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Josephine Wolff; How Is Technology Changing the World, and How Should the World Change Technology?. Global Perspectives 1 February 2021; 2 (1): 27353. doi: https://doi.org/10.1525/gp.2021.27353

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Technologies are becoming increasingly complicated and increasingly interconnected. Cars, airplanes, medical devices, financial transactions, and electricity systems all rely on more computer software than they ever have before, making them seem both harder to understand and, in some cases, harder to control. Government and corporate surveillance of individuals and information processing relies largely on digital technologies and artificial intelligence, and therefore involves less human-to-human contact than ever before and more opportunities for biases to be embedded and codified in our technological systems in ways we may not even be able to identify or recognize. Bioengineering advances are opening up new terrain for challenging philosophical, political, and economic questions regarding human-natural relations. Additionally, the management of these large and small devices and systems is increasingly done through the cloud, so that control over them is both very remote and removed from direct human or social control. The study of how to make technologies like artificial intelligence or the Internet of Things “explainable” has become its own area of research because it is so difficult to understand how they work or what is at fault when something goes wrong (Gunning and Aha 2019) .

This growing complexity makes it more difficult than ever—and more imperative than ever—for scholars to probe how technological advancements are altering life around the world in both positive and negative ways and what social, political, and legal tools are needed to help shape the development and design of technology in beneficial directions. This can seem like an impossible task in light of the rapid pace of technological change and the sense that its continued advancement is inevitable, but many countries around the world are only just beginning to take significant steps toward regulating computer technologies and are still in the process of radically rethinking the rules governing global data flows and exchange of technology across borders.

These are exciting times not just for technological development but also for technology policy—our technologies may be more advanced and complicated than ever but so, too, are our understandings of how they can best be leveraged, protected, and even constrained. The structures of technological systems as determined largely by government and institutional policies and those structures have tremendous implications for social organization and agency, ranging from open source, open systems that are highly distributed and decentralized, to those that are tightly controlled and closed, structured according to stricter and more hierarchical models. And just as our understanding of the governance of technology is developing in new and interesting ways, so, too, is our understanding of the social, cultural, environmental, and political dimensions of emerging technologies. We are realizing both the challenges and the importance of mapping out the full range of ways that technology is changing our society, what we want those changes to look like, and what tools we have to try to influence and guide those shifts.

Technology can be a source of tremendous optimism. It can help overcome some of the greatest challenges our society faces, including climate change, famine, and disease. For those who believe in the power of innovation and the promise of creative destruction to advance economic development and lead to better quality of life, technology is a vital economic driver (Schumpeter 1942) . But it can also be a tool of tremendous fear and oppression, embedding biases in automated decision-making processes and information-processing algorithms, exacerbating economic and social inequalities within and between countries to a staggering degree, or creating new weapons and avenues for attack unlike any we have had to face in the past. Scholars have even contended that the emergence of the term technology in the nineteenth and twentieth centuries marked a shift from viewing individual pieces of machinery as a means to achieving political and social progress to the more dangerous, or hazardous, view that larger-scale, more complex technological systems were a semiautonomous form of progress in and of themselves (Marx 2010) . More recently, technologists have sharply criticized what they view as a wave of new Luddites, people intent on slowing the development of technology and turning back the clock on innovation as a means of mitigating the societal impacts of technological change (Marlowe 1970) .

At the heart of fights over new technologies and their resulting global changes are often two conflicting visions of technology: a fundamentally optimistic one that believes humans use it as a tool to achieve greater goals, and a fundamentally pessimistic one that holds that technological systems have reached a point beyond our control. Technology philosophers have argued that neither of these views is wholly accurate and that a purely optimistic or pessimistic view of technology is insufficient to capture the nuances and complexity of our relationship to technology (Oberdiek and Tiles 1995) . Understanding technology and how we can make better decisions about designing, deploying, and refining it requires capturing that nuance and complexity through in-depth analysis of the impacts of different technological advancements and the ways they have played out in all their complicated and controversial messiness across the world.

These impacts are often unpredictable as technologies are adopted in new contexts and come to be used in ways that sometimes diverge significantly from the use cases envisioned by their designers. The internet, designed to help transmit information between computer networks, became a crucial vehicle for commerce, introducing unexpected avenues for crime and financial fraud. Social media platforms like Facebook and Twitter, designed to connect friends and families through sharing photographs and life updates, became focal points of election controversies and political influence. Cryptocurrencies, originally intended as a means of decentralized digital cash, have become a significant environmental hazard as more and more computing resources are devoted to mining these forms of virtual money. One of the crucial challenges in this area is therefore recognizing, documenting, and even anticipating some of these unexpected consequences and providing mechanisms to technologists for how to think through the impacts of their work, as well as possible other paths to different outcomes (Verbeek 2006) . And just as technological innovations can cause unexpected harm, they can also bring about extraordinary benefits—new vaccines and medicines to address global pandemics and save thousands of lives, new sources of energy that can drastically reduce emissions and help combat climate change, new modes of education that can reach people who would otherwise have no access to schooling. Regulating technology therefore requires a careful balance of mitigating risks without overly restricting potentially beneficial innovations.

Nations around the world have taken very different approaches to governing emerging technologies and have adopted a range of different technologies themselves in pursuit of more modern governance structures and processes (Braman 2009) . In Europe, the precautionary principle has guided much more anticipatory regulation aimed at addressing the risks presented by technologies even before they are fully realized. For instance, the European Union’s General Data Protection Regulation focuses on the responsibilities of data controllers and processors to provide individuals with access to their data and information about how that data is being used not just as a means of addressing existing security and privacy threats, such as data breaches, but also to protect against future developments and uses of that data for artificial intelligence and automated decision-making purposes. In Germany, Technische Überwachungsvereine, or TÜVs, perform regular tests and inspections of technological systems to assess and minimize risks over time, as the tech landscape evolves. In the United States, by contrast, there is much greater reliance on litigation and liability regimes to address safety and security failings after-the-fact. These different approaches reflect not just the different legal and regulatory mechanisms and philosophies of different nations but also the different ways those nations prioritize rapid development of the technology industry versus safety, security, and individual control. Typically, governance innovations move much more slowly than technological innovations, and regulations can lag years, or even decades, behind the technologies they aim to govern.

In addition to this varied set of national regulatory approaches, a variety of international and nongovernmental organizations also contribute to the process of developing standards, rules, and norms for new technologies, including the International Organization for Standardization­ and the International Telecommunication Union. These multilateral and NGO actors play an especially important role in trying to define appropriate boundaries for the use of new technologies by governments as instruments of control for the state.

At the same time that policymakers are under scrutiny both for their decisions about how to regulate technology as well as their decisions about how and when to adopt technologies like facial recognition themselves, technology firms and designers have also come under increasing criticism. Growing recognition that the design of technologies can have far-reaching social and political implications means that there is more pressure on technologists to take into consideration the consequences of their decisions early on in the design process (Vincenti 1993; Winner 1980) . The question of how technologists should incorporate these social dimensions into their design and development processes is an old one, and debate on these issues dates back to the 1970s, but it remains an urgent and often overlooked part of the puzzle because so many of the supposedly systematic mechanisms for assessing the impacts of new technologies in both the private and public sectors are primarily bureaucratic, symbolic processes rather than carrying any real weight or influence.

Technologists are often ill-equipped or unwilling to respond to the sorts of social problems that their creations have—often unwittingly—exacerbated, and instead point to governments and lawmakers to address those problems (Zuckerberg 2019) . But governments often have few incentives to engage in this area. This is because setting clear standards and rules for an ever-evolving technological landscape can be extremely challenging, because enforcement of those rules can be a significant undertaking requiring considerable expertise, and because the tech sector is a major source of jobs and revenue for many countries that may fear losing those benefits if they constrain companies too much. This indicates not just a need for clearer incentives and better policies for both private- and public-sector entities but also a need for new mechanisms whereby the technology development and design process can be influenced and assessed by people with a wider range of experiences and expertise. If we want technologies to be designed with an eye to their impacts, who is responsible for predicting, measuring, and mitigating those impacts throughout the design process? Involving policymakers in that process in a more meaningful way will also require training them to have the analytic and technical capacity to more fully engage with technologists and understand more fully the implications of their decisions.

At the same time that tech companies seem unwilling or unable to rein in their creations, many also fear they wield too much power, in some cases all but replacing governments and international organizations in their ability to make decisions that affect millions of people worldwide and control access to information, platforms, and audiences (Kilovaty 2020) . Regulators around the world have begun considering whether some of these companies have become so powerful that they violate the tenets of antitrust laws, but it can be difficult for governments to identify exactly what those violations are, especially in the context of an industry where the largest players often provide their customers with free services. And the platforms and services developed by tech companies are often wielded most powerfully and dangerously not directly by their private-sector creators and operators but instead by states themselves for widespread misinformation campaigns that serve political purposes (Nye 2018) .

Since the largest private entities in the tech sector operate in many countries, they are often better poised to implement global changes to the technological ecosystem than individual states or regulatory bodies, creating new challenges to existing governance structures and hierarchies. Just as it can be challenging to provide oversight for government use of technologies, so, too, oversight of the biggest tech companies, which have more resources, reach, and power than many nations, can prove to be a daunting task. The rise of network forms of organization and the growing gig economy have added to these challenges, making it even harder for regulators to fully address the breadth of these companies’ operations (Powell 1990) . The private-public partnerships that have emerged around energy, transportation, medical, and cyber technologies further complicate this picture, blurring the line between the public and private sectors and raising critical questions about the role of each in providing critical infrastructure, health care, and security. How can and should private tech companies operating in these different sectors be governed, and what types of influence do they exert over regulators? How feasible are different policy proposals aimed at technological innovation, and what potential unintended consequences might they have?

Conflict between countries has also spilled over significantly into the private sector in recent years, most notably in the case of tensions between the United States and China over which technologies developed in each country will be permitted by the other and which will be purchased by other customers, outside those two countries. Countries competing to develop the best technology is not a new phenomenon, but the current conflicts have major international ramifications and will influence the infrastructure that is installed and used around the world for years to come. Untangling the different factors that feed into these tussles as well as whom they benefit and whom they leave at a disadvantage is crucial for understanding how governments can most effectively foster technological innovation and invention domestically as well as the global consequences of those efforts. As much of the world is forced to choose between buying technology from the United States or from China, how should we understand the long-term impacts of those choices and the options available to people in countries without robust domestic tech industries? Does the global spread of technologies help fuel further innovation in countries with smaller tech markets, or does it reinforce the dominance of the states that are already most prominent in this sector? How can research universities maintain global collaborations and research communities in light of these national competitions, and what role does government research and development spending play in fostering innovation within its own borders and worldwide? How should intellectual property protections evolve to meet the demands of the technology industry, and how can those protections be enforced globally?

These conflicts between countries sometimes appear to challenge the feasibility of truly global technologies and networks that operate across all countries through standardized protocols and design features. Organizations like the International Organization for Standardization, the World Intellectual Property Organization, the United Nations Industrial Development Organization, and many others have tried to harmonize these policies and protocols across different countries for years, but have met with limited success when it comes to resolving the issues of greatest tension and disagreement among nations. For technology to operate in a global environment, there is a need for a much greater degree of coordination among countries and the development of common standards and norms, but governments continue to struggle to agree not just on those norms themselves but even the appropriate venue and processes for developing them. Without greater global cooperation, is it possible to maintain a global network like the internet or to promote the spread of new technologies around the world to address challenges of sustainability? What might help incentivize that cooperation moving forward, and what could new structures and process for governance of global technologies look like? Why has the tech industry’s self-regulation culture persisted? Do the same traditional drivers for public policy, such as politics of harmonization and path dependency in policy-making, still sufficiently explain policy outcomes in this space? As new technologies and their applications spread across the globe in uneven ways, how and when do they create forces of change from unexpected places?

These are some of the questions that we hope to address in the Technology and Global Change section through articles that tackle new dimensions of the global landscape of designing, developing, deploying, and assessing new technologies to address major challenges the world faces. Understanding these processes requires synthesizing knowledge from a range of different fields, including sociology, political science, economics, and history, as well as technical fields such as engineering, climate science, and computer science. A crucial part of understanding how technology has created global change and, in turn, how global changes have influenced the development of new technologies is understanding the technologies themselves in all their richness and complexity—how they work, the limits of what they can do, what they were designed to do, how they are actually used. Just as technologies themselves are becoming more complicated, so are their embeddings and relationships to the larger social, political, and legal contexts in which they exist. Scholars across all disciplines are encouraged to join us in untangling those complexities.

Josephine Wolff is an associate professor of cybersecurity policy at the Fletcher School of Law and Diplomacy at Tufts University. Her book You’ll See This Message When It Is Too Late: The Legal and Economic Aftermath of Cybersecurity Breaches was published by MIT Press in 2018.

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Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review

• Published: 30 March 2021
• Volume 26 , pages 6719–6746, ( 2021 )

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• Manar Abu Talib   ORCID: orcid.org/0000-0003-3001-0077 1 ,
• Anissa M. Bettayeb 1 &
• Razan I. Omer 1  

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With the advent of COVID-19 arose the need for social distancing measures, including the imposition of far-reaching lockdowns in many countries. The lockdown has wreaked havoc on many aspects of daily life, but education has been particularly hard hit by this unprecedented situation. The closure of educational institutions brought along many changes, including the transition to more technology-based education. This is a systematic literature review that seeks to explore the transition, in the context of the pandemic, from traditional education that involves face-to-face interaction in physical classrooms to online distance education. It examines the ways in which this transition has impacted academia and students and looks at the potential long-term consequences it may have caused. It also presents some of the suggestions made by the studies included in the paper, which may help alleviate the negative impact of lockdown on education and promote a smoother transition to online learning.

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1 Introduction

Severe acute respiratory syndrome, also known as COVID-19, is a contagious respiratory disease caused by the SARS-CoV-2 virus, which was first identified in a seafood market in Wuhan in late December 2019 (Huang, 2020 ).

