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Research Roundup: How Technology Is Transforming Work

• Dagny Dukach

New studies explore its impact on hiring, employee experience, and more.

Digital technologies promise to bring new levels of productivity and efficiency in a wide variety of applications and organizations. But how are they transforming the experience of the employees who actually interact with them every day? In this research roundup, we share highlights from several recent studies that explore the nuanced ways in which technology is influencing today’s workplace and workforce — including both its undeniable benefits and substantial risks.

From AI recruiting tools to industrial automation and robotic assistants, new digital technologies are transforming the modern workplace. Many of these systems promise to improve efficiency, productivity, and well-being — but how are they actually affecting the people who interact with them every day?

• Dagny Dukach is a former associate editor at Harvard Business Review.

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Articles on Information technology

Displaying 1 - 20 of 59 articles.

An anonymous coder nearly hacked a big chunk of the internet. How worried should we be?

Sigi Goode , Australian National University

Maps shape our lives – showing us not just where we are, but who we are

Mike Duggan , King's College London

How better and cheaper software could save millions of dollars while improving Canada’s health-care  system

Joshua M. Pearce , Western University

Artificial intelligence is already in our hospitals. 5 questions people want answered

Stacy Carter , University of Wollongong ; Emma Frost , University of Wollongong ; Farah Magrabi , Macquarie University , and Yves Saint James Aquino , University of Wollongong

How will AI affect workers? Tech waves of the past show how unpredictable the path can be

Bhaskar Chakravorti , Tufts University

Remembering South Africa’s “Grand Geek” Barry Dwolatzky - engineer and programming pioneer

Estelle Trengove , University of the Witwatersrand

How hiring more women IT experts improves cybersecurity risk management

Camélia Radu , Université du Québec à Montréal (UQAM) and Nadia Smaili , Université du Québec à Montréal (UQAM)

The information age is starting to transform fishing worldwide

Nicholas P. Sullivan , Tufts University

How AI is shaping the cybersecurity arms race

Sagar Samtani , Indiana University

Instagram Kids: tech development must move from usability to safety

Fiona Carroll , Cardiff Metropolitan University and Ana Calderon , Cardiff Metropolitan University

COVID-19 revealed how sick the US health care delivery system really is

Elizabeth A. Regan , University of South Carolina

Ontario’s digital health program has a data quality problem, despite billions in spending

Linying Dong , Toronto Metropolitan University and Karim Keshavjee , University of Toronto

Australia, fighting Facebook, is the latest country to struggle against foreign influence on journalism

Vanessa Freije , University of Washington

What South Africa’s teachers brought to the virtual classroom during  COVID-19

Mmaki Jantjies , University of the Western Cape

Privacy, perceptions and effectiveness: the challenges of developing coronavirus contact-tracing apps

Roxana Ologeanu-Taddei , Université de Montpellier

South Africa would gain from co-operation among BRICS countries on beneficiation

Byelongo Elisée Isheloke , University of Cape Town

With the increase in remote work, businesses need to protect themselves against cyberattacks

Michael Parent , Simon Fraser University

The lack of women in cybersecurity leaves the online world at greater risk

Nir Kshetri , University of North Carolina – Greensboro

Coronavirus: the first big test of the information age and what it could mean for privacy

Alistair S. Duff , Edinburgh Napier University

Australia’s digital competitiveness is slipping. Here’s how we can catch up

David Tuffley , Griffith University

Related Topics

• Artificial intelligence (AI)
• Coronavirus
• Cybersecurity
• Digital economy
• Public health

Top contributors

Director of UWA Centre for Software Practice, The University of Western Australia

Lecturer in Software Engineering, Monash University

Head, The Cyber Academy, Edinburgh Napier University

Senior Lecturer in Applied Ethics & CyberSecurity, Griffith University

Assistant Professor in Management of Information Sytems, Propedia

Senior Lecturer, Loughborough University

Lecturer, School of Information Studies, Charles Sturt University

Associate Director Student Experience, Monash University

ESRC Future Research Leader Fellow, The University of Edinburgh

Lecturer in Computer Science, University of Hull

Senior Lecturer in Computing, Goldsmiths, University of London

Professor of Cybersecurity, School of Computer Science and Informatics, De Montfort University

Emeritus Professor of General Practice, University of Sydney

PhD Research Student, Loughborough University

Senior Lecturer, Electrical and Computer Engineering, RMIT University

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• 04 Jun 2024
• Research & Ideas

Navigating Consumer Data Privacy in an AI World

Consumers expect companies to do everything they can to protect their personal data, but breaches continue to happen at an alarming rate. Eva Ascarza and Ta-Wei Huang say companies must take bold steps to proactively manage customers’ sensitive data if they want to earn trust and remain competitive.

• 16 Jan 2024
• Cold Call Podcast

How SolarWinds Responded to the 2020 SUNBURST Cyberattack

In December of 2020, SolarWinds learned that they had fallen victim to hackers. Unknown actors had inserted malware called SUNBURST into a software update, potentially granting hackers access to thousands of its customers’ data, including government agencies across the globe and the US military. General Counsel Jason Bliss needed to orchestrate the company’s response without knowing how many of its 300,000 customers had been affected, or how severely. What’s more, the existing CEO was scheduled to step down and incoming CEO Sudhakar Ramakrishna had yet to come on board. Bliss needed to immediately communicate the company’s action plan with customers and the media. In this episode of Cold Call, Professor Frank Nagle discusses SolarWinds’ response to this supply chain attack in the case, “SolarWinds Confronts SUNBURST.”

• 20 Jun 2023

Looking to Leave a Mark? Memorable Leaders Don't Just Spout Statistics, They Tell Stories

That killer fever chart in your slide deck might not be as impressive as you think. In fact, your audience might soon forget that critical data point. If you want them to remember your message, research by Thomas Graeber suggests that nothing sticks to the mind like a good story.

• 15 Nov 2022

Why TikTok Is Beating YouTube for Eyeball Time (It’s Not Just the Dance Videos)

Quirky amateur video clips might draw people to TikTok, but its algorithm keeps them watching. John Deighton and Leora Kornfeld explore the factors that helped propel TikTok ahead of established social platforms, and where it might go next.

• 12 Apr 2022

Swiping Right: How Data Helped This Online Dating Site Make More Matches

Machine learning might have the answer to an age-old dating conundrum: Who makes the first move? Research by Edward McFowland probes how data can spur more digital interactions, with potentially wide-reaching implications. Open for comment; 0 Comments.

• 15 Sep 2021

Don't Bring Me Down: Probing Why People Tune Out Bad News

People often go out of their way to avoid unpleasant information, but not always for the reasons you might expect. Research by Christine Exley and colleagues. Open for comment; 0 Comments.

• 11 May 2021
• Working Paper Summaries

Time Dependency, Data Flow, and Competitive Advantage

The perishability of data has strategic implications for businesses that provide data-driven products and services. This paper illustrates how different business areas might differ with respect to the rate of decay in data value and the importance of data flow in their operations.

• 24 Mar 2020

Free Riding in Loan Approvals: Evidence From SME Lending in Peru

Using data from a large Peruvian bank trying to expand credit access to small and medium enterprises, this study shows that competing lenders use one another’s loan approvals as an input into their own approval process. Such “free riding” has great impact on market outcomes and might warrant policy intervention.

• 11 Dec 2019

When to Apply?

Using a series of experiments, the authors studied gender differences in how job-seekers perceive their own qualifications for different opportunities and how this affects their decision to apply. Results suggest that soft touch employer interventions can improve the diversity of applicant pools even if candidate beliefs about their own ability are unchanged.

• 02 May 2019
• Sharpening Your Skills

How To Ask Better Questions

To make the best decisions, managers must ask the right questions. This collection of past studies by Harvard Business School researchers will help you gather the critical information needed to prepare for action. Open for comment; 0 Comments.

• 28 Nov 2018

On Target: Rethinking the Retail Website

Target is one big-brand retailer that seems to have survived and even thrived in the apocalyptic retail landscape. What's its secret? Srikant Datar discusses the company's relentless focus on online data. Open for comment; 0 Comments.

• 06 Jun 2018

Complex Disclosure

This study shows that companies looking to hide unfavorable information might strategically be making contract terms unnecessarily complex, harming consumers and undermining the effectiveness of disclosure. These results highlight a role for regulation that would encourage simpler forms of disclosure.

• 30 Mar 2018
• What Do You Think?

What Should Mark Zuckerberg Do?

SUMMING UP: Facebook doesn't necessarily need a better data-privacy policy, James Heskett's readers suggest. Instead, Mark Zuckerberg needs a new business model. Open for comment; 0 Comments.

• 23 Feb 2018

Trade Creditors' Information Advantage

Trade credit represents about a quarter of the liabilities of US firms. There are several theories explaining this fact. This study reexamines whether suppliers hold private information about their trade partners, by analyzing their behavior in bankruptcy.

• 11 Jan 2018

Brokers and Order Flow Leakage: Evidence from Fire Sales

This study finds that brokers tend to reveal the occurrence of a fire sale to their best clients, allowing them to generate significant profits by predating on the liquidating fund. Such information leakage comes at the expense of higher price impact, and leads to a more costly liquidation for the fire sale originator.

• 03 Nov 2016

Ideological Segregation among Online Collaborators: Evidence from Wikipedians

This study analyzes the dynamics supporting or undermining segregated conversations. Among the findings: In spite of their great differences, contributors on Wikipedia tend to move toward less segregated conversations. Contributors’ positions become more neutral over time, not more extreme. In addition, the conflict resolution mechanisms and the mix of informal and formal norms at Wikipedia play an important role in encouraging a community that works toward a neutral point of view.

• 29 Jun 2015

Consumer-centered Health Care Depends on Accessible Medical Records

There is a problem with medical records—they are scattered everywhere. John Quelch discusses approaches to integrate patient data so that medical professionals and patients can make better decisions. Open for comment; 0 Comments.

• 19 Jan 2015

Is Wikipedia More Biased Than Encyclopædia Britannica?

By identifying politically biased language in Encyclopædia Britannica and Wikipedia, Feng Zhu hopes to learn whether professional editors or open-sourced experts provide the most objective entries. Open for comment; 0 Comments.

• 26 Mar 2014

How Electronic Patient Records Can Slow Doctor Productivity

Electronic health records are sweeping through the medical field, but some doctors report a disturbing side effect. Instead of becoming more efficient, some practices are becoming less so. Robert Huckman's research explains why. Open for comment; 0 Comments.

• 10 Jun 2013

How Numbers Talk to People

In their new book Keeping Up with the Quants, Thomas H. Davenport and Jinho Kim offer tools to sharpen quantitative analysis and make better decisions. Read our excerpt. Open for comment; 0 Comments.

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• v.27(4); 2020 Apr

Leveraging the health information technology infrastructure to advance federal research priorities

Teresa zayas-cabán.

1 Office of the National Coordinator for Health Information Technology, U.S. Department of Health and Human Services, Washington, DC, USA

Amy P Abernethy

2 Food and Drug Administration, Silver Spring, Maryland, USA

Patricia Flatley Brennan

3 National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA

Stephanie Devaney

4 All of Us Research Program, National Institutes of Health, Rockville, Maryland, USA

Anthony R Kerlavage

5 National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA

Rachel Ramoni

6 Office of Research and Development, Veterans Health Administration, Washington, DC, USA

P Jon White

7 Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda) that identifies health IT priorities for research in consultation with relevant federal agencies. This article describes support for the Agenda from the Food and Drug Administration, the National Institutes of Health, and the Veterans Health Administration. Advancing the Agenda will benefit these agencies and support their missions as well as the entire ecosystem leveraging the health IT infrastructure or using data from health IT systems for research.

INTRODUCTION

Use of health information technology (IT) by U.S. healthcare providers and patient access to electronic health data have increased significantly in the past decade. 1–5 This has been facilitated by technological changes in information system capabilities and infrastructure, 6–9 as well as legislation, governmental programs, and policies. 5 , 10–14 In parallel, new health research information systems and capabilities are creating accelerated potential for research, discovery, and clinical translation. Large-scale efforts across the research enterprise are standardizing and increasing access to research data. 15 New approaches, such as machine learning and advanced analytic techniques, have recently demonstrated possibilities for new discovery. 16–18 In addition, novel security approaches, 19 new models of consent, 20 and open science initiatives 21 are facilitating appropriate data sharing and enabling discovery. These efforts highlight the value of a robust research data infrastructure, while also revealing challenges. U.S. federal scientific policy has an essential role in addressing barriers and accelerating data-driven discoveries.

ADVANCING DISCOVERY THROUGH HEALTH IT POLICY AND DEVELOPMENT

The Office of the National Coordinator for Health Information Technology (ONC) is responsible for regulating the certification of health IT, including electronic health records (EHRs); promulgating health IT data standards; and coordinating nationwide efforts to implement and use health IT for clinical care and research in the United States. 22 ONC has established a strategic goal to foster research, scientific knowledge, and innovation. Related projects, including data standard development, 23 , 24 interoperability functionality development, 25 and future-oriented policy development, 26 have been individually successful and have been conducted in partnership with the National Institutes of Health (NIH), Food and Drug Administration (FDA), Agency for Healthcare Research and Quality (AHRQ), and others, but the broader mission requires increased strategic coordination among all federal science agencies and initiatives.

Accordingly, ONC led the development of the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda), 27 , 28 which identifies priorities for policy and technological development in the United States, which are listed in Table 1 . The Agenda has 2 overarching goals: (1) leverage high-quality electronic health data for research and (2) advance a health IT infrastructure to support research.

Health IT priorities for research policy and development

IT: information technology.

The Agenda was developed in consultation with leading U.S. federal agencies that are using electronic health data and the health IT infrastructure to advance health research. Several federal agencies have a role to play in advancing the health IT infrastructure and use of electronic health data for research. For example, while it does not have a direct role in advancing scientific policy, the Centers for Medicare & Medicaid Services plays a role in the development and adoption of health IT. The Centers for Disease Control and Prevention (CDC) funds an extensive research portfolio and requires a robust IT infrastructure to advance public health science. FDA, NIH, and the Veterans Health Administration (VHA) are leading efforts to leverage electronic health data and infrastructure advancements for research across the full spectrum of health and disease. The Agenda represents the shared vision of these leading U.S. federal health research funding agencies for future federal science policies, as well as for technological development of health IT systems that support biomedical research and translation.

