively prove your solution, you need a lot of evidence, but if you are only looking to prove its existence, you don’t need as much. Even a thoroughly theory-driven, theory-generating project needs something data-like (reinterpretation of old data, for example).

  • If your project is based on finding patterns of human behavior, there are formalized methods for estimating effect sizes (generally known as a “power analysis” or “power estimate”). A quick-n-dirty estimate is that your error bars will go like 1/sqrt(N). If you can estimate differences in your treatments based on the literature, you can guess about how many subjects you will need. If your estimates suggest you will need many more subjects than you have access to, you need to revise your research question.
  • If your project is based on finding cases of human behavior, you will need to think carefully about episode selection. How many episodes will you need to prove your point substantially? A good estimate is 3-5, most of which should be similar and one of which should be contrasting. More or fewer are possible.

Adjust your research question and methods in light of how much data you will be able to generate.

Write down a preliminary data collection and analysis plan.

  • You may find that drawing a logic model or conjecture map is helpful. You may find that a narrative of what you’re planning to do and how is helpful.
  • Compare your plan with your chosen theories and research question. Does your plan make use of your theories? Is it likely to answer your research question? Is it possible with the time and resources you have allotted?

Imagine that everything in data collection goes swimmingly and all of your data are fantastic. What does the answer to your research question look like? To what extent can you answer it with your methods and access? If course, you won’t know exactly what the answer will be – if you already knew, it wouldn’t be research – but you should be able to guess at an approximate shape to the answer.

  • If you think you’ll need additional kinds of data to better triangulate an answer your question, amend your access and methods.
  • If you think you’ll need a lot more data than you can get, amend your research question.

Another process which can help with intentional research design is conjecture mapping ; you might also consider the emergent processes outlined in “ Progressive Refinement… ”. If your research project is larger than you can complete in one semester, you are strongly encouraged to think about an iterative design using the principles in Planning Research Projects . Alternately, if your research project has a substantial curriculum development aspect, you should consider Design-Based Research (DBR). Lastly, you might consider whether your project is research at all: maybe you’re doing evaluation, not research .

Develop your skill in designing research projects

These exercises will develop your skill in designing research projects. If you do them a lot, then designing research studies will become a habit for you.

When you read papers , imagine using their theory and methods with a different population, or using their access with different theory and methods, or their research question with different access and methods. Make notes about your choices, so that later you can cite these papers in your own work. This exercise also makes you a better reader of papers.

Read through the abstracts of NSF’s recent awards for either IUSE or EDU:CORE . For every project, imagine that you have been given a supplement to do some research related to that project. What would be interesting? What would be possible, but not personally interesting? What would be exciting, but you don’t know very much about? You should be able to find something personally interesting or exciting in almost all of the projects. Design a study for each. This exercise also makes you a better citizen of the broader education research community, because you will know a lot more about the shape of current work in the community.

Read through the NSF’s upcoming deadlines for programs sponsored by Directorate for STEM Education (EDU), particularly the DUE and DRL divisions. For each one, sketch out a research study: what would you investigate? who might you partner with? This exercise also makes you a better researcher, because you will become more knowledgeable about how to frame your work to get funding.

Generative writing is the biggest tool in your researcher toolbox. Go back to your old notes about research designs, and enrich them with your new thoughts as you learn more.

Check out all articles in this Handbook tagged with “ doing research ”.

Read this delightful piece by the former editor of Sociology of Education.

Read this paper on quality in qualitative research design: Tracy, S.J., 2010. Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative inquiry, 16(10), pp.837-851.

Read this paper on elements of research project designs.

Read this overview on designing projects for the scholarship of teaching and learning.

Additional topics to consider

Planning research projects.

How to develop a timeline for an education research project that makes space for emergence.

Evaluation and Research

What is the difference between evaluation and research?

Iterative design

Why and how to use an iterative design for successful research projects.

This article was first written on January 1, 2015, and last modified on February 8, 2024.

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Research Design Considerations

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Editor's Note: The online version of this article contains references and resources for further reading and the authors' professional information.

The Challenge

“I'd really like to do a survey” or “Let's conduct some interviews” might sound like reasonable starting points for a research project. However, it is crucial that researchers examine their philosophical assumptions and those underpinning their research questions before selecting data collection methods. Philosophical assumptions relate to ontology, or the nature of reality, and epistemology, the nature of knowledge. Alignment of the researcher's worldview (ie, ontology and epistemology) with methodology (research approach) and methods (specific data collection, analysis, and interpretation tools) is key to quality research design. This Rip Out will explain philosophical differences between quantitative and qualitative research designs and how they affect definitions of rigorous research.

What Is Known

Worldviews offer different beliefs about what can be known and how it can be known, thereby shaping the types of research questions that are asked, the research approach taken, and ultimately, the data collection and analytic methods used. Ontology refers to the question of “What can we know?” Ontological viewpoints can be placed on a continuum: researchers at one end believe that an observable reality exists independent of our knowledge of it, while at the other end, researchers believe that reality is subjective and constructed, with no universal “truth” to be discovered. 1,2 Epistemology refers to the question of “How can we know?” 3 Epistemological positions also can be placed on a continuum, influenced by the researcher's ontological viewpoint. For example, the positivist worldview is based on belief in an objective reality and a truth to be discovered. Therefore, knowledge is produced through objective measurements and the quantitative relationships between variables. 4 This might include measuring the difference in examination scores between groups of learners who have been exposed to 2 different teaching formats, in order to determine whether a particular teaching format influenced the resulting examination scores.

In contrast, subjectivists (also referred to as constructionists or constructivists ) are at the opposite end of the continuum, and believe there are multiple or situated realities that are constructed in particular social, cultural, institutional, and historical contexts. According to this view, knowledge is created through the exploration of beliefs, perceptions, and experiences of the world, often captured and interpreted through observation, interviews, and focus groups. A researcher with this worldview might be interested in exploring the perceptions of students exposed to the 2 teaching formats, to better understand how learning is experienced in the 2 settings. It is crucial that there is alignment between ontology (what can we know?), epistemology (how can we know it?), methodology (what approach should be used?), and data collection and analysis methods (what specific tools should be used?). 5

Key Differences in Qualitative and Quantitative Approaches

Use of theory.

Quantitative approaches generally test theory, while qualitative approaches either use theory as a lens that shapes the research design or generate new theories inductively from their data. 4

Use of Logic

Quantitative approaches often involve deductive logic, starting off with general arguments of theories and concepts that result in data points. 4 Qualitative approaches often use inductive logic or both inductive and deductive logic, start with the data, and build up to a description, theory, or explanatory model. 4

Purpose of Results

Quantitative approaches attempt to generalize findings; qualitative approaches pay specific attention to particular individuals, groups, contexts, or cultures to provide a deep understanding of a phenomenon in local context. 4

Establishing Rigor

Quantitative researchers must collect evidence of validity and reliability. Some qualitative researchers also aim to establish validity and reliability. They seek to be as objective as possible through techniques, including cross-checking and cross-validating sources during observations. 6 Other qualitative researchers have developed specific frameworks, terminology, and criteria on which qualitative research should be evaluated. 6,7 For example, the use of credibility, transferability, dependability, and confirmability as criteria for rigor seek to establish the accuracy, trustworthiness, and believability of the research, rather than its validity and reliability. 8 Thus, the framework of rigor you choose will depend on your chosen methodology (see “Choosing a Qualitative Research Approach” Rip Out).

View of Objectivity

A goal of quantitative research is to maintain objectivity, in other words, to reduce the influence of the researcher on data collection as much as possible. Some qualitative researchers also attempt to reduce their own influence on the research. However, others suggest that these approaches subscribe to positivistic ideals, which are inappropriate for qualitative research, 6,9,10 as researchers should not seek to eliminate the effects of their influence on the study but to understand them through reflexivity . 11 Reflexivity is an acknowledgement that, to make sense of the social world, a researcher will inevitably draw on his or her own values, norms, and concepts, which prevent a totally objective view of the social world. 12

Sampling Strategies

Quantitative research favors using large, randomly generated samples, especially if the intent of the research is to generalize to other populations. 6 Instead, qualitative research often focuses on participants who are likely to provide rich information about the study questions, known as purposive sampling . 6

How You Can Start TODAY

  • Consider how you can best address your research problem and what philosophical assumptions you are making.
  • Consider your ontological and epistemological stance by asking yourself: What can I know about the phenomenon of interest? How can I know what I want to know? W hat approach should I use and why? Answers to these questions might be relatively fixed but should be flexible enough to guide methodological choices that best suit different research problems under study. 5
  • Select an appropriate sampling strategy. Purposive sampling is often used in qualitative research, with a goal of finding information-rich cases, not to generalize. 6
  • Be reflexive: Examine the ways in which your history, education, experiences, and worldviews have affected the research questions you have selected and your data collection methods, analyses, and writing. 13

How You Can Start TODAY—An Example

Let's assume that you want to know about resident learning on a particular clinical rotation. Your initial thought is to use end-of-rotation assessment scores as a way to measure learning. However, these assessments cannot tell you how or why residents are learning. While you cannot know for sure that residents are learning, consider what you can know—resident perceptions of their learning experiences on this rotation.

Next, you consider how to go about collecting this data—you could ask residents about their experiences in interviews or watch them in their natural settings. Since you would like to develop a theory of resident learning in clinical settings, you decide to use grounded theory as a methodology, as you believe asking residents about their experience using in-depth interviews is the best way for you to elicit the information you are seeking. You should also do more research on grounded theory by consulting related resources, and you will discover that grounded theory requires theoretical sampling. 14,15 You also decide to use the end-of-rotation assessment scores to help select your sample.

Since you want to know how and why students learn, you decide to sample extreme cases of students who have performed well and poorly on the end-of-rotation assessments. You think about how your background influences your standpoint about the research question: Were you ever a resident? How did you score on your end-of-rotation assessments? Did you feel this was an accurate representation of your learning? Are you a clinical faculty member now? Did your rotations prepare you well for this role? How does your history shape the way you view the problem? Seek to challenge, elaborate, and refine your assumptions throughout the research.

As you proceed with the interviews, they trigger further questions, and you then decide to conduct interviews with faculty members to get a more complete picture of the process of learning in this particular resident clinical rotation.

What You Can Do LONG TERM

  • Familiarize yourself with published guides on conducting and evaluating qualitative research. 5,16–18 There is no one-size-fits-all formula for qualitative research. However, there are techniques for conducting your research in a way that stays true to the traditions of qualitative research.
  • Consider the reporting style of your results. For some research approaches, it would be inappropriate to quantify results through frequency or numerical counts. 19 In this case, instead of saying “5 respondents reported X,” you might consider “respondents who reported X described Y.”
  • Review the conventions and writing styles of articles published with a methodological approach similar to the one you are considering. If appropriate, consider using a reflexive writing style to demonstrate understanding of your own role in shaping the research. 6

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3.4: Components of a Research Project

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Learning Objectives

  • Describe useful strategies to employ when searching for literature.
  • Describe why sociologists review prior literature and how they organize their literature reviews.
  • Identify the main sections contained in scholarly journal articles.
  • Identify and describe the major components researchers need to plan for when designing a research project.
  • Describe the importance of a research proposal.

In this section, we’ll examine the most typical components that make up a research proposal and research project, bringing in a few additional components to those we have already discussed. Keep in mind that our purpose at this stage is simply to provide a general overview of research design. The specifics of each of the following components will vary from project to project. Further, the stage of a project at which each of these components comes into play may vary.

Searching for Literature

Familiarizing yourself with research that has already been conducted on your topic is one of the first stages of conducting a research project and is crucial for coming up with a good research design. But where to start? How to start? As you search for literature, you may have to be fairly broad in your search for articles.

I’m guessing you may feel you’ve heard enough about electronic gadget addiction in this chapter, so let’s consider a different example here. On my campus, much to the chagrin of a group of student smokers, smoking was recently banned. These students were so upset by the idea that they would no longer be allowed to smoke on university grounds that they staged several smoke-outs during which they gathered in populated areas around campus and enjoyed a puff or two together.