The disease is airborne and mainly spreads through physical proximity with infected people. Clinical analysis results of the virus showed person-to-person transmission (Li et al., 2020 ). Broadly speaking, there are two modes of transmission—direct and indirect. The direct mode involves droplet and air transmission, while indirect transmission may occur via contaminated surfaces (Karia, 2020 ).

Due to its highly contagious nature, the COVID-19 virus swept the globe in the matter of weeks. Between December 2019 and October 2020, more than 45 million cases of COVID-19 were reported, including over a million deaths. (European Centre for Disease Prevention and Control, 2020 ). By March 2020, the epidemic was declared a pandemic by the World Health Organization (WHO, 2020 ).

The call for social distancing and limiting face-to-face contact outside the immediate family has never been louder. Social distancing is a deliberate increase in the physical gap between individuals to minimize the spread of disease (Red Cross, 2020 ).

Many facets of everyday life have been devastated by the pandemic. It prompted counties around the world to adopt a sequence of emergency response systems (Zhang et al., 2020 ). Authorities worldwide issued stay-at-home orders, imposing prolonged periods of lockdown, which led to a disruption in educational activities globally. This was done to curb infection rates and flatten the incidence curve in an effort to prevent healthcare systems from being overwhelmed.

In many parts of the world, this meant a temporary shutdown of educational institutions. These nationwide closures impacted millions of students and their families, particularly those from underprivileged communities (UNESCO, 2020 ).

Some of the educational institutions that faced closure progressively re-opened and started operating under online learning models in order to continue the academic progress of students, while simultaneously observing measures to reduce the impact of the current health crisis.

Previous outbreaks of infectious diseases such as swine flu have prompted significant school closures worldwide, with varying degrees of effectiveness (Barnum, 2020 ). If school closures happen late during a pandemic, they are less effective and may have little impact at all (Zumla et al., 2010 ). Educational institutions have been compelled to make an immediate transition to remote methods of learning that rely heavily on technology. The immediate transition to online learning has not made it possible for many to be adequately prepared for the challenges ahead (Hodges et al., 2020 ). This migration to remote learning had to be implemented as quickly as possible, and for many learning institutions, it happened several months into the academic year, leaving both staff and students with little time to plan, adjust and adapt.

This shed the light on various underlying economic and social issues. According to UNESCO, more than a billion learners worldwide have been affected at some point by the school closures that were initiated in response to the COVID-19 pandemic. As of November 2020, over 300 million learners spread across over 30 countries, which constitute approximately 18% of total enrolled learners, have been kept out of schools due to lockdown (UNESCO, 2020 ).

While the disruption in learning caused by COVID-19 is unprecedented, important insights can be gained about its far-reaching implications through an examination of relevant existing studies and data.

This paper is a systematic literature review that looks at the existing literature and discusses the crisis-response migration methods to technology-based online learning done by mainly higher learning institutions in terms of their impact on instructional delivery, students and faculty, and education as a whole. Firstly, it categorizes the studies in terms of which facet of education the impact of COVID-19 in was explored. Then, it performs a SWOT analysis on the digital transformation to online learning. In other words, it looks at the strengths, weaknesses, opportunities and threats. Lastly, it attempts to collect and summarize student and faculty feedback on online education and then outlines some of the recommendations made by either the students and faculty or the authors of the selected studies for improving the system.

The rest of the paper is divided into six sections. Section 2 discusses some of the related works, while Section 3 presents the methodology used in this study, including the selected research questions, search strategy, study selection process, quality assessment rules and data extraction strategy. It also presents some statistics about the selected papers. Section 4 presents the findings of the study and discusses them in detail, while Section 5 concludes with a summary of the research outcomes and possible future work. Section 6 constitutes an acknowledgement of various contributions to the creation of this paper.

2 Related work

In response to COVID-19, a lot of countries were faced with pressure to contain the spread of this highly contagious disease. To many educational institutions, this meant either partial or complete closure. Others transitioned to technology-based distance learning.

A systematic review was conducted by Viner et al. ( 2020 ) examines existing knowledge to identify the effects of school closures and other social distancing measures during outbreaks on infection rates and virus transmission. It suggested that school closures play a relatively small role in the control of disease transmission, and that the insignificant benefits such closures bring to transmission reduction could be easily outweighed by their profound negative economic and social consequences (Viner et al., 2020 ).

There is no strong evidence to support the effectiveness of full closure in controlling the pandemic. If anything, there are significant economic downfalls to such a response, not to mention the academic delay incurred by students. That is why a lot of academic institutions opted for the less drastic measure of transitioning to online distance education (ODE).

ODE is the use of the internet and certain other significant technology for the production of educational content, instructional delivery and program management (Fry, 2001 ). ODE can be delivered in two main formats: synchronous and asynchronous. As the name suggests, synchronous distance education (SDE) involves live, real-time interaction between teachers and students. It aims to simulate the communication model of a traditional classroom. Examples of SDE would include live webinars or virtual classrooms. Asynchronous education, on the other hand, introduces temporal flexibility. It does not require real-time interaction; instead, the educational material is available online for students to access at their own convenience. Examples of asynchronous education would be video recordings and emails (The Florida Center for Instructional Technology, n.d. ).

A systematic review and meta-analysis provided on randomized controlled trials (RCTs) conducted by papers released between January 2000 and March 2020 on the effectiveness and acceptance of SDE in health sciences as compared to more traditional educational methods measured the knowledge of students, their skills (using objective assessments) and their overall satisfaction (using subjective evaluations). It found there to be no significant difference between traditional education and synchronous distance education in terms of effectiveness and objective assessments. However, in subjective evaluations, SDE resulted in a higher satisfaction rating, indicating that it was preferred to some extent by students, despite being neither better nor worse in the earlier two measures (He et al., 2020 ).

Additionally, Carrillo & Flores ( 2020 ) conducted a review of the literature between January 2000 and April 2020 on online teaching and learning practices in teacher education to explore how and why online teaching and learning in teacher education occur, and also discussing its implications in the context of the pandemic. The review highlighted the complex nature of the model, discussing such factors as social, cognitive and teaching issues and the need for a comprehensive view of the pedagogy of online technology-based education used to support teaching and learning (Carrillo & Flores, 2020 ).

Daoud et al. ( 2020 ) conducted a systematic review focused on the issue of equity regarding home internet access by evaluating the educational value of having internet at home for school-aged children. It found a range of correlations that were mostly positive between access to home internet and educational value across three functions: qualification (academic knowledge and skills), subjectification (strengthening individuality) and socialization (of future citizens). However, the correlation was not straightforward, nor did it imply causation. The educational value in home internet use is influenced by variables regarding the nature of online activities such as how the technology is being used and socio-economic status (Daoud et al., 2020 ).

Di Pietro et al. ( 2020 ) produced a paper that attempts to explore the direct and indirect ways in which the COVID-19 pandemic may impact education. Based on the existing literature and pre-COVID-19 data, it made predictions about the impact on and future of education. The paper drew four main conclusions: 1) learning is expected to suffer a setback on average; 2) the effect on academic performance is likely to vary with socio-economic status; 3) inequality in socio-economic status may manifest in an emotional response, as those from less privileged backgrounds may be under more environmental stress; 4) the widening social gap may persist and have long-term implications (Di Pietro et al., 2020 ).

Some online emergency learning approaches are criticized for not adhering to sound pedagogical norms, best practices and prior studies (Hodges et al., 2020 ). Some have noted the potential negative effects of educational technology fixes being implemented quickly without balancing their effect (Selwyn et al., 2020 ; St. Amour, 2020 ). In addition, leaping into online education and online learning platforms has also raised concerns regarding surveillance and privacy and its impact on the lives of students (Harwell, 2020 ).

A study that aims to map the scientific literature in the areas of education and management in the context of the COVID-19 pandemic suggests the existence of three distinct groups or research flows in the published literature. These main themes were identified as: 1) education based on online constructs and distance learning; 2) the impact of COVID-19 from a management perspective; and 3) studies with a particular focus on Canada. The studies chosen for the analysis were found to be of various typologies, the most relevant of which was qualitative. The analysis revealed that research on the disruption in education and scientific production caused by the pandemic is rather scarce, which might be the result of the lack of empirical data (Rodrigues et al., 2020 ).

Since this phenomenon is still relatively recent, there is a lack of research that discusses the direct effect of the digital transformation in higher education caused by the pandemic, its pros, cons and future implications. This systematic literature review is different from those described above, as it provides an extensive review on the research done on the impact of the COVID-19 pandemic on formal education. Specifically, this study explores the ways in which the transition from traditional in-person educational models that involve face-to-face interaction and classroom teaching to ODE has impacted academia and students, and the consequences it might have had on student performance and the well-being of all involved.

The pandemic might have set in motion changes that are to last millennia in the way education is conducted across the globe. It is therefore imperative to study the direct impact of the pandemic on the education sector and understand the role it played in revolutionizing the way we think about education in order to make informed pedagogical choices in the future and ensure a smooth transition into more flexible but effective online teaching methods. As a result, our research paper has the following important contributions:

Explore the kind of changes the shift to online education has caused

Discuss the impact of these changes on students and teachers

Provide an insight into the current state of education and how the pandemic could affect its future

Table  1 summarizes the literature reviews discussed in this section as well as this study’s objective.

3 Methodology

This study is a Systematic Literature Review (SLR) based on the guidelines for performing such reviews laid out in the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (Moher et al., 2015 ), which are comprised of three main stages: search, eligibility and data collection and extraction. For example:

Search defines the search strategy in terms of what keywords and search engines or libraries will be used.

Eligibility is concerned with setting up inclusion and exclusion criteria aligned with the research objectives to specify the study and reporting standards, and then applying them to the collected papers.

Data collection and extraction is the process of obtaining eligible reports and extracting data from them in order to investigate the posed research questions.

This study tackles the topic of education during the COVID-19 pandemic and the accompanying shift to remote learning. The review process is composed of six stages. The first stage was coming up with research questions that reflect the aim of the study. The second involved collecting papers relevant to the topic. In the third stage, exclusion and inclusion criteria were defined and applied to the collected papers. The fourth stage involved extracting answers to the research questions from papers that made it through the final round of exclusion. The fifth and final stage was the synthesis of data obtained through this information extraction process to reach meaningful conclusions.

Figure  1 below illustrates this process.

Research methodology

3.1 Research questions

This systematic literature review aims to examine and summarize the impact COVID-19 had on education through the shift to online learning it caused in early 2020. The following five research questions were posed:

What are the aspects and impacts of COVID-19 on education?

RQ1 aims to identify the underlying theme or lens through which the impact of COVID-19 on education was explored in the papers. In other words, on what aspect of education or the educational system is the paper attempting to shed light on the impact of COVID-19?

What are the limitations of online education?

RQ2 examines the implemented online teaching models critically and identifies their flaws as defined in the research papers. This is the first phase of a SWOT analysis, which stands for strengths, weaknesses, opportunities, and threats. It considers the weakness and threats of online education.

What are the advantages & opportunities laid out by this digital transformation in higher education?

The aim of RQ3 is to recognize the benefits and opportunities presented by this unprecedented move toward digital-based learning in higher education institutions. This is the second phase of the SWOT analysis and it focuses on the digital transformation’s strengths and opportunities.

What was the feedback of students and teachers?

RQ4 collects and summarizes the responses of students and teachers to this transformation and how it impacted their experience.

What recommendations were made?

RQ5 attempts to summarize the recommendations put forward by either the authors of the studies or the people who participated in them.

3.2 Search strategy

The research questions were used as a guideline to roughly identify the main search keywords. Terms synonymous or highly related to the main search keywords were included in the search. Google Scholar was used for the search, which employed variations of the following search keywords: “COVID-19” “effects” “impact” “education” “higher education” “academia” “university” “online learning” “students” “teaching” “e-learning”.

The number of results varied by combination of keywords, but on average between 200 and 300 results showed up per search, a number increasing by the day given the current relevance of the topics at hand. The majority of papers came from journals.

3.3 Study selection

All papers based on the search keywords mentioned above that seemed, if only tenuously, relevant to the topic of education during COVID-19 were collected. Only papers that were published later than 2019 were retained. Papers that did not belong to high-quality, prestigious journals were excluded.

To ensure the quality of the selected papers and they do not belong to predatory journals, we first checked them against Elsevier’s abstract and citation database, Scopus. We also made sure they belonged to either the first quartile (Q1) or second quartile (Q2) according to the SCImago Journal Rank (SJR). SJR indicates the scientific influence of scholarly journals. Moreover, the journals were reviewed against Beall’s List, which is a list of predatory open-access publishers that did not perform proper peer review and they publish any article as long as the authors paid the open-access fee. This brought the number of papers selected for the purpose of this study down dramatically to 47—less than half of all papers collected initially.

As mentioned earlier, the search based on the selected keywords yielded somewhere between 100 and 300 results. Over 100 papers seemed relevant and were downloaded to serve as a starting point. Moving on, we filtered the papers based on their compliance with our inclusion criteria. The process can be summarized as follows:

download papers that showed up in the search results

delete any duplicates

apply the inclusion and exclusion criteria to get rid of any irrelevant papers

set aside survey and review papers

extract answers to the research questions from the selected papers while applying the quality assessment rules stated in section 3.4 that were designed to include only qualified papers.

Table  2 summarizes the applied inclusion and exclusion criteria of study papers.

3.4 Quality assessment rules (QARs)

This final step is to determine the quality of the collected research papers. To measure the quality of the papers included in the study and confirm their pertinence to our research objectives, ten Quality Assessment Rules (QARs) were set. Marks out of 10 were given to each paper based on its compliance with the established QARs. The QARs were formulated based on our understanding of the current state of research in this field and the research gap this paper is attempting to fill. The papers were scored for their ability to meet high research standards while adequately addressing our research question. For each of the ten questions, a paper is given a score as follows: “fully answered” = 1, “above average” = 0.75, “average” = 0.5, “below average” = 0.25, “not answered” = 0. The summation of the marks achieved for the 10 QARs is the paper’s ranking. Papers that score 5 or higher are accepted, while the remaining are excluded.

Are the study objectives clearly defined?