AGENCY INITIATIVES

The Agenda priorities are critical to achieve the missions of these federal agencies. In fact, several U.S. federal agencies already sponsor existing initiatives, described subsequently, which highlight how the Agenda priorities underpin meaningful improvement of research.

Food and Drug Administration

FDA has broad responsibilities to protect the public health. 29 , 30 FDA’s regulatory responsibilities are supported by a significant IT infrastructure, which receives and manages large quantities of data from application submissions, surveillance, research, and other sources. To be successful, FDA requires access to timely, detailed data, which would be advanced by Agenda priorities 1, 3, and 4. In particular, previous FDA experience with clinical data and claims data—such as the development of the Sentinel System—has highlighted limitations that can affect current data sources, including limited detail and lagging data updates, further emphasizing the need to advance relevant priorities outlined in the Agenda. 31 , 32

A modern IT infrastructure capable of consuming, aggregating, and analyzing large and diverse datasets is needed to achieve FDA’s broad goals and highlighted by priorities 6 and 7 of the Agenda. In September 2019, FDA published its Technology Modernization Action Plan, which is focused on modernizing its technical infrastructure, enhancing its capabilities to develop relevant technology products, and collaborating with key stakeholders to achieve interoperability. 33 To be successful, FDA will require improved data storage and services, along with new tools for aggregation and research, which are highlighted by priorities 4, 6, and 7 in the Agenda.

As data collected in the health system are increasingly used to inform FDA’s regulatory decision making, interoperability and harmonization efforts outlined in the Agenda are needed for the efficient collection and use of high-quality data. The 21st Century Cures Act of 2016 13 underscored the promise of real-world data, which can be derived from EHRs, mobile devices, claims and billings activities, product and disease registries, and other sources, and evidence to support FDA’s regulatory decision making. 34 In particular, FDA recently published a framework for the Real-World Evidence Program and related use cases to evaluate the use of new types of data and the subsequent analyses in regulatory decisions for drugs and biologics and understand practical application. 35 FDA also provided guidance for the use of real-world data in the evaluation of medical devices and has used real-world data as part of medical device regulatory decisions. 36 , 37 However, interoperability, standardization, and harmonization are needed for the efficient collection and use of high-quality real-world data for these purposes, consistent with the need to advance priorities 2, 3, and 4 of the Agenda.

The increasing complexity of data that inform the regulatory process has led the FDA to develop novel IT tools for those purposes. For example, precisionFDA is a next-generation DNA sequencing platform that allows researchers to compare their genomic sequencing data against reference datasets and analyze their data using online genomic information libraries. 38 , 39 This initiative has provided researchers with access to comparative data on genomic datasets and powerful analytic tools, which demonstrates the need for advanced aggregation functions and tools to support data analysis and research as noted under priorities 6 and 7 of the Agenda. In addition, other federal agencies such as the National Cancer Institute (NCI) and CDC are participating in precisionFDA, highlighting the fact that several agencies have similar research-related needs and creating an example of the type of cross-agency collaboration that is needed to advance Agenda priorities.

National Institutes of Health

NIH is the nation’s medical research agency. To achieve its mission “to enhance health, lengthen life, and reduce illness and disability,” 40 NIH-funded researchers need access to high-quality electronic health data and research data infrastructure and tools. 41 Advancing the Agenda priorities would help meet these needs. NIH is already advancing some of these priorities through several initiatives. In particular, in 2018 NIH launched the Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability Initiative, which provides commercial cloud storage and computer support for high-value datasets resulting from NIH-funded research, addressing Agenda priority 4, promoting efficient data storage and discovery. 42 In 2018, NIH also published its Strategic Plan for Data Science (the Plan), which aims to connect NIH data systems, support storage and sharing of data, increase data management and analytic capabilities, enhance the relevant workforce, and implement good stewardship policies. 43 The Plan is aligned with Agenda priorities 3, 4, 6, and 7 in highlighting the need for data to be findable, accessible, interoperable, and reusable, which can be achieved, in part, through more consistent use of data standards.

Most recently, to improve interoperability of research data, NIH released a notice encouraging researchers to make use of the Health Level Seven International ® Fast Healthcare Interoperability Resources ® standard to accelerate the use of clinical data for research purposes and the exchange of research data. 44 Not only will this advance priority 3 in the Agenda, but also for NIH to reach goals outlined in the notice, it will require coordinated collaboration with ONC, researchers, and developers to continue to advance standards development as outlined under priority 2 of the Agenda.

The National Library of Medicine, the world’s largest biomedical library and a leading funder of informatics research, provides valuable data and information resources for researchers, healthcare professionals, and the public. The National Library of Medicine Strategic Plan 2017-2027 identifies 3 goals, which focus on providing the tools for data-driven research, enhanced dissemination and engagement pathways, and building the needed research workforce. 45 , 46 To reach these goals, it is critical to create an ecosystem that addresses Agenda priorities 7, 8, and 9. In addition, molecular and genomic databases provided by the National Center for Biotechnology Information support next-generation sequence alignment and clinical variation discovery and documentation, highlighting the need to address Agenda priority 5 regarding emerging health data. 47

The All of Us Research Program at NIH intends to “collect and study data” longitudinally “from one million or more people,” leading to precision medicine treatments and prevention strategies based on individual differences. 48 All of Us is both generating primary data (eg, individual genetic sequences) and collecting data from healthcare providers. This initiative has required new policy and IT to address challenges in data acquisition, curation, and analysis, identified across Agenda priorities. 48–50 All of Us will require ongoing advances in data aggregation and analysis, as noted under priorities 6 and 7 of the Agenda, as well as increasing access to interoperable health data, as outlined under priorities 3 and 4 of the Agenda.

NCI is also gaining new insights from large datasets and leveraging health IT for research. NCI’s efforts under the Precision Medicine Initiative 51 and the Cancer Moonshot 52 , 53 have funded the collection of tumor genomic information, relevant clinical trials, and related cloud data sharing and computing capabilities. The Center for Biomedical Informatics and Information Technology supports the needed advanced data infrastructure and capabilities. 54 , 55 In addition, the Surveillance, Epidemiology, and End Results Program is creating linkages between state registries, EHRs, pharmacies, and Medicare data. 56 To be successful, these and other NCI programs must have access to a robust health data infrastructure that aggregates and harmonizes health data from diverse and novel sources for advanced analysis, such as environmental sensor data or wearable technology, which will be achieved via implementation of the Agenda. 57 Specifically, NCI’s programmatic goals require advancement of key informatics issues outlined under priorities 3, 4, 5, 6, and 7 of the Agenda for improved interoperability, data access, storage, aggregation, and analysis of both traditional and emerging health and health-related data.

Veterans Health Administration

VHA, which provides care for more than 9 million veterans at 170 medical centers around the nation, is also a major biomedical research funder and uses health information systems for care delivery and research. 58 VHA’s strategic research priorities require access to high-quality electronic health data and would be accelerated by implementation of the Agenda. The ability to make discoveries from these data depends on efficient storage and would benefit from advancing priority 4 in the Agenda. In addition, as veterans’ health care increasingly includes care outside of VHA facilities, interoperability with private sector health information systems is essential, making it critical to address priorities 2 and 3 in the Agenda.

The Million Veteran Program (MVP) is a massive cohort program, with more than 800 000 veteran volunteers to date. 59 , 60 MVP includes electronic health data, genomic information, and survey data, some of which is drawn from the VA Informatics and Computing Infrastructure, which also supports thousands of other VA research projects. 61 MVP recently expanded to include veterans who do not receive care through VHA, underscoring the centrality of interoperability. The VA Informatics and Computing Infrastructure and MVP rely on interoperable health and health-related data and advanced storage and analytics, which will be well served by addressing Agenda priorities 2, 3, 4, 5, 6, and 7.

ONC, FDA, NIH, and VHA individually have missions, goals, and programs that require the advanced use of electronic health data for research and public benefit. Federal health research funding agencies face common barriers and would benefit from collective action on electronic health data policies and technological development. They also have significant roles in improving the health IT infrastructure through their funding priorities and related policies so that that infrastructure can be more effectively leveraged for research use of health data. While several separate efforts currently underway are addressing some Agenda priorities, these agencies support the Agenda and recognize the need for comprehensive and coordinated action. Other agencies such as Centers for Medicare & Medicaid Services and the CDC also have aligned authority or interests and are exploring supportive collaborations. Several agencies are already advancing cross-agency collaboration such as through NCI and CDC participation in precisionFDA, and relevant consultation regarding implementation of pertinent 21st Century Cures Act provisions. Successful implementation of the Agenda will include strategic coordinated action by federal health research funding agencies, yielding a variety of benefits for the agencies and beyond, including efficient use of financial and technical resources, shared policies across research initiatives, increased impact through common policies, and—most importantly—improved health through scientific discovery.

This work was partially funded through U.S. Department of Health and Human Services Contract Number HHSP233201600021I, Task Order Number HHSP23337008T, with RTI International.

AUTHOR CONTRIBUTIONS

TZ-C and PJW led the conception of the article, through ongoing collaboration with APA, PFB, SD, ARK, and RR. TZ-C and PJW led drafting of the article. All the authors revised the article critically and provided intellectual content; and approved the final version for submission. The order of authors listed in the manuscript has been approved by all authors.

ACKNOWLEDGMENTS

The authors thank their federal partners at the Agency for Healthcare Research and Quality, Department of Veterans Affairs, Centers for Disease Control and Prevention, Food and Drug Administration, National Cancer Institute, National Institutes of Health, National Library of Medicine, and National Science Foundation for their collaboration. They thank Palladian Partners and Jesse Zarley for copyediting support and reference formatting assistance. The authors would also like to thank Kevin Chaney from the Office of the National Coordinator for Health Information Technology and the RTI International team, which included Linda Dimitropoulos, Alison Banger, Stephanie Rizk, Jacqueline Bagwell, Alexa Ortiz, and Sydney DeStefano, for their leadership and contributions to the overarching project that examined the use of health IT to advance research.

CONFLICT OF INTEREST STATEMENT

None declared.

Trends in the Information Technology sector

Subscribe to the center for technology innovation newsletter, makada henry-nickie , makada henry-nickie executive director - jpmorgan chase & co, former nonresident fellow - governance studies kwadwo frimpong , and kwadwo frimpong research associate hao sun hao sun assistant professor, department of government and public affairs - gallaudet university, senior research analyst, center for technology innovation - the brookings institution.

March 29, 2019

• 41 min read

The U.S. leads the global landscape in technology innovation. The country’s competitive edge, according to the World Economic Forum’s 2018 Global Competitive Index, is due to its business dynamism, strong institutional pillars, financing mechanisms, and vibrant innovation ecosystem. 1 Innovation is a trademark feature of American competitiveness and has powered its global dominance since the post-World-War industrial revolution. Countries that lead the world in generating advanced technologies and leveraging the full productive capacity of their digital economies can gain a strategic competitive advantage.

Figure 1: Global distribution of top 100 digital companies and market capitalization (US $billion)

Digital technologies have risen to prominence as a critical determinant of economic growth, national security, and international competitiveness. The digital economy has a profound influence on the world’s trajectory and the societal well-being of ordinary citizens. It affects everything from resource allocation to income distribution and growth.

But how do we measure the digital economy and its contributions to growth and pertinent social indicators? Watanabe (2016), Brynjolfsson (2018), Nakamura (2018), Moulton (2018), and many other experts acknowledge the difficulty of precisely evaluating a digital economy characterized by rapidly changing products and services. Researchers estimate that “the digital economy is worth $11.5 trillion globally, equivalent to 15.5 percent of global GDP and has grown two and a half times faster than global GDP over the past 15 years.” 2

For its part, the Bureau of Economic Analysis (BEA) attributes the challenges of measuring the digital economy to a lack of consensus around activities included in the definition and the rapid pace at which the underlying nature of digital technologies evolves. The BEA estimates that the U.S. digital economy grew at an annual average rate of 5.6 percent between 2006 and 2016 and “accounted for 6.5 percent of current-dollar GDP.” 3

“Tracking the digital economy’s growth trajectory is essential because it serves as an integral forward-looking barometer of U.S. economic growth and international competitiveness.”

National statistical accounting challenges notwithstanding, tracking the digital economy’s growth trajectory is essential because it serves as an integral forward-looking barometer of U.S. economic growth and international competitiveness. Conceptually, the digital economy comprises goods and services that either were produced using digital technologies or include these technologies. The information and communications technology (ICT) industry stands at the center of much of this activity, underpinning the digital economy and serving as a reliable yardstick of its performance. Niebel (2018) confirms the link between ICT industry investments and economic growth, finding that between 1995 and 2010, “ICT contribute[d] substantially to economic growth” for developed, developing, and emerging countries. 4

In the digital era, innovation, entrepreneurial dynamism, and information and ICT production will drive America’s competitive edge. The ICT industry and ICT-enabled industries make important contributions to economic growth. This paper attempts to value those contributions and benchmark the importance of the ICT sector in the U.S. economy by assessing its contributions to economic growth, job creation. The sector’s downstream contributions to the small business ecosystem and investments in reskilling and upskilling initiatives are examined. Finally, systemic challenges related to data privacy, trade, and immigration facing the sector are reviewed.

Benchmarking global competitiveness

Deep investments in ICT assets: Computer hardware, software, and internet, and broadband infrastructure, for example, are crucial determinants of growth in advanced economies. An OECD study by Vincenzo Spiezia posits that increased GDP growth and country-specific global competitiveness can be primarily attributed to growth rates in ICT investment. 5  The impact of ICT assets, measured as the value of ICT-capital services as a percentage of GDP, is instructive in assessing the ICT sector’s full growth contribution. And on that front, the U.S. has secured a global lead, maintaining relatively strong competitiveness compared with other OECD member states. India and China have emerged as front-runners in this space, particularly with respect to the high levels of capital (or capital services) that ICT assets bring to GDP growth.