A student in my research methods class wanted to understand what motivated this group of students to engage in activism centered around what she perceived to be, in this age of smoke-free facilities, a relatively deviant act. Were the protesters otherwise politically active? How much effort and coordination had it taken to organize the smoke-outs? The student researcher began her research by attempting to familiarize herself with the literature on her topic. Yet her search in Sociological Abstracts for “college student activist smoke-outs,” yielded no results. Concluding there was no prior research on her topic, she informed me that she would need an alternative assignment to the annotated bibliography I required since there was no literature for her to review. How do you suppose I responded to this news? What went wrong with this student’s search for literature?

In her first attempt, the student had been too narrow in her search for articles. But did that mean she was off the hook for completing the annotated bibliography assignment? Absolutely not. Instead, she went back to Sociological Abstracts and searched again using different combinations of search terms. Rather than searching for “college student activist smoke-outs” she tried, among other sets of terms, “college student activism.” This time her search yielded a great many articles. Of course, they were not focused on prosmoking activist efforts, but they were focused on her population of interest, college students, and on her broad topic of interest, activism. I suggested that reading articles on college student activism might give her some idea about what other researchers have found in terms of what motivates college students to become involved in activist efforts. I also suggested she could play around with her search terms and look for research on activism centered on other sorts of activities that are perceived by some as deviant, such as marijuana use or veganism. In other words, she needed to be broader in her search for articles.

While this student found success by broadening her search for articles, her reading of those articles needed to be narrower than her search. Once she identified a set of articles to review by searching broadly, it was time to remind herself of her specific research focus: college student activist smoke-outs. Keeping in mind her particular research interest while reviewing the literature gave her the chance to think about how the theories and findings covered in prior studies might or might not apply to her particular point of focus. For example, theories on what motivates activists to get involved might tell her something about the likely reasons the students she planned to study got involved. At the same time, those theories might not cover all the particulars of student participation in smoke-outs. Thinking about the different theories then gave the student the opportunity to focus her research plans and even to develop a few hypotheses about what she thought she was likely to find.

Reviewing the Literature

Developing an annotated bibliography is often one of the early steps that researchers take as they begin to familiarize themselves with prior research on their topic. A second step involves a literature review in which a researcher positions his or her work within the context of prior scholarly work in the area. A literature review addresses the following matters: What sorts of questions have other scholars asked about this topic? What do we already know about this topic? What questions remain? As the researcher answers these questions, he or she synthesizes what is contained in the literature, possibly organizing prior findings around themes that are relevant to his or her particular research focus.

I once advised an undergraduate student who conducted a research project on speciesism, the belief that some species are superior to or have more value and rights than others. Her research question was “Why and how do humans construct divisions between themselves and animals?” This student organized her review of literature around the two parts of her research question: the why and the how. In the “why” section of her literature review, she described prior research that addressed questions of why humans are sometimes speciesist. She organized subsections around the three most common answers that were presented in the scholarly literature. She used the same structure in the “how” section of her literature review, arranging subsections around the answers posed in previous literature about how humans construct divisions between themselves and animals. This organizational scheme helped readers understand what we already know about the topic and what theories we rely on to help make sense of the topic. In addition, by also highlighting what we still don’t know, it helped the student set the stage for her own empirical research on the topic

The preceding discussion about how to organize a review of scholarly literature assumes that we all know how to read scholarly literature. Yes, yes, I understand that you must know how to read. But reading scholarly articles can be a bit more challenging than reading a textbook. Here are a few pointers about how to do it successfully. First, it is important to understand the various sections that are typically contained in scholarly journals’ reports of empirical research. One of the most important and easiest to spot sections of a journal article is its abstract , the short paragraph at the beginning of an article that summarizes the author’s research question, methods used to answer the question, and key findings. The abstract may also give you some idea about the theoretical proclivities of the author. As a result, reading the abstract gives you both a framework for understanding the rest of the article and the punch line. It tells you what the author(s) found and whether the article is relevant to your area of inquiry.

After the abstract, most journal articles will contain the following sections (although exact section names are likely to vary): introduction, literature review, methodology, findings, and discussion. Of course, there will also be a list of references cited, lists of references cited are a useful source for finding additional literature in an area. and there may be a few tables, figures, or appendices at the end of the article as well. While you should get into the habit of familiarizing yourself with articles you wish to cite in their entirety , there are strategic ways to read journal articles that can make them a little easier to digest. Once you have read the abstract and determined that this is an article you’d like to read in full, read through the discussion section at the end of the article next. Because your own review of literature is likely to emphasize findings from previous literature, you should make sure that you have a clear idea about what those findings are. Reading an article’s discussion section helps you understand what the author views as the study’s major findings and how the author perceives those findings to relate to other research.

As you read through the rest of the article, think about the elements of research design that we have covered. What approach does the researcher take? Is the research exploratory, descriptive, or explanatory? Is it inductive or deductive? Idiographic or nomothetic? What claims does the author make about causality? What are the author’s units of analysis and observation? Use what you have learned about the promise and potential pitfalls associated with each of these research elements to help you responsibly read and understand the articles you review. Future chapters of this text will address other elements of journal articles, including choices about measurement, sampling, and research method. As you learn about these additional items, you will increasingly gain more knowledge that you can apply as you read and critique the scholarly literature in your area of inquiry.

Additional Important Components

Thinking about the overarching goals of your research project and finding and reviewing the existing literature on your topic are two of the initial steps you’ll take when designing a research project. Forming a clear research question, is another crucial step. There are a number of other important research design components you’ll need to consider, and we will discuss those here.

At the same time that you work to identify a clear research question, you will probably also think about the overarching goals of your research project. Will it be exploratory, descriptive, or explanatory? Will your approach be idiographic or nomothetic, inductive or deductive? How you design your project might also be determined in part by whether you aim for your research to have some direct application or if your goal is to contribute more generally to sociological knowledge about your topic. Next, think about what your units of analysis and units of observation will be. These will help you identify the key concepts you will study. Once you have identified those concepts, you’ll need to decide how to define them, and how you’ll know that you’re observing them when it comes time to collect your data. Defining your concepts, and knowing them when you see them, has to do with conceptualization and operationalization, the focus of a later chapter. Of course, you also need to know what approach you will take to collect your data. Thus identifying your research method is another important part of research design. You also need to think about who your research participants will be and what larger group(s) they may represent. These topics will be the focus of a later chapter too. Last, but certainly not least, you should consider any potential ethical concerns that could arise during the course of your research project. These concerns might come up during your data collection, but they might also arise when you get to the point of analyzing or sharing your research results.

Decisions about the various research components do not necessarily occur in sequential order. In fact, you may have to think about potential ethical concerns even before zeroing in on a specific research question. Similarly, the goal of being able to make generalizations about your population of interest could shape the decisions you make about your method of data collection. Putting it all together, the following list shows some of the major components you’ll need to consider as you design your research project:

  • Research question
  • Literature review
  • Research strategy (idiographic or nomothetic, inductive or deductive)
  • Research goals (basic or applied)
  • Units of analysis and units of observation
  • Key concepts (conceptualization and operationalization)
  • Method of data collection
  • Research participants (sample and population)
  • Ethical concerns

Research Proposal

At the stage before actually starting the research it is often a good idea to write a research proposal detailing all of the decisions made in the preceding stages of the research process and the rationale behind each decision. This multi-part proposal should address what research questions you wish to study and why, the prior literature, theories you wish to employ along with hypotheses to be tested (if you are doing deductive research, how measurement will be done, what research method to be employed and why, and desired sampling strategy (or who the subjects are.  Also, do not forget to include a budget.  Funding agencies typically require such a proposal in order to select the best proposals for funding. Even if funding is not sought for a research project, a proposal may serve as a useful vehicle for seeking feedback from other researchers and identifying potential problems with the research project (e.g., whether some important constructs were missing from the study) before starting data collection. This initial feedback is invaluable because it is often too late to correct critical problems after data is collected in a research study.


  • When identifying and reading relevant literature, be broad in your search for articles, but be narrower in your reading of articles.
  • Writing an annotated bibliography can be a helpful first step to familiarize yourself with prior research in your area of interest.
  • Literature reviews summarize and synthesize prior research.
  • Literature reviews are typically organized around substantive ideas that are relevant to one’s research question rather than around individual studies or article authors.
  • When designing a research project, be sure to think about, plan for, and identify a research question, a review of literature, a research strategy, research goals, units of analysis and units of observation, key concepts, method(s) of data collection, population and sample, and potential ethical concerns.
  • A research proposal is also important to consider.
  • Find and read a complete journal article that addresses a topic that is of interest to you. In four to eight sentences, summarize the author’s research question, theoretical framing, methods used, and major findings. Reread the article, and see how close you were in reporting these key elements. What did you understand and remember best? What did you leave out? What reading strategies may have helped you better recall relevant details from the article?
  • Using the example of students’ electronic gadget addictions, design a hypothetical research project by identifying a plan for each of the nine components of research design that are presented in this section.

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  • Starting the research process

A Beginner's Guide to Starting the Research Process

Research process steps

When you have to write a thesis or dissertation , it can be hard to know where to begin, but there are some clear steps you can follow.

The research process often begins with a very broad idea for a topic you’d like to know more about. You do some preliminary research to identify a  problem . After refining your research questions , you can lay out the foundations of your research design , leading to a proposal that outlines your ideas and plans.

This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project.

Table of contents

Step 1: choose your topic, step 2: identify a problem, step 3: formulate research questions, step 4: create a research design, step 5: write a research proposal, other interesting articles.

First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you’re interested in—maybe you already have specific research interests based on classes you’ve taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose .

Even if you already have a good sense of your topic, you’ll need to read widely to build background knowledge and begin narrowing down your ideas. Conduct an initial literature review to begin gathering relevant sources. As you read, take notes and try to identify problems, questions, debates, contradictions and gaps. Your aim is to narrow down from a broad area of interest to a specific niche.

Make sure to consider the practicalities: the requirements of your programme, the amount of time you have to complete the research, and how difficult it will be to access sources and data on the topic. Before moving onto the next stage, it’s a good idea to discuss the topic with your thesis supervisor.

>>Read more about narrowing down a research topic

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So you’ve settled on a topic and found a niche—but what exactly will your research investigate, and why does it matter? To give your project focus and purpose, you have to define a research problem .

The problem might be a practical issue—for example, a process or practice that isn’t working well, an area of concern in an organization’s performance, or a difficulty faced by a specific group of people in society.

Alternatively, you might choose to investigate a theoretical problem—for example, an underexplored phenomenon or relationship, a contradiction between different models or theories, or an unresolved debate among scholars.

To put the problem in context and set your objectives, you can write a problem statement . This describes who the problem affects, why research is needed, and how your research project will contribute to solving it.

>>Read more about defining a research problem

Next, based on the problem statement, you need to write one or more research questions . These target exactly what you want to find out. They might focus on describing, comparing, evaluating, or explaining the research problem.

A strong research question should be specific enough that you can answer it thoroughly using appropriate qualitative or quantitative research methods. It should also be complex enough to require in-depth investigation, analysis, and argument. Questions that can be answered with “yes/no” or with easily available facts are not complex enough for a thesis or dissertation.

In some types of research, at this stage you might also have to develop a conceptual framework and testable hypotheses .

>>See research question examples

The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you’ll use to collect and analyze it, and the location and timescale of your research.

There are often many possible paths you can take to answering your questions. The decisions you make will partly be based on your priorities. For example, do you want to determine causes and effects, draw generalizable conclusions, or understand the details of a specific context?

You need to decide whether you will use primary or secondary data and qualitative or quantitative methods . You also need to determine the specific tools, procedures, and materials you’ll use to collect and analyze your data, as well as your criteria for selecting participants or sources.

>>Read more about creating a research design

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in designing a research project what are the bases you consider

Finally, after completing these steps, you are ready to complete a research proposal . The proposal outlines the context, relevance, purpose, and plan of your research.

As well as outlining the background, problem statement, and research questions, the proposal should also include a literature review that shows how your project will fit into existing work on the topic. The research design section describes your approach and explains exactly what you will do.