Is the impact of COVID-19 on education well-defined?

Is the specific context and usage (themes) clearly defined?

Is the study method well-designed and justifiable?

Is the scope of the study large enough?

Are the advantages and opportunities of the proposed teaching/technology methods well-explained?

Are the weaknesses and limitations of the proposed teaching/technology methods well-explained?

Are student/teacher evaluations reported?

Are the recommendations of the proposed methods suitable?

Overall, does the study enrich the academic community or industry?

3.5 Data extraction strategy

In this step, the final list of papers was analyzed to answer the research questions and extract any pertinent information.

The following information was extracted from each paper: Paper title, Publisher, Journal, month of publication, description of the paper’s objective, the answers to RQ1, RQ2, RQ3, RQ4 and RQ5.

Due to the indistinct terminology used within some papers and the relative narrowness of our research questions in comparison to the questions posed by the collected papers, there were gaps in the answer extraction as reflected in Fig.  4 .

In some cases, the authors had to infer answers that weren’t explicity expressed in the papers. This meant that some of the answers extracted were personal intrepretations of the findings done by the authors.

3.6 Statistics about the selected papers

As can be seen from Fig. 2 , Elsevier & IJWIL journals held the 2nd and 3rd positions, coming in at 19% and 17% respectively. Other publishers, including Springer, Routledge & MDPI, contributed similar amounts of papers and came at 13% of the total paper count or less.

Publishers of the selected papers by frequency

However, 32% of the papers were put out by miscellaneous publishers. These publishers include: The BMJ, ACS Publication, Science Press, Wiley, Taylor and Francis Ltd., Primrose Hall Publishing Group, Scientific Research Publishing, Academy of Science of South Africa, Association for Learning Technology, Association for Social Studies Educators, Modestum and Kathmandu University.

Figure  3 shows the months of publication of the selected papers. It is noteworthy that the largest number of papers relevant to this review were produced in July, three to four months after many lockdowns were implemented and distance learning was put in effect. The number of papers selected for this review subsequently declined. For 13 of the selected papers, the month of publication was either not explicitly specified or couldn’t be identified by the authors.

Frequency of selected papers by month

As can be seen from Fig. 4 , all research questions were answered by more than 70% of the papers, which speaks to their broadness and generality. The only exception was RQ5, which had a 61.70% answer rate, mostly from papers discussing the topic of “student experience”, as will be shown in the following section.

Frequency of answers for each research question

4 Results and discussion

The majority of educational institutions in the chosen studies migrated to distance learning. While not all papers specified the particular methods or platforms employed, video conferencing, E-portals, webinars, websites, video recordings, simulations and online quizzes were frequently listed as the primary means of conducting classes and evaluating student performance.

A total of 47 studies were compiled using the quality criteria mentioned in section 3.4 . A list of these studies is included in Table  7 in Appendix A. Here in section 4 , we present the findings of this literature review. The outcomes of each research question are explored in detail in each of the following five sections.

4.1 Area of focus

In this section, the first research question (RQ1) is addressed, which aims to identify the underlying theme or lens through which the impact of COVID-19 on education was explored in the papers. There were four main identifiable themes:

Impact on Education : explores the transition from traditional classroom teaching methods to more technology-based learning, and the impact of that transition.

Student Experience : explores the impact the lockdown had on students either academically or personally and their experience with ODE as well as their academic performance using remote learning methods.

Proposal : proposes and/or experiments with a remote teaching method or platform.

Policy : explores the responses to the pandemic and the role of policymaking in leveling the playfield in education.

Equality : discusses the disparity observed between different social groups during the pandemic and the impact it had on accessibility and equity.

In this review, 25 papers discussed the impact of COVID-19 on education, namely the digital transformation driven by it, its advantages and disadvantages, and what this could mean going forward.

Eighteen papers included discussions about the experience of students and staff with ODE, as well as the participants’ views on its potential upsides and downsides. Most of the answers given for RQ5 came from this group.

Four papers proposed solutions for remote learning or experimented with a particular platform to analyze its efficacy.

Three papers looked at the current academic situation through a political lens, discussing education-related policy in light of the pandemic.

Two papers discussed how the lockdown and the accompanying transition to technology-based learning further exacerbated differences in educational progress between the children of lower income families with limited access to Wi-Fi and digital devices or services and those of higher income families that do not share the same struggles.

Figure  5 highlights the differences in the frequency of the discussed areas. It is worth noting that these percentages add up to more than 100% because there is overlap between the papers in terms of the areas chosen for discussion.

Topics discussed in selected papers

4.2 Disadvantages & limitations

This section addresses research question 2 (RQ2), which takes a critical view of the implemented teaching models and identifies their shortcomings as described in the papers that studied or mentioned them.

The key disadvantages can be summarized in the following points:

Inequality & inaccessibility : there is a gap in student access to this type of education, which is usually related to family income.. Transitioning to online learning exacerbated differences between privileged and underprivileged students. Students from less prosperous regions have limited or no access to digital devices and Wi-Fi. They also have lower technical abilities., granting more privileged students an unfair academic advantage. This disparity extends to educational institutions in rural areas or deprived parts of the world that may be less well-equipped than those in urban areas.

Inadequacy : while technology can be a great aid to the learning experience, it cannot act as a complete substitute, particularly for STEM fields that require hands-on training in laboratories or operation rooms. This is especially true for health care sciences. 34% of the chosen studies focused on medical education specifically, looking at nursing or residency programs in particular. These papers tended to emphasize the value of practical training and how indirect knowledge gained from simulations or demonstration videos alone cannot act as a substitute.

Communication quality : building and sustaining relationships and developing rapport between students, their peers, and their teachers became more difficult due to the devaluation or lack of face-to-face contact, as well as the inherent ambiguity of written interactions.. Clarifying instructions and gauging student response, engagement and participation, or lack thereof, becomes more difficult for teachers and instructors in the absence of direct contact and the ability to monitor students face-to-face.

Technical difficulties : poor internet reception or Wi-Fi, connection stability, glitches and other technical failures can interfere with the flow of communication.

Stress, workload and morale : the forced and rapid transition to online learning affected mental health among students. Many experienced lockdown-related anxieties about financial stability and socializing that indirectly affected their performance. Academic staff had to deal with an increased or even doubled workload. Also, lack of face-to-face social interaction for extended periods of time can have a detrimental effect on mental health.

Technological literacy : due to the sudden and forced nature of this digital transition, a lot of educational institutions were caught off-guard, allowing them little to no time to prepare their academic staff. This left non-tech savvy teachers and instructors underprepared and/or underequipped to handle sophisticated computer and internet related tasks. Instructors’ lack of technological competence and previous training in or familiarity with utilizing online tools posed an obstacle. The inability of academic staff to use technology negatively impacted the success of ODE in many cases.

Student engagement, participation and motivation : student engagement was sometimes lacking due to factors such as reliance on recorded lectures, a lack of motivation or interest, stress and boredom, as well as the distraction caused by using electronic devices. Added to this was fatigue induced by prolonged staring at screens and feelings of isolation and depression from lack of personal contact.

Student performance assessment : due to the difficulties associated with bringing students to campus to administer tests, academic staff were faced with the challenge of redesigning evaluations in a way that fairly and reliably captured student performance. This was particularly challenging in practical courses.

Work-life balance : ODE allows great flexibility in time and location. While this flexibility may be convenient, it’s a double-edged sword that could also blur the boundaries between academic and personal life. Whereas in conventional educational models lectures are strictly bound by fixed times and physical locations.

Privacy concerns : concerns about breach of privacy, data protection and anonymous misconduct.

Table  3 lists the research articles that mentioned disadvantages and limitations of distance education based on the aforementioned points.

4.3 Advantages & opportunities

This section addresses research question 3 (RQ3), which aims to identify the advantages and opportunities laid by this digital transformation in education.

There are several main identifiable key advantages and opportunities. They can be summarized as follows:

Remote learning : ODE transcends the borders of time and geographical location. It allows students the flexibility to tune in into their lectures from the comfort of their own homes or any other location. It also allows students to self-regulate their learning and proceed at their own pace thanks to the temporal flexibility of online learning, which is made possible by features such as lecture recording.

Discussion & Communication : online learning facilitates a modern and convenient mode of communication. Important discussions can be raised during lectures and participating students can benefit from these discussions by listening or by engaging through chat. It is also an effective means of communication as participants do not have to meet in person or face the discomfort that can accompany speaking in front of a live audience, thereby further encouraging discussion. Online learning also helps parents of young children to be more involved in their children’s education.

Impetus for change : this forced digital transformation in education exposed problems within the system and pushed educators to contemplate and review current and previous models of education, providing a window into what a technology-based education and work environment might be like, thereby stimulating pedagogical innovations and accelerating change. It is hastening progress and can be viewed as an impetus for the reform of curriculum and teaching approaches.

Equally effective : the implementation of online learning and the use of simulations and other methods for didactic purposes were perceived as useful and adequate, if not complete, substitutes for traditional learning. It accomplished its goal of continuing the delivery of education amidst the pandemic, while also helping students meet the requirements expected from them.

Efficient : contributed to or improved knowledge dissemination, with cost-effectiveness, flexibility and overall efficiency as added benefits.

Exposure to tech : incorporating technology into education exposes students to modern and relevant technologies. This helps both students and academic staff close the technological literacy gap while also fostering expertise in online and digital media, thereby preparing students for the job market in an increasingly technology-reliant world of digitization and automation.

Decreased costs : the shift to online education can be credited for the decrease in educational costs. It provides students with a comparable learning experience without the need for expensive infrastructure, not to mention a reduction in other hidden costs such as travel expenses.

Table  4 lists the research articles that mentioned advantages and opportunities of distance education based on the aforementioned points.

4.4 Student and teacher feedback

This section addresses the fourth research question (RQ4), which aims to gauge the response of students and teachers to this transformation and how it impacted their experience.

The papers that explored the topic of student experience provided the main insights to this question, which can be summarized as follows:

Satisfactory or beneficial : ODE was regarded as a good learning experience and helpful in the sense that it assisted in cultivating knowledge in a unique and efficient manner.

Adequate and effective : ODE was deemed satisfactory in achieving its objective of continuing education. In some cases, it was thought to have had no significant impact on studies. And in other cases it was thought to boost productivity.

Expressed doubts or concern : participants expressed doubts about the efficacy of ODE, uncertainty about the future, and concern over the long-term consequences of the digital transformation on health, security and equity..

Overwhelming : some staff had difficulty adjusting given how abrupt the transition was. Many had to devise new student performance assessment methods to compensate for the inability to directly monitor students in exams and quizzes. In some cases, the transition led to an increase in workload.

Potential : some participants thought ODE could support their teaching or studies, recommended it for future use or viewed it as a catalyst for revision of existing norms.

Appreciation for staff or peers : participants expressed appreciation and gratitude towards others within the institution for their efforts in coping with the situation, providing assistance and being responsive.

Improvement in performance : ODE was thought to enhance efficiency, performance and attention, as well as help in the learning process.

Preferred to traditional : although students expressed sentiments of missing peer-to-peer interaction, the majority were open to and some even favoured ODE to conventional learning that requires physical attendance and is restricted to classrooms. This may be due to the flexibility, convenience and low cost of online learning.

Anxiety inducing : some participants reported feelings of stress or anxiety in trying to grapple with the current pandemic situation while adapting to the new learning scheme.

Table  5 lists the research articles that described feedback received on distance education based on the aforementioned points.

4.5 Study recommendations

This section addresses research question 5 (RQ5), which attempts to summarize the recommendations put forward by either the authors of the selected studies or the people who participated in them.

The following are the key recommendations made:

Support for students : boosting and maintaining motivation of students to improve morale and help combat any lockdown-induced stress or anxiety.

High-quality tools : providing accessible, user-friendly, error-free and high-quality E-learning portals and other types of online platforms.

Providing & receiving feedback : providing and receiving feedback to and from students to improve the quality of online education.

Investigating efficacy : exploring the outcomes of ODE and reflecting on the differences between it and traditional education in order to ascertain which aspects of it are viable and meet the demands sets by the pandemic situation. This is also to assist teachers in employing effective teaching techniques and to enable researchers and institutions to continue the development of online educational tools.

Stating objectives : students need to feel the relevance of the study material to the real world, as well as understand the course requirements. To that end, teachers must spell out expectations and clarify course objectives as well as the importance of the syllabus. They also need to delineate their roles and responsibilities as lecturers and mentors early on in the academic year.

Policymaking : policymakers should seek to understand and mitigate any risks or inequalities created by this rapid transition to online learning, which may be caused by income or workload disparities.

Redesign : the revisiting and rethinking of pedagogical strategies and the development of orienting principles to guide the transition to online education, as well as making the necessary adjustments to infrastructure.

Training of staff & students : providing students and teachers with adaptability training to familiarize them with technology, increase their competence and prepare them to deal with technical issues that can occur during online lectures. This will also help in the smart application of technology to realize its potential in the realm of online education.

Diversifying : maximizing efficiency by avoiding reliance on a single method or platform and instead using a variety of online learning resources. For example, a course could use both video conferencing and text messaging.

Broadening accessibility : this could mean providing underequipped students with the equipment necessary to partake in online activities, such as electronic devices and stable internet connection.

Table  6 lists the research articles that made recommendations based on the points listed above.

5 Conclusion and future work

It goes with without saying that the COVID-19 pandemic has had profound impacts on society and on the way humans organize themselves in the real world. It has exposed systematic issues within institutions and brought about long overdue changes. The educational system was no exception to this.

This review aimed to look at and evaluate the impact these changes have had on education, with a particular focus on the digital transformation and the shift to online learning caused by the pandemic. To do so, we took a look at more than 40 papers from high impact journals that touched on the topic of education during the times of COVID-19.

Many institutions and governments were underprepared for this abrupt migration to technology-based working and learning. This resulted in issues of inequality, lack of access and lack of skills to facilitate this type of learning. There are limitations inherent to ODE that prevent it from acting as a full substitute to traditional education. This is particularly true in fields where hands-on training is an absolute necessity to meet learning requirements.