In addition to the demonstrated positive impact from ICT sectors on the total economy, a transformational shift has occurred from the ICT manufacturing sector to the ICT service sector. This move from a hardware- to software-centric level of growth has been particularly pronounced in developing countries due to deeper and wider mobile-cellular networks. 6 Moreover, the maturing mobile ecosystem has been fueled by greater accessibility among mobile internet users and the affordability of smartphones and portable devices.

Figure 2: IT service output of 4 economies, 2005-2015

Beyond the increasing contributions of ICT-services to GDP growth, investments in the ICT sector have significantly boosted labor productivity. 7 In this area, the U.S. economy has maintained its global leadership position with despite only incremental increase in wages from $62 per hour in 2005 to $71.2 per hour in 2015. China and India have also benefited from prior structural investments in ICT sectors, especially in terms of internet infrastructure and mobile operating platforms.

The McKinsey Global Institute notes the economies of scale that mobile users and the proliferation of e-commerce have brought to ICT sectors. 8 These emerging developments have benefited from ICT investment and doubled labor productivity between 2005 and 2017. Conversely, such high levels of productivity have remained notably absent in most OECD member states; their median of labor productivity has only increased incrementally to $54 per hour despite holding historical advantages at $51 per hour.

Figure 3: Labor productivity per hour worked in 2017 US$, 2005-2017

Spending on R&D innovation has spurred labor productivity and the integration of ICT with the broader economy. The U.S. is a clear front-runner in this category: Total spending on R&D grew from $268.6 billion in 2000 to $496.6 billion by 2015 (Figure 4). While OECD peer countries increased their spending during this period only incrementally, India and China have made substantial R&D investments (in terms of total dollar amount)—eclipsing the investment totals of all other nations. India’s spending on R&D tripled, whereas China’s spending increased more than tenfold. These substantial investments in innovation have bolstered the swift transformation of these countries’ economies.

Figure 4: Domestic expenditures on R&D innovation, 2005-2015

In light of these developments, the U.S. and other OECD members should continue to prioritize investment in ICT at the state and local levels to maintain global competitiveness and boost labor productivity. Targeted ICT investments in 5G technologies and infrastructure along with R&D innovation combine to bolster the digital economy and accelerate the ICT-sector’s diffusion effect to less technologically-intensive sectors. Policy-guided investments can augment the capital contributions that ICT sectors make toward GDP growth and will boost labor productivity as a result.

Taking all these factors into account, it is evident that the IT industry is central to the digital pivot for developed and developing countries. In the U.S., the industry’s share of real economic growth has risen steadily since 2007, propelling the sector to relative prominence. Accelerated adoption of rapidly developing technologies such as cloud computing, robotic automation, artificial intelligence (AI), machine learning, the internet of things (IoT), and 5G technologies is promising for the IT industry and should promote ongoing growth.

U.S. information technology sector

Within and outside information technology (IT), the U.S. has delivered slow and steady economic growth since emerging from the financial crisis. U.S. GDP growth averaged 2.3 percent between 2010 and 2018, according to BEA figures. Diving below aggregate GDP statistics reveals a diverging growth story within which the services-producing sector headlines as a growth protagonist. Services-producing industries, which account for more than 80 percent of total output, have anchored much of U.S. economic performance and post-crisis recovery.

The IT industry is growing in dominance within the services-producing sector, powered in large part by a vibrant technology sector. But the industry is relatively small in absolute size, accounting for only 6 percent of the total economy, says BEA.

Figure 5: Industry contributions to changes in real gross domestic product

The ICT sector is a growth powerhouse, despite its diminutive stature. Over the last four years, the industry has driven remarkable gains, powering real economic growth and employment. The proliferation of digital technologies will continue to bring unprecedented structural changes to the U.S. economy, cementing the IT industry’s position as a leading source of growth and employment. Yet exactly how the IT industry will shape various aspects of the economy remains difficult to predict.

What is clear, is that the IT industry has expanded since the Great Recession, outpacing the value-add contributions of goods-producing industries to gross domestic output (Figure 5). Declining prominence in goods-producing sectors is not exclusive to the U.S., in fact this trajectory is consistent with similar trends in OECD peer countries and other advanced economies.

More broadly, the IT industry is an important contributor to the burgeoning digital economy and feeds the domestic economy through two primary channels: the production of cutting-edge technologies and the distribution of scale of innovation across other economic sectors. The IT services sector distributes innovative technologies from consulting services to downstream business organizations seeking to improve efficiency, generating significant multiplier effects across the industry value chain. IT spending on services, infrastructure, and software is on track to rise to $3.8 trillion, according to Gartner’s forecast, a 3.2 percent increase from $3.7 trillion in 2018. 9

The IT industry is also impressively robust. It persevered through the U.S. economy’s slow recovery, growing from an annual value-add of $835 billion in 2008 to $1,480 billion in 2017—an increase of 77 percent (Table 1). The services-producing sector, though much larger, grew 20 percent over the same period. Meanwhile, the goods-producing sector posted a modest 5 percent increase to real economic growth.

Table 1: Value-add produced by industry, selected years ($ millions)  

(Source: U.S. Bureau of Economic Analysis) 10

In 2017 alone, the IT industry’s contribution to real economic output exceeded that of the professional and business services, finance and insurance, and manufacturing sectors, according to BEA figures on industry contributions to GDP. Although the industry has inspired sweeping business model changes and produced considerable business value across the value chain, the effects of mounting IT investment spending will likely be dampened by rapidly decreasing costs of technological solutions, driven largely by automation. Despite the changing cost structure of the technological distribution channel, growing IT spending should continue to have a net positive impact on the industry and on aggregate real economic output.

Industry composition and anticipated trends

Analyzing aggregate growth trends in the IT industry provides a useful but incomplete picture of the sub-industries that are critical to its growth and the broader economy. The industry is composed of three major sub-industry groups with related yet distinct core production activities: semi-conductors and semi-conductor equipment, software and services, and technological hardware and equipment.

Examining disaggregated growth patterns within the IT industry can clarify how prior performance has underpinned its overall trajectory. According to BEA figures, the broadcasting and telecommunications industry is the largest in absolute size but generated 14 percent of the IT industry’s growth gain between 2007 and 2017—the lowest rate for all sub-groups. By contrast, the data processing, internet publishing, and publishing industries (including software) produced tremendous growth rates that belie their size. The data processing, internet publishing, and other information services sector increased its contribution to GDP threefold between 2007 and 2017, ballooning from a value-add of $65.2 billion to $263.6 billion. Meanwhile, the publishing industries sector (including software) saw its share of real economic growth rise by 39 percent.

“An increasingly digital economy, driven by non-physical outputs (e.g., service delivery, software, and computing), will be the centerpiece of the U.S.’s global competitive advantage.”

An increasingly digital economy, driven by non-physical outputs (e.g., service delivery, software, and computing), will be the centerpiece of the U.S.’s global competitive advantage. However, quantifying precise value-add contributions is difficult under the current growth accounting framework. Classifying ICT services is especially challenging, as grouping this sub-industry’s primary production activities blurs the lines between services provided and technology produced.

Data processing, internet publishing, and other information services are the fastest-growing segments of services-producing industries. Rapid adoption and commercialization of digital technologies in non-ICT industries, which have inspired substantial productivity gains, may also lead to severe underappraisal of the value-add contribution of the IT industry and its overall employment gains.

The demand for IT-based services is disproportionate across many industry verticals; however, certain sectors present appealing opportunities for revenue generation for IT service providers. Whereas aggregate IT spending is expected to rise on a global scale, growth will be unevenly distributed across key geographical markets: North America (the U.S. and Canada); the Asia-Pacific region; Europe, the Middle East, and Africa (EMEA); and Latin America.

Table 2: Worldwide forecast of spending on core IT services, 2017-2019 ($ billions)

(Source: Gartner (2018). Gartner Says Global IT Spending to Grow 3.2 Percent in 2019. Retrieved from https://www.gartner.com/en/newsroom/press-releases/2018-10-17-gartner-says-global-it-spending-to-grow-3-2-percent-in-2019)

North America will constitute the bulk of worldwide IT expenditures from 2015–2019 and is expected to gross more than $1 trillion in spending in 2019. The EMEA region is estimated to be the second-largest source of regional spending, with Asia-Pacific coming in third due to a contraction in growth in most Asian economies. 11

Enterprise software is forecasted to be the predominant driver of growth in overall IT spending in 2019 at 8.3 percent, followed by IT services at 4.7 percent. 12  Devices, a segment driven by an increase in the average selling prices of mobile phones, will experience moderate growth (2.4 percent) in 2019, a slight downturn from 3.6 percent in 2018. Counterintuitively, data centers and communication services will exhibit the most sluggish growth of all segments (1.6 percent and 1.2 percent, respectively) in 2019, declining sharply from the preceding year (6 percent and 2.4 percent, respectively). 13

Emerging technologies such as AI, IoT, and blockchain will continue to influence the IT industry into 2022. While growth in expenditures on traditional technologies (hardware, software, services, and telecom) is expected to largely mimic the single-digit GDP growth over this period, growth in advanced technologies is anticipated to be much more prolific, stretching into the double digits and commanding an increasingly greater share of total IT spending. 14

“As spending on legacy technology systems declines, growth will be driven by key platforms: cloud, mobile, social and big data, and analytics.”

As spending on legacy technology systems declines, growth will be driven by key platforms: cloud, mobile, social and big data, and analytics. A growing share of technology spending will be diverted toward newer capabilities such as AI, robotics, and augmented reality, fueled in part by the cost savings generated by cloud-based technology and automation. 15  The business industry’s shift toward innovation and growth from cost reduction has been fueled by ongoing modernization and wider accessibility to cloud-based services. According to a recent Deloitte survey on everything-as-a-service (XaaS) capabilities, “For companies in which more than three-quarters of the enterprise IT is XaaS, and in companies that have been using flexible consumption for more than three years, ‘accelerated innovation’ has overtaken ‘reduced costs’ as a key priority for their XaaS initiatives.”

A spike in consumer demand for flexible pay-as-you-go models coupled with large IT companies integrating costly cloud-based tools with enterprise systems has brought the cloud to the mass market. Consequently, high-end technologies such as AI and IoT—tools normally restricted to a select few large companies and innovative startups—have been made available to a range of small, medium, and large-sized firms. 16

AI has spearheaded this explosive trend; large companies have sought to integrate AI into cloud-based technologies and have delivered these tools on a mass scale. This evolution has cemented the status of cloud and other software-as-a-service capabilities as a core platform for growth within IT-service-based and business industries. 17

This shift toward innovation is no more evident than in the rapid proliferation of enterprise software systems, projected to be the fastest-growing IT segment worldwide in 2019. The convergence around this inflection point toward enterprise cloud-based digital transformation and innovation will remain a key source of opportunity for IT-service-based providers.

Automation will undoubtedly shape the IT industry’s future as well. Automation offers the potential to improve productivity by introducing robots and AI into the workplace. These tools will help employees complete more tasks and leverage human capabilities. Automated processes and digital assistants can also facilitate worker productivity, bringing substantial benefits to the macroeconomy.

These developments are promising for productivity, but their impacts on workers remain to be seen. Organizations may be able to do more with fewer people. If that happens, society at large could be threatened as fewer workers would be needed to service the economy; if companies can get by with fewer employees, job prospects will certainly be affected.

New jobs will undoubtedly be created in this scenario, and the demand for data sciences, coding, digital platforms, and e-commerce will grow—but aside from delivery jobs, it will be difficult for affected workers to develop the skills needed in these areas. The mismatch between skills required and workers’ capabilities will necessitate the expansion of worker retraining programs.  

Distributing ICT impact

The rapid rise of the digital age and the IT sector has shaped nearly all contours of the U.S. economy, helping to fuel upstream and downstream growth in employment and productivity, small businesses, and corporate investments in workforce training for the digital age.

Since 2006, the IT industry has experienced drastic shifts in its conventional to current form of production and related service delivery. The BEA has recognized this change and, under its newly released account of the digital economy, introduced a sub-category called the “IT and Related Industry” to capture the growing overlap between information services and professional service delivery.

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According to the BEA, employment in the IT and IT-related industry has grown substantially. Annual growth figures, except during the U.S. subprime mortgage crisis of 2007 to 2009, expanded at almost twice the rate of the total employment market from 2006 to 2016. 18 The highest annual growth rate reached over 4.1 percent in 2014, double the employment growth rate of the total economy in the same year.

Based on data from the U.S. Bureau of Labor Statistics regarding projected employment in the year 2026, service-providing industries are expected to account for the majority of 11.5 million newly created jobs. 19 Among the top five fastest-growing industries over the next decade, the IT-related industry holds two positions: Professional and business services together with professional, scientific, and technical services will account for 15.4 percent of projected new jobs.

In addition, the total U.S. economy is anticipated to expand job opportunities at a compound annual increase of 0.7 percent from 2016 to 2026. The professional and business service industry will be a burgeoning driver in creating potential job opportunities at a compound annual increase of 1 percent during this time frame. Jobs within the traditional IT industry are only projected to grow at a compound annual increase of 0.2 percent by comparison, slower than average within the total economy.

ICT powering jobs

The IT industry was the most promising domain with respect to job creation between 2006 and 2016. The industry’s employment growth trajectory becomes more apparent through a disaggregated picture at the sub-industry level, which reveals incremental shifts within the total sector, especially in professional service delivery.

BEA defines the professional service delivery sector as comprising the three main segments: 1) legal services; 2) computer systems design and related services; and 3) miscellaneous professional, scientific, and technical services. On aggregates, the professional services sector significantly expanded between 2006 and 2017. Conventional legal services sector posted slower growth rates, whereas the other two sub-sectors grew considerably, particularly the computer system design and related services industry. Such growth led to a near doubling of job creation numbers during the same period. 20

Job growth patterns at the sub-industry level highlight IT service delivery as a major contributing factor to the professional service delivery sector. Job growth in this sector also signifies further integration of the IT service industry with other-sector economic activities. This trend exemplifies the role of the IT service delivery industry in supplying services to other sectors and its influence on the expansion of the U.S. job market.  