You might have to get the proposal approved by your supervisor before you get started, and it will guide the process of writing your thesis or dissertation.

>>Read more about writing a research proposal

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.


  • Sampling methods
  • Simple random sampling
  • Stratified sampling
  • Cluster sampling
  • Likert scales
  • Reproducibility


  • Null hypothesis
  • Statistical power
  • Probability distribution
  • Effect size
  • Poisson distribution

Research bias

  • Optimism bias
  • Cognitive bias
  • Implicit bias
  • Hawthorne effect
  • Anchoring bias
  • Explicit bias

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Project Planning for the Beginner: Research Design

  • Defining a Topic
  • Reviewing the Literature
  • Developing a Researchable Question

Research Design

  • Planning, Data, Writing and Dissemination

What Is a Research Plan?

This refers to the overall plan for your research, and will be used by you and your supervisor to indicate your intentions for your research and the method(s) you’ll use to carry it out. It includes:

• A specification of your research questions

• An outline of your proposed research methods

• A timetable for doing the work

What Is Research Design?

The term “ research design “ is usually used in reference to experimental research, and refers to the design of your experiment. However, you will also see the term “research design” used in other types of research. Below is a list of possible research designs you might encounter or adopt for your research:

• Descriptive or exploratory (e.g., case study , naturalistic observation )

• Correlational (e.g., case-control study, observational study )

• Quasi-experimental (e.g., field experiment , quasi-experiment )

• Experimental (experiment with random allocation and a control and test group )

• Review (e.g. literature review , systematic review )

• Meta-analytic (e.g. meta-analysis )

Research Design Choices

How do i match my research method to my research question.

The method(s) you use must be capable of answering the research questions you have set. Here are some things you may have to consider:

• Often questions can be answered in different ways using different methods

• You may be working with multiple methods

• Methods can answer different sorts of questions

• Questions can be answered in different ways.

The matching of method(s) to questions always matters . Some methods work better for particular sorts of questions.

If your question is a hypothesis which must be falsifiable, you can answer it using the following possible methods:

• An experimental method using statistical methods to test your hypothesis.

• Survey data (either generated by you or secondary data) using statistical methods to test your hypothesis.

If your question requires you to describe a social context and/or process, then you can answer it using the following possible methods:

• You can use data from your own surveys and/or secondary data to carry out descriptive statistics and numerical taxonomy methods for classification .

• You can use qualitative material derived from:

• Documentary research

• Qualitative interviews

• Focus groups

• Visual research

• Ethnographic methods

• Any combination of the above may be deployed.

If your question(s) require you to make causal statements about how certain things have come to be as they are, then you might consider using the following:

• You can build quantitative causal models using techniques which derive from statistical regression analysis and seeing if the models “fit” your quantitative data set.

• You can do this through building simulations .

• You can do this by using figurational methods, particularly qualitative comparative analysis , which start either with the construction of quantitative descriptions of cases from qualitative accounts of those cases, or with an existing data set which contains quantitative descriptions of cases. 

• You can combine both approaches.

If your question(s) require you to produce interpretive accounts of human social actions with a focus on the meanings actors have attached to those actions, then you might consider using the following:

• You can use documentary resources which include accounts of action(s) and the meanings actors have attached to those actions. This is a key approach in historical research.

• You can conduct qualitative interviews .

• You can hold focus groups .

• You can do this using ethnographic observation .

• You can combine any or all of above approaches.

If your question(s) are evaluative, this could mean that you have to find out if some intervention has worked, how it has worked if it has, and why it didn’t work if it didn’t. You might then consider using the following:

• Any combination of quantitative and qualitative methods which fit the data you have.

• You should always use process tracing to generate a careful historical account of the intervention and its context(s). 

Checklist: Question to Ask When Deciding On a Method

Here are seven questions you should be able to answer about the methods you have chosen for your research. 

  • Does your method/do your methods fit the research question(s)?
  • Do you understand how the methods relate to your methodological position?
  • Do you know how to use the method(s)  ?  If not, can you learn how to use the method(s)?
  • Do you have the resources you need to use the methods? For example:

• statistical software

• qualitative data analysis software

• an adequate computer

• access to secondary data sets

• audio-visual equipment

• language training

• transport You need to work through this list and add anything else that you need.

  • If you are using multiple methods, do you know how you are going to combine them to carry out the research?
  • If you are using multiple methods, do you know how you are going to combine the  products of using them when writing up your research? 
  • << Previous: Developing a Researchable Question
  • Next: Planning, Data, Writing and Dissemination >>
  • Last Updated: May 11, 2022 2:56 PM
  • URL: https://libguides.sph.uth.tmc.edu/c.php?g=949457

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Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project — the samples or groups, measures, treatments or programs, and methods of assignment — work together to try to address the central research questions. Here, after a brief introduction to research design , I’ll show you how we classify the major types of designs . You’ll see that a major distinction is between the experimental designs that use random assignment to groups or programs and the quasi-experimental designs that don’t use random assignment. [People often confuse what is meant by random selection with the idea of random assignment. You should make sure that you understand the distinction between random selection and random assignment .] Understanding the relationships among designs is important in making design choices and thinking about the strengths and weaknesses of different designs. Then, I’ll talk about the heart of the art form of designing designs for research and give you some ideas about how you can think about the design task. Finally, I’ll consider some of the more recent advances in quasi-experimental thinking — an area of special importance in applied social research and program evaluation.

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Research Design 101: A Guide To Planning Experiment Design

in designing a research project what are the bases you consider

Brigitta Puskás

Every day, we conduct research. Every research study has its own purpose it lines up with. But how do our researchers plan their research ? What methods for designing research reflect the goals and delivers results? In this article, we go back to the very basics of research and its types. Then, we walk you through our process of assumption validation and experiment design in an everyday setting.

What we will cover in this article:

  • The basic types of research
  • The different types of research methods
  • Study design in research
  • The types of qualitative research and a research design in qualitative research
  • The types of quantitative research and a research design in quantitative research

research design methods

The research problem defines research design

According to American sociologist Earl Robert Babbie, “Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon.”

The design of your research , on the other hand, provides your customized toolkit for a specific research problem. You need to make sure that the tools fit the problem. Research design represents the set of methods and procedures you utilize during the process of data collection and analysis specified in the research problem.

We create a research design as a framework to deliver answers to research questions. Based on the research problem, the design of a study defines defines:

  • The right choice of study type (descriptive or experimental)
  • Sub-type (e.g., descriptive-longitudinal case study)
  • The hypotheses
  • The independent and dependent variables
  • The scope of experimental design
  • Data collection methods and a statistical analysis plan, if applicable.

research design alternatives

Types of research: Inductive and deductive research

You will find this familiar if you have ever written a thesis. Basically, you can start researching a subject from two ends.

We use inductive research methods to analyze a phenomenon, while deductive research methods verify it.

To put it into practice: We either want to analyze why more people spend more time texting on weekends than on weekdays (inductive research), or assume that it results from them having more time on those days — and then we test this assumption (deductive research).

We associate inductive research approaches generally with qualitative methods and techniques, while deductive methods connect more to quantitative research.

Researching business and technology

The above holds true for any type of research, from physics to neurology, ornithology to user research. “Average people” don’t usually deal with all these fancy research-related expressions (other than that one time with your thesis paper back in college).

But businesses and tech companies do research all the time as well. In a business setting, researchers mainly ask:

  • What do organizations or businesses really want to find out?
  • What processes and mechanisms need analyzing to chase the idea?
  • What arguments need building up around a concept?
  • What evidence will people require to believe in the idea or concept?

research design information

Research purposes

Research serves three purposes, depending on prior knowledge and the context. We might not even know what will come out in the end (exploratory research). We might want to structure already existing information in a newer / better way (descriptive research) or to find explanations for a given phenomenon.

Let’s dive more into detail!

1. Exploratory research

If we want to explore the phenomenon and research questions but don’t know for sure whether to offer a final conclusion, choose explanatory research. Conduct this type of research to take a look at new problem areas which no one has explored yet.

For example, we want to know what people use their phones for during the week and on weekends. We dive into what apps exist, how we can group them, how people choose, how their prioritize apps, etc.

Exploratory research proves essential for laying the foundation for more conclusive research and data collection.

2. Descriptive Research:

Descriptive research focuses on shedding light on specific issues through the process of data collection. Lead these studies to describe a behavior or phenomenon.

Descriptive research has three main goals: describing, explaining and validating research findings.

For example, we look at when people use apps and what for.

3. Explanatory Research:

Conduct explanatory research or causal research to understand the impact of certain changes in existing standard procedures. Conducting experiments represents the most popular form of casual research, such as research conducted to understand the effect of rebranding on customer loyalty.

For example, we look at why people seem to use their phones longer on average on weekends than on weekdays.

The research process

We broadly classify research methods as qualitative research and quantitative research.

Both methods have distinctive properties and data collection methods. In this segment, we will learn more about both.

Whichever research method you decide to go with, first evaluate the problem from an analytical point of view.

User interviews with post-its

Qualitative research design: Types of qualitative research

As a research method, qualitative research collects data using conversational methods in which participants involved in the research answer open-ended questions. We collect the essentially non-numerical responses.

This method not only helps a researcher understand what participants think but also why they think in a particular way.

These qualitative research methods see wide usage:

  • One-to-one Interviews
  • Focus Groups
  • Ethnographic Research
  • Text Analysis
  • Case Study Research

research design data

Quantitative research design: Types of quantitative research

Quantitative research methods deal with numbers and anything that can deal with a measurable form in a systematic way of investigating the phenomenon. We use it to answer questions in terms of justifying relationships with measurable variables to explain, predict or control a phenomenon.

Researchers often use three methods to conduct this type of research

  • Survey Research
  • Descriptive Research
  • Correlational Research

research design methods

What makes up research design? Identifying the ideal research methodologies

To choose the appropriate research methods, you must clearly identify the research objectives. Take into consideration this example of research objectives you may have for your business:

  • First, find out your clients’ needs.
  • Know their preferences and understand what they find important.
  • Find an appropriate way to make them aware of your products and services.
  • Find ways to improve your products or services to suit your customers’ needs.

After identifying what you need to know, ask which research methods will offer you that information.

Organize your questions within the framework of the 7 Ps of marketing, which influences your company – product, price, promotion, place, people, processes and physical tests.

Research methods in psychology

Psychologists use many different methods for conducting research. Each has advantages and disadvantages that make it suitable for certain situations and unsuitable for others.

Case studies, surveys, naturalistic observation and laboratory observation exemplify descriptive or correlational research methods. Using them, researchers can describe different events, experiences or behaviors, and look for links between them. However, they do not enable researchers to determine causes of behavior.

Remember: Correlation Is Not Causation! Two factors may have a connection without one causing the other to occur. Often, a third factor explains the correlation.

Why does it matter to know the basics of psychological research? Because in any situation when we deal with people, psychological occurrences might come into play.

UX designer working on a project

Differences between research methods and research design

Research methods.

Generalized and established, research methods address research questions (e.g., qualitative vs. quantitative methods). Not all methods apply for all research questions, so the area of research that you want to explore limits the choice of method.

Research Design

Research design involves determining how to apply your chosen method to answer your research question. Think of your study’s design as a blueprint detailing what to do and how to accomplish it.

Key aspects of research design include research methodology, participant/sample collection and assignment and data collection procedures and instruments.


Think of the choice of research methods, then design a reciprocal process extending well into your study. For example, a flaw in the design may arise over the course of your study.

Changing the design of the study may lead to the choice of a different method. In turn, this may lead to subsequent changes in the design to accommodate the new method(s).

research design ux research

UX research design

UX research design makes up the plan. It provides the logical structure of any scientific work. It helps you stay on track and systematize the research so to deliver valid data and confidence in decision making based on the results.

Research design functions to ensure the effectiveness and objectivity of your work by providing a blueprint of sorts for the collection, measurement and analysis of the data.

in designing a research project what are the bases you consider

Assumptions and validation in practice: Experiment design

How it uses the assumptions and experiments below:

  • Figure out which kind of assumption you have.
  • Conduct an experiment like the one listed to see if you assumed correctly.
  • If your team did, move forward to the next assumption..
  • If they didn’t, evaluate other options.