On the plus side, the new forced dependence on technology in education may hasten some already underway changes. On the negative side, requiring children to continue their studies at home may worsen educational disparities caused by inequalities.

From the viewpoint of learners and educators, there are a range of difficulties in switching from offline to online learning modes. Another stumbling block in the acceptance of online teaching is involving students and indulging them in teaching-learning progression. It takes an hour to create content that not only covers the curriculum, but also inspires learners.

We found that some of the key disadvantages of ODE that were cited in the collected papers were inequality of access, inadequacy of online teaching, poor communication quality, technical difficulties, increased workload and stress, low technological literacy, difficulty in assessment of student engagement and performance, bad work-life balance and some privacy concerns.

Whereas the main advantages of ODE according to the papers were flexibility and convenience, discussion & communication, effectiveness as a didactic tool, efficiency, decreased costs, increased exposure to technology and that it was seen as an impetus for change.

The papers that explored the topic of student experience aimed to gauge the response of students and teachers to this transformation and how it impacted their experience and we found that the main feedback point given was that online education was satisfactory, beneficial and effective. However, some expressed doubts over the efficacy of remote learning, uncertainty about the future, and concern over the long-term consequences on health, security and access due to this digital transformation. Others found it to be overwhelming or anxiety inducing. However, some observed an improvement in performance and expressed more appreciation towards their peers and faculty members.

Although the adoption of online teaching during COVID-19 is commendable, the quality of teaching and courses offered online must also be developed and strengthened. Some of the advice that has been put forward to help in that regard includes supporting students by improving morale, providing high-quality e-learning tools, giving and receiving feedback from students, investigating the outcomes of ODE, clarifying course objectives and expectations to students, providing training for students and teachers to familiarize them with technology, diversfying instructional delivery methods, broadening accessibility to online learning, soliciting policymakers to make necessary changes and the revisiting and redesigning of pedagogical strategies.

The flexibilty and convenience ODE offers and the much-needed push for change it has inspired cannot be denied. However, its efficiency in terms of student outcome as compared to traditional education is still a point of dispute. It is therefore imperative to continue investigating online education. Policymakers should take the findings of research on education seriously in order to bridge whatever gaps may be present.

Future research could draw from a broader diversity of sources to reach wider conclusions.

Data availability

The data is available to anyone for review.

Code availability

Not applicable.

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The authors would like to thank University of Sharjah and OpenUAE Research and Development Group for funding this research study. We are also grateful to our research assistants who helped in collecting, summarizing, and analyzing the research articles for this SLR study.

This research paper was funded by the University of Sharjah (for OpenUAE Research and Development Group).

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Abu Talib, M., Bettayeb, A.M. & Omer, R.I. Analytical study on the impact of technology in higher education during the age of COVID-19: Systematic literature review. Educ Inf Technol 26 , 6719–6746 (2021). https://doi.org/10.1007/s10639-021-10507-1

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Computer-based technology and student engagement: a critical review of the literature

• Laura A. Schindler   ORCID: orcid.org/0000-0001-8730-5189 1 ,
• Gary J. Burkholder 2 , 3 ,
• Osama A. Morad 1 &
• Craig Marsh 4  

International Journal of Educational Technology in Higher Education volume  14 , Article number:  25 ( 2017 ) Cite this article

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Computer-based technology has infiltrated many aspects of life and industry, yet there is little understanding of how it can be used to promote student engagement, a concept receiving strong attention in higher education due to its association with a number of positive academic outcomes. The purpose of this article is to present a critical review of the literature from the past 5 years related to how web-conferencing software, blogs, wikis, social networking sites ( Facebook and Twitter ), and digital games influence student engagement. We prefaced the findings with a substantive overview of student engagement definitions and indicators, which revealed three types of engagement (behavioral, emotional, and cognitive) that informed how we classified articles. Our findings suggest that digital games provide the most far-reaching influence across different types of student engagement, followed by web-conferencing and Facebook . Findings regarding wikis, blogs, and Twitter are less conclusive and significantly limited in number of studies conducted within the past 5 years. Overall, the findings provide preliminary support that computer-based technology influences student engagement, however, additional research is needed to confirm and build on these findings. We conclude the article by providing a list of recommendations for practice, with the intent of increasing understanding of how computer-based technology may be purposefully implemented to achieve the greatest gains in student engagement.

Introduction

The digital revolution has profoundly affected daily living, evident in the ubiquity of mobile devices and the seamless integration of technology into common tasks such as shopping, reading, and finding directions (Anderson, 2016 ; Smith & Anderson, 2016 ; Zickuhr & Raine, 2014 ). The use of computers, mobile devices, and the Internet is at its highest level to date and expected to continue to increase as technology becomes more accessible, particularly for users in developing countries (Poushter, 2016 ). In addition, there is a growing number of people who are smartphone dependent, relying solely on smartphones for Internet access (Anderson & Horrigan, 2016 ) rather than more expensive devices such as laptops and tablets. Greater access to and demand for technology has presented unique opportunities and challenges for many industries, some of which have thrived by effectively digitizing their operations and services (e.g., finance, media) and others that have struggled to keep up with the pace of technological innovation (e.g., education, healthcare) (Gandhi, Khanna, & Ramaswamy, 2016 ).

Integrating technology into teaching and learning is not a new challenge for universities. Since the 1900s, administrators and faculty have grappled with how to effectively use technical innovations such as video and audio recordings, email, and teleconferencing to augment or replace traditional instructional delivery methods (Kaware & Sain, 2015 ; Westera, 2015 ). Within the past two decades, however, this challenge has been much more difficult due to the sheer volume of new technologies on the market. For example, in the span of 7 years (from 2008 to 2015), the number of active apps in Apple’s App Store increased from 5000 to 1.75 million. Over the next 4 years, the number of apps is projected to rise by 73%, totaling over 5 million (Nelson, 2016 ). Further compounding this challenge is the limited shelf life of new devices and software combined with significant internal organizational barriers that hinder universities from efficiently and effectively integrating new technologies (Amirault, 2012 ; Kinchin, 2012 ; Linder-VanBerschot & Summers 2015 ; Westera, 2015 ).

Many organizational barriers to technology integration arise from competing tensions between institutional policy and practice and faculty beliefs and abilities. For example, university administrators may view technology as a tool to attract and retain students, whereas faculty may struggle to determine how technology coincides with existing pedagogy (Lawrence & Lentle-Keenan, 2013 ; Lin, Singer, & Ha, 2010 ). In addition, some faculty may be hesitant to use technology due to lack of technical knowledge and/or skepticism about the efficacy of technology to improve student learning outcomes (Ashrafzadeh & Sayadian, 2015 ; Buchanan, Sainter, & Saunders, 2013 ; Hauptman, 2015 ; Johnson, 2013 ; Kidd, Davis, & Larke, 2016 ; Kopcha, Rieber, & Walker, 2016 ; Lawrence & Lentle-Keenan, 2013 ; Lewis, Fretwell, Ryan, & Parham, 2013 ; Reid, 2014 ). Organizational barriers to technology adoption are particularly problematic given the growing demands and perceived benefits among students about using technology to learn (Amirault, 2012 ; Cassidy et al., 2014 ; Gikas & Grant, 2013 ; Paul & Cochran, 2013 ). Surveys suggest that two-thirds of students use mobile devices for learning and believe that technology can help them achieve learning outcomes and better prepare them for a workforce that is increasingly dependent on technology (Chen, Seilhamer, Bennett, & Bauer, 2015 ; Dahlstrom, 2012 ). Universities that fail to effectively integrate technology into the learning experience miss opportunities to improve student outcomes and meet the expectations of a student body that has grown accustomed to the integration of technology into every facet of life (Amirault, 2012 ; Cook & Sonnenberg, 2014 ; Revere & Kovach, 2011 ; Sun & Chen, 2016 ; Westera, 2015 ).

The purpose of this paper is to provide a literature review on how computer-based technology influences student engagement within higher education settings. We focused on computer-based technology given the specific types of technologies (i.e., web-conferencing software, blogs, wikis, social networking sites, and digital games) that emerged from a broad search of the literature, which is described in more detail below. Computer-based technology (hereafter referred to as technology) requires the use of specific hardware, software, and micro processing features available on a computer or mobile device. We also focused on student engagement as the dependent variable of interest because it encompasses many different aspects of the teaching and learning process (Bryson & Hand, 2007 ; Fredricks, Blumenfeld, & Parks, 1994; Wimpenny & Savin-Baden, 2013 ), compared narrower variables in the literature such as final grades or exam scores. Furthermore, student engagement has received significant attention over the past several decades due to shifts towards student-centered, constructivist instructional methods (Haggis, 2009 ; Wright, 2011 ), mounting pressures to improve teaching and learning outcomes (Axelson & Flick, 2011 ; Kuh, 2009 ), and promising studies suggesting relationships between student engagement and positive academic outcomes (Carini, Kuh, & Klein, 2006 ; Center for Postsecondary Research, 2016 ; Hu & McCormick, 2012 ). Despite the interest in student engagement and the demand for more technology in higher education, there are no articles offering a comprehensive review of how these two variables intersect. Similarly, while many existing student engagement conceptual models have expanded to include factors that influence student engagement, none highlight the overt role of technology in the engagement process (Kahu, 2013 ; Lam, Wong, Yang, & Yi, 2012 ; Nora, Barlow, & Crisp, 2005 ; Wimpenny & Savin-Baden, 2013 ; Zepke & Leach, 2010 ).

Our review aims to address existing gaps in the student engagement literature and seeks to determine whether student engagement models should be expanded to include technology. The review also addresses some of the organizational barriers to technology integration (e.g., faculty uncertainty and skepticism about technology) by providing a comprehensive account of the research evidence regarding how technology influences student engagement. One limitation of the literature, however, is the lack of detail regarding how teaching and learning practices were used to select and integrate technology into learning. For example, the methodology section of many studies does not include a pedagogical justification for why a particular technology was used or details about the design of the learning activity itself. Therefore, it often is unclear how teaching and learning practices may have affected student engagement levels. We revisit this issue in more detail at the end of this paper in our discussions of areas for future research and recommendations for practice. We initiated our literature review by conducting a broad search for articles published within the past 5 years, using the key words technology and higher education , in Google Scholar and the following research databases: Academic Search Complete, Communication & Mass Media Complete, Computers & Applied Sciences Complete, Education Research Complete, ERIC, PsycARTICLES, and PsycINFO . Our initial search revealed themes regarding which technologies were most prevalent in the literature (e.g., social networking, digital games), which then lead to several, more targeted searches of the same databases using specific keywords such as Facebook and student engagement. After both broad and targeted searches, we identified five technologies (web-conferencing software, blogs, wikis, social networking sites, and digital games) to include in our review.

We chose to focus on technologies for which there were multiple studies published, allowing us to identify areas of convergence and divergence in the literature and draw conclusions about positive and negative effects on student engagement. In total, we identified 69 articles relevant to our review, with 36 pertaining to social networking sites (21 for Facebook and 15 for Twitter ), 14 pertaining to digital games, seven pertaining to wikis, and six pertaining to blogs and web-conferencing software respectively. Articles were categorized according to their influence on specific types of student engagement, which will be described in more detail below. In some instances, one article pertained to multiple types of engagement. In the sections that follow, we will provide an overview of student engagement, including an explanation of common definitions and indicators of engagement, followed by a synthesis of how each type of technology influences student engagement. Finally, we will discuss areas for future research and make recommendations for practice.

• Student engagement

Interest in student engagement began over 70 years ago with Ralph Tyler’s research on the relationship between time spent on coursework and learning (Axelson & Flick, 2011 ; Kuh, 2009 ). Since then, the study of student engagement has evolved and expanded considerably, through the seminal works of Pace ( 1980 ; 1984 ) and Astin ( 1984 ) about how quantity and quality of student effort affect learning and many more recent studies on the environmental conditions and individual dispositions that contribute to student engagement (Bakker, Vergel, & Kuntze, 2015 ; Gilboy, Heinerichs, & Pazzaglia, 2015 ; Martin, Goldwasser, & Galentino, 2017 ; Pellas, 2014 ). Perhaps the most well-known resource on student engagement is the National Survey of Student Engagement (NSSE), an instrument designed to assess student participation in various educational activities (Kuh, 2009 ). The NSSE and other engagement instruments like it have been used in many studies that link student engagement to positive student outcomes such as higher grades, retention, persistence, and completion (Leach, 2016 ; McClenney, Marti, & Adkins, 2012 ; Trowler & Trowler, 2010 ), further convincing universities that student engagement is an important factor in the teaching and learning process. However, despite the increased interest in student engagement, its meaning is generally not well understood or agreed upon.

Student engagement is a broad and complex phenomenon for which there are many definitions grounded in psychological, social, and/or cultural perspectives (Fredricks et al., 1994; Wimpenny & Savin-Baden, 2013 ; Zepke & Leach, 2010 ). Review of definitions revealed that student engagement is defined in two ways. One set of definitions refer to student engagement as a desired outcome reflective of a student’s thoughts, feelings, and behaviors about learning. For example, Kahu ( 2013 ) defines student engagement as an “individual psychological state” that includes a student’s affect, cognition, and behavior (p. 764). Other definitions focus primarily on student behavior, suggesting that engagement is the “extent to which students are engaging in activities that higher education research has shown to be linked with high-quality learning outcomes” (Krause & Coates, 2008 , p. 493) or the “quality of effort and involvement in productive learning activities” (Kuh, 2009 , p. 6). Another set of definitions refer to student engagement as a process involving both the student and the university. For example, Trowler ( 2010 ) defined student engagement as “the interaction between the time, effort and other relevant resources invested by both students and their institutions intended to optimize the student experience and enhance the learning outcomes and development of students and the performance, and reputation of the institution” (p. 2). Similarly, the NSSE website indicates that student engagement is “the amount of time and effort students put into their studies and other educationally purposeful activities” as well as “how the institution deploys its resources and organizes the curriculum and other learning opportunities to get students to participate in activities that decades of research studies show are linked to student learning” (Center for Postsecondary Research, 2017 , para. 1).