Productivity impact

In addition to the employment boost provided by the IT and related industry, associated industry productivity has grown as well. The average GDP output per employee in the IT and related industry was more than twice the average productivity of the total economy from 2006 to 2016. Based on estimates of BEA figures, annual GDP output per employee within the IT and related industry increased from $321,659 to $408,129. Meanwhile, GDP output per employee within the total economy only increased from $120,876 to $132,873 during the same time. 21

When examining productivity of the IT and related industry, it is important to include its digital spillover value towards non-ICT industries. Huawei and Oxford Economics (2018) assert that a robust digital economy includes direct digital products along with digital spillovers from primary digital industries to secondary, non-digital industries. In such an accounting framework, Huawei and Oxford argue that “digital spillovers” should play a key role in estimating the true productive capacity of a digital economy. 22  A prime example of increasing integration between the ICT and non-ICT sectors is the ICT sector’s consistent contribution to the productive capacity of other sectors; between 2006 and 2016, the ICT industry accounted for more than 11 percent of the total supply of commodities and services within the U.S.

Despite its relatively small size as measured by GDP output statistics, the ICT industry has played an instrumental role in driving economic growth and employment within the U.S. economy.

Downstream impact on the small business ecosystem

A dynamic ICT industry serves as a prominent growth mechanism in the small business ecosystem, delivering downstream value and boosting productivity. Small business enterprises (SBEs), defined as companies with fewer than 500 employees, are the backbone of the U.S. economy and account for more than 99.7 percent of the 5.6 million U.S. employer firms, comprising an essential constituent of the IT industry. 23

Through varied platforms and cost-effective access to cutting-edge technologies, small businesses have the foundational support to spur innovation, commercial collaboration, and important knowledge transfers within the small business sector. These benefits will emerge in more pronounced ways as newer digital technologies (e.g., cloud-based services) mature and penetrate non-ICT segments.

More traditional tech tools, such as mobile applications, will also grow to critical mass in the small business value chain. This proliferation of modern tech-based solutions is key; according to the U.S. Chamber of Commerce’s Q-2 2018 Small Business Index, “Companies that feel ahead of the technological curve are more likely to feel better about their business and cash flow and are planning to hire at a higher rate.”

Table 3: U.S. Chamber of Commerce Small Business Index (2018, Q2)

(Source: Figures adapted from U.S. Chamber of Commerce Small Business Index [2018])

Tools such as cloud computing, big data, and customer-relationship management systems are similarly central to tech-optimism. Not only do these innovations help businesses assimilate into the digital ecosystem, but small businesses’ willingness to invest in these capabilities and other IT-related services exposes them to better local market opportunities and profit margins.

Additionally, according to a survey by the U.S. Chamber of Commerce, higher technology adoption rates are tied to confidence in small business health and cash flow—essential conditions for successful scaling in the small business ecosystem. SBEs, driven in part by their readiness to spend on IT services and infrastructure, will emerge as an important consumer constituent to the ICT services industry.

ICT software and platform infrastructure are providing unprecedented opportunities for small businesses to scale without the commonly accompanying price tag; historically, these factors represented major barriers to technological adoption in small business markets. Recently, however, a mass transition to cloud-hosted accounting software applications unfolded within the small business ecosystem and laid the groundwork for other systems’ entrance thanks to cloud-based applications.

Cloud-based technologies represent another game-changing opportunity for small businesses, offering access to new markets and bringing unexpected benefits to the value chain. Lund and Tyson (2018) point out that the benefits of digital technologies in the small business ecosystem carry implications for global trade patterns. They further contend that online marketplaces/platforms are critical mechanisms for trade growth, especially as smaller transactions increase in scale and relevance for economic growth. The evolutionary rise of micro-multinational enterprises with access to new markets has been made possible thanks to retail intermediaries such as Amazon in the U.S. and Alibaba in China, which host 2.0 million and 10.0 million third-party sellers (micro-multinational enterprises), respectively.

“Cloud-based technologies represent another game-changing opportunity for small businesses, offering access to new markets and bringing unexpected benefits to the value chain.”

Cloud-based technologies also hold great promise for the small business ecosystem as a defining digital technology with a demonstrated capacity to positively disrupt the value chain. In a survey assessing small business openness to cloud computing technologies in Australia, Fakieh et al. (2016) observed that small companies were motivated to adopt cloud-based technologies because of cost savings for firms with limited budgets and substantial returns on productivity and business outcomes. 24  Additionally, the authors note that affordable cloud computing technologies are essential to boosting SME productivity and business outcomes. According to Cisco’s Global Cloud Index, private and public cloud workloads are expected to increase appreciably by 2021 and to grow by compounded annual growth rates of 27 and 73 percent, respectively. 25  The Global Cloud Index expects software-as-a-service (SaaS) to be the primary driver behind cloud-service delivery models; in fact, SaaS is expected to account for 75 percent of global cloud workloads by 2021.

SaaS and platform-as-a-service will also facilitate the transformation of big data, AI, and machine learning analytics into accessible technologies for small businesses. Luo and Bu (2015) state, “ICT significantly facilitates effective knowledge sharing and knowledge integration, which further bolsters value chain integration and synergy development among primary and support activities of a value-chain system.” 26  A stream of emerging research continues to add credible evidence to the role of the ICT sector as a growth-enabling channel that enhances small business productivity, competitiveness, and ultimate value-add to domestic economic growth.

ICT sector shaping the future of work

ICT technologies are essential productivity and growth inputs, but fully exploiting the potential of digital technologies is predicated on a capable workforce that can convert technical knowledge into productive outputs. Growth trends in ICT sectors worldwide and a highly skilled workforce shape management decisions when choosing corporate headquarters and manufacturing centers. For example, in an interview with Fortune Global Forum, Apple CEO Tim Cook emphasized the importance of a highly skilled workforce in attracting manufacturing business:

“China has moved into very advanced manufacturing, so you find in China the intersection of craftsman kind of skill, and sophisticated robotics and the computer science world. That intersection, which is very rare to find anywhere, that kind of skill, is very important to our business because of the precision and quality level that we like.” 27

Cook’s rationale for selecting China as Apple’s manufacturing home base for the iPhone was more about China’s skilled workforce—in terms of quality and quantity—than the low cost of labor. Cook argues that in China, “You could fill multiple football fields” with tooling engineers; in the U.S., however, “I’m not sure we could fill the room.” Cook connects the competitive advantage of China’s skilled workforce to a longstanding priority on applied vocational training within the country’s education system. Building a highly skilled workforce is vital to maximizing the ICT sector’s productivity growth potential and sustaining America’s global competitive advantage.

Workforce challenges are most acute for the ICT industry given its growth trajectory and leadership on the digital technology frontier. Arguably, the sector is at the forefront of 21 st -century human capital challenges, including skill mismatches, skilled-worker shortages, and attracting and retaining highly skilled workers in tight labor markets. According to the World Economic Forum, “By 2022, no fewer than 54 percent of all employees will require significant reskilling and upskilling.” 28

While broadening technological adoption has been tied to industry growth, the widening collection of digital technologies compounds these labor market trends. Increased access to IT infrastructure and digital technologies continues to shape workforce needs within the IT industry as well as non-IT sectors. As a consequence, organizations are rapidly integrating emerging technologies into their business processes and accelerating the transformation of their workforce needs.

Beyond large enterprises such as General Electric Company, Verizon, and Lockheed Martin, each of which is making substantial investments to upskill and retrain their workforce, a large gap remains in robust workforce preparedness across the industry. According to Towers Watson, “90 percent of maturing companies expect digital disruption, but only 44 percent are adequately preparing for it.” 29

Nonetheless, those that are making significant strides to address human capital challenges are doing so through a combination of the following approaches: 1) retraining their existing workforce; 2) defining new skill sets and recruiting fresh talent to fill emerging gaps in business; and 3) leveraging automation. 30

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Amidst a “reskilling revolution,” hiring and developing a company’s talent pool from within, rather than competing with large industry peers and smaller innovative companies, has been increasingly lauded as the new “recruiting tool” and a more effective model to bridge the technical skills gap. Retraining existing talent rather than relying on external hiring is less costly; turnover costs can equal as much as 16 percent of an hourly-waged employee’s compensation or 213 percent of the salary for a highly trained position. 31  Additionally, retraining allows companies to build upon their workforce’s institutional knowledge and not lose valuable time waiting for newly acquired workers to adjust to company practices.

In many instances, the rapid evolution of digital technologies shortens the effective shelf-life of technical skills, which complicates the debate on identifying a cogent national workforce strategy to address skill shortages. In the meantime, relying on internal reskilling programs represents an anodyne response to the growing concern of skills mismatch in the intensely competitive ICT sector that allows industry leaders to boost market competitiveness. However, program adoption is unevenly distributed across the ICT sector, and many companies continue to rely on a mix of workforce strategies to assuage workforce challenges.

AT&T has emerged as an industry leader in workforce retraining initiatives and has adopted two main strategies to equip 95 percent of its workforce with highly sought-after skills by 2020. 32  First, it has invested in creating new career pipelines to attract entry-level talent. Second, it has invested in a variety of training schemes, including a $1 billion web-based global retraining program comprised of online courses; academic-degree-based partnerships with Coursera and leading universities such as Georgia Tech; and an online portal that allows employees to follow a career road map to transition into new roles.

AT&T’s investments have been paying off: Employees who are retraining are twice as likely to be hired into advanced emerging occupations (e.g., data scientists) and four times as likely to advance in their careers. AT&T’s success in and commitment to building an internal program rather than relying on external hiring has become a model for other IT leaders who are slowly adopting the same approach.

Similarly, IBM has committed $1 billion to training and development programs for its U.S-based employees over the next four years. 33  However, the company’s initiatives are unique in its attempts to make career inroads into the IT industry more accessible to a wider pool of candidates rather than a select few. First, the company has issued over a million digital badges in every country–digital credentials that showcase completion of a class or training and serve as a signal to IBM and the broader labor market of newly acquired skills. Second, IBM is recruiting highly skilled candidates through its “New Collar Certificate Program” by placing a premium on sought-after skills as opposed to formal academic credentials like a four-year degree. Regardless of where the skills were attained (i.e., at a coding boot camp or community college), there will be roles at the company for these applicants as long as they possess the requisite capabilities.

Ultimately, due to the nature of contemporary jobs and the diversity of workplace settings, online learning content and micro-learning are sure to become increasingly popular among organizations to boost business value in the digital economy.

Future challenges

Regulatory uncertainty and the rise of massive security breaches present major challenges for the IT industry moving forward. The proliferation of AI, machine learning, and robotic automation technologies across leading IT service companies supports the industry’s robust outlook. However, widespread security concerns place millions of consumers and the small business ecosystem at risk. What’s more, the radical shift in political attitudes around critical domestic issues (particularly trade and immigration) calls the industry’s future into question. Ambiguities around data privacy, cybersecurity, and trade warrant particular attention.

Data privacy

Political tides are influencing the ICT industry with regard to data protection and broader concerns. In terms of regulations, escalating trade tariff frictions between the U.S. and China concerning trade imbalances have deflected attention from the silent rise of regional data protectionist policies. In 2018, China, India, and Vietnam introduced data protectionist legislation to circumscribe cross-border data flow.

These sovereign governments have pointed to data protection as paramount in mandating local storage of consumer data. Regardless of the motivating factors, such restrictions limit the free flow of data across international borders with important consequences for the IT industry. Potential outcomes include increased compliance risks, growing infrastructure costs to maintain fractionalized enterprise data storage systems, and a corresponding rise in investments to navigate transient compliance requirements.

“Digital privacy protection is of critical importance in a vibrant digital society that respects consumers’ rights to control access to their data and balances safeguards within an ecosystem that supports innovation and growth.”

Digital privacy protection is of critical importance in a vibrant digital society that respects consumers’ rights to control access to their data and balances safeguards within an ecosystem that supports innovation and growth. However, the pace of massive data breaches has eclipsed regulators’ ability to constrain these events and improve institutional accountability.

The lack of a cogent national regulatory framework to address data privacy challenges emerging from massive amounts of business and consumer-related data, coupled with shifts in individuals’ privacy preferences, presents inherent threats to the IT industry. Operational planning is particularly at risk. The absence of clear, consistent signals from federal authorities on the future of data privacy regulation in the U.S. could be costly for the IT industry, along with non-IT stakeholders. Nevertheless, two regulatory models provide insight into future directions for an eventual U.S. policy on digital privacy.

Globally, Europe’s General Data Protection Regulation (GDPR) provides a regulatory model that, at its core, aims to protect consumers and increase control over their personal data via informed consent. GDPR also incentivizes enterprise compliance and accountability through punitive fines.

Domestically, the state of California has emerged as a vanguard in data protection, promulgating The California Consumer Privacy Act  (CCPA) as a legislative response to data privacy concerns. CCPA closely parallels GDPR’s structural design and reliance on penalties for non-compliance. GDPR and CCPA also converge on the importance of data privacy for consumers. Despite obvious consumer benefits, these regulatory regimes present substantial non-compliance risks for the IT industry in terms of pecuniary harms and reputational damage.

Trade and immigration tensions

The political landscape also carries major implications for global trade and the flow of workers across borders, heightening the complexities associated with cross-border movements of diverse forms of capital. National political arguments prioritizing domestic economic interests have supplanted transnational and global cooperative relationships that have been the hallmark of trade norms for the last several decades. Conversations around cross-border movement are now generating tangible policies rather than abstract political discussion. The recent partial shutdown of the U.S. government offers worrisome evidence of this shift and exacerbates financial instability as a consequence of the U.S.–China trade wars, which have adversely affected financial markets around the world.

What’s more, anti-immigrant populist sentiment influenced the Brexit referendum vote, which mandated the U.K.’s exit from the European Union. Beyond the destabilizing economic uncertainty stemming from this vote and subsequent political stalemate around plans to implement a required exit, the anti-immigration agenda was clear. Immigration friction sentiments formed a critical flashpoint of the Brexit discourse, one that has since been replicated in the German and U.S. elections.