Assumption 1: We think we have found a problem. Experiment 1 — Online research: Let’s research whether people discuss this problem online. Google, Twitter, and Quora can help. Also check if a solution already exists. Assumption 2: Based on our research, we still think Group X finds this a problem. This group consists of a lot of people, and they all experience the problem. Experiment 2 — Census data and interviews: How many people actually comprise this group? Lead demographic research based on stats and numbers. If this group seems large, talk to some of them in person. See if they all mention the problem. If so, you seem to have proven your point. Assumption 3: We think we have found a solution to this great problem. Experiment 3 — Field research: Now sketch it and talk to some potential users. Then, get out of the building and show it to the target group because we want to make sure they think that your solution will help. If they do, we can move on to the next step.

Assumption 4: We now assume Group X will indeed pay for our solution to their problem. Experiment 4 — Price before Product, Period: Ask potential customers how much they’d pay for this solution, if anything. If they do, figure out if we can actually make it happen.

Assumption 5: We find the solution feasible. Experiment 5 — Feasibility testing: Chat with your engineers/devs. What do they think about building it? Establish if they find it not super hard to do. They will likely appreciate getting involved early on. Assumption 6: We think adding Extra Feature Z will add a lot of value to our solution. Experiment 6 — A/B testing with a mockup: Go and interview users to find out whether the feature makes its inclusion critical. Perhaps create a landing page with and without the feature listed and look at conversion. Don’t ask users if they’ll miss it; show them the product without it and check if they complain. (Useful tools: Invision, UserTesting.com, or AlphaHQ) Assumption 7: We think people use what we designed to solve the problem. Experiment 7  — Usability testing with prototypes: Create a paper or clickable mock and ask users to complete the task. Better yet, just see what happens without any prompt. Invision, UserTesting.com, AlphaHQ, Validately can help you out. Assumption 8 : We think we can build this in Time Period Y. Experiment 8 — Project length estimation: At this point, get more people on board. First, get the engineers into a room, breaking down the product into high-level flows and features. Have them provide high-level point estimates (difficulty: 1-5 points) or T-shirt sizes (difficulty: S, M, L, XL) to get a better overview of how complex your product idea winds up, and how long it would take to build. Assumption 9: Based on what we know, we think the product is running on the right track. Experiment 9 — User testing: The time has come to involve some real users in the process. Talk to some customers about whether they value it enough to actually pay for. Assumption 10: We think we might have reached the stage to kick it all off and launch. Experiment 10 — Prepare the battlefield: Test the product within the organization. Ask the marketing and sales departments whether they all have what they need. A launch roadmap might also help. Here, we’re checking for internal feasibility and how it will all fit the given timeframe. Assumption 11: We assume people will use the product we’re launching. Experiment 11 — Setting up analytics: Setting up Google Analytics, Hotjar, Heap.io and/or other tracking tools. Set these up before launch. Assumption 12: We assume people use our product to solve the problem. Experiment 12 — Ask your customers: Go back to your target users and see how they use the tool you’ve built. Talk to random other users about what they use it for. You may learn of an additional market. Assumption 13: We might miss another feature that we think might work. Experiment 13 : Return to Assumption 6 .

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in designing a research project what are the bases you consider

Illustration by James Round

How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

  • Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
  • Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

  • Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
  • Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
  • Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
  • Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
  • Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
  • Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

  • describe clearly and concisely the question you’ve chosen to study
  • summarise the state of the art in knowledge about the question, and where your project could contribute new insight
  • identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

  • What will be the general topic of your paper?
  • What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

  • Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
  • Your question should have more than one plausible answer.
  • Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):
Publication date:
Title of book, chapter, or article:
If a chapter or article, title of journal or book where they appear:
Brief description of this work, including main findings and methods ( c 75 words):
Summary of how this work contributes to your project ( c 75 words):
Brief description of the implications of this work ( c 25 words):
Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

  • What are the central concepts or variables in your project? Offer a brief definition of each.
  • Do any data sources exist on those concepts or variables, or would you need to collect data?
  • Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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in designing a research project what are the bases you consider

There are hundreds of different expert opinions on the topic of designing a research project, compiling thousands of books on the subject. No matter which method the author presents, there are advantages and disadvantages to the researcher.

Because there are so many different types of research and even more unique personalities of researchers, it’s not a surprise that the approach to designing a research project is also various in nature. However, they all start similarly, with an idea and a vision. From there, the design must be strategically incorporated, with a clear picture of the start, the end, and every step in between. While there are many different ways a researcher can attempt this strategy, there are three main approaches that are suggested in academics: the deductive, inductive, and abductive approaches.

Types of Approaches

Each approach has the same ultimate goal: a successful outcome. But the rest of the strategy is unique and should be applied based on the researcher’s preferences and the type of research project performed.

●      Deductive approaches - These strategies are used when the idea is to develop a hypothesis from a working theory. The research process is then created with the intent to test the hypothesis for accuracy. By working from a deductive angle, the researcher serves to determine a conclusion based on the expected premises considered. The hypothesis may be correct or incorrect, but it’s the observation that is being looked for.

This approach works well when one is looking for a causal connection between a concept and a variable, when quantitative data is being measured, and with generalized research findings.

●      Inductive approaches - Frequently called “inductive reasoning,” this approach takes the opposite view as deductive. Inductive approaches look at the predicted end of the process and looks for patterns based on observations and hypothetical premises.

This study works well for a researcher who has no specified direction for the project once it is set in motion. Instead, they use the data as it is observed and analyzed in order to move on to the next step. Patterns are observed and then a theory is generated that guides the researcher forward.

●      Abductive approaches - This approach is used when both inductive and deductive approaches have disadvantages that the researcher wants to avoid. This reasoning method is more of an explanation of why certain things that are confusing or unexpected occurred the way they did.

These approaches have their purposes, and once you decide which one you want to use, you can move on to strategizing your next steps.

Strategies for Designing a Research Project

The approach you use combined with the strategy of designing your project is important. These five strategies are the typical academic writing options:

●      Survey research - As it implies, survey research is based on a collection of data obtained through surveying a specific pool of participants who fit a required demographic. The results are then analyzed and applied to the research project.

●      Experiment - A research project designed off an experiment method typically has a scientific process to it. A hypothesis starts the work out and then variables and independent variables are tested, manipulated, and compared for results in a controlled environment.

●      Case Studies - This strategy uses an investigation through empirical inquiry into a real-life situation. The study is based on an in-depth evaluation of an event, a person, or a group with the intent to answer a question or determine the cause of a principle.

●      The Grounded Theory approach - With this approach, the researcher designs a project based on a question or a set of qualitative data. Data is then collected methodically and studied in relevance to its application to the question or initial data.

●      Desk research - Researchers compile desk research for important reasons. This is an analysis of a secondary source of data that was already gathered, such as metadata categories, and is then applied to a theory or a hypothesis to determine the relevance to an outcome.

Whichever approach and strategy you use to design your project, it must be consistent and strategically planned out from conception to publication.

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  • Afghanistan
  • Åland Islands
  • American Samoa
  • Antigua and Barbuda
  • Bolivia (Plurinational State of)
  • Bonaire, Sint Eustatius and Saba
  • Bosnia and Herzegovina
  • Bouvet Island
  • British Indian Ocean Territory
  • Brunei Darussalam
  • Burkina Faso
  • Cayman Islands
  • Central African Republic
  • Christmas Island
  • Cocos (Keeling) Islands
  • Congo (Democratic Republic of the)
  • Cook Islands
  • Côte d'Ivoire
  • Curacao !Curaçao
  • Dominican Republic
  • El Salvador
  • Equatorial Guinea
  • Falkland Islands (Malvinas)
  • Faroe Islands
  • French Guiana
  • French Polynesia
  • French Southern Territories
  • Guinea-Bissau
  • Heard Island and McDonald Islands
  • Iran (Islamic Republic of)
  • Isle of Man
  • Korea (Democratic Peoples Republic of)
  • Korea (Republic of)
  • Lao People's Democratic Republic
  • Liechtenstein
  • Marshall Islands
  • Micronesia (Federated States of)
  • Moldova (Republic of)
  • Netherlands
  • New Caledonia
  • New Zealand
  • Norfolk Island
  • North Macedonia
  • Northern Mariana Islands
  • Palestine, State of
  • Papua New Guinea
  • Philippines
  • Puerto Rico
  • Russian Federation
  • Saint Barthélemy
  • Saint Helena, Ascension and Tristan da Cunha
  • Saint Kitts and Nevis
  • Saint Lucia
  • Saint Martin (French part)
  • Saint Pierre and Miquelon
  • Saint Vincent and the Grenadines
  • Sao Tome and Principe
  • Saudi Arabia
  • Sierra Leone
  • Sint Maarten (Dutch part)
  • Solomon Islands
  • South Africa
  • South Georgia and the South Sandwich Islands
  • South Sudan
  • Svalbard and Jan Mayen
  • Switzerland
  • Syrian Arab Republic
  • Tanzania, United Republic of
  • Timor-Leste
  • Trinidad and Tobago
  • Turkmenistan
  • Turks and Caicos Islands
  • United Arab Emirates
  • United Kingdom of Great Britain and Northern Ireland
  • United States of America
  • United States Minor Outlying Islands
  • Venezuela (Bolivarian Republic of)
  • Virgin Islands (British)
  • Virgin Islands (U.S.)
  • Wallis and Futuna
  • Western Sahara

Research for Organizing

Research for Organizing

A Toolkit for Participatory Action Research from TakeRoot Justice

Download the Entire Chapter as a PDF


This section is designed to assist you with the planning phase of your Participatory Action Research (PAR) project. The section includes activities that will enable your group to make informed decisions about starting a research project, developing research goals and questions, choosing a research method, and creating a plan and timeline to guide your research. It also includes tools that will help your team to design and plan your overall research project.

Download Activity 2.1

Activity: 2.1 Developing Research Goals and Questions

Purpose of Activity:

The purpose of this activity is to have participants discuss the goals and purpose of the research project. After you’ve discussed what the research is trying to accomplish and why your organization is doing it, the participants will come up with research questions that will guide the research process.

By the End of Activity Participants Will:

  • Discuss the social or policy change you want to bring about through your research and campaign work
  • Discuss why research is useful or relevant to your organization or campaign
  • Determine the overarching questions you want to answer through your research

Before this Activity Participants Will Need to:

Be introduced to the basics of Participatory Action Research (PAR)

Decide that PAR is right for your organization

Tools Needed:

Copies of Tool 2.1: Guiding Questions for Developing Research Goals and Questions

Materials Needed:

Butcher paper

Research Goals

Research Question

Intended Audience:

Community Members

Time Needed:

Part I:  What and Why of PAR  (20 minutes)

Facilitator Instructions:

1. Provide a brief summary of your campaign to set the context for the discussion 2. Explain that today we will have a discussion about using participatory action research in our campaign. We are going to try to begin to develop goals and questions that can guide our research. 3.  Write “What?” at the top of a piece of butcher paper, and go through the questions below with the participants. Record responses on butcher paper, and keep the paper for later. (If you have 7 or more participants you can break out into small groups).

…is the social or policy change you want to bring about at the end of the day?

…are the overarching questions you want to answer through your research?

…information do you need to better understand and document the issues you are addressing?

…primary question do you want to answer with your research?

4.  Once you’ve answered each “What?” question sufficiently, write “Why?” on a new sheet of butcher paper. Go through each of the questions below with participants. Record responses.

…is research useful or important for your organization? Will it be used…

…internally, to inform and assess needs in the community?

…externally, to mobilize and educate community members or elected officials around an issue?

Part II:  Developing Research Goals (20 minutes)

  • Put up a piece of butcher paper that says “Research Goals: What you want to accomplish with your research?”
  • Facilitate a discussion based upon your group’s answer to the “What” and “Why” questions that leads the group to establish the goals of the research and the research questions.
  • Ask the question: based on the answers to the “What” and “Why” questions, what are our goals for this research? What do we want to accomplish through doing this research?
  • Ask people to popcorn responses and record their responses on butcher paper.
  • Explain that now that we have some research goals, we need to frame those goals as questions in order to conduct research.