Many existing models of student engagement reflect the latter set of definitions, depicting engagement as a complex, psychosocial process involving both student and university characteristics. Such models organize the engagement process into three areas: factors that influence student engagement (e.g., institutional culture, curriculum, and teaching practices), indicators of student engagement (e.g., interest in learning, interaction with instructors and peers, and meaningful processing of information), and outcomes of student engagement (e.g., academic achievement, retention, and personal growth) (Kahu, 2013 ; Lam et al., 2012 ; Nora et al., 2005 ). In this review, we examine the literature to determine whether technology influences student engagement. In addition, we will use Fredricks et al. ( 2004 ) typology of student engagement to organize and present research findings, which suggests that there are three types of engagement (behavioral, emotional, and cognitive). The typology is useful because it is broad in scope, encompassing different types of engagement that capture a range of student experiences, rather than narrower typologies that offer specific or prescriptive conceptualizations of student engagement. In addition, this typology is student-centered, focusing exclusively on student-focused indicators rather than combining student indicators with confounding variables, such as faculty behavior, curriculum design, and campus environment (Coates, 2008 ; Kuh, 2009 ). While such variables are important in the discussion of student engagement, perhaps as factors that may influence engagement, they are not true indicators of student engagement. Using the typology as a guide, we examined recent student engagement research, models, and measures to gain a better understanding of how behavioral, emotional, and cognitive student engagement are conceptualized and to identify specific indicators that correspond with each type of engagement, as shown in Fig. 1 .

Conceptual framework of types and indicators of student engagement

Behavioral engagement is the degree to which students are actively involved in learning activities (Fredricks et al., 2004 ; Kahu, 2013 ; Zepke, 2014 ). Indicators of behavioral engagement include time and effort spent participating in learning activities (Coates, 2008 ; Fredricks et al., 2004 ; Kahu, 2013 ; Kuh, 2009 ; Lam et al., 2012 ; Lester, 2013 ; Trowler, 2010 ) and interaction with peers, faculty, and staff (Coates, 2008 ; Kahu, 2013 ; Kuh, 2009 ; Bryson & Hand, 2007 ; Wimpenny & Savin-Baden, 2013 : Zepke & Leach, 2010 ). Indicators of behavioral engagement reflect observable student actions and most closely align with Pace ( 1980 ) and Astin’s ( 1984 ) original conceptualizations of student engagement as quantity and quality of effort towards learning. Emotional engagement is students’ affective reactions to learning (Fredricks et al., 2004 ; Lester, 2013 ; Trowler, 2010 ). Indicators of emotional engagement include attitudes, interests, and values towards learning (Fredricks et al., 2004 ; Kahu, 2013 ; Lester, 2013 ; Trowler, 2010 ; Wimpenny & Savin-Baden, 2013 ; Witkowski & Cornell, 2015 ) and a perceived sense of belonging within a learning community (Fredricks et al., 2004 ; Kahu, 2013 ; Lester, 2013 ; Trowler, 2010 ; Wimpenny & Savin-Baden, 2013 ). Emotional engagement often is assessed using self-report measures (Fredricks et al., 2004 ) and provides insight into how students feel about a particular topic, delivery method, or instructor. Finally, cognitive engagement is the degree to which students invest in learning and expend mental effort to comprehend and master content (Fredricks et al., 2004 ; Lester, 2013 ). Indicators of cognitive engagement include: motivation to learn (Lester, 2013 ; Richardson & Newby, 2006 ; Zepke & Leach, 2010 ); persistence to overcome academic challenges and meet/exceed requirements (Fredricks et al., 2004 ; Kuh, 2009 ; Trowler, 2010 ); and deep processing of information (Fredricks et al., 2004 ; Kahu, 2013 ; Lam et al., 2012 ; Richardson & Newby, 2006 ) through critical thinking (Coates, 2008 ; Witkowski & Cornell, 2015 ), self-regulation (e.g., set goals, plan, organize study effort, and monitor learning; Fredricks et al., 2004 ; Lester, 2013 ), and the active construction of knowledge (Coates, 2008 ; Kuh, 2009 ). While cognitive engagement includes motivational aspects, much of the literature focuses on how students use active learning and higher-order thinking, in some form, to achieve content mastery. For example, there is significant emphasis on the importance of deep learning, which involves analyzing new learning in relation previous knowledge, compared to surface learning, which is limited to memorization, recall, and rehearsal (Fredricks et al., 2004 ; Kahu, 2013 ; Lam et al., 2012 ).

While each type of engagement has distinct features, there is some overlap across cognitive, behavioral, and emotional domains. In instances where an indicator could correspond with more than one type of engagement, we chose to match the indicator to the type of engagement that most closely aligned, based on our review of the engagement literature and our interpretation of the indicators. Similarly, there is also some overlap among indicators. As a result, we combined and subsumed similar indicators found in the literature, where appropriate, to avoid redundancy. Achieving an in-depth understanding of student engagement and associated indicators was an important pre-cursor to our review of the technology literature. Very few articles used the term student engagement as a dependent variable given the concept is so broad and multidimensional. We found that specific indicators (e.g., interaction, sense of belonging, and knowledge construction) of student engagement were more common in the literature as dependent variables. Next, we will provide a synthesis of the findings regarding how different types of technology influence behavioral, emotional, and cognitive student engagement and associated indicators.

Influence of technology on student engagement

We identified five technologies post-literature search (i.e., web-conferencing, blogs, wikis, social networking sites , and digital games) to include in our review, based on frequency in which they appeared in the literature over the past 5 years. One commonality among these technologies is their potential value in supporting a constructivist approach to learning, characterized by the active discovery of knowledge through reflection of experiences with one’s environment, the connection of new knowledge to prior knowledge, and interaction with others (Boghossian, 2006 ; Clements, 2015 ). Another commonality is that most of the technologies, except perhaps for digital games, are designed primarily to promote interaction and collaboration with others. Our search yielded very few studies on how informational technologies, such as video lectures and podcasts, influence student engagement. Therefore, these technologies are notably absent from our review. Unlike the technologies we identified earlier, informational technologies reflect a behaviorist approach to learning in which students are passive recipients of knowledge that is transmitted from an expert (Boghossian, 2006 ). The lack of recent research on how informational technologies affect student engagement may be due to the increasing shift from instructor-centered, behaviorist approaches to student-centered, constructivist approaches within higher education (Haggis, 2009 ; Wright, 2011 ) along with the ubiquity of web 2.0 technologies.

• Web-conferencing

Web-conferencing software provides a virtual meeting space where users login simultaneously and communicate about a given topic. While each software application is unique, many share similar features such as audio, video, or instant messaging options for real-time communication; screen sharing, whiteboards, and digital pens for presentations and demonstrations; polls and quizzes for gauging comprehension or eliciting feedback; and breakout rooms for small group work (Bower, 2011 ; Hudson, Knight, & Collins, 2012 ; Martin, Parker, & Deale, 2012 ; McBrien, Jones, & Cheng, 2009 ). Of the technologies included in this literature review, web-conferencing software most closely mimics the face-to-face classroom environment, providing a space where instructors and students can hear and see each other in real-time as typical classroom activities (i.e., delivering lectures, discussing course content, asking/answering questions) are carried out (Francescucci & Foster, 2013 ; Hudson et al., 2012 ). Studies on web-conferencing software deployed Adobe Connect, Cisco WebEx, Horizon Wimba, or Blackboard Collaborate and made use of multiple features, such as screen sharing, instant messaging, polling, and break out rooms. In addition, most of the studies integrated web-conferencing software into courses on a voluntary basis to supplement traditional instructional methods (Andrew, Maslin-Prothero, & Ewens, 2015 ; Armstrong & Thornton, 2012 ; Francescucci & Foster, 2013 ; Hudson et al., 2012 ; Martin et al., 2012 ; Wdowik, 2014 ). Existing studies on web-conferencing pertain to all three types of student engagement.

Studies on web-conferencing and behavioral engagement reveal mixed findings. For example, voluntary attendance in web-conferencing sessions ranged from 54 to 57% (Andrew et al., 2015 ; Armstrong & Thornton, 2012 ) and, in a comparison between a blended course with regular web-conferencing sessions and a traditional, face-to-face course, researchers found no significant difference in student attendance in courses. However, students in the blended course reported higher levels of class participation compared to students in the face-to-face course (Francescucci & Foster, 2013 ). These findings suggest while web-conferencing may not boost attendance, especially if voluntary, it may offer more opportunities for class participation, perhaps through the use of communication channels typically not available in a traditional, face-to-face course (e.g., instant messaging, anonymous polling). Studies on web-conferencing and interaction, another behavioral indicator, support this assertion. For example, researchers found that students use various features of web-conferencing software (e.g., polling, instant message, break-out rooms) to interact with peers and the instructor by asking questions, expressing opinions and ideas, sharing resources, and discussing academic content (Andrew et al., 2015 ; Armstrong & Thornton, 2012 ; Hudson et al., 2012 ; Martin et al., 2012 ; Wdowik, 2014 ).

Studies on web-conferencing and cognitive engagement are more conclusive than those for behavioral engagement, although are fewer in number. Findings suggest that students who participated in web-conferencing demonstrated critical reflection and enhanced learning through interactions with others (Armstrong & Thornton, 2012 ), higher-order thinking (e.g., problem-solving, synthesis, evaluation) in response to challenging assignments (Wdowik, 2014 ), and motivation to learn, particularly when using polling features (Hudson et al., 2012 ). There is only one study examining how web-conferencing affects emotional engagement, although it is positive suggesting that students who participated in web-conferences had higher levels of interest in course content than those who did not (Francescucci & Foster, 2013 ). One possible reason for the positive cognitive and emotional engagement findings may be that web-conferencing software provides many features that promote active learning. For example, whiteboards and breakout rooms provide opportunities for real-time, collaborative problem-solving activities and discussions. However, additional studies are needed to isolate and compare specific web-conferencing features to determine which have the greatest effect on student engagement.

A blog, which is short for Weblog, is a collection of personal journal entries, published online and presented chronologically, to which readers (or subscribers) may respond by providing additional commentary or feedback. In order to create a blog, one must compose content for an entry, which may include text, hyperlinks, graphics, audio, or video, publish the content online using a blogging application, and alert subscribers that new content is posted. Blogs may be informal and personal in nature or may serve as formal commentary in a specific genre, such as in politics or education (Coghlan et al., 2007 ). Fortunately, many blog applications are free, and many learning management systems (LMSs) offer a blogging feature that is seamlessly integrated into the online classroom. The ease of blogging has attracted attention from educators, who currently use blogs as an instructional tool for the expression of ideas, opinions, and experiences and for promoting dialogue on a wide range of academic topics (Garrity, Jones, VanderZwan, de la Rocha, & Epstein, 2014 ; Wang, 2008 ).

Studies on blogs show consistently positive findings for many of the behavioral and emotional engagement indicators. For example, students reported that blogs promoted interaction with others, through greater communication and information sharing with peers (Chu, Chan, & Tiwari, 2012 ; Ivala & Gachago, 2012 ; Mansouri & Piki, 2016 ), and analyses of blog posts show evidence of students elaborating on one another’s ideas and sharing experiences and conceptions of course content (Sharma & Tietjen, 2016 ). Blogs also contribute to emotional engagement by providing students with opportunities to express their feelings about learning and by encouraging positive attitudes about learning (Dos & Demir, 2013 ; Chu et al., 2012 ; Yang & Chang, 2012 ). For example, Dos and Demir ( 2013 ) found that students expressed prejudices and fears about specific course topics in their blog posts. In addition, Yang and Chang ( 2012 ) found that interactive blogging, where comment features were enabled, lead to more positive attitudes about course content and peers compared to solitary blogging, where comment features were disabled.

The literature on blogs and cognitive engagement is less consistent. Some studies suggest that blogs may help students engage in active learning, problem-solving, and reflection (Chawinga, 2017 ; Chu et al., 2012 ; Ivala & Gachago, 2012 ; Mansouri & Piki, 2016 ), while other studies suggest that students’ blog posts show very little evidence of higher-order thinking (Dos & Demir, 2013 ; Sharma & Tietjen, 2016 ). The inconsistency in findings may be due to the wording of blog instructions. Students may not necessarily demonstrate or engage in deep processing of information unless explicitly instructed to do so. Unfortunately, it is difficult to determine whether the wording of blog assignments contributed to the mixed results because many of the studies did not provide assignment details. However, studies pertaining to other technologies suggest that assignment wording that lacks specificity or requires low-level thinking can have detrimental effects on student engagement outcomes (Hou, Wang, Lin, & Chang, 2015 ; Prestridge, 2014 ). Therefore, blog assignments that are vague or require only low-level thinking may have adverse effects on cognitive engagement.

A wiki is a web page that can be edited by multiple users at once (Nakamaru, 2012 ). Wikis have gained popularity in educational settings as a viable tool for group projects where group members can work collaboratively to develop content (i.e., writings, hyperlinks, images, graphics, media) and keep track of revisions through an extensive versioning system (Roussinos & Jimoyiannis, 2013 ). Most studies on wikis pertain to behavioral engagement, with far fewer studies on cognitive engagement and none on emotional engagement. Studies pertaining to behavioral engagement reveal mixed results, with some showing very little enduring participation in wikis beyond the first few weeks of the course (Nakamaru, 2012 ; Salaber, 2014 ) and another showing active participation, as seen in high numbers of posts and edits (Roussinos & Jimoyiannis, 2013 ). The most notable difference between these studies is the presence of grading, which may account for the inconsistencies in findings. For example, in studies where participation was low, wikis were ungraded, suggesting that students may need extra motivation and encouragement to use wikis (Nakamaru, 2012 ; Salaber, 2014 ). Findings regarding the use of wikis for promoting interaction are also inconsistent. In some studies, students reported that wikis were useful for interaction, teamwork, collaboration, and group networking (Camacho, Carrión, Chayah, & Campos, 2016 ; Martínez, Medina, Albalat, & Rubió, 2013 ; Morely, 2012 ; Calabretto & Rao, 2011 ) and researchers found evidence of substantial collaboration among students (e.g., sharing ideas, opinions, and points of view) in wiki activity (Hewege & Perera, 2013 ); however, Miller, Norris, and Bookstaver ( 2012 ) found that only 58% of students reported that wikis promoted collegiality among peers. The findings in the latter study were unexpected and may be due to design flaws in the wiki assignments. For example, the authors noted that wiki assignments were not explicitly referred to in face-to-face classes; therefore, this disconnect may have prevented students from building on interactive momentum achieved during out-of-class wiki assignments (Miller et al., 2012 ).