Besides this, negative sentiments toward immigrant labor have shaped political debates and national policies that promote closing borders to important labor flows of highly skilled immigrants. Recently, through a series of legislation under the “Buy American/Hire American” executive order, the U.S. has applied greater scrutiny and more stringent requirements to employment-based immigration (specifically the H-1B temporary foreign worker visa). These impending laws are expected to disproportionately affect the ICT industry. According to the Department of Labor’s H1-B visa statistics, 57.6 percent of certified positions for FY 2018 were related to jobs in computer programming and software development fields; in FY 2017, computer-related occupations accounted for 70 percent of successfully awarded visa applications.

On Feb. 22, 2019, the Department of Homeland Security proposed a ban on the work authorization of 100,000 H-4 visa holders—a special work authorization for spouses/children of H-1B visa holders who are awaiting permanent residency status—reducing the attractiveness of the U.S. to foreign workers and their dependent families. With foreign workers and H-1B holders constituting most of the talent pool in large tech companies, such a development could greatly disrupt companies’ business models and workforce strategies. Final implementation is uncertain given anticipated legal challenges to the proposed rule.

Furthermore, recently implemented administrative changes to the H-1B visa lottery compound the effects of anti-immigrant labor market policies. Despite the unknown final impact of the lottery change, summarily these rules and regulations alter competitive dynamics among highly skilled workers. By reducing the dominance of large IT staffing firms (e.g., Tata Consultancy Services, Infosys, and Wipro) in employment-visa based petitions with candidates who fail to fit “highly skilled occupational requirements,” many major tech firms will lose out on a valuable talent source of permanent and temporary workers. To that end, heightened workforce pressures across the ICT industry will likely cause many IT firms to relocate more operations offshore to compensate for the shortfall in domestic-based foreign talent if workforce training efforts cannot meet the industry’s demand for highly skilled workers.

The IT industry is shaping the U.S. economy in several important ways, most notably with respect to sectoral innovation, economic growth, overall business operations, and regulatory policy. It is clear that the industry, despite its relative immaturity compared with more established sectors, will remain a key player in the nation’s economic landscape. However, its prospects are tempered by looming issues related to international affairs.

“It is clear that the IT industry, despite its relative immaturity compared with more established sectors, will remain a key player in the nation’s economic landscape.”

In the long run, closing borders presents significant risks to the IT industry and may come at the expense of the industry’s innovation, competitiveness, and capacity to develop and distribute products and services. Ensuing responses to the turbulence around trade wars, immigration, and cross-border communication will guide the industry’s development in potentially drastic ways. Such changes, however difficult they are to forecast, will likely bring ripple effects to IT and related industry as well as the economy at large. Industry experts should thus continue to monitor developments in IT and adjacent areas carefully to safeguard its evolution, provide targeted workforce recommendations, and devise appropriate protectionary measures for businesses and consumers.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Apple, AT&T, Cisco, IBM, Lockheed Martin, and Verizon are donors to The Brookings Institution. The findings, interpretations, and conclusions posted in this piece are not influenced by any donation. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment.

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A comparative study of the influence of communication on the adoption of digital agriculture in the united states and brazil  †.

1. Introduction

2. materials and methods, 2.1. study region, 2.2. survey instrument, 2.3. data collection, 2.4. data analysis.

• n = number of elements in the sample;
• p = probability of finding the phenomenon studied in the population;
• q = probability of not finding the phenomenon studied in the population; and
• E = margin of error.

2.5. Sample Characteristics

3. results and discussion, 3.1. technology adoption, decisions, and benefits, 3.2. level of influence from mass media, social media, and interpersonal meetings, 3.3. relationship between the adoption of technologies and communication channels, 4. conclusions, author contributions, institutional review board statement, data availability statement, acknowledgments, conflicts of interest.

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Colussi, J.; Sonka, S.; Schnitkey, G.D.; Morgan, E.L.; Padula, A.D. A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil. Agriculture 2024 , 14 , 1027. https://doi.org/10.3390/agriculture14071027

Colussi J, Sonka S, Schnitkey GD, Morgan EL, Padula AD. A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil. Agriculture . 2024; 14(7):1027. https://doi.org/10.3390/agriculture14071027

Colussi, Joana, Steve Sonka, Gary D. Schnitkey, Eric L. Morgan, and Antônio D. Padula. 2024. "A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil" Agriculture 14, no. 7: 1027. https://doi.org/10.3390/agriculture14071027

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Environmental Science: Water Research & Technology

Solving biofouling problem of uranium extraction from seawater by plasma technology.

The effective extraction of uranium (U(VI)) from seawater is critical for the sound development of nuclear energy in near future. Biofouling is one of the core problems of U(VI) extraction from seawater that must be solved soon. In this work, plasma technology is applied to solve biofouling problem of U(VI) extraction from seawater. Experimental results show that reactive oxygen species (ROS) formed during plasma discharging process can effectively kill marine microorganisms in 30 min by destroying its wall membrane structure and remove its extracellular polymers (EPS), which can sound improve its U(VI) adsorption capability. Plasma treatment also has a significant effect on the microorganism compositions in seawater, and can effectively kill Proteobacteria species including V. alginolyticus. In summary, plasma sterilization is a fast, effective, and simple process. It can sound solve the biofouling problem, and simultaneously improve the recovery capability of PAO based materials for U(VI) from seawater.

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Fact-Checking Biden’s and Trump’s Claims on Domestic Policy

We scrutinized the presidential candidates’ recent claims on abortion, health care, crime and climate change ahead of the debate.

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President Biden and former President Donald J. Trump will face off Thursday night for the first time in four years, giving each ample opportunity to fling accusations about the other’s positions. Some will hew close to the facts, but there will most likely be ample exaggeration or statements lacking adequate nuance.

The two candidates have not been shy in their critiques and attacks on each other on the campaign trail.

The presumptive nominees have sparred over immigration policy and the state of the economy . Mr. Trump has portrayed the country, hyperbolically, under Mr. Biden as lawless. Mr. Biden has sometimes omitted context while describing Mr. Trump’s views on abortion rights and the Affordable Care Act.

Here’s a fact check of some of their recent claims on domestic issues.

Mr. Trump misrepresented abortion laws and crime levels across the country.

What Was Said

“It’s hard to believe they have some states passing legislation where you can execute the baby after birth.” — Mr. Trump in an interview on Fox News in June

False. No state has passed a law allowing the execution of a baby after it is born, which is infanticide.

Since the Supreme Court overturned the constitutional right to abortion, about 20 states have enacted protections enshrining the right in state constitutions and shielding those seeking or providing abortions in the state from restrictions in other states. None of these new laws allow for “executing” the baby after birth.

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Education reform and change driven by digital technology: a bibliometric study from a global perspective

• Chengliang Wang 1 ,
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• Teng Yu   ORCID: orcid.org/0000-0001-5198-7261 2 , 3 ,
• Yidan Liu 1 , 4 &
• Yuhui Jing 1  

Humanities and Social Sciences Communications volume  11 , Article number:  256 ( 2024 ) Cite this article

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• Development studies
• Science, technology and society

Amidst the global digital transformation of educational institutions, digital technology has emerged as a significant area of interest among scholars. Such technologies have played an instrumental role in enhancing learner performance and improving the effectiveness of teaching and learning. These digital technologies also ensure the sustainability and stability of education during the epidemic. Despite this, a dearth of systematic reviews exists regarding the current state of digital technology application in education. To address this gap, this study utilized the Web of Science Core Collection as a data source (specifically selecting the high-quality SSCI and SCIE) and implemented a topic search by setting keywords, yielding 1849 initial publications. Furthermore, following the PRISMA guidelines, we refined the selection to 588 high-quality articles. Using software tools such as CiteSpace, VOSviewer, and Charticulator, we reviewed these 588 publications to identify core authors (such as Selwyn, Henderson, Edwards), highly productive countries/regions (England, Australia, USA), key institutions (Monash University, Australian Catholic University), and crucial journals in the field ( Education and Information Technologies , Computers & Education , British Journal of Educational Technology ). Evolutionary analysis reveals four developmental periods in the research field of digital technology education application: the embryonic period, the preliminary development period, the key exploration, and the acceleration period of change. The study highlights the dual influence of technological factors and historical context on the research topic. Technology is a key factor in enabling education to transform and upgrade, and the context of the times is an important driving force in promoting the adoption of new technologies in the education system and the transformation and upgrading of education. Additionally, the study identifies three frontier hotspots in the field: physical education, digital transformation, and professional development under the promotion of digital technology. This study presents a clear framework for digital technology application in education, which can serve as a valuable reference for researchers and educational practitioners concerned with digital technology education application in theory and practice.

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Introduction.

Digital technology has become an essential component of modern education, facilitating the extension of temporal and spatial boundaries and enriching the pedagogical contexts (Selwyn and Facer, 2014 ). The advent of mobile communication technology has enabled learning through social media platforms (Szeto et al. 2015 ; Pires et al. 2022 ), while the advancement of augmented reality technology has disrupted traditional conceptions of learning environments and spaces (Perez-Sanagustin et al., 2014 ; Kyza and Georgiou, 2018 ). A wide range of digital technologies has enabled learning to become a norm in various settings, including the workplace (Sjöberg and Holmgren, 2021 ), home (Nazare et al. 2022 ), and online communities (Tang and Lam, 2014 ). Education is no longer limited to fixed locations and schedules, but has permeated all aspects of life, allowing learning to continue at any time and any place (Camilleri and Camilleri, 2016 ; Selwyn and Facer, 2014 ).

The advent of digital technology has led to the creation of several informal learning environments (Greenhow and Lewin, 2015 ) that exhibit divergent form, function, features, and patterns in comparison to conventional learning environments (Nygren et al. 2019 ). Consequently, the associated teaching and learning processes, as well as the strategies for the creation, dissemination, and acquisition of learning resources, have undergone a complete overhaul. The ensuing transformations have posed a myriad of novel issues, such as the optimal structuring of teaching methods by instructors and the adoption of appropriate learning strategies by students in the new digital technology environment. Consequently, an examination of the principles that underpin effective teaching and learning in this environment is a topic of significant interest to numerous scholars engaged in digital technology education research.

Over the course of the last two decades, digital technology has made significant strides in the field of education, notably in extending education time and space and creating novel educational contexts with sustainability. Despite research attempts to consolidate the application of digital technology in education, previous studies have only focused on specific aspects of digital technology, such as Pinto and Leite’s ( 2020 ) investigation into digital technology in higher education and Mustapha et al.’s ( 2021 ) examination of the role and value of digital technology in education during the pandemic. While these studies have provided valuable insights into the practical applications of digital technology in particular educational domains, they have not comprehensively explored the macro-mechanisms and internal logic of digital technology implementation in education. Additionally, these studies were conducted over a relatively brief period, making it challenging to gain a comprehensive understanding of the macro-dynamics and evolutionary process of digital technology in education. Some studies have provided an overview of digital education from an educational perspective but lack a precise understanding of technological advancement and change (Yang et al. 2022 ). Therefore, this study seeks to employ a systematic scientific approach to collate relevant research from 2000 to 2022, comprehend the internal logic and development trends of digital technology in education, and grasp the outstanding contribution of digital technology in promoting the sustainability of education in time and space. In summary, this study aims to address the following questions:

RQ1: Since the turn of the century, what is the productivity distribution of the field of digital technology education application research in terms of authorship, country/region, institutional and journal level?

RQ2: What is the development trend of research on the application of digital technology in education in the past two decades?

RQ3: What are the current frontiers of research on the application of digital technology in education?

Literature review

Although the term “digital technology” has become ubiquitous, a unified definition has yet to be agreed upon by scholars. Because the meaning of the word digital technology is closely related to the specific context. Within the educational research domain, Selwyn’s ( 2016 ) definition is widely favored by scholars (Pinto and Leite, 2020 ). Selwyn ( 2016 ) provides a comprehensive view of various concrete digital technologies and their applications in education through ten specific cases, such as immediate feedback in classes, orchestrating teaching, and community learning. Through these specific application scenarios, Selwyn ( 2016 ) argues that digital technology encompasses technologies associated with digital devices, including but not limited to tablets, smartphones, computers, and social media platforms (such as Facebook and YouTube). Furthermore, Further, the behavior of accessing the internet at any location through portable devices can be taken as an extension of the behavior of applying digital technology.

The evolving nature of digital technology has significant implications in the field of education. In the 1890s, the focus of digital technology in education was on comprehending the nuances of digital space, digital culture, and educational methodologies, with its connotations aligned more towards the idea of e-learning. The advent and subsequent widespread usage of mobile devices since the dawn of the new millennium have been instrumental in the rapid expansion of the concept of digital technology. Notably, mobile learning devices such as smartphones and tablets, along with social media platforms, have become integral components of digital technology (Conole and Alevizou, 2010 ; Batista et al. 2016 ). In recent times, the burgeoning application of AI technology in the education sector has played a vital role in enriching the digital technology lexicon (Banerjee et al. 2021 ). ChatGPT, for instance, is identified as a novel educational technology that has immense potential to revolutionize future education (Rospigliosi, 2023 ; Arif, Munaf and Ul-Haque, 2023 ).

Pinto and Leite ( 2020 ) conducted a comprehensive macroscopic survey of the use of digital technologies in the education sector and identified three distinct categories, namely technologies for assessment and feedback, mobile technologies, and Information Communication Technologies (ICT). This classification criterion is both macroscopic and highly condensed. In light of the established concept definitions of digital technology in the educational research literature, this study has adopted the characterizations of digital technology proposed by Selwyn ( 2016 ) and Pinto and Leite ( 2020 ) as crucial criteria for analysis and research inclusion. Specifically, this criterion encompasses several distinct types of digital technologies, including Information and Communication Technologies (ICT), Mobile tools, eXtended Reality (XR) Technologies, Assessment and Feedback systems, Learning Management Systems (LMS), Publish and Share tools, Collaborative systems, Social media, Interpersonal Communication tools, and Content Aggregation tools.

Methodology and materials

Research method: bibliometric.