Part III: Developing Research Questions (20 minutes)

  • Frame the activity: explain that part of being a researcher is to ask questions and find answers.  To design a research project you need to first figure out what big questions you want to answer.  We will use our list of goals to figure out what questions we want to ask
  • Put up a piece of butcher paper that says: “Research Questions: What big questions do you want to answer with your research?”  Also write an example of a research question on the butcher paper.  For example, if one of our goals is to document rapid development of luxury housing in our neighborhood, our question would be, “What is the current state of housing development in our neighborhood?”
  • Ask the question: based on the answers to the “What” and “Why” questions and the goals we just created, what big questions do we want to answer through our research?
  • Explain to the groups that these goals and questions will be the foundation for your research design and implementation.

Download Activity 2.2

Activity: 2.2 Choosing Your Research Method

This activity is designed to help organizers and members understand the various options for how they can conduct research and choose the research method(s) they will use.

  • Finalize research goals and questions
  • Understand relevant research methods
  • Discuss the strengths and weaknesses of different research methods
  • Decide the research method appropriate for your group

Develop research goals and research questions

Copies of Tool 2.2: Guiding Questions for Choosing a Research Method

Copies of Tool 2.3: PAR Menu of Methods

Post-it notes

Quantitative Data

Qualitative Data

Focus Groups

Community Mapping

Community Visioning

Secondary Data

Media Review

Literature Review

Community Members or Organizers

Part I: Nailing Down your Research Goals and Questions  (15 minutes)

  • Frame the activity in the context of your campaign: now that we’ve decided to do participatory research we need to dig into how to do it. There are a bunch of different ways we can conduct research so we need to explore these different research methods.
  • Put up the butcher paper with “Research Goals” and “Research Questions” from Section 2, Activity 1.
  • Ask the group, is anything missing?
  • Wrap it up: Summarize what has been said and explain that these goals and questions will help to determine which methods you will use to conduct your research.

Part II:  Brainstorm as a Big Group  (25 minutes)

  • Explain that now that we have determined some of our goals and research questions, we need to dig into how to do the research.
  • Next, facilitate a discussion that answers the questions: how do we do the research, when do we do it and where? Record responses on butcher paper, and keep butcher paper for Part 3 (This can also be done in break-out groups).

…can you document or better understand the issue? Do you need “hard” numbers (quantitative data) and/or stories of personal experience (qualitative data) or both?

…are you going to give legs to your research? What action strategies could you employ to make the research and report as impactful as possible?

…are the stakeholders in the issue? Who has interest? Who is affected?

…needs to have their voice be heard?

…are you trying to influence? Who has power over the issue?

…is your target audience (community members, elected officials, media)?

…will collect your data?

…can you find the people you need to talk to get your data?

…can you find existing information that is relevant to your research?

…can you go for support and assistance (non-profits, universities, government agencies)?

Part II:  Understanding the Research Methods  (35 minutes)

  • Choose 3-4 methods that you think are the most relevant to your project (from Tool T2.1 PAR Menu of Methods).
  • Break the participants into 3-4 groups and assign one method that you’ve chosen to each group.
  • Pass out Tool T2.1 “PAR Menu of Methods” to each group.
  • Tell each group to read over the description for the method they have been assigned and give them 5-7 minutes to make up a skit for that method.  Encourage them to be creative.
  • Have each small group perform their skit.
  • After each skit, facilitate a discussion with the full group.  Ask the group: what did you see in the skit? What do you think are the pros and cons of that method for our work?  Record the pros and cons list on butcher paper.

Part III:  Decide Your Research Method  (20 Minutes)

  • Place the butcher papers from each A2.2 activity next to each other at the focal point of the room.
  • First, ask a volunteer to read your responses to the “How” “Who” and “Where” questions from the first activity to remind everyone of your initial conversations.
  • Facilitate a discussion: now that we know more about each of the possible research methods, which methods align with the groups responses to the “How”, “Who” and “Where” questions?
  • Make a decision about which method(s) make the most sense for your project. Record the methods you choose to put into your research workplan (see Tool 2.3).

Download Activity 2.3

Activity: 2.3 Developing Your Research Timeline

This activity is designed to enable your research team to sit together and plan out the remaining steps of your research project. Through the activity, participants will devise a timeline that will map out all of the necessary steps in your project, and will specify who is going to be responsible for each step of the project. By the end of the activity you will have created a research timeline that you can use to guide the rest of your project.

By the End of this Activity You Will:

  • Map out all of the steps of your research project in a timeline
  • Decide who is going to do what and when they are going to do it
  • Create a system of accountability for your research project

Have been introduced to the basics of Participatory Action Research (PAR)

Have created the research goals and questions for your project

Have decided on your research method

Tool 2.4: Research Timeline Template

Data Report Back

Policy Recommendation

Members and Organizers that will be active in research process

Part I:  Creating Your Research Plan and Timeline  (15 minutes)

1.  Before the meeting prepare the room.

  • Prepare two pieces of butcher paper in advance; Butcher Paper 1:  a list of the main steps in PAR (listed below), Butcher Paper 2: recreate the table below on large sheets of butcher paper big enough so that you can write in each box. Depending on the specifics of your project you may need to modify this table.
  • Place the two pieces of butcher paper next to each other at the front of the room with the PAR steps to the left of the table.
  • Fill out the first three steps (Organizing Goal, Research Question, and Research Plan) in the table if you have already done them. Fill out any other steps that you have already discussed or figured out (for example you might have chosen someone to design the research instruments).

2.  Introduce the activity; today we are going to create our research plan. By the end of the meeting we will have completed a timeline of the research steps and will have split up who will do what. 3.  Describe the butcher paper sheets you have created. Describe that you will be using these sheets to create your timeline. 4.  Go through each of the PAR steps that you will use for your project and fill out the what, when and who of each step with participants. 5.  After you’ve completed the table, take a moment to congratulate everyone as you have now finished the planning stages of your research project! 6.  Keep all of the Butcher Paper sheets you created and use them to type up your Research Plan (see Tool 2.4 and T2.5:  Template for Research Work Plan and Research Timeline Template).

Download Tool 2.1

Tool: 2.1 Guiding Questions for Developing Research Goals and Questions

Descarga Herramienta 2.1 En Espanol


…is the social or policy change you want to bring about at the end of the day?________________________________________________________________________________________________________________

…are your organizing goals, and how can this research be helpful achieving these goals? ________________________________________________________________________________________________________________

…information do you need to better understand and document the issues you are addressing? ________________________________________________________________________________________________________________

…is research useful or important for your organization? ________________________________________________________________________________________________________________

… internally, to inform and assess needs in the community?          YES          NO


… externally, to mobilize and educate community members around an  issue?

YES        NO

…to support a specific policy campaign or influence policy and public debate around an issue?

YES           NO

Download Tool 2.2

Tool: 2.2 Guiding Questions for Choosing a Research Method

Descarga Herramienta 2.2 En Espanol

…  can you document or better understand the issue?  Do you need “hard” numbers (quantitative data) or stories of personal experience (qualitative data)?

Quantitative         Qualitative           Both


…  are you going to give legs to your research? What action strategies could you employ to make the research and report as effective as possible? ________________________________________________________

… are the stakeholders in the issue? Who has interest, who is affected? ________________________________________________________

…needs their voice to be heard? ________________________________________________________

…are you trying to influence? Who has power over the issue? ________________________________________________________

…is your target audience (community members, elected officials, media)? ________________________________________________________

…will collect your data? ________________________________________________________

… can you go to for information and other existing data? ________________________________________________________

…can you go for support and assistance (non-profits, universities, government agencies)? ________________________________________________________

… is the right time to do research? ________________________________________________________

…In your campaign? ________________________________________________________

…In the political context? ________________________________________________________

…In your organization? …In the political context? ________________________________________________________

Download Tool 2.3

Tool: 2.3 Participatory Action Research (PAR) Menu of Methods

Descarga Herramienta 2.3 En Espanol

  • Surveys-  Ask specific questions and tend to include short answer, multiple-choice, and scaled-answer questions. Surveys can be done online, through the mail, and can be written and filled out in person.  The most effective way to conduct surveys in support of organizing is in an in person “interview style” so that the surveyor can make personal connections with the respondent. Surveys are helpful for getting information or data from a wider group of people and are better for getting quantitative information like numbers, than they are for getting qualitative information, like people’s stories. Surveys can be helpful when making policy demands because elected officials, policymakers and the media tend to respond to hard numbers.
  • Interviews-  Are guided conversations about a specific topic, are often done one-on-one, and tend to use open-ended questions in order to get in-depth explanations.  Interviews are useful when you want to get more specific, detailed information than you would get from a survey and you want to get deeper into people’s experiences and personal stories. Interviews are appropriate when dealing with sensitive or personal information that people may not be comfortable writing on a survey or sharing in a group setting (such as a focus group). Interviews can also assist the organizing outreach process because they facilitate one-to-one interaction, but they can be more time intensive then surveys.
  • Focus Groups-  Are small group sessions (7-12 people) that are led by a facilitator in order to obtain opinions based on the research question.  Like interviews, focus groups are good for getting qualitative data, and are an effective way to get people’s personal stories, testimonies, and experiences from a group setting. They can also be useful for delving deeper into a specific issue or research question not fully addressed by another method.  Focus groups can be useful in allowing participants to bounce ideas and stories off of each other.  Due to the group setting, they can also be more challenging than interviews for discussing sensitive topics.
  • Community Mapping/Canvassing-  Is a process of documenting and visually presenting trends or patterns in a given community.  Community maps and canvassing can be used to document many physical, spatial dynamics of a neighborhood from new construction sites, to new luxury condos, to green spaces, to new businesses, to vacant lots, etc. This is an effective tool for tracking physical changes in a neighborhood, and specifically as a way to document the impact of gentrification on a neighborhood.
  • Community Visioning-  Is a process where group of community members come together to develop an alternative vision or proposal for the future of their community.  Visioning can be used to develop public policy demands and can be particularly useful when communities are working to impact the physical development of their community.  This can also be useful for groups working to influence a particular issue or policy.
  • Mystery Shopping-  Is a process where community members posing as customers call or visit businesses and document their experience and observations.  Usually mystery shoppers have a specific set of criteria they are looking for when they visit or call a business.  This is a good way to document employment practices, compliance with labor laws, and consumer fraud.
  • Secondary data-  Is data that comes from someone else’s research.  This is distinct from “primary data” which is original data that you collect through your own research in the field.  Secondary data is helpful for getting background information that will complement the ground-level information that comes from people’s experiences (primary data). It can also be helpful to do a bit of secondary data collection before you begin your primary data collection in order to focus your research questions and help you to develop your research instruments (such as surveys and interview guides). Secondary data can come from a variety of public and private sources, such as the U.S. Census Bureau, city and state agencies, research organizations and academic institutions.
  • Media Review-  Is a systematic review of a certain number of news articles or clips from a variety of sources about a specific topic to uncover the most common words or themes that emerge.  This can be used as background research to help inform your research design and can also be used on its own to give you data about how a specific issue is being presented or framed in the media.
  • Literature Review-  Is a review of existing articles, academic studies or reports in order to find out what information already exists about the topic you are exploring.  This can be part of your secondary research; can help inform your research questions and can help you identify gaps in research and information on a given issue.

Download Tool 2.4 as a Word Doc

Tool: 2.4 Research Work Plan Template

Why is This Tool Useful?

Descarga Herramienta 2.4 En Espanol

This tool will help to document your research plan and methodology.  It is also useful in developing a workplan, timeline and accountability mechanism for your project to make sure that each member of your research team is doing the work they have committed to doing and are keeping up with deadlines.   This can also be helpful in putting together proposals for funding or other support because you will have all the information about your project in one place. Below is a template for a research plan.  Sections can be shifted and deleted as needed.

Name of Organization(s):

Name of Research Project:

This section should include some background information about the social issue that your research will address and/ or the campaign that your research will support.

Overview of project

This section should provide a brief overview of the research project including what issue you are addressing and why, what information you plan to collect, whom you are collecting the information from and how you are collecting information (See Tools 2.1 and 2.2).