Studies regarding cognitive engagement are limited in number but more consistent than those concerning behavioral engagement, suggesting that wikis promote high levels of knowledge construction (i.e., evaluation of arguments, the integration of multiple viewpoints, new understanding of course topics; Hewege & Perera, 2013 ), and are useful for reflection, reinforcing course content, and applying academic skills (Miller et al., 2012 ). Overall, there is mixed support for the use of wikis to promote behavioral engagement, although making wiki assignments mandatory and explicitly referring to wikis in class may help bolster participation and interaction. In addition, there is some support for using wikis to promote cognitive engagement, but additional studies are needed to confirm and expand on findings as well as explore the effect of wikis on emotional engagement.

Social networking sites

Social networking is “the practice of expanding knowledge by making connections with individuals of similar interests” (Gunawardena et al., 2009 , p. 4). Social networking sites, such as Facebook, Twitter, Instagram, and LinkedIn, allow users to create and share digital content publicly or with others to whom they are connected and communicate privately through messaging features. Two of the most popular social networking sites in the educational literature are Facebook and Twitter (Camus, Hurt, Larson, & Prevost, 2016 ; Manca & Ranieri, 2013 ), which is consistent with recent statistics suggesting that both sites also are exceedingly popular among the general population (Greenwood, Perrin, & Duggan, 2016 ). In the sections that follow, we examine how both Facebook and Twitter influence different types of student engagement.

Facebook is a web-based service that allows users to create a public or private profile and invite others to connect. Users may build social, academic, and professional connections by posting messages in various media formats (i.e., text, pictures, videos) and commenting on, liking, and reacting to others’ messages (Bowman & Akcaoglu, 2014 ; Maben, Edwards, & Malone, 2014 ; Hou et al., 2015 ). Within an educational context, Facebook has often been used as a supplementary instructional tool to lectures or LMSs to support class discussions or develop, deliver, and share academic content and resources. Many instructors have opted to create private Facebook groups, offering an added layer of security and privacy because groups are not accessible to strangers (Bahati, 2015 ; Bowman & Akcaoglu, 2014 ; Clements, 2015 ; Dougherty & Andercheck, 2014 ; Esteves, 2012 ; Shraim, 2014 ; Maben et al., 2014 ; Manca & Ranieri, 2013 ; Naghdipour & Eldridge, 2016 ; Rambe, 2012 ). The majority of studies on Facebook address behavioral indicators of student engagement, with far fewer focusing on emotional or cognitive engagement.

Studies that examine the influence of Facebook on behavioral engagement focus both on participation in learning activities and interaction with peers and instructors. In most studies, Facebook activities were voluntary and participation rates ranged from 16 to 95%, with an average of rate of 47% (Bahati, 2015 ; Bowman & Akcaoglu, 2014 ; Dougherty & Andercheck, 2014 ; Fagioli, Rios-Aguilar, & Deil-Amen, 2015 ; Rambe, 2012 ; Staines & Lauchs, 2013 ). Participation was assessed by tracking how many students joined course- or university-specific Facebook groups (Bahati, 2015 ; Bowman & Akcaoglu, 2014 ; Fagioli et al., 2015 ), visited or followed course-specific Facebook pages (DiVall & Kirwin, 2012 ; Staines & Lauchs, 2013 ), or posted at least once in a course-specific Facebook page (Rambe, 2012 ). The lowest levels of participation (16%) arose from a study where community college students were invited to use the Schools App, a free application that connects students to their university’s private Facebook community. While the authors acknowledged that building an online community of college students is difficult (Fagioli et al., 2015 ), downloading the Schools App may have been a deterrent to widespread participation. In addition, use of the app was not tied to any specific courses or assignments; therefore, students may have lacked adequate incentive to use it. The highest level of participation (95%) in the literature arose from a study in which the instructor created a Facebook page where students could find or post study tips or ask questions. Followership to the page was highest around exams, when students likely had stronger motivations to access study tips and ask the instructor questions (DiVall & Kirwin, 2012 ). The wide range of participation in Facebook activities suggests that some students may be intrinsically motivated to participate, while other students may need some external encouragement. For example, Bahati ( 2015 ) found that when students assumed that a course-specific Facebook was voluntary, only 23% participated, but when the instructor confirmed that the Facebook group was, in fact, mandatory, the level of participation rose to 94%.

While voluntary participation in Facebook activities may be lower than desired or expected (Dyson, Vickers, Turtle, Cowan, & Tassone, 2015 ; Fagioli et al., 2015 ; Naghdipour & Eldridge, 2016 ; Rambe, 2012 ), students seem to have a clear preference for Facebook compared to other instructional tools (Clements, 2015 ; DiVall & Kirwin, 2012 ; Hurt et al., 2012 ; Hou et al., 2015 ; Kent, 2013 ). For example, in one study where an instructor shared course-related information in a Facebook group, in the LMS, and through email, the level of participation in the Facebook group was ten times higher than in email or the LMS (Clements, 2015 ). In other studies, class discussions held in Facebook resulted in greater levels of participation and dialogue than class discussions held in LMS discussion forums (Camus et al., 2016 ; Hurt et al., 2012 ; Kent, 2013 ). Researchers found that preference for Facebook over the university’s LMS is due to perceptions that the LMS is outdated and unorganized and reports that Facebook is more familiar, convenient, and accessible given that many students already visit the social networking site multiple times per day (Clements, 2015 ; Dougherty & Andercheck, 2014 ; Hurt et al., 2012 ; Kent, 2013 ). In addition, students report that Facebook helps them stay engaged in learning through collaboration and interaction with both peers and instructors (Bahati, 2015 ; Shraim, 2014 ), which is evident in Facebook posts where students collaborated to study for exams, consulted on technical and theoretical problem solving, discussed course content, exchanged learning resources, and expressed opinions as well as academic successes and challenges (Bowman & Akcaoglu, 2014 ; Dougherty & Andercheck, 2014 ; Esteves, 2012 Ivala & Gachago, 2012 ; Maben et al., 2014 ; Rambe, 2012 ; van Beynen & Swenson, 2016 ).

There is far less evidence in the literature about the use of Facebook for emotional and cognitive engagement. In terms of emotional engagement, studies suggest that students feel positively about being part of a course-specific Facebook group and that Facebook is useful for expressing feelings about learning and concerns for peers, through features such as the “like” button and emoticons (Bowman & Akcaoglu, 2014 ; Dougherty & Andercheck, 2014 ; Naghdipour & Eldridge, 2016 ). In addition, being involved in a course-specific Facebook group was positively related to students’ sense of belonging in the course (Dougherty & Andercheck, 2014 ). The research on cognitive engagement is less conclusive, with some studies suggesting that Facebook participation is related to academic persistence (Fagioli et al., 2015 ) and self-regulation (Dougherty & Andercheck, 2014 ) while other studies show low levels of knowledge construction in Facebook posts (Hou et al., 2015 ), particularly when compared to discussions held in the LMS. One possible reason may be because the LMS is associated with formal, academic interactions while Facebook is associated with informal, social interactions (Camus et al., 2016 ). While additional research is needed to confirm the efficacy of Facebook for promoting cognitive engagement, studies suggest that Facebook may be a viable tool for increasing specific behavioral and emotional engagement indicators, such as interactions with others and a sense of belonging within a learning community.

Twitter is a web-based service where subscribers can post short messages, called tweets, in real-time that are no longer than 140 characters in length. Tweets may contain hyperlinks to other websites, images, graphics, and/or videos and may be tagged by topic using the hashtag symbol before the designated label (e.g., #elearning). Twitter subscribers may “follow” other users and gain access to their tweets and also may “retweet” messages that have already been posted (Hennessy, Kirkpatrick, Smith, & Border, 2016 ; Osgerby & Rush, 2015 ; Prestridge, 2014 ; West, Moore, & Barry, 2015 ; Tiernan, 2014 ;). Instructors may use Twitter to post updates about the course, clarify expectations, direct students to additional learning materials, and encourage students to discuss course content (Bista, 2015 ; Williams & Whiting, 2016 ). Several of the studies on the use of Twitter included broad, all-encompassing measures of student engagement and produced mixed findings. For example, some studies suggest that Twitter increases student engagement (Evans, 2014 ; Gagnon, 2015 ; Junco, Heibergert, & Loken, 2011 ) while other studies suggest that Twitter has little to no influence on student engagement (Junco, Elavsky, & Heiberger, 2013 ; McKay, Sanko, Shekhter, & Birnbach, 2014 ). In both studies suggesting little to no influence on student engagement, Twitter use was voluntary and in one of the studies faculty involvement in Twitter was low, which may account for the negative findings (Junco et al., 2013 ; McKay et al., 2014 ). Conversely, in the studies that show positive findings, Twitter use was mandatory and often directly integrated with required assignments (Evans, 2014 ; Gagnon, 2015 ; Junco et al., 2011 ). Therefore, making Twitter use mandatory, increasing faculty involvement in Twitter, and integrating Twitter into assignments may help to increase student engagement.

Studies pertaining to specific behavioral student engagement indicators also reveal mixed findings. For example, in studies where course-related Twitter use was voluntary, 45-91% of students reported using Twitter during the term (Hennessy et al., 2016 ; Junco et al., 2013 ; Ross, Banow, & Yu, 2015 ; Tiernan, 2014 ; Williams & Whiting, 2016 ), but only 30-36% reported making contributions to the course-specific Twitter page (Hennessy et al., 2016 ; Tiernan, 2014 ; Ross et al., 2015 ; Williams & Whiting, 2016 ). The study that reported a 91% participation rate was unique because the course-specific Twitter page was accessible via a public link. Therefore, students who chose only to view the content (58%), rather than contribute to the page, did not have to create a Twitter account (Hennessy et al., 2016 ). The convenience of not having to create an account may be one reason for much higher participation rates. In terms of low participation rates, a lack of literacy, familiarity, and interest in Twitter , as well as a preference for Facebook , are cited as contributing factors (Bista, 2015 ; McKay et al., 2014 ; Mysko & Delgaty, 2015 ; Osgerby & Rush, 2015 ; Tiernan, 2014 ). However, when the use of Twitter was required and integrated into class discussions, the participation rate was 100% (Gagnon, 2015 ). Similarly, 46% of students in one study indicated that they would have been more motivated to participate in Twitter activities if they were graded (Osgerby & Rush, 2015 ), again confirming the power of extrinsic motivating factors.

Studies also show mixed results for the use of Twitter to promote interactions with peers and instructors. Researchers found that when instructors used Twitter to post updates about the course, ask and answer questions, and encourage students to tweet about course content, there was evidence of student-student and student-instructor interactions in tweets (Hennessy et al., 2016 ; Tiernan, 2014 ). Some students echoed these findings, suggesting that Twitter is useful for sharing ideas and resources, discussing course content, asking the instructor questions, and networking (Chawinga, 2017 ; Evans, 2014 ; Gagnon, 2015 ; Hennessy et al., 2016 ; Mysko & Delgaty, 2015 ; West et al., 2015 ) and is preferable over speaking aloud in class because it is more comfortable, less threatening, and more concise due to the 140 character limit (Gagnon, 2015 ; Mysko & Delgaty, 2015 ; Tiernan, 2014 ). Conversely, other students reported that Twitter was not useful for improving interaction because they viewed it predominately for social, rather than academic, interactions and they found the 140 character limit to be frustrating and restrictive. A theme among the latter studies was that a large proportion of the sample had never used Twitter before (Bista, 2015 ; McKay et al., 2014 ; Osgerby & Rush, 2015 ), which may have contributed to negative perceptions.

The literature on the use of Twitter for cognitive and emotional engagement is minimal but nonetheless promising in terms of promoting knowledge gains, the practical application of content, and a sense of belonging among users. For example, using Twitter to respond to questions that arose in lectures and tweet about course content throughout the term is associated with increased understanding of course content and application of knowledge (Kim et al., 2015 ; Tiernan, 2014 ; West et al., 2015 ). While the underlying mechanisms pertaining to why Twitter promotes an understanding of content and application of knowledge are not entirely clear, Tiernan ( 2014 ) suggests that one possible reason may be that Twitter helps to break down communication barriers, encouraging shy or timid students to participate in discussions that ultimately are richer in dialogue and debate. In terms of emotional engagement, students who participated in a large, class-specific Twitter page were more likely to feel a sense of community and belonging compared to those who did not participate because they could more easily find support from and share resources with other Twitter users (Ross et al., 2015 ). Despite the positive findings about the use of Twitter for cognitive and emotional engagement, more studies are needed to confirm existing results regarding behavioral engagement and target additional engagement indicators such as motivation, persistence, and attitudes, interests, and values about learning. In addition, given the strong negative perceptions of Twitter that still exist, additional studies are needed to confirm Twitter ’s efficacy for promoting different types of behavioral engagement among both novice and experienced Twitter users, particularly when compared to more familiar tools such as Facebook or LMS discussion forums.