The research on econometric properties has been present in various aspects of human production and life, yet systematic scientific theoretical guidance has been lacking, resulting in disorganization. In 1969, British scholar Pritchard ( 1969 ) proposed “bibliometrics,” which subsequently emerged as an independent discipline in scientific quantification research. Initially, Pritchard defined bibliometrics as “the application of mathematical and statistical methods to books and other media of communication,” however, the definition was not entirely rigorous. To remedy this, Hawkins ( 2001 ) expanded Pritchard’s definition to “the quantitative analysis of the bibliographic features of a body of literature.” De Bellis further clarified the objectives of bibliometrics, stating that it aims to analyze and identify patterns in literature, such as the most productive authors, institutions, countries, and journals in scientific disciplines, trends in literary production over time, and collaboration networks (De Bellis, 2009 ). According to Garfield ( 2006 ), bibliometric research enables the examination of the history and structure of a field, the flow of information within the field, the impact of journals, and the citation status of publications over a longer time scale. All of these definitions illustrate the unique role of bibliometrics as a research method for evaluating specific research fields.

This study uses CiteSpace, VOSviewer, and Charticulator to analyze data and create visualizations. Each of these three tools has its own strengths and can complement each other. CiteSpace and VOSviewer use set theory and probability theory to provide various visualization views in fields such as keywords, co-occurrence, and co-authors. They are easy to use and produce visually appealing graphics (Chen, 2006 ; van Eck and Waltman, 2009 ) and are currently the two most widely used bibliometric tools in the field of visualization (Pan et al. 2018 ). In this study, VOSviewer provided the data necessary for the Performance Analysis; Charticulator was then used to redraw using the tabular data exported from VOSviewer (for creating the chord diagram of country collaboration); this was to complement the mapping process, while CiteSpace was primarily utilized to generate keyword maps and conduct burst word analysis.

Data retrieval

This study selected documents from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) in the Web of Science Core Collection as the data source, for the following reasons:

(1) The Web of Science Core Collection, as a high-quality digital literature resource database, has been widely accepted by many researchers and is currently considered the most suitable database for bibliometric analysis (Jing et al. 2023a ). Compared to other databases, Web of Science provides more comprehensive data information (Chen et al. 2022a ), and also provides data formats suitable for analysis using VOSviewer and CiteSpace (Gaviria-Marin et al. 2019 ).

(2) The application of digital technology in the field of education is an interdisciplinary research topic, involving technical knowledge literature belonging to the natural sciences and education-related literature belonging to the social sciences. Therefore, it is necessary to select Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) as the sources of research data, ensuring the comprehensiveness of data while ensuring the reliability and persuasiveness of bibliometric research (Hwang and Tsai, 2011 ; Wang et al. 2022 ).

After establishing the source of research data, it is necessary to determine a retrieval strategy (Jing et al. 2023b ). The choice of a retrieval strategy should consider a balance between the breadth and precision of the search formula. That is to say, it should encompass all the literature pertaining to the research topic while excluding irrelevant documents as much as possible. In light of this, this study has set a retrieval strategy informed by multiple related papers (Mustapha et al. 2021 ; Luo et al. 2021 ). The research by Mustapha et al. ( 2021 ) guided us in selecting keywords (“digital” AND “technolog*”) to target digital technology, while Luo et al. ( 2021 ) informed the selection of terms (such as “instruct*,” “teach*,” and “education”) to establish links with the field of education. Then, based on the current application of digital technology in the educational domain and the scope of selection criteria, we constructed the final retrieval strategy. Following the general patterns of past research (Jing et al. 2023a , 2023b ), we conducted a specific screening using the topic search (Topics, TS) function in Web of Science. For the specific criteria used in the screening for this study, please refer to Table 1 .

Literature screening

Literature acquired through keyword searches may contain ostensibly related yet actually unrelated works. Therefore, to ensure the close relevance of literature included in the analysis to the research topic, it is often necessary to perform a manual screening process to identify the final literature to be analyzed, subsequent to completing the initial literature search.

The manual screening process consists of two steps. Initially, irrelevant literature is weeded out based on the title and abstract, with two members of the research team involved in this phase. This stage lasted about one week, resulting in 1106 articles being retained. Subsequently, a comprehensive review of the full text is conducted to accurately identify the literature required for the study. To carry out the second phase of manual screening effectively and scientifically, and to minimize the potential for researcher bias, the research team established the inclusion criteria presented in Table 2 . Three members were engaged in this phase, which took approximately 2 weeks, culminating in the retention of 588 articles after meticulous screening. The entire screening process is depicted in Fig. 1 , adhering to the PRISMA guidelines (Page et al. 2021 ).

The process of obtaining and filtering the necessary literature data for research.

Data standardization

Nguyen and Hallinger ( 2020 ) pointed out that raw data extracted from scientific databases often contains multiple expressions of the same term, and not addressing these synonymous expressions could affect research results in bibliometric analysis. For instance, in the original data, the author list may include “Tsai, C. C.” and “Tsai, C.-C.”, while the keyword list may include “professional-development” and “professional development,” which often require merging. Therefore, before analyzing the selected literature, a data disambiguation process is necessary to standardize the data (Strotmann and Zhao, 2012 ; Van Eck and Waltman, 2019 ). This study adopted the data standardization process proposed by Taskin and Al ( 2019 ), mainly including the following standardization operations:

Firstly, the author and source fields in the data are corrected and standardized to differentiate authors with similar names.

Secondly, the study checks whether the journals to which the literature belongs have been renamed in the past over 20 years, so as to avoid the influence of periodical name change on the analysis results.

Finally, the keyword field is standardized by unifying parts of speech and singular/plural forms of keywords, which can help eliminate redundant entries in the knowledge graph.

Performance analysis (RQ1)

This section offers a thorough and detailed analysis of the state of research in the field of digital technology education. By utilizing descriptive statistics and visual maps, it provides a comprehensive overview of the development trends, authors, countries, institutions, and journal distribution within the field. The insights presented in this section are of great significance in advancing our understanding of the current state of research in this field and identifying areas for further investigation. The use of visual aids to display inter-country cooperation and the evolution of the field adds to the clarity and coherence of the analysis.

Time trend of the publications

To understand a research field, it is first necessary to understand the most basic quantitative information, among which the change in the number of publications per year best reflects the development trend of a research field. Figure 2 shows the distribution of publication dates.

Time trend of the publications on application of digital technology in education.

From the Fig. 2 , it can be seen that the development of this field over the past over 20 years can be roughly divided into three stages. The first stage was from 2000 to 2007, during which the number of publications was relatively low. Due to various factors such as technological maturity, the academic community did not pay widespread attention to the role of digital technology in expanding the scope of teaching and learning. The second stage was from 2008 to 2019, during which the overall number of publications showed an upward trend, and the development of the field entered an accelerated period, attracting more and more scholars’ attention. The third stage was from 2020 to 2022, during which the number of publications stabilized at around 100. During this period, the impact of the pandemic led to a large number of scholars focusing on the role of digital technology in education during the pandemic, and research on the application of digital technology in education became a core topic in social science research.

Analysis of authors

An analysis of the author’s publication volume provides information about the representative scholars and core research strengths of a research area. Table 3 presents information on the core authors in adaptive learning research, including name, publication number, and average number of citations per article (based on the analysis and statistics from VOSviewer).

Variations in research foci among scholars abound. Within the field of digital technology education application research over the past two decades, Neil Selwyn stands as the most productive author, having published 15 papers garnering a total of 1027 citations, resulting in an average of 68.47 citations per paper. As a Professor at the Faculty of Education at Monash University, Selwyn concentrates on exploring the application of digital technology in higher education contexts (Selwyn et al. 2021 ), as well as related products in higher education such as Coursera, edX, and Udacity MOOC platforms (Bulfin et al. 2014 ). Selwyn’s contributions to the educational sociology perspective include extensive research on the impact of digital technology on education, highlighting the spatiotemporal extension of educational processes and practices through technological means as the greatest value of educational technology (Selwyn, 2012 ; Selwyn and Facer, 2014 ). In addition, he provides a blueprint for the development of future schools in 2030 based on the present impact of digital technology on education (Selwyn et al. 2019 ). The second most productive author in this field, Henderson, also offers significant contributions to the understanding of the important value of digital technology in education, specifically in the higher education setting, with a focus on the impact of the pandemic (Henderson et al. 2015 ; Cohen et al. 2022 ). In contrast, Edwards’ research interests focus on early childhood education, particularly the application of digital technology in this context (Edwards, 2013 ; Bird and Edwards, 2015 ). Additionally, on the technical level, Edwards also mainly prefers digital game technology, because it is a digital technology that children are relatively easy to accept (Edwards, 2015 ).

Analysis of countries/regions and organization

The present study aimed to ascertain the leading countries in digital technology education application research by analyzing 75 countries related to 558 works of literature. Table 4 depicts the top ten countries that have contributed significantly to this field in terms of publication count (based on the analysis and statistics from VOSviewer). Our analysis of Table 4 data shows that England emerged as the most influential country/region, with 92 published papers and 2401 citations. Australia and the United States secured the second and third ranks, respectively, with 90 papers (2187 citations) and 70 papers (1331 citations) published. Geographically, most of the countries featured in the top ten publication volumes are situated in Australia, North America, and Europe, with China being the only exception. Notably, all these countries, except China, belong to the group of developed nations, suggesting that economic strength is a prerequisite for fostering research in the digital technology education application field.

This study presents a visual representation of the publication output and cooperation relationships among different countries in the field of digital technology education application research. Specifically, a chord diagram is employed to display the top 30 countries in terms of publication output, as depicted in Fig. 3 . The chord diagram is composed of nodes and chords, where the nodes are positioned as scattered points along the circumference, and the length of each node corresponds to the publication output, with longer lengths indicating higher publication output. The chords, on the other hand, represent the cooperation relationships between any two countries, and are weighted based on the degree of closeness of the cooperation, with wider chords indicating closer cooperation. Through the analysis of the cooperation relationships, the findings suggest that the main publishing countries in this field are engaged in cooperative relationships with each other, indicating a relatively high level of international academic exchange and research internationalization.

In the diagram, nodes are scattered along the circumference of a circle, with the length of each node representing the volume of publications. The weighted arcs connecting any two points on the circle are known as chords, representing the collaborative relationship between the two, with the width of the arc indicating the closeness of the collaboration.

Further analyzing Fig. 3 , we can extract more valuable information, enabling a deeper understanding of the connections between countries in the research field of digital technology in educational applications. It is evident that certain countries, such as the United States, China, and England, display thicker connections, indicating robust collaborative relationships in terms of productivity. These thicker lines signify substantial mutual contributions and shared objectives in certain sectors or fields, highlighting the interconnectedness and global integration in these areas. By delving deeper, we can also explore potential future collaboration opportunities through the chord diagram, identifying possible partners to propel research and development in this field. In essence, the chord diagram successfully encapsulates and conveys the multi-dimensionality of global productivity and cooperation, allowing for a comprehensive understanding of the intricate inter-country relationships and networks in a global context, providing valuable guidance and insights for future research and collaborations.

An in-depth examination of the publishing institutions is provided in Table 5 , showcasing the foremost 10 institutions ranked by their publication volume. Notably, Monash University and Australian Catholic University, situated in Australia, have recorded the most prolific publications within the digital technology education application realm, with 22 and 10 publications respectively. Moreover, the University of Oslo from Norway is featured among the top 10 publishing institutions, with an impressive average citation count of 64 per publication. It is worth highlighting that six institutions based in the United Kingdom were also ranked within the top 10 publishing institutions, signifying their leading position in this area of research.

Analysis of journals

Journals are the main carriers for publishing high-quality papers. Some scholars point out that the two key factors to measure the influence of journals in the specified field are the number of articles published and the number of citations. The more papers published in a magazine and the more citations, the greater its influence (Dzikowski, 2018 ). Therefore, this study utilized VOSviewer to statistically analyze the top 10 journals with the most publications in the field of digital technology in education and calculated the average citations per article (see Table 6 ).

Based on Table 6 , it is apparent that the highest number of articles in the domain of digital technology in education research were published in Education and Information Technologies (47 articles), Computers & Education (34 articles), and British Journal of Educational Technology (32 articles), indicating a higher article output compared to other journals. This underscores the fact that these three journals concentrate more on the application of digital technology in education. Furthermore, several other journals, such as Technology Pedagogy and Education and Sustainability, have published more than 15 articles in this domain. Sustainability represents the open access movement, which has notably facilitated research progress in this field, indicating that the development of open access journals in recent years has had a significant impact. Although there is still considerable disagreement among scholars on the optimal approach to achieve open access, the notion that research outcomes should be accessible to all is widely recognized (Huang et al. 2020 ). On further analysis of the research fields to which these journals belong, except for Sustainability, it is evident that they all pertain to educational technology, thus providing a qualitative definition of the research area of digital technology education from the perspective of journals.

Temporal keyword analysis: thematic evolution (RQ2)

The evolution of research themes is a dynamic process, and previous studies have attempted to present the developmental trajectory of fields by drawing keyword networks in phases (Kumar et al. 2021 ; Chen et al. 2022b ). To understand the shifts in research topics across different periods, this study follows past research and, based on the significant changes in the research field and corresponding technological advancements during the outlined periods, divides the timeline into four stages (the first stage from January 2000 to December 2005, the second stage from January 2006 to December 2011, the third stage from January 2012 to December 2017; and the fourth stage from January 2018 to December 2022). The division into these four stages was determined through a combination of bibliometric analysis and literature review, which presented a clear trajectory of the field’s development. The research analyzes the keyword networks for each time period (as there are only three articles in the first stage, it was not possible to generate an appropriate keyword co-occurrence map, hence only the keyword co-occurrence maps from the second to the fourth stages are provided), to understand the evolutionary track of the digital technology education application research field over time.

2000.1–2005.12: germination period

From January 2000 to December 2005, digital technology education application research was in its infancy. Only three studies focused on digital technology, all of which were related to computers. Due to the popularity of computers, the home became a new learning environment, highlighting the important role of digital technology in expanding the scope of learning spaces (Sutherland et al. 2000 ). In specific disciplines and contexts, digital technology was first favored in medical clinical practice, becoming an important tool for supporting the learning of clinical knowledge and practice (Tegtmeyer et al. 2001 ; Durfee et al. 2003 ).