Goals of project

This section should include a bulleted list of what you hope to achieve through doing this research project.  Some examples include:

  • To gather current and detailed data from our community.
  • To develop skills and leadership of members.
  • To build the base of members in our organization.
  • To educate elected officials about our organization’s campaign.

Research Questions

This should include a bulleted list of the overarching questions you hope to answer through your research.  Research questions are different from survey or interview questions because they are broad and can help to guide the more specific questions you will ask in your surveys, interviews, focus groups, canvassing Tool, etc. Some examples include:

  • What is the impact of poor housing conditions on residents of Chinatown?
  • What types of benefits are workers getting and what are they not getting from their employers?
  • How do various policies and procedures at methadone programs affect participant’s access to methadone?
  • What is the current state of luxury housing development in low-income communities of color in NYC?

Methodology/Research Components

This section should include all the methods you will use to answer your research questions along with a short description for each method. Below are some examples, but you should feel free to chose other methods (see Tool 2.3)

  • Short survey:   This short survey will be focused on collecting updated and detailed data on x, y and z.  The goal will be to collect 500 surveys.  The surveys will be translated into Spanish and French languages and administered by members of our organization.
  • In Depth Interviews:  Members and organizers will conduct in depth interviews with 5-10 workers in order to collect qualitative data about x and y and to show z.
  • Secondary Research:  Members will conduct an analysis of current literature and data to support the findings from field research.
  • Media Review:  Members will review 100 articles found in local newspapers in the last three years that include the word “public housing” in the headline.  Researchers will identify the most prevalent words and themes in these articles.

Project Output

This section should include a few sentences about what you will create at the end of this project.  This could be a report, a 1 or 2 page summary of your findings, a map, a video, etc.

How the PAR Project Will Support Community Organizing

This section should explain how your research will support and be integrated into your organizing campaign.  Will your research help with leadership development? Help to build your base? Help to garner media attention about a policy issue you are fighting for?

This table should include all of the different tasks that you will need to complete for the research project, along with who will be responsible for completing the task and by what date.  The tasks will differ depending on which methods you chose but Tool 2.5 will provide a template as a place to start.

Download Tool 2.5 as a Word Doc

Tool: 2.5 Research Timeline Template

Download Tool 2.5 as a PDF

Download Tool 2.6 as a PDF

Tool: 2.6 Advisory Board Invitation Template

Download Tool 2.6 as a Word Doc

Tool 2.6:  Sample Advisory Board Invitation Template

Why is this tool useful?

Developing a Research Advisory Board can be a great way to bring together a team of resource allies to support and add capacity to your Participatory Action Research. Academics, lawyers or policy analysts that specialize in the issue you are researching are all good examples of potential advisors. We recommend bringing advisors together as a group early in the process and being clear about the role they will play and what they can expect from the process. Below is a sample letter you can send to invite advisors to an initial meeting. We also have a sample agenda for a Research Advisory Board meet (see Tool 2.7).


Dear ________________,

I hope you are well! I am writing to you to ask you to be a part of an exciting new research project of the  [YOUR ORGANIZATION’S NAME]  by serving on our advisory board.


As part of this work,   we are planning to conduct a participatory action research project focusing on [RESEARCH TOPIC].

Because of your familiarity with [ORGANIZATION NAME] and your expertise with these issues or strategies, I am reaching out to you in the hopes that you will serve on a Research Advisory Team to provide feedback on our research.  As an advisor, I am requesting that you participate in one or more of the following:

  • Read a draft of our report and provide feedback;
  • Participate in one or more conference calls about the report;
  • Provide feedback on policy recommendations;
  • Provide advice on how to best use the report to advance  [ORGANIZATION’S NAME] ’s advocacy and organizing goals.

Please let me know by  [INSERT DATE]  if you are willing to participate on this Research Advisory Team.  We will be scheduling for a meeting for  [INSERT DATE].  Please don’t hesitate to call  (XXX) XXX- XXXX  or email [ INSERT EMAIL HERE ] if you would like additional information or have further questions.  We hope you will join us in this important work!



Download Tool 2.7 as a PDF

Tool: 2.7 Sample Advisory Board Meeting Agenda Template

Download Tool 2.7 as a Word Doc

Developing a Research Advisory Board can be a great way to bring together a team of resource allies to support and add capacity to your Participatory Action Research. Academics, lawyers or policy analysts that specialize in the issue you are researching are all good examples of potential advisors. Once the Research Advisory Board (see Tool 2.6) is assembled, it is a good idea to bring the Board together as early in the research process as possible. The research plan should be more or less complete by this point (see Tool 2.4), and advisors can give valuable feedback on research goals and questions, methodology, project output and the timeline. The advisors should also walk away with a concrete understanding of their role in the work and what you will be asking of them in participating in the research process. It is also a good idea to make sure the research timeline is mostly complete (see Tool 2.5) because this will make planning next steps with the board easier. Below is a sample meeting agenda for the Research Advisory Board, which can be used to ensure that the meeting is productive and provides crucial feedback on the project.

Research Advisory Board Meeting

Download The Case Study

Case Study: 2.1 Center for Frontline Retail and CDP Report: Pathways to Success: The Need for Accessible, Appropriate Trainings for Retail Workers, 2017

Download the Report

in designing a research project what are the bases you consider

Background on the Organization and Issue

The Center for Frontline Retail (CFR) is a worker-led organization committed to improving the lives of retail workers through community organizing, industry analysis, and leadership development. CFR works to simultaneously elevate workers’ voices and raise standards in the retail sector. CFR’s prior research has shown that retail workers face discrimination and harassment in the workplace, along with unfair scheduling practices.

Through discussions with their members, CFR identified a lack of training opportunities for workers, impacting their ability to advance in the sector.  . CFR also noticed that women and people of color are disproportionately affected by the lack of training from employers and as a result lack opportunities for career advancement.

In order to document the lack of training and advancement opportunities for retail workers, and the disproportionate effect of this on women and people of color, CFR partnered with the Community Development Project on a participatory action research project in order to voice the concerns of retail workers and highlight CFR’s training model as a pathway for advancement. This project ultimately resulted in a report that describes workers’ desire for, and barriers to, training and advancement opportunities in the retail industry, outlines policies that would set aside money to train retail workers, and puts the CFR training model forward to train and educate entry level workers, as well as higher level training to grow within the retail industry.

Below is a description of the Center for Frontline Retail Research Project, based on the Participatory Action Research guiding framework  (see Tools  2.1  and  2.2 ).

Were the Organizing Goals connected to this research?

  • To generate data on the training needs of retail workers in NYC.
  • To document and generate data on the extent to which retail workers are offered training and education programs by their employers, and distinguish whether workers of color and women are able to access such programs.
  • To document the experiences of people of color and women working in the retail industry in accessing appropriate trainings and education programs.
  • To explore and document the existing training and education programs that are available to retail workers and their associated costs.

Overall questions did CFR want to answer through their research?

  • What is the current training and education landscape for retail workers in NYC?
  • What are the training and education needs of retail workers (with focus on women and people of color)?
  • What are the experiences of women and people of color working in retail in accessing training and other career advancement opportunities?

Is this research useful or important for CFR?

  • INTERNALLY: to base build and educate retail workers; to develop member leaders and their outreach skills.
  • EXTERNALLY: to inform a curriculum developed for retail workers that would provide crucial training for career advancement; put together the landscape of barriers that retail workers face in accessing education and training; put forward recommendations for retailers to adopt high road retail strategies.

Are the Stakeholders in this Issue?

  • Retail workers in New York City

Was CFR trying to influence?

  • New York City Council Members, Mayor’s Office of Workforce Development, retail employers and brands, developers of commercial retail spaces

Did CFR gather information (what methods did they use)?

  • SHORT SURVEY :   CFR members administered a survey to 300 retail workers in order to understand the training needs and existing training opportunities of retail workers working in general merchandise stores in New York City, specifically discount, fast fashion and high end stores. Retail workers were targeted during classes at the Center for Frontline Retail and when retail workers were on breaks throughout the work day.
  • FOCUS GROUPS:  In order to build and expand on the quantitative data gathered from surveys, CFR also conducted three focus groups with their members in order to collect qualitative data about the experiences and stories of retail workers accessing trainings in the workplace, and to show the barriers and discrimination faced by women and people of color.
  • SECONDARY RESEARCH : CDP conducted an analysis of current literature and data to support findings from research, and to document the current landscape of trainings, curriculum and education programs in retail.

Did Research support CFR’s organizing efforts?

  • The survey project provided opportunities to base build and educate community members. The focus groups provided member leaders with the opportunity to learn facilitation skills and a deepened understanding of the landscape of barriers facing workers.
  • The data collected through the research was written into a report and presented to key stakeholders in the retail sector, such as retail employers, the New York City Mayor’s Office of Workforce Development, and developers of commercial work spaces who could partner with CFR to provide training to potential retail workers.

Read the report  here . Read coverage of the report release in  Crains NY  and the  Associated Press .

  • Designing Your Research project
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Designing Research

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Our page Introduction to Research Methods explains that the philosophical approach that you take to the world, and to its investigation, underpins the methods that you use to carry out research.

This page explains some basic types of research, and their advantages and disadvantages.

Your philosophy, and therefore your choice of research methods, is likely to be influenced by many things: your colleagues’ views, your organisation’s approach, your supervisor’s beliefs, and your own experience.

There is no right or wrong answer to choosing your research methods.

However, the method you choose needs to answer your research question.

For example:

If you want to explore the reasons why people choose certain careers, you are going to need to talk to people. Counting the number of people choosing nursing will not tell you why these choices are made.

If, on the other hand, you want to know whether more people opt for caring professions, then you will want some hard data about applications to universities and colleges, and job applications.

Approaching Research Five Questions:

Whatever approach you choose for your research, you need to consider five questions:

What is the unit of analysis? For example, country, company or individual.

Are you relying on universal theory or local knowledge? In other words, will your results be generalisable, and produce universally applicable results, or are there local factors that will affect your results?

Will theory or data come first? Should you read the literature first, and then develop your theory, or will you gather your data and develop your theory from that? Recently, opinion seems to have swung towards this being an iterative process.

Will your study be cross-sectional or longitudinal? Are you looking at one point in time, or changes over time?

  • Will you verify or falsify a theory? You cannot conclusively prove any theory; the best that you can do is find nothing that disproves it. It is therefore easier to formulate a theory that you can try to disprove, because you only need one ‘wrong’ answer to do so.

All Swans are White

One way of thinking about this is to formulate a theory that all swans are white. To verify this, you would have to look at every swan in the world. In the UK, you can gather a vast amount of data that suggests that your theory is correct, but still not prove it conclusively.

To disprove it, in other words taking the falsification route, you simply have to find one swan which is not white. Visit a zoo or Australia to find a black swan and your theory can be discarded.

Some Basic Research Designs

There are several broad types of research design, some of which are broadly quantitative, some qualitative, and some mixed.

Experimental Designs

These usually involve two groups: an experimental group, which receives an intervention of some sort, and a control group, which either receives no intervention, or a non-effective one. Clinical trials are usually of this type. The aim of research of this type is to remove all possible alternative explanations for the results (high internal validity ) and to make them as generalisable as possible (high external validity ).

Useful when you want to test a particular intervention, and you can disguise whether it is being used or not. Less useful when you need to understand why something is happening.

Quasi-Experimental Designs

These are used when an experimental design would be ideal but is not possible, for example because of the length of time required for the study or the difficulty of keeping an experimental group separate from the control group. Researchers usually test before and after an intervention to see what effect it has had. Again, these types of studies try to maximise validity.

Useful when a full experimental design is not possible but you need that kind of separation of the groups. Less useful when you can carry out a full experimental design, or you need to understand why something is happening.

Survey Research

Surveys may be factual, inferential or exploratory. They may either start with an idea, and try to prove it by collecting information, or collect a large amount of information and see what emerges. The main issue with a survey is reliability : whether the survey accurately assesses the desired variable. Surveys are usually pre-tested on a small sample before being used more widely and, for this reason, many researchers choose to use established questionnaires rather than develop their own whenever possible. They can be used either on a large sample or as structured interviews on a smaller sample.