• Digital games

Digital games are “applications using the characteristics of video and computer games to create engaging and immersive learning experiences for delivery of specified learning goals, outcomes and experiences” (de Freitas, 2006 , p. 9). Digital games often serve the dual purpose of promoting the achievement of learning outcomes while making learning fun by providing simulations of real-world scenarios as well as role play, problem-solving, and drill and repeat activities (Boyle et al., 2016 ; Connolly, Boyle, MacArthur, Hainey, & Boyle, 2012 ; Scarlet & Ampolos, 2013 ; Whitton, 2011 ). In addition, gamified elements, such as digital badges and leaderboards, may be integrated into instruction to provide additional motivation for completing assigned readings and other learning activities (Armier, Shepherd, & Skrabut, 2016 ; Hew, Huang, Chu, & Chiu, 2016 ). The pedagogical benefits of digital games are somewhat distinct from the other technologies addressed in this review, which are designed primarily for social interaction. While digital games may be played in teams or allow one player to compete against another, the focus of their design often is on providing opportunities for students to interact with academic content in a virtual environment through decision-making, problem-solving, and reward mechanisms. For example, a digital game may require students to adopt a role as CEO in a computer-simulated business environment, make decisions about a series of organizational issues, and respond to the consequences of those decisions. In this example and others, digital games use adaptive learning principles, where the learning environment is re-configured or modified in response to the actions and needs of students (Bower, 2016 ). Most of the studies on digital games focused on cognitive and emotional indicators of student engagement, in contrast to the previous technologies addressed in this review which primarily focused on behavioral indicators of engagement.

Existing studies provide support for the influence of digital games on cognitive engagement, through achieving a greater understanding of course content and demonstrating higher-order thinking skills (Beckem & Watkins, 2012 ; Farley, 2013 ; Ke, Xie, & Xie, 2016 ; Marriott, Tan, & Marriott, 2015 ), particularly when compared to traditional instructional methods, such as giving lectures or assigning textbook readings (Lu, Hallinger, & Showanasai, 2014 ; Siddique, Ling, Roberson, Xu, & Geng, 2013 ; Zimmermann, 2013 ). For example, in a study comparing courses that offered computer simulations of business challenges (e.g, implementing a new information technology system, managing a startup company, and managing a brand of medicine in a simulated market environment) and courses that did not, students in simulation-based courses reported higher levels of action-directed learning (i.e., connecting theory to practice in a business context) than students in traditional, non-simulation-based courses (Lu et al., 2014 ). Similarly, engineering students who participated in a car simulator game, which was designed to help students apply and reinforce the knowledge gained from lectures, demonstrated higher levels of critical thinking (i.e., analysis, evaluation) on a quiz than students who only attended lectures (Siddique et al., 2013 ).

Motivation is another cognitive engagement indicator that is linked to digital games (Armier et al., 2016 ; Chang & Wei, 2016 ; Dichev & Dicheva, 2017 ; Grimley, Green, Nilsen, & Thompson, 2012 ; Hew et al., 2016 ; Ibáñez, Di-Serio, & Delgado-Kloos, 2014 ; Ke et al., 2016 ; Liu, Cheng, & Huang, 2011 ; Nadolny & Halabi, 2016 ). Researchers found that incorporating gamified elements into courses, such as giving students digital rewards (e.g., redeemable points, trophies, and badges) for participating in learning activities or creating competition through the use of leaderboards where students can see how they rank against other students positively affects student motivation to complete learning tasks (Armier et al., 2016 ; Chang & Wei, 2016 ; Hew et al., 2016 ; Nadolny & Halabi, 2016 ). In addition, students who participated in gamified elements, such as trying to earn digital badges, were more motivated to complete particularly difficult learning activities (Hew et al., 2016 ) and showed persistence in exceeding learning requirements (Ibáñez et al., 2014 ). Research on emotional engagement may help to explain these findings. Studies suggest that digital games positively affect student attitudes about learning, evident in student reports that games are fun, interesting, and enjoyable (Beckem & Watkins, 2012 ; Farley, 2013 ; Grimley et al., 2012 ; Hew et al., 2016 ; Liu et al., 2011 ; Zimmermann, 2013 ), which may account for higher levels of student motivation in courses that offered digital games.

Research on digital games and behavioral engagement is more limited, with only one study suggesting that games lead to greater participation in educational activities (Hew et al., 2016 ). Therefore, more research is needed to explore how digital games may influence behavioral engagement. In addition, research is needed to determine whether the underlying technology associated with digital games (e.g., computer-based simulations and virtual realities) produce positive engagement outcomes or whether common mechanisms associated with both digital and non-digital games (e.g., role play, rewards, and competition) account for those outcomes. For example, studies in which non-digital, face-to-face games were used also showed positive effects on student engagement (Antunes, Pacheco, & Giovanela, 2012 ; Auman, 2011 ; Coffey, Miller, & Feuerstein, 2011 ; Crocco, Offenholley, & Hernandez, 2016 ; Poole, Kemp, Williams, & Patterson, 2014 ; Scarlet & Ampolos, 2013 ); therefore, it is unclear if and how digitizing games contributes to student engagement.

Discussion and implications

Student engagement is linked to a number of academic outcomes, such as retention, grade point average, and graduation rates (Carini et al., 2006 ; Center for Postsecondary Research, 2016 ; Hu & McCormick, 2012 ). As a result, universities have shown a strong interest in how to increase student engagement, particularly given rising external pressures to improve learning outcomes and prepare students for academic success (Axelson & Flick, 2011 ; Kuh, 2009 ). There are various models of student engagement that identify factors that influence student engagement (Kahu, 2013 ; Lam et al., 2012 ; Nora et al., 2005 ; Wimpenny & Savin-Baden, 2013 ; Zepke & Leach, 2010 ); however, none include the overt role of technology despite the growing trend and student demands to integrate technology into the learning experience (Amirault, 2012 ; Cook & Sonnenberg, 2014 ; Revere & Kovach, 2011 ; Sun & Chen, 2016 ; Westera, 2015 ). Therefore, the primary purpose of our literature review was to explore whether technology influences student engagement. The secondary purpose was to address skepticism and uncertainty about pedagogical benefits of technology (Ashrafzadeh & Sayadian, 2015 ; Kopcha et al., 2016 ; Reid, 2014 ) by reviewing the literature regarding the efficacy of specific technologies (i.e., web-conferencing software, blogs, wikis, social networking sites, and digital games) for promoting student engagement and offering recommendations for effective implementation, which are included at the end of this paper. In the sections that follow, we provide an overview of the findings, an explanation of existing methodological limitations and areas for future research, and a list of best practices for integrating the technologies we reviewed into the teaching and learning process.

Summary of findings

Findings from our literature review provide preliminary support for including technology as a factor that influences student engagement in existing models (Table 1 ). One overarching theme is that most of the technologies we reviewed had a positive influence on multiple indicators of student engagement, which may lead to a larger return on investment in terms of learning outcomes. For example, digital games influence all three types of student engagement and six of the seven indicators we identified, surpassing the other technologies in this review. There were several key differences in the design and pedagogical use between digital games and other technologies that may explain these findings. First, digital games were designed to provide authentic learning contexts in which students could practice skills and apply learning (Beckem & Watkins, 2012 ; Farley, 2013 ; Grimley et al., 2012 ; Ke et al., 2016 ; Liu et al., 2011 ; Lu et al., 2014 ; Marriott et al., 2015 ; Siddique et al., 2013 ), which is consistent with experiential learning and adult learning theories. Experiential learning theory suggests that learning occurs through interaction with one’s environment (Kolb, 2014 ) while adult learning theory suggests that adult learners want to be actively involved in the learning process and be able apply learning to real life situations and problems (Cercone, 2008 ). Second, students reported that digital games (and gamified elements) are fun, enjoyable, and interesting (Beckem & Watkins, 2012 ; Farley, 2013 ; Grimley et al., 2012 ; Hew et al., 2016 ; Liu et al., 2011 ; Zimmermann, 2013 ), feelings that are associated with a flow-like state where one is completely immersed in and engaged with the activity (Csikszentmihalyi, 1988 ; Weibel, Wissmath, Habegger, Steiner, & Groner, 2008 ). Third, digital games were closely integrated into the curriculum as required activities (Farley, 2013 ; Grimley et al., 2012 , Ke et al., 2016 ; Liu et al., 2011 ; Marriott et al., 2015 ; Siddique et al., 2013 ) as opposed to wikis, Facebook , and Twitter , which were often voluntary and used to supplement lectures (Dougherty & Andercheck, 2014 Nakamaru, 2012 ; Prestridge, 2014 ; Rambe, 2012 ).

Web-conferencing software and Facebook also yielded the most positive findings, influencing four of the seven indicators of student engagement, compared to other collaborative technologies, such as blogs, wikis, and Twitter . Web-conferencing software was unique due to the sheer number of collaborative features it offers, providing multiple ways for students to actively engage with course content (screen sharing, whiteboards, digital pens) and interact with peers and the instructor (audio, video, text chats, breakout rooms) (Bower, 2011 ; Hudson et al., 2012 ; Martin et al., 2012 ; McBrien et al., 2009 ); this may account for the effects on multiple indicators of student engagement. Positive findings regarding Facebook ’s influence on student engagement could be explained by a strong familiarity and preference for the social networking site (Clements, 2015 ; DiVall & Kirwin, 2012 ; Hurt et al., 2012 ; Hou et al., 2015 ; Kent, 2013 ; Manca & Ranieri, 2013 ), compared to Twitter which was less familiar or interesting to students (Bista, 2015 ; McKay et al., 2014 ; Mysko & Delgaty, 2015 ; Osgerby & Rush, 2015 ; Tiernan, 2014 ). Wikis had the lowest influence on student engagement, with mixed findings regarding behavioral engagement, limited, but conclusive findings, regarding one indicator of cognitive engagement (deep processing of information), and no studies pertaining to other indicators of cognitive engagement (motivation, persistence) or emotional engagement.

Another theme that arose was the prevalence of mixed findings across multiple technologies regarding behavioral engagement. Overall, the vast majority of studies addressed behavioral engagement, and we expected that technologies designed specifically for social interaction, such as web-conferencing, wikis, and social networking sites, would yield more conclusive findings. However, one possible reason for the mixed findings may be that the technologies were voluntary in many studies, resulting in lower than desired participation rates and missed opportunities for interaction (Armstrong & Thornton, 2012 ; Fagioli et al., 2015 ; Nakamaru, 2012 ; Rambe, 2012 ; Ross et al., 2015 ; Williams & Whiting, 2016 ), and mandatory in a few studies, yielding higher levels of participation and interaction (Bahati, 2015 ; Gagnon, 2015 ; Roussinos & Jimoyiannis, 2013 ). Another possible reason for the mixed findings is that measures of variables differed across studies. For example, in some studies participation meant that a student signed up for a Twitter account (Tiernan, 2014 ), used the Twitter account for class (Williams & Whiting, 2016 ), or viewed the course-specific Twitter page (Hennessy et al., 2016 ). The pedagogical uses of the technologies also varied considerably across studies, making it difficult to make comparisons. For example, Facebook was used in studies to share learning materials (Clements, 2015 ; Dyson et al., 2015 ), answer student questions about academic content or administrative issues (Rambe, 2012 ), prepare for upcoming exams and share study tips (Bowman & Akcaoglu, 2014 ; DiVall & Kirwin, 2012 ), complete group work (Hou et al., 2015 ; Staines & Lauchs, 2013 ), and discuss course content (Camus et al., 2016 ; Kent, 2013 ; Hurt et al., 2012 ). Finally, cognitive indicators (motivation and persistence) drew the fewest amount of studies, which suggests that research is needed to determine whether technologies affect these indicators.

Methodological limitations

While there appears to be preliminary support for the use of many of the technologies to promote student engagement, there are significant methodological limitations in the literature and, as a result, findings should be interpreted with caution. First, many studies used small sample sizes and were limited to one course, one degree level, and one university. Therefore, generalizability is limited. Second, very few studies used experimental or quasi-experimental designs; therefore, very little evidence exists to substantiate a cause and effect relationship between technologies and student engagement indicators. In addition, in many studies that did use experimental or quasi-experimental designs, participants were not randomized; rather, participants who volunteered to use a specific technology were compared to those who chose not to use the technology. As a result, there is a possibility that fundamental differences between users and non-users could have affected the engagement results. Furthermore, many of the studies did not isolate specific technological features (e.g, using only the breakout rooms for group work in web-conferencing software, rather than using the chat feature, screen sharing, and breakout rooms for group work). Using multiple features at once could have conflated student engagement results. Third, many studies relied on one source to measure technological and engagement variables (single source bias), such as self-report data (i.e., reported usage of technology and perceptions of student engagement), which may have affected the validity of the results. Fourth, many studies were conducted during a very brief timeframe, such as one academic term. As a result, positive student engagement findings may be attributed to a “novelty effect” (Dichev & Dicheva, 2017 ) associated with using a new technology. Finally, many studies lack adequate details about learning activities, raising questions about whether poor instructional design may have adversely affected results. For example, an instructor may intend to elicit higher-order thinking from students, but if learning activity instructions are written using low-level verbs, such as identify, describe, and summarize, students will be less likely to engage in higher-order thinking.

Areas for future research

The findings of our literature review suggest that the influence of technology on student engagement is still a developing area of knowledge that requires additional research to build on promising, but limited, evidence, clarify mixed findings, and address several gaps in the literature. As such, our recommendations for future areas of research are as follows:

Examine the effect of collaborative technologies (i.e., web-conferencing, blogs, wikis, social networking sites ) on emotional and cognitive student engagement. There are significant gaps in the literature regarding whether these technologies affect attitudes, interests, and values about learning; a sense of belonging within a learning community; motivation to learn; and persistence to overcome academic challenges and meet or exceed requirements.

Clarify mixed findings, particularly regarding how web-conferencing software, wikis, and Facebook and Twitter affect participation in learning activities. Researchers should make considerable efforts to gain consensus or increase consistency on how participation is measured (e.g., visited Facebook group or contributed one post a week) in order to make meaningful comparisons and draw conclusions about the efficacy of various technologies for promoting behavioral engagement. In addition, further research is needed to clarify findings regarding how wikis and Twitter influence interaction and how blogs and Facebook influence deep processing of information. Future research studies should include justifications for the pedagogical use of specific technologies and detailed instructions for learning activities to minimize adverse findings from poor instructional design and to encourage replication.

Conduct longitudinal studies over several academic terms and across multiple academic disciplines, degree levels, and institutions to determine long-term effects of specific technologies on student engagement and to increase generalizability of findings. Also, future studies should take individual factors into account, such as gender, age, and prior experience with the technology. Studies suggest that a lack of prior experience or familiarity with Twitter was a barrier to Twitter use in educational settings (Bista, 2015 , Mysko & Delgaty, 2015 , Tiernan, 2014 ); therefore, future studies should take prior experience into account.