2006.1–2011.12: initial development period

Between January 2006 and December 2011, it was the initial development period of digital technology education research. Significant growth was observed in research related to digital technology, and discussions and theoretical analyses about “digital natives” emerged. During this phase, scholars focused on the debate about “how to use digital technology reasonably” and “whether current educational models and school curriculum design need to be adjusted on a large scale” (Bennett and Maton, 2010 ; Selwyn, 2009 ; Margaryan et al. 2011 ). These theoretical and speculative arguments provided a unique perspective on the impact of cognitive digital technology on education and teaching. As can be seen from the vocabulary such as “rethinking”, “disruptive pedagogy”, and “attitude” in Fig. 4 , many scholars joined the calm reflection and analysis under the trend of digital technology (Laurillard, 2008 ; Vratulis et al. 2011 ). During this phase, technology was still undergoing dramatic changes. The development of mobile technology had already caught the attention of many scholars (Wong et al. 2011 ), but digital technology represented by computers was still very active (Selwyn et al. 2011 ). The change in technological form would inevitably lead to educational transformation. Collins and Halverson ( 2010 ) summarized the prospects and challenges of using digital technology for learning and educational practices, believing that digital technology would bring a disruptive revolution to the education field and bring about a new educational system. In addition, the term “teacher education” in Fig. 4 reflects the impact of digital technology development on teachers. The rapid development of technology has widened the generation gap between teachers and students. To ensure smooth communication between teachers and students, teachers must keep up with the trend of technological development and establish a lifelong learning concept (Donnison, 2009 ).

In the diagram, each node represents a keyword, with the size of the node indicating the frequency of occurrence of the keyword. The connections represent the co-occurrence relationships between keywords, with a higher frequency of co-occurrence resulting in tighter connections.

2012.1–2017.12: critical exploration period

During the period spanning January 2012 to December 2017, the application of digital technology in education research underwent a significant exploration phase. As can be seen from Fig. 5 , different from the previous stage, the specific elements of specific digital technology have started to increase significantly, including the enrichment of technological contexts, the greater variety of research methods, and the diversification of learning modes. Moreover, the temporal and spatial dimensions of the learning environment were further de-emphasized, as noted in previous literature (Za et al. 2014 ). Given the rapidly accelerating pace of technological development, the education system in the digital era is in urgent need of collaborative evolution and reconstruction, as argued by Davis, Eickelmann, and Zaka ( 2013 ).

In the domain of digital technology, social media has garnered substantial scholarly attention as a promising avenue for learning, as noted by Pasquini and Evangelopoulos ( 2016 ). The implementation of social media in education presents several benefits, including the liberation of education from the restrictions of physical distance and time, as well as the erasure of conventional educational boundaries. The user-generated content (UGC) model in social media has emerged as a crucial source for knowledge creation and distribution, with the widespread adoption of mobile devices. Moreover, social networks have become an integral component of ubiquitous learning environments (Hwang et al. 2013 ). The utilization of social media allows individuals to function as both knowledge producers and recipients, which leads to a blurring of the conventional roles of learners and teachers. On mobile platforms, the roles of learners and teachers are not fixed, but instead interchangeable.

In terms of research methodology, the prevalence of empirical studies with survey designs in the field of educational technology during this period is evident from the vocabulary used, such as “achievement,” “acceptance,” “attitude,” and “ict.” in Fig. 5 . These studies aim to understand learners’ willingness to adopt and attitudes towards new technologies, and some seek to investigate the impact of digital technologies on learning outcomes through quasi-experimental designs (Domínguez et al. 2013 ). Among these empirical studies, mobile learning emerged as a hot topic, and this is not surprising. First, the advantages of mobile learning environments over traditional ones have been empirically demonstrated (Hwang et al. 2013 ). Second, learners born around the turn of the century have been heavily influenced by digital technologies and have developed their own learning styles that are more open to mobile devices as a means of learning. Consequently, analyzing mobile learning as a relatively novel mode of learning has become an important issue for scholars in the field of educational technology.

The intervention of technology has led to the emergence of several novel learning modes, with the blended learning model being the most representative one in the current phase. Blended learning, a novel concept introduced in the information age, emphasizes the integration of the benefits of traditional learning methods and online learning. This learning mode not only highlights the prominent role of teachers in guiding, inspiring, and monitoring the learning process but also underlines the importance of learners’ initiative, enthusiasm, and creativity in the learning process. Despite being an early conceptualization, blended learning’s meaning has been expanded by the widespread use of mobile technology and social media in education. The implementation of new technologies, particularly mobile devices, has resulted in the transformation of curriculum design and increased flexibility and autonomy in students’ learning processes (Trujillo Maza et al. 2016 ), rekindling scholarly attention to this learning mode. However, some scholars have raised concerns about the potential drawbacks of the blended learning model, such as its significant impact on the traditional teaching system, the lack of systematic coping strategies and relevant policies in several schools and regions (Moskal et al. 2013 ).

2018.1–2022.12: accelerated transformation period

The period spanning from January 2018 to December 2022 witnessed a rapid transformation in the application of digital technology in education research. The field of digital technology education research reached a peak period of publication, largely influenced by factors such as the COVID-19 pandemic (Yu et al. 2023 ). Research during this period was built upon the achievements, attitudes, and social media of the previous phase, and included more elements that reflect the characteristics of this research field, such as digital literacy, digital competence, and professional development, as depicted in Fig. 6 . Alongside this, scholars’ expectations for the value of digital technology have expanded, and the pursuit of improving learning efficiency and performance is no longer the sole focus. Some research now aims to cultivate learners’ motivation and enhance their self-efficacy by applying digital technology in a reasonable manner, as demonstrated by recent studies (Beardsley et al. 2021 ; Creely et al. 2021 ).

The COVID-19 pandemic has emerged as a crucial backdrop for the digital technology’s role in sustaining global education, as highlighted by recent scholarly research (Zhou et al. 2022 ; Pan and Zhang, 2020 ; Mo et al. 2022 ). The online learning environment, which is supported by digital technology, has become the primary battleground for global education (Yu, 2022 ). This social context has led to various studies being conducted, with some scholars positing that the pandemic has impacted the traditional teaching order while also expanding learning possibilities in terms of patterns and forms (Alabdulaziz, 2021 ). Furthermore, the pandemic has acted as a catalyst for teacher teaching and technological innovation, and this viewpoint has been empirically substantiated (Moorhouse and Wong, 2021 ). Additionally, some scholars believe that the pandemic’s push is a crucial driving force for the digital transformation of the education system, serving as an essential mechanism for overcoming the system’s inertia (Romero et al. 2021 ).

The rapid outbreak of the pandemic posed a challenge to the large-scale implementation of digital technologies, which was influenced by a complex interplay of subjective and objective factors. Objective constraints included the lack of infrastructure in some regions to support digital technologies, while subjective obstacles included psychological resistance among certain students and teachers (Moorhouse, 2021 ). These factors greatly impacted the progress of online learning during the pandemic. Additionally, Timotheou et al. ( 2023 ) conducted a comprehensive systematic review of existing research on digital technology use during the pandemic, highlighting the critical role played by various factors such as learners’ and teachers’ digital skills, teachers’ personal attributes and professional development, school leadership and management, and administration in facilitating the digitalization and transformation of schools.

The current stage of research is characterized by the pivotal term “digital literacy,” denoting a growing interest in learners’ attitudes and adoption of emerging technologies. Initially, the term “literacy” was restricted to fundamental abilities and knowledge associated with books and print materials (McMillan, 1996 ). However, with the swift advancement of computers and digital technology, there have been various attempts to broaden the scope of literacy beyond its traditional meaning, including game literacy (Buckingham and Burn, 2007 ), information literacy (Eisenberg, 2008 ), and media literacy (Turin and Friesem, 2020 ). Similarly, digital literacy has emerged as a crucial concept, and Gilster and Glister ( 1997 ) were the first to introduce this concept, referring to the proficiency in utilizing technology and processing digital information in academic, professional, and daily life settings. In practical educational settings, learners who possess higher digital literacy often exhibit an aptitude for quickly mastering digital devices and applying them intelligently to education and teaching (Yu, 2022 ).

The utilization of digital technology in education has undergone significant changes over the past two decades, and has been a crucial driver of educational reform with each new technological revolution. The impact of these changes on the underlying logic of digital technology education applications has been noticeable. From computer technology to more recent developments such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), the acceleration in digital technology development has been ongoing. Educational reforms spurred by digital technology development continue to be dynamic, as each new digital innovation presents new possibilities and models for teaching practice. This is especially relevant in the post-pandemic era, where the importance of technological progress in supporting teaching cannot be overstated (Mughal et al. 2022 ). Existing digital technologies have already greatly expanded the dimensions of education in both time and space, while future digital technologies aim to expand learners’ perceptions. Researchers have highlighted the potential of integrated technology and immersive technology in the development of the educational metaverse, which is highly anticipated to create a new dimension for the teaching and learning environment, foster a new value system for the discipline of educational technology, and more effectively and efficiently achieve the grand educational blueprint of the United Nations’ Sustainable Development Goals (Zhang et al. 2022 ; Li and Yu, 2023 ).

Hotspot evolution analysis (RQ3)

The examination of keyword evolution reveals a consistent trend in the advancement of digital technology education application research. The emergence and transformation of keywords serve as indicators of the varying research interests in this field. Thus, the utilization of the burst detection function available in CiteSpace allowed for the identification of the top 10 burst words that exhibited a high level of burst strength. This outcome is illustrated in Table 7 .

According to the results presented in Table 7 , the explosive terminology within the realm of digital technology education research has exhibited a concentration mainly between the years 2018 and 2022. Prior to this time frame, the emerging keywords were limited to “information technology” and “computer”. Notably, among them, computer, as an emergent keyword, has always had a high explosive intensity from 2008 to 2018, which reflects the important position of computer in digital technology and is the main carrier of many digital technologies such as Learning Management Systems (LMS) and Assessment and Feedback systems (Barlovits et al. 2022 ).

Since 2018, an increasing number of research studies have focused on evaluating the capabilities of learners to accept, apply, and comprehend digital technologies. As indicated by the use of terms such as “digital literacy” and “digital skill,” the assessment of learners’ digital literacy has become a critical task. Scholarly efforts have been directed towards the development of literacy assessment tools and the implementation of empirical assessments. Furthermore, enhancing the digital literacy of both learners and educators has garnered significant attention. (Nagle, 2018 ; Yu, 2022 ). Simultaneously, given the widespread use of various digital technologies in different formal and informal learning settings, promoting learners’ digital skills has become a crucial objective for contemporary schools (Nygren et al. 2019 ; Forde and OBrien, 2022 ).

Since 2020, the field of applied research on digital technology education has witnessed the emergence of three new hotspots, all of which have been affected to some extent by the pandemic. Firstly, digital technology has been widely applied in physical education, which is one of the subjects that has been severely affected by the pandemic (Parris et al. 2022 ; Jiang and Ning, 2022 ). Secondly, digital transformation has become an important measure for most schools, especially higher education institutions, to cope with the impact of the pandemic globally (García-Morales et al. 2021 ). Although the concept of digital transformation was proposed earlier, the COVID-19 pandemic has greatly accelerated this transformation process. Educational institutions must carefully redesign their educational products to face this new situation, providing timely digital learning methods, environments, tools, and support systems that have far-reaching impacts on modern society (Krishnamurthy, 2020 ; Salas-Pilco et al. 2022 ). Moreover, the professional development of teachers has become a key mission of educational institutions in the post-pandemic era. Teachers need to have a certain level of digital literacy and be familiar with the tools and online teaching resources used in online teaching, which has become a research hotspot today. Organizing digital skills training for teachers to cope with the application of emerging technologies in education is an important issue for teacher professional development and lifelong learning (Garzón-Artacho et al. 2021 ). As the main organizers and practitioners of emergency remote teaching (ERT) during the pandemic, teachers must put cognitive effort into their professional development to ensure effective implementation of ERT (Romero-Hall and Jaramillo Cherrez, 2022 ).

The burst word “digital transformation” reveals that we are in the midst of an ongoing digital technology revolution. With the emergence of innovative digital technologies such as ChatGPT and Microsoft 365 Copilot, technology trends will continue to evolve, albeit unpredictably. While the impact of these advancements on school education remains uncertain, it is anticipated that the widespread integration of technology will significantly affect the current education system. Rejecting emerging technologies without careful consideration is unwise. Like any revolution, the technological revolution in the education field has both positive and negative aspects. Detractors argue that digital technology disrupts learning and memory (Baron, 2021 ) or causes learners to become addicted and distracted from learning (Selwyn and Aagaard, 2020 ). On the other hand, the prudent use of digital technology in education offers a glimpse of a golden age of open learning. Educational leaders and practitioners have the opportunity to leverage cutting-edge digital technologies to address current educational challenges and develop a rational path for the sustainable and healthy growth of education.

Discussion on performance analysis (RQ1)

The field of digital technology education application research has experienced substantial growth since the turn of the century, a phenomenon that is quantifiably apparent through an analysis of authorship, country/region contributions, and institutional engagement. This expansion reflects the increased integration of digital technologies in educational settings and the heightened scholarly interest in understanding and optimizing their use.

Discussion on authorship productivity in digital technology education research

The authorship distribution within digital technology education research is indicative of the field’s intellectual structure and depth. A primary figure in this domain is Neil Selwyn, whose substantial citation rate underscores the profound impact of his work. His focus on the implications of digital technology in higher education and educational sociology has proven to be seminal. Selwyn’s research trajectory, especially the exploration of spatiotemporal extensions of education through technology, provides valuable insights into the multifaceted role of digital tools in learning processes (Selwyn et al. 2019 ).

Other notable contributors, like Henderson and Edwards, present diversified research interests, such as the impact of digital technologies during the pandemic and their application in early childhood education, respectively. Their varied focuses highlight the breadth of digital technology education research, encompassing pedagogical innovation, technological adaptation, and policy development.

Discussion on country/region-level productivity and collaboration

At the country/region level, the United Kingdom, specifically England, emerges as a leading contributor with 92 published papers and a significant citation count. This is closely followed by Australia and the United States, indicating a strong English-speaking research axis. Such geographical concentration of scholarly output often correlates with investment in research and development, technological infrastructure, and the prevalence of higher education institutions engaging in cutting-edge research.