Useful when you want to gather data from lots of different people and you can formulate questions that can be answered fairly simply. Less useful when you want to explore individual experience in detail.

See our page: Surveys and Survey Design for more information.

Action Research and Cooperative Inquiry

This type of research assumes that the researcher is a key part of the research, rather than an external force. It emerged from the idea that the best way to learn about an organisation is to try to change it, and also that those involved in change should be encouraged to influence the change.

Useful when you, the researcher, are part of the organisation. Less useful when you need to gather hard data from an objective viewpoint.


In this type of research, the researcher immerses him or herself in the research setting and becomes a part of the group under study. Some of the original ethnographers went to live with remote tribes in the jungle. Ethnographic studies are very authentic : the researcher understands the organisation from the inside.

Useful for researchers who are internal to the organisation that they are studying, which often happens for those on executive MBAs. Less useful when you need an objective study.

Narrative approaches

These approaches gather information by developing or gathering stories about a particular subject.

Useful for generating a ‘group history’ of events, or finding out about relationships or values. Less useful when you need an objective approach.

Case studies

These take either one or several examples, and study it or them in detail, then draw out the more general lessons for wider application. Researchers may try to take a more rigorous approach to demonstrating validity, and ensure that logic is applied to any comparisons, or focus on creating a detailed picture. Although a case study cannot prove a theory, it can be used to disprove one if the data from the organisation do not fit the theory.

Useful when you want to find out about one organisation, when one organisation is considered to be an exemplar, or to compare a few organisations and identify the key differences in approach. Less useful for drawing generalised lessons that can be applied to any other organisation, although there may be some.

Grounded theory

This approach examines the same event or process in several different settings or organisations. The researcher carries out a process of sampling, making comparisons between samples, using these to evolve a theory. When no new insights emerge from new data, the researcher has reached theoretical saturation . Some experts recommend no prior reading, but others suggest reading the literature beforehand to familiarise yourself with the territory.

Useful when you have plenty to time to immerse yourself and do repeat samplings, testing your data on subsequent samples. Less useful when you need to do something quickly and produce results immediately.

Mixing and Matching: A Word of Warning

Mixing different research methods from different philosophical backgrounds may strengthen a piece of research by adding to the generalizability, while providing richer insights.

However, there is a danger that mixing methods in this way simply adds another layer of complexity and the two parts of the design will not join together coherently.

The researcher also needs to be skilled in the use of both types of method and not just one.

The most important aspect of the research design is that it answers your research question. If this can best be done by using mixed methods, then go ahead.

If, however, one single type of study will adequately answer your question, then it is probably best not to complicate it.

Continue to: Quantitative and Qualitative Research Methods Sampling and Sample Design

See also: Surveys and Survey Design Interviews for Research | Focus Groups

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  • Advice for Choosing a Research Project

By Margo R. Monroe


After joining a lab, the focus shifts to choosing an unexplored and impactful research topic that aligns with your interests. We've outlined some important factors to consider and summarize helpful advice from the successful PIs who were previously featured in " 9 Tips to Achieve Success in Academia ".

Important factors to consider when choosing a research project

person choosing between lab options

What will the impact be in a best case scenario?  If you get your dream results, what will your paper look like? What will be the impact on your field? You want to choose a research question that people (especially you!) care about.

Have you critically evaluated your plan?  Have you read the relevant literature to understand where the field is today? Have you talked to veterans in the lab or the field? What are possible pitfalls in your strategy and how can you mitigate them? If you were to write a grant for this project, what would be your critical experiments and why?

What techniques and skills do you need to use to reach these milestones? Can you get assistance from people who have the required expertise to help move your project forward? Most projects typically require a diverse set of skills. It is important to know who in the lab and/or what facilities are available in order to realize your project ideas. What mentors are available for guidance, intelligent discussion, and/or brainstorming sessions to maximize productivity and direction of the project?

  • What is your timeline?  A typical research project can take several years to complete and has multiple benchmarks. Think about what your personal goals are and set milestones along the way so that you don't get stuck doing the same experiment for too long. Keep evaluating your project along the way.

Advice from principal investigators

Tom Ellis  highlights the importance of keeping up-to-date with the literature of a couple of well-known journals that discuss general science in the area of interest. “Have a look at what others have done recently that has been a big hit, and especially look at the new tools and methods that have been developed. Can you think of a project that combines an exciting new method or approach with another in a way not done before in your field?” He points out to “not be shackled by your own subject - maybe something used in astrophysics can be applied to fungal biology.”

Connie Cepko  advises students to consider their goal of PhD training when selecting a research topic. The end point of training is not to become a pro in a field, but to be trained to think and perform like a scientist. Researchers should  pick a topic that “looks at the complexity of biology and break apart a piece that can address a topic in a mechanistic way using the technology available.” Choosing a research project “entails good judgement with the current technology to identify a problem, asking what approach will I take and what can I learn, learning the difference between good and bad data, and knowing how to follow the design, execute, analyze, repeat pathway that is required of scientists.”

Professor George Church  encourages graduate students and postdocs to follow their passions and dive into a project that aligns with your dreams. He also highlights the importance of combining “new discoveries or technologies increase chances that your project will be fresh as well.”

Don't underestimate the importance of choosing a solid research topic and approach . At Addgene , we've heard of labs where new hires spend the first 3 months reading and writing a proposal before even touching a pipetteman. Take the time to generate new ideas and think about them critically before diving in.

Research projects are designed to train graduate students and postdocs to think analytically and critically. Passion fuels the drive to continue persuing milestones and working hard. Being patient, being selective, and talking to peers and mentors will help elucidate which project is right for you.


  • Thank you to  Dr. Tom Ellis  (Imperial College London),  Dr. Connie Cepko  (Harvard Medical School) , and  Dr. George Church  (Harvard Medical School) for taking the time to speak with us about adding new scientists to their labs.
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Doing Qualitative Research in Language Education pp 43–60 Cite as

Designing Qualitative Studies

  • Seyyed-Abdolhamid Mirhosseini 2  
  • First Online: 11 November 2020

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The qualitative research question provides the conceptual base and the direction for actual research involvements. But the actual process of ‘doing’ research involves gathering evidence (data) and making sense of collected data bodies. The successful handling of these processes of dealing with data—that are multifaceted and quite challenging processes—requires some prior planning. The planning is a complex theoretical undertaking and is compounded by numerous practical considerations. Moreover, in addition to a priori planning for the project, you need to constantly assess the early plan and modify it to meet the emerging conditions of the inquiry process. This vibrant and challenging process of planning for your qualitative research is called ‘designing’. This chapter is about designing qualitative language education research as the link between the theoretical considerations and the practical side of the research endeavor.

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Atkinson, P., Delamont, S., & Hammersley, M. (1988). Qualitative research traditions: A British response to Jacob. Review of Educational Research Summer, 58 (2), 231–250.

Article   Google Scholar  

Barkhuizen, G. (2011). Narrative knowledging in TESOL. TESOL Quarterly, 45 (3), 391–414.

Barkhuizen, G. (2020). Core dimensions in narrative inquiry. In J. McKinley & H. Rose (Eds.), The Routledge handbook of research methods in applied linguistics (pp. 188–198). London: Routledge.

Google Scholar  

Barkhuizen, G., Benson, P., & Chik, A. (2014). Narrative inquiry in language teaching and learning research . London: Routledge.

Brown, J. D. (2004). Resources on quantitative/statistical research for applied linguists. Second Language Research, 20 (4), 372–393.

Brown, J. D. (2014). Mixed methods research for TESOL . Edinburgh, Scotland: Edinburgh University Press.

Book   Google Scholar  

Casanave, C. P. (2012). Heading in the wrong direction? A response to Porte and Richards. Journal of Second Language Writing, 21 (3), 296–297.

Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis . London: Sage.

Denzin, N. K., & Giardina, M. D. (Eds.). (2014). Qualitative inquiry outside the academy . Walnut Creek, CA: Left Coast Press.

Dornyei, Z. (2007). Research methods in applied linguistics: Quantitative, qualitative, and mixed methodologies . Oxford, UK: Oxford University Press.

Duff, P. (2013). Ethnographic research in applied linguistics: Exploring language teaching, learning, and use in diverse communities . London: Routledge.

Duff, P., & Bell, J. S. (2002). Narrative inquiry: More than just telling stories. TESOL Quarterly, 36 (2), 207–2131.

Flick, U. (2004). Design and process in qualitative research. In U. Flick, E. von Kardorff, & I. Steinke (Eds.), A companion to qualitative research (pp. 146–152). London: Sage.

Flick, U. (2007). Designing qualitative research . London: Sage.

Flick, U. (2009). An introduction to qualitative research (4th ed.). London: Sage.

Flick, U. (Ed.). (2014). The Sage handbook of qualitative data analysis . London: Sage.

Hadley, G. (2020). Grounded theory method. In J. McKinley & H. Rose (Eds.), The Routledge handbook of research methods in applied linguistics (pp. 264–275). London: Routledge.

Hashemi, M. R. (2020). Expanding the scope of mixed methods research in applied linguistics. In J. McKinley & H. Rose (Eds.), The Routledge handbook of research methods in applied linguistics (pp. 39–51). London: Routledge.

Jacob, E. (1987). Qualitative research traditions: A review. Review of Educational Research, 57 (1), 1–50.

Knapp, M. S. (2017). The practice of designing qualitative research on educational leadership: Notes for emerging scholars and practitioner-scholars. Journal of Research on Leadership Education, 12 (1), 26–50.

Koro-Ljungberg, M., & Bussing, R. (2013). Methodological modifications in a longitudinal qualitative research design. Field Methods, 25 (4), 423–440.

Lin, A. (2014). Critical discourse analysis in applied linguistics: A methodological review. Annual Review of Applied Linguistics, 34 , 213–232.

Lowe, R. J., & Lawrence, L. (Eds.). (2020). Duoethnography in English language teaching research: Reflection and classroom application . Clevedon, UK: Multilingual Matters.

Mason, J. (2002). Qualitative researching (2nd ed.). London: Sage.

Maxwell, J. A. (2013). Qualitative research design: An interactive approach . London: Sage.

Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). San Francisco: Jossey-Bass.

Mirhosseini, S. A. (2018a). Mixed methods research in TESOL: Procedures combined or epistemology confused? TESOL Quarterly, 52 (2), 468–478.

Mirhosseini, S. A. (2018b). An invitation to the less-treaded path of autoethnography in TESOL research. TESOL Journal, 9 (1), 76–92.

Riazi, A. M. (2017). Mixed methods research in language teaching and learning . London: Equinox Publishing.

Starfield, S. (2020). Autoethnography and critical ethnography. In J. McKinley & H. Rose (Eds.), The Routledge handbook of research methods in applied linguistics (pp. 165–175). London: Routledge.

ten Have, P. (2004). Understanding qualitative research and ethnomethodology . London: Sage.

Trainor, A. A., & Graue, E. (2013). Reviewing qualitative research in the social sciences . London: Routledge.

Wei, L. (2020). Ethnography: Origins, features, accountability and criticality. In J. McKinley & H. Rose (Eds.), The Routledge handbook of research methods in applied linguistics (pp. 154–164). London: Routledge.

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What is design research methodology and why is it important?

What is design research.

Design research is the process of gathering, analyzing and interpreting data and insights to inspire, guide and provide context for designs. It’s a research discipline that applies both quantitative and qualitative research methods to help make well-informed design decisions.

Not to be confused with user experience research – focused on the usability of primarily digital products and experiences – design research is a broader discipline that informs the entire design process across various design fields. Beyond focusing solely on researching with users, design research can also explore aesthetics, cultural trends, historical context and more.

Design research has become more important in business, as brands place greater emphasis on building high-quality customer experiences as a point of differentiation.

Elevate Your Brand's Potential with Qualtrics

Design research vs. market research

The two may seem like the same thing at face value, but really they use different methods, serve different purposes and produce different insights.