China’s notable inclusion as the only non-Western country among the top contributors to the field suggests a growing research capacity and interest in digital technology in education. However, the lower average citation per paper for China could reflect emerging engagement or different research focuses that may not yet have achieved the same international recognition as Western counterparts.

The chord diagram analysis furthers this understanding, revealing dense interconnections between countries like the United States, China, and England, which indicates robust collaborations. Such collaborations are fundamental in addressing global educational challenges and shaping international research agendas.

Discussion on institutional-level contributions to digital technology education

Institutional productivity in digital technology education research reveals a constellation of universities driving the field forward. Monash University and the Australian Catholic University have the highest publication output, signaling Australia’s significant role in advancing digital education research. The University of Oslo’s remarkable average citation count per publication indicates influential research contributions, potentially reflecting high-quality studies that resonate with the broader academic community.

The strong showing of UK institutions, including the University of London, The Open University, and the University of Cambridge, reinforces the UK’s prominence in this research field. Such institutions are often at the forefront of pedagogical innovation, benefiting from established research cultures and funding mechanisms that support sustained inquiry into digital education.

Discussion on journal publication analysis

An examination of journal outputs offers a lens into the communicative channels of the field’s knowledge base. Journals such as Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology not only serve as the primary disseminators of research findings but also as indicators of research quality and relevance. The impact factor (IF) serves as a proxy for the quality and influence of these journals within the academic community.

The high citation counts for articles published in Computers & Education suggest that research disseminated through this medium has a wide-reaching impact and is of particular interest to the field. This is further evidenced by its significant IF of 11.182, indicating that the journal is a pivotal platform for seminal work in the application of digital technology in education.

The authorship, regional, and institutional productivity in the field of digital technology education application research collectively narrate the evolution of this domain since the turn of the century. The prominence of certain authors and countries underscores the importance of socioeconomic factors and existing academic infrastructure in fostering research productivity. Meanwhile, the centrality of specific journals as outlets for high-impact research emphasizes the role of academic publishing in shaping the research landscape.

As the field continues to grow, future research may benefit from leveraging the collaborative networks that have been elucidated through this analysis, perhaps focusing on underrepresented regions to broaden the scope and diversity of research. Furthermore, the stabilization of publication numbers in recent years invites a deeper exploration into potential plateaus in research trends or saturation in certain sub-fields, signaling an opportunity for novel inquiries and methodological innovations.

Discussion on the evolutionary trends (RQ2)

The evolution of the research field concerning the application of digital technology in education over the past two decades is a story of convergence, diversification, and transformation, shaped by rapid technological advancements and shifting educational paradigms.

At the turn of the century, the inception of digital technology in education was largely exploratory, with a focus on how emerging computer technologies could be harnessed to enhance traditional learning environments. Research from this early period was primarily descriptive, reflecting on the potential and challenges of incorporating digital tools into the educational setting. This phase was critical in establishing the fundamental discourse that would guide subsequent research, as it set the stage for understanding the scope and impact of digital technology in learning spaces (Wang et al. 2023 ).

As the first decade progressed, the narrative expanded to encompass the pedagogical implications of digital technologies. This was a period of conceptual debates, where terms like “digital natives” and “disruptive pedagogy” entered the academic lexicon, underscoring the growing acknowledgment of digital technology as a transformative force within education (Bennett and Maton, 2010 ). During this time, the research began to reflect a more nuanced understanding of the integration of technology, considering not only its potential to change where and how learning occurred but also its implications for educational equity and access.

In the second decade, with the maturation of internet connectivity and mobile technology, the focus of research shifted from theoretical speculations to empirical investigations. The proliferation of digital devices and the ubiquity of social media influenced how learners interacted with information and each other, prompting a surge in studies that sought to measure the impact of these tools on learning outcomes. The digital divide and issues related to digital literacy became central concerns, as scholars explored the varying capacities of students and educators to engage with technology effectively.

Throughout this period, there was an increasing emphasis on the individualization of learning experiences, facilitated by adaptive technologies that could cater to the unique needs and pacing of learners (Jing et al. 2023a ). This individualization was coupled with a growing recognition of the importance of collaborative learning, both online and offline, and the role of digital tools in supporting these processes. Blended learning models, which combined face-to-face instruction with online resources, emerged as a significant trend, advocating for a balance between traditional pedagogies and innovative digital strategies.

The later years, particularly marked by the COVID-19 pandemic, accelerated the necessity for digital technology in education, transforming it from a supplementary tool to an essential platform for delivering education globally (Mo et al. 2022 ; Mustapha et al. 2021 ). This era brought about an unprecedented focus on online learning environments, distance education, and virtual classrooms. Research became more granular, examining not just the pedagogical effectiveness of digital tools, but also their role in maintaining continuity of education during crises, their impact on teacher and student well-being, and their implications for the future of educational policy and infrastructure.

Across these two decades, the research field has seen a shift from examining digital technology as an external addition to the educational process, to viewing it as an integral component of curriculum design, instructional strategies, and even assessment methods. The emergent themes have broadened from a narrow focus on specific tools or platforms to include wider considerations such as data privacy, ethical use of technology, and the environmental impact of digital tools.

Moreover, the field has moved from considering the application of digital technology in education as a primarily cognitive endeavor to recognizing its role in facilitating socio-emotional learning, digital citizenship, and global competencies. Researchers have increasingly turned their attention to the ways in which technology can support collaborative skills, cultural understanding, and ethical reasoning within diverse student populations.

In summary, the past over twenty years in the research field of digital technology applications in education have been characterized by a progression from foundational inquiries to complex analyses of digital integration. This evolution has mirrored the trajectory of technology itself, from a facilitative tool to a pervasive ecosystem defining contemporary educational experiences. As we look to the future, the field is poised to delve into the implications of emerging technologies like AI, AR, and VR, and their potential to redefine the educational landscape even further. This ongoing metamorphosis suggests that the application of digital technology in education will continue to be a rich area of inquiry, demanding continual adaptation and forward-thinking from educators and researchers alike.

Discussion on the study of research hotspots (RQ3)

The analysis of keyword evolution in digital technology education application research elucidates the current frontiers in the field, reflecting a trajectory that is in tandem with the rapidly advancing digital age. This landscape is sculpted by emergent technological innovations and shaped by the demands of an increasingly digital society.

Interdisciplinary integration and pedagogical transformation

One of the frontiers identified from recent keyword bursts includes the integration of digital technology into diverse educational contexts, particularly noted with the keyword “physical education.” The digitalization of disciplines traditionally characterized by physical presence illustrates the pervasive reach of technology and signifies a push towards interdisciplinary integration where technology is not only a facilitator but also a transformative agent. This integration challenges educators to reconceptualize curriculum delivery to accommodate digital tools that can enhance or simulate the physical aspects of learning.

Digital literacy and skills acquisition

Another pivotal frontier is the focus on “digital literacy” and “digital skill”, which has intensified in recent years. This suggests a shift from mere access to technology towards a comprehensive understanding and utilization of digital tools. In this realm, the emphasis is not only on the ability to use technology but also on critical thinking, problem-solving, and the ethical use of digital resources (Yu, 2022 ). The acquisition of digital literacy is no longer an additive skill but a fundamental aspect of modern education, essential for navigating and contributing to the digital world.

Educational digital transformation

The keyword “digital transformation” marks a significant research frontier, emphasizing the systemic changes that education institutions must undergo to align with the digital era (Romero et al. 2021 ). This transformation includes the redesigning of learning environments, pedagogical strategies, and assessment methods to harness digital technology’s full potential. Research in this area explores the complexity of institutional change, addressing the infrastructural, cultural, and policy adjustments needed for a seamless digital transition.

Engagement and participation

Further exploration into “engagement” and “participation” underscores the importance of student-centered learning environments that are mediated by technology. The current frontiers examine how digital platforms can foster collaboration, inclusivity, and active learning, potentially leading to more meaningful and personalized educational experiences. Here, the use of technology seeks to support the emotional and cognitive aspects of learning, moving beyond the transactional view of education to one that is relational and interactive.

Professional development and teacher readiness

As the field evolves, “professional development” emerges as a crucial area, particularly in light of the pandemic which necessitated emergency remote teaching. The need for teacher readiness in a digital age is a pressing frontier, with research focusing on the competencies required for educators to effectively integrate technology into their teaching practices. This includes familiarity with digital tools, pedagogical innovation, and an ongoing commitment to personal and professional growth in the digital domain.

Pandemic as a catalyst

The recent pandemic has acted as a catalyst for accelerated research and application in this field, particularly in the domains of “digital transformation,” “professional development,” and “physical education.” This period has been a litmus test for the resilience and adaptability of educational systems to continue their operations in an emergency. Research has thus been directed at understanding how digital technologies can support not only continuity but also enhance the quality and reach of education in such contexts.

Ethical and societal considerations

The frontier of digital technology in education is also expanding to consider broader ethical and societal implications. This includes issues of digital equity, data privacy, and the sociocultural impact of technology on learning communities. The research explores how educational technology can be leveraged to address inequities and create more equitable learning opportunities for all students, regardless of their socioeconomic background.

Innovation and emerging technologies

Looking forward, the frontiers are set to be influenced by ongoing and future technological innovations, such as artificial intelligence (AI) (Wu and Yu, 2023 ; Chen et al. 2022a ). The exploration into how these technologies can be integrated into educational practices to create immersive and adaptive learning experiences represents a bold new chapter for the field.

In conclusion, the current frontiers of research on the application of digital technology in education are multifaceted and dynamic. They reflect an overarching movement towards deeper integration of technology in educational systems and pedagogical practices, where the goals are not only to facilitate learning but to redefine it. As these frontiers continue to expand and evolve, they will shape the educational landscape, requiring a concerted effort from researchers, educators, policymakers, and technologists to navigate the challenges and harness the opportunities presented by the digital revolution in education.

Conclusions and future research

Conclusions.

The utilization of digital technology in education is a research area that cuts across multiple technical and educational domains and continues to experience dynamic growth due to the continuous progress of technology. In this study, a systematic review of this field was conducted through bibliometric techniques to examine its development trajectory. The primary focus of the review was to investigate the leading contributors, productive national institutions, significant publications, and evolving development patterns. The study’s quantitative analysis resulted in several key conclusions that shed light on this research field’s current state and future prospects.

(1) The research field of digital technology education applications has entered a stage of rapid development, particularly in recent years due to the impact of the pandemic, resulting in a peak of publications. Within this field, several key authors (Selwyn, Henderson, Edwards, etc.) and countries/regions (England, Australia, USA, etc.) have emerged, who have made significant contributions. International exchanges in this field have become frequent, with a high degree of internationalization in academic research. Higher education institutions in the UK and Australia are the core productive forces in this field at the institutional level.

(2) Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology are notable journals that publish research related to digital technology education applications. These journals are affiliated with the research field of educational technology and provide effective communication platforms for sharing digital technology education applications.

(3) Over the past two decades, research on digital technology education applications has progressed from its early stages of budding, initial development, and critical exploration to accelerated transformation, and it is currently approaching maturity. Technological progress and changes in the times have been key driving forces for educational transformation and innovation, and both have played important roles in promoting the continuous development of education.

(4) Influenced by the pandemic, three emerging frontiers have emerged in current research on digital technology education applications, which are physical education, digital transformation, and professional development under the promotion of digital technology. These frontier research hotspots reflect the core issues that the education system faces when encountering new technologies. The evolution of research hotspots shows that technology breakthroughs in education’s original boundaries of time and space create new challenges. The continuous self-renewal of education is achieved by solving one hotspot problem after another.

The present study offers significant practical implications for scholars and practitioners in the field of digital technology education applications. Firstly, it presents a well-defined framework of the existing research in this area, serving as a comprehensive guide for new entrants to the field and shedding light on the developmental trajectory of this research domain. Secondly, the study identifies several contemporary research hotspots, thus offering a valuable decision-making resource for scholars aiming to explore potential research directions. Thirdly, the study undertakes an exhaustive analysis of published literature to identify core journals in the field of digital technology education applications, with Sustainability being identified as a promising open access journal that publishes extensively on this topic. This finding can potentially facilitate scholars in selecting appropriate journals for their research outputs.

Limitation and future research

Influenced by some objective factors, this study also has some limitations. First of all, the bibliometrics analysis software has high standards for data. In order to ensure the quality and integrity of the collected data, the research only selects the periodical papers in SCIE and SSCI indexes, which are the core collection of Web of Science database, and excludes other databases, conference papers, editorials and other publications, which may ignore some scientific research and original opinions in the field of digital technology education and application research. In addition, although this study used professional software to carry out bibliometric analysis and obtained more objective quantitative data, the analysis and interpretation of data will inevitably have a certain subjective color, and the influence of subjectivity on data analysis cannot be completely avoided. As such, future research endeavors will broaden the scope of literature screening and proactively engage scholars in the field to gain objective and state-of-the-art insights, while minimizing the adverse impact of personal subjectivity on research analysis.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/F9QMHY

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Acknowledgements

This research was supported by the Zhejiang Provincial Social Science Planning Project, “Mechanisms and Pathways for Empowering Classroom Teaching through Learning Spaces under the Strategy of High-Quality Education Development”, the 2022 National Social Science Foundation Education Youth Project “Research on the Strategy of Creating Learning Space Value and Empowering Classroom Teaching under the background of ‘Double Reduction’” (Grant No. CCA220319) and the National College Student Innovation and Entrepreneurship Training Program of China (Grant No. 202310337023).

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Conceptualization: Y.J., C.W.; methodology, C.W.; software, C.W., Y.L.; writing-original draft preparation, C.W., Y.L.; writing-review and editing, T.Y., Y.L., C.W.; supervision, X.C., T.Y.; project administration, Y.J.; funding acquisition, X.C., Y.L. All authors read and approved the final manuscript. All authors have read and approved the re-submission of the manuscript.

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Wang, C., Chen, X., Yu, T. et al. Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11 , 256 (2024). https://doi.org/10.1057/s41599-024-02717-y

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According to a previous report by  The Information , major tech companies such as Alibaba, Baidu, ByteDance, and Tencent have also been instructed to reduce their spending on foreign-made chips like NVIDIA’s. The Chinese government, which is aggressively promoting its own data center projects, is said to be boosting demand for Huawei’s AI chips as well.

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