Design research focuses on understanding user needs, behaviors and experiences to inform and improve product or service design.  Market research , on the other hand, is more concerned with the broader market dynamics, identifying opportunities, and maximizing sales and profitability.

Both are essential for the success of a product or service, but cater to different aspects of its lifecycle.

Design research in action: A mini mock case study

A popular furniture brand, known for its sleek and simple designs, faced an unexpected challenge: dropping sales in some overseas markets. To address this, they turned to design research – using quantitative and qualitative methods – to build a holistic view of the issue.

Company researchers visited homes in these areas to interview members of their target audience and understand local living spaces and preferences. Through these visits, they realized that while the local customers appreciated quality, their choices in furniture were heavily influenced by traditions and regional aesthetics, which the company's portfolio wasn’t addressing.

To further their understanding, the company rolled out surveys, asking people about their favorite materials, colors and furniture functionalities. They discovered a consistent desire for versatile furniture pieces that could serve multiple purposes. Additionally, the preference leaned towards certain regional colors and patterns that echoed local culture.

Armed with these insights, the company took to the drawing board. They worked on combining their minimalist style with the elements people in those markets valued. The result was a refreshed furniture line that seamlessly blended the brand's signature simplicity with local tastes. As this new line hit the market, it resonated deeply with customers in the markets, leading to a notable recovery in sales and even attracting new buyers.

design research method image

When to use design research

Like most forms of research, design research should be used whenever there are gaps in your understanding of your audience’s needs, behaviors or preferences. It’s most valuable when used throughout the product development and design process.

When differing opinions within a team can derail a design process, design research provides concrete data and evidence-based insights, preventing decisions based on assumptions.

Design research brings value to any product development and design process, but it’s especially important in larger, resource intensive projects to minimize risk and create better outcomes for all.

The benefits of design research

Design research may be perceived as time-consuming, but in reality it’s often a time – and money – saver that can. easily prove to be the difference between strong product-market fit and a product with no real audience.

Deeper customer knowledge

Understanding your audience on a granular level is paramount – without tapping into the nuances of their desires, preferences and pain points, you run the risk of misalignment.

Design research dives deep into these intricacies, ensuring that products and services don't just meet surface level demands. Instead, they can resonate and foster a bond between the user and the brand, building foundations for lasting loyalty .

Efficiency and cost savings

More often than not, designing products or services based on assumptions or gut feelings leads to costly revisions, underwhelming market reception and wasted resources.

Design research offers a safeguard against these pitfalls by grounding decisions in real, tangible insights directly from the target market – streamlining the development process and ensuring that every dollar spent yields maximum value.

New opportunities

Design research often brings to light overlooked customer needs and emerging trends. The insights generated can shift the trajectory of product development, open doors to new and novel solutions, and carve out fresh market niches.

Sometimes it's not just about avoiding mistakes – it can be about illuminating new paths of innovation.

Enhanced competitive edge

In today’s world, one of the most powerful ways to stand out as a business is to be relentlessly user focused. By ensuring that products and services are continuously refined based on user feedback, businesses can maintain a step ahead of competitors.

Whether it’s addressing pain points competitors might overlook, or creating user experiences that are not just satisfactory but delightful, design research can be the foundations for a sharpened competitive edge.

Design research methods

The broad scope of design research means it demands a variety of research tools, with both numbers-driven and people-driven methods coming into play. There are many methods to choose from, so we’ve outlined those that are most common and can have the biggest impact.

four design research methods

This stage is about gathering initial insights to set a clear direction.

Literature review

Simply put, this research method involves investigating existing secondary research, like studies and articles, in your design area. It's a foundational method that helps you understand current knowledge and identify any gaps – think of it like surveying the landscape before navigating through it.

Field observations

By observing people's interactions in real-world settings, we gather genuine insights. Field observations are about connecting the dots between observed behaviors and your design's intended purpose. This method proves invaluable as it can reveal how design choices can impact everyday experiences.

Stakeholder interviews

Talking to those invested in the design's outcome, be it users or experts, is key. These discussions provide first-hand feedback that can clarify user expectations and illuminate the path towards a design that resonates with its audience.

This stage is about delving deeper and starting to shape your design concepts based on what you’ve already discovered.

Design review

This is a closer look at existing designs in the market or other related areas. Design reviews are very valuable because they can provide an understanding of current design trends and standards – helping you see where there's room for innovation or improvement.

Without a design review, you could be at risk of reinventing the wheel.

Persona building

This involves creating detailed profiles representing different groups in your target audience using real data and insights.

Personas help bring to life potential users, ensuring your designs address actual needs and scenarios. By having these "stand-in" users, you can make more informed design choices tailored to specific user experiences.

Putting your evolving design ideas to the test and gauging their effectiveness in the real world.

Usability testing

This is about seeing how real users interact with a design.

In usability testing you observe this process, note where they face difficulties and moments of satisfaction. It's a hands-on way to ensure that the design is intuitive and meets user needs.

Benchmark testing

Benchmark testing is about comparing your design's performance against set standards or competitor products.

Doing this gives a clearer idea of where your design stands in the broader context and highlights areas for improvement or differentiation. With these insights you can make informed decisions to either meet or exceed those benchmarks.

This final stage is about gathering feedback once your design is out in the world, ensuring it stays relevant and effective.

Feedback surveys

After users have interacted with the design for some time, use feedback surveys to gather their thoughts. The results of these surveys will help to ensure that you have your finger on the pulse of user sentiment – enabling iterative improvements.

Remember, simple questions can reveal a lot about what's working and where improvements might be needed.

Focus groups

These are structured, moderator-led discussions with a small group of users . The aim is for the conversation to dive deep into their experiences with the design and extract rich insights – not only capturing what users think but also why.

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  1. PPT

    in designing a research project what are the bases you consider

  2. Writing a Research Proposal

    in designing a research project what are the bases you consider

  3. Research Proposal How to Write: Detail Guide and Template

    in designing a research project what are the bases you consider

  4. (PDF) Chapter 3 Planning and Designing research projects (The research

    in designing a research project what are the bases you consider

  5. How to Do a Research Project: Step-by-Step Process

    in designing a research project what are the bases you consider

  6. What should the research proposal process look like?

    in designing a research project what are the bases you consider


  1. Top 10 Practical Inventions and Crafts from High Level Handyman

  2. Top 10 Practical Inventions and Crafts from High Level Handyman

  3. Designing a Research Project Dissertation for Mcom Students & Research Scholars

  4. Shocking Details Emerge As CIA Psychics Expose Underground Alien Base!

  5. Aug 19 Webinar 58 Designing Research for DEI Practical Questions and Applications

  6. Research Methodology


  1. What Is a Research Design

    Step 1: Consider your aims and approach Step 2: Choose a type of research design Step 3: Identify your population and sampling method Step 4: Choose your data collection methods Step 5: Plan your data collection procedures Step 6: Decide on your data analysis strategies Other interesting articles Frequently asked questions about research design

  2. Research Design

    Step 1: Consider your aims and approach Step 2: Choose a type of research design Step 3: Identify your population and sampling method Step 4: Choose your data collection methods Step 5: Plan your data collection procedures Step 6: Decide on your data analysis strategies Frequently asked questions Introduction Step 1 Step 2 Step 3 Step 4 Step 5

  3. 2 Considerations in Designing Your Research Approach

    Considerations in Designing Your Research Approach - Practical Research: A Basic Guide to Planning, Doing, and Writing 2 Considerations in Designing Your Research Approach

  4. Research: a Practical Handbook

    If your research project is larger than you can complete in one semester, you are strongly encouraged to think about an iterative design using the principles in Planning Research Projects. Alternately, if your research project has a substantial curriculum development aspect, you should consider Design-Based Research (DBR).

  5. Research Design Considerations

    Alignment of the researcher's worldview (ie, ontology and epistemology) with methodology (research approach) and methods (specific data collection, analysis, and interpretation tools) is key to quality research design.

  6. PDF 1 Designing and Managing Research Projects: An overview

    4 Designing and managing your research project If you are a largely a newcomer to research and have never designed or undertaken a research project before, it is probably wise to start the book at the beginning and work through each of the chapters systematically. This should provide a fairly good general

  7. 3.4: Components of a Research Project

    When designing a research project, be sure to think about, plan for, and identify a research question, a review of literature, a research strategy, research goals, units of analysis and units of observation, key concepts, method (s) of data collection, population and sample, and potential ethical concerns. A research proposal is also important ...

  8. A Beginner's Guide to Starting the Research Process

    Step 4: Create a research design. The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you'll use to collect and analyze it, and the location and timescale of your research. There are often many possible paths you can take to answering ...

  9. Designing and Proposing Your Research Project

    Designing your own study and writing your research proposal takes time, often more so than conducting the study. This practical, accessible guide walks you through the entire process. You will learn to identify and narrow your research topic, develop your research question, design your study, and choose appropriate sampling and measurement ...

  10. Design of Research Projects

    A research design can be understood as a plan for how to organise a research project to make sure we get from questions to answers (Yin, 1984, p. 28). In this plan we work out and make visible the logical structure of the project (De Vaus & de Vaus, 2001 ).

  11. How to design a scientific research project

    Now that you have a general research question, you need to develop specific, testable hypotheses. This might be a cyclical process with the next step, designing an experiment. You want to write a specific hypothesis, then think of how you might go about testing it.

  12. LibGuides: Project Planning for the Beginner: Research Design

    This Sage Research Methods tool is designed for the first time researcher to guide you through your research project. Each concept has a specif meaning in terms of research projects. ... you will also see the term "research design" used in other types of research. Below is a list of possible research designs you might encounter or adopt for ...

  13. Research Design

    Design. Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project — the samples or groups, measures, treatments or programs, and methods of assignment — work together to try to address the central research questions.

  14. (PDF) Basics of Research Design: A Guide to selecting appropriate

    Research Design Basics of Research Design: A Guide to selecting appropriate research design Authors: Bostley Muyembe Asenahabi Alupe University Abstract and Figures For a research to be...

  15. Research Design 101: A Guide To Planning Experiment Design

    October 3, 2018 UX Research Every day, we conduct research. Every research study has its own purpose it lines up with. But how do our researchers plan their research? What methods for designing research reflect the goals and delivers results? In this article, we go back to the very basics of research and its types.

  16. How to plan a research project

    Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won't delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis.

  17. Approaches to Designing a Research Project

    The approach you use combined with the strategy of designing your project is important. These five strategies are the typical academic writing options: Survey research - As it implies, survey research is based on a collection of data obtained through surveying a specific pool of participants who fit a required demographic. The results are then ...

  18. Designing Your Research Project

    Designing Your Research Project Getting Your Data I. Surveys II. Interviews III. Focus Groups IV. Community Mapping V. Community Visioning VI. Mystery Shopping VII. Field Notes and Observations Entering Your Data Into a Database Analyzing Your Data Presenting and Packaging the Report Releasing the Report Glossary of Terms Tips for Facilitators

  19. How to Create a Research Design Strategy for Your Project

    Research design is the plan and strategy that guides your research process. It helps you define your research question, choose your methods, collect and analyze your data, and interpret...

  20. Designing Research

    The researcher also needs to be skilled in the use of both types of method and not just one. The most important aspect of the research design is that it answers your research question. If this can best be done by using mixed methods, then go ahead. If, however, one single type of study will adequately answer your question, then it is probably ...

  21. Advice for Choosing a Research Project

    The end point of training is not to become a pro in a field, but to be trained to think and perform like a scientist. Researchers should pick a topic that "looks at the complexity of biology and break apart a piece that can address a topic in a mechanistic way using the technology available.". Choosing a research project "entails good ...

  22. Designing Qualitative Studies

    The components and concerns about a project that you need to consider in designing your qualitative language education research can be placed in three main categories plus two sets of additional considerations: the first main category includes issues of purpose, theoretical bases, and the research question; the second one is about a diversity ...

  23. What is design research methodology and why is it important?

    Design research offers a safeguard against these pitfalls by grounding decisions in real, tangible insights directly from the target market - streamlining the development process and ensuring that every dollar spent yields maximum value. New opportunities. Design research often brings to light overlooked customer needs and emerging trends.