Compare student engagement outcomes between and among different technologies and non-technologies. For example, studies suggest that students prefer Facebook over Twitter (Bista, 2015 ; Osgerby & Rush, 2015 ), but there were no studies that compared these technologies for promoting student engagement. Also, studies are needed to isolate and compare different features within the same technology to determine which might be most effective for increasing engagement. Finally, studies on digital games (Beckem & Watkins, 2012 ; Grimley et al., 2012 ; Ke et al., 2016 ; Lu et al., 2014 ; Marriott et al., 2015 ; Siddique et al., 2013 ) and face-to-face games (Antunes et al., 2012 ; Auman, 2011 ; Coffey et al., 2011 ; Crocco et al., 2016 ; Poole et al., 2014 ; Scarlet & Ampolos, 2013 ) show similar, positive effects on student engagement, therefore, additional research is needed to determine the degree to which the delivery method (i.e.., digital versus face-to-face) accounts for positive gains in student engagement.

Determine whether other technologies not included in this review influence student engagement. Facebook and Twitter regularly appear in the literature regarding social networking, but it is unclear how other popular social networking sites, such as LinkedIn, Instagram, and Flickr, influence student engagement. Future research should focus on the efficacy of these and other popular social networking sites for promoting student engagement. In addition, there were very few studies about whether informational technologies, which involve the one-way transmission of information to students, affect different types of student engagement. Future research should examine whether informational technologies, such as video lectures, podcasts, and pre-recorded narrated Power Point presentations or screen casts, affect student engagement. Finally, studies should examine the influence of mobile software and technologies, such as educational apps or smartphones, on student engagement.

Achieve greater consensus on the meaning of student engagement and its distinction from similar concepts in the literature, such as social and cognitive presence (Garrison & Arbaugh, 2007 )

Recommendations for practice

Despite the existing gaps and mixed findings in the literature, we were able to compile a list of recommendations for when and how to use technology to increase the likelihood of promoting student engagement. What follows is not an exhaustive list; rather, it is a synthesis of both research findings and lessons learned from the studies we reviewed. There may be other recommendations to add to this list; however, our intent is to provide some useful information to help address barriers to technology integration among faculty who feel uncertain or unprepared to use technology (Ashrafzadeh & Sayadian, 2015 ; Hauptman, 2015 ; Kidd et al., 2016 ; Reid, 2014 ) and to add to the body of practical knowledge in instructional design and delivery. Our recommendations for practice are as follows:

Consider context before selecting technologies. Contextual factors such as existing technological infrastructure and requirements, program and course characteristics, and the intended audience will help determine which technologies, if any, are most appropriate (Bullen & Morgan, 2011 ; Bullen, Morgan, & Qayyum, 2011 ). For example, requiring students to use a blog that is not well integrated with the existing LMS may prove too frustrating for both the instructor and students. Similarly, integrating Facebook- and Twitter- based learning activities throughout a marketing program may be more appropriate, given the subject matter, compared to doing so in an engineering or accounting program where social media is less integral to the profession. Finally, do not assume that students appreciate or are familiar with all technologies. For example, students who did not already have Facebook or Twitter accounts were less likely to use either for learning purposes and perceived setting up an account to be an increase in workload (Bista, 2015 , Clements, 2015 ; DiVall & Kirwin, 2012 ; Hennessy et al., 2016 ; Mysko & Delgaty, 2015 , Tiernan, 2014 ). Therefore, prior to using any technology, instructors may want to determine how many students already have accounts and/or are familiar with the technology.

Carefully select technologies based on their strengths and limitations and the intended learning outcome. For example, Twitter is limited to 140 characters, making it a viable tool for learning activities that require brevity. In one study, an instructor used Twitter for short pop quizzes during lectures, where the first few students to tweet the correct answer received additional points (Kim et al., 2015 ), which helped students practice applying knowledge. In addition, studies show that students perceive Twitter and Facebook to be primarily for social interactions (Camus et al., 2016 ; Ross et al., 2015 ), which may make these technologies viable tools for sharing resources, giving brief opinions about news stories pertaining to course content, or having casual conversations with classmates rather than full-fledged scholarly discourse.

Incentivize students to use technology, either by assigning regular grades or giving extra credit. The average participation rates in voluntary web-conferencing, Facebook , and Twitter learning activities in studies we reviewed was 52% (Andrew et al., 2015 ; Armstrong & Thornton, 2012 ; Bahati, 2015 ; Bowman & Akcaoglu, 2014 ; Divall & Kirwin, 2012 ; Dougherty & Andercheck, 2014 ; Fagioli et al., 2015 ; Hennessy et al., 2016 ; Junco et al., 2013 ; Rambe, 2012 ; Ross et al., 2015 ; Staines & Lauchs, 2013 ; Tiernan, 2014 ; Williams & Whiting, 2016 ). While there were far fewer studies on the use of technology for graded or mandatory learning activities, the average participation rate reported in those studies was 97% (Bahati2015; Gagnon, 2015 ), suggesting that grading may be a key factor in ensuring students participate.

Communicate clear guidelines for technology use. Prior to the implementation of technology in a course, students may benefit from an overview the technology, including its navigational features, privacy settings, and security (Andrew et al., 2015 ; Hurt et al., 2012 ; Martin et al., 2012 ) and a set of guidelines for how to use the technology effectively and professionally within an educational setting (Miller et al., 2012 ; Prestridge, 2014 ; Staines & Lauchs, 2013 ; West et al., 2015 ). In addition, giving students examples of exemplary and poor entries and posts may also help to clarify how they are expected to use the technology (Shraim, 2014 ; Roussinos & Jimoyiannis, 2013 ). Also, if instructors expect students to use technology to demonstrate higher-order thinking or to interact with peers, there should be explicit instructions to do so. For example, Prestridge ( 2014 ) found that students used Twitter to ask the instructor questions but very few interacted with peers because they were not explicitly asked to do so. Similarly, Hou et al., 2015 reported low levels of knowledge construction in Facebook , admitting that the wording of the learning activity (e.g., explore and present applications of computer networking) and the lack of probing questions in the instructions may have been to blame.

Use technology to provide authentic and integrated learning experiences. In many studies, instructors used digital games to simulate authentic environments in which students could apply new knowledge and skills, which ultimately lead to a greater understanding of content and evidence of higher-order thinking (Beckem & Watkins, 2012 ; Liu et al., 2011 ; Lu et al., 2014 ; Marriott et al., 2015 ; Siddique et al., 2013 ). For example, in one study, students were required to play the role of a stock trader in a simulated trading environment and they reported that the simulation helped them engage in critical reflection, enabling them to identify their mistakes and weaknesses in their trading approaches and strategies (Marriott et al., 2015 ). In addition, integrating technology into regularly-scheduled classroom activities, such as lectures, may help to promote student engagement. For example, in one study, the instructor posed a question in class, asked students to respond aloud or tweet their response, and projected the Twitter page so that everyone could see the tweets in class, which lead to favorable comments about the usefulness of Twitter to promote engagement (Tiernan, 2014 ).

Actively participate in using the technologies assigned to students during the first few weeks of the course to generate interest (Dougherty & Andercheck, 2014 ; West et al., 2015 ) and, preferably, throughout the course to answer questions, encourage dialogue, correct misconceptions, and address inappropriate behavior (Bowman & Akcaoglu, 2014 ; Hennessy et al., 2016 ; Junco et al., 2013 ; Roussinos & Jimoyiannis, 2013 ). Miller et al. ( 2012 ) found that faculty encouragement and prompting was associated with increases in students’ expression of ideas and the degree to which they edited and elaborated on their peers’ work in a course-specific wiki.

Be mindful of privacy, security, and accessibility issues. In many studies, instructors took necessary steps to help ensure privacy and security by creating closed Facebook groups and private Twitter pages, accessible only to students in the course (Bahati, 2015 ; Bista, 2015 ; Bowman & Akcaoglu, 2014 ; Esteves, 2012 ; Rambe, 2012 ; Tiernan, 2014 ; Williams & Whiting, 2016 ) and by offering training to students on how to use privacy and security settings (Hurt et al., 2012 ). Instructors also made efforts to increase accessibility of web-conferencing software by including a phone number for students unable to access audio or video through their computer and by recording and archiving sessions for students unable to attend due to pre-existing conflicts (Andrew et al., 2015 ; Martin et al., 2012 ). In the future, instructors should also keep in mind that some technologies, like Facebook and Twitter , are not accessible to students living in China; therefore, alternative arrangements may need to be made.

In 1985, Steve Jobs predicted that computers and software would revolutionize the way we learn. Over 30 years later, his prediction has yet to be fully confirmed in the student engagement literature; however, our findings offer preliminary evidence that the potential is there. Of the technologies we reviewed, digital games, web-conferencing software, and Facebook had the most far-reaching effects across multiple types and indicators of student engagement, suggesting that technology should be considered a factor that influences student engagement in existing models. Findings regarding blogs, wikis, and Twitter, however, are less convincing, given a lack of studies in relation to engagement indicators or mixed findings. Significant methodological limitations may account for the wide range of findings in the literature. For example, small sample sizes, inconsistent measurement of variables, lack of comparison groups, and missing details about specific, pedagogical uses of technologies threaten the validity and reliability of findings. Therefore, more rigorous and robust research is needed to confirm and build upon limited but positive findings, clarify mixed findings, and address gaps particularly regarding how different technologies influence emotional and cognitive indicators of engagement.

Abbreviations

Learning management system

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• 10 February 2020

Scrutinizing the effects of digital technology on mental health

• Jonathan Haidt &

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The topic in brief

• There is an ongoing debate about whether social media and the use of digital devices are detrimental to mental health.

• Adolescents tend to be heavy users of these devices, and especially of social media.

• Rates of teenage depression began to rise around 2012, when adolescent use of social media became common (Fig. 1).

• Some evidence indicates that frequent users of social media have higher rates of depression and anxiety than do light users.

• But perhaps digital devices could provide a way of gathering data about mental health in a systematic way, and make interventions more timely.

Figure 1 | Depression on the rise. Rates of depression among teenagers in the United States have increased steadily since 2012. Rates are higher and are increasing more rapidly for girls than for boys. Some researchers think that social media is the cause of this increase, whereas others see social media as a way of tackling it. (Data taken from the US National Survey on Drug Use and Health, Table 11.2b; go.nature.com/3ayjaww )

JONATHAN HAIDT: A guilty verdict

A sudden increase in the rates of depression, anxiety and self-harm was seen in adolescents — particularly girls — in the United States and the United Kingdom around 2012 or 2013 (see go.nature.com/2up38hw ). Only one suspect was in the right place at the right time to account for this sudden change: social media. Its use by teenagers increased most quickly between 2009 and 2011, by which point two-thirds of 15–17-year-olds were using it on a daily basis 1 . Some researchers defend social media, arguing that there is only circumstantial evidence for its role in mental-health problems 2 , 3 . And, indeed, several studies 2 , 3 show that there is only a small correlation between time spent on screens and bad mental-health outcomes. However, I present three arguments against this defence.

First, the papers that report small or null effects usually focus on ‘screen time’, but it is not films or video chats with friends that damage mental health. When research papers allow us to zoom in on social media, rather than looking at screen time as a whole, the correlations with depression are larger, and they are larger still when we look specifically at girls ( go.nature.com/2u74der ). The sex difference is robust, and there are several likely causes for it. Girls use social media much more than do boys (who, in turn, spend more of their time gaming). And, for girls more than boys, social life and status tend to revolve around intimacy and inclusion versus exclusion 4 , making them more vulnerable to both the ‘fear of missing out’ and the relational aggression that social media facilitates.

Second, although correlational studies can provide only circumstantial evidence, most of the experiments published in recent years have found evidence of causation ( go.nature.com/2u74der ). In these studies, people are randomly assigned to groups that are asked to continue using social media or to reduce their use substantially. After a few weeks, people who reduce their use generally report an improvement in mood or a reduction in loneliness or symptoms of depression.

The best way forward

Third, many researchers seem to be thinking about social media as if it were sugar: safe in small to moderate quantities, and harmful only if teenagers consume large quantities. But, unlike sugar, social media does not act just on those who consume it. It has radically transformed the nature of peer relationships, family relationships and daily activities 5 . When most of the 11-year-olds in a class are on Instagram (as was the case in my son’s school), there can be pervasive effects on everyone. Children who opt out can find themselves isolated. A simple dose–response model cannot capture the full effects of social media, yet nearly all of the debate among researchers so far has been over the size of the dose–response effect. To cite just one suggestive finding of what lies beyond that model: network effects for depression and anxiety are large, and bad mental health spreads more contagiously between women than between men 6 .

In conclusion, digital media in general undoubtedly has many beneficial uses, including the treatment of mental illness. But if you focus on social media, you’ll find stronger evidence of harm, and less exculpatory evidence, especially for its millions of under-age users.

What should we do while researchers hash out the meaning of these conflicting findings? I would urge a focus on middle schools (roughly 11–13-year-olds in the United States), both for researchers and policymakers. Any US state could quickly conduct an informative experiment beginning this September: randomly assign a portion of school districts to ban smartphone access for students in middle school, while strongly encouraging parents to prevent their children from opening social-media accounts until they begin high school (at around 14). Within 2 years, we would know whether the policy reversed the otherwise steady rise of mental-health problems among middle-school students, and whether it also improved classroom dynamics (as rated by teachers) and test scores. Such system-wide and cross-school interventions would be an excellent way to study the emergent effects of social media on the social lives and mental health of today’s adolescents.

NICK ALLEN: Use digital technology to our advantage

It is appealing to condemn social media out of hand on the basis of the — generally rather poor-quality and inconsistent — evidence suggesting that its use is associated with mental-health problems 7 . But focusing only on its potential harmful effects is comparable to proposing that the only question to ask about cars is whether people can die driving them. The harmful effects might be real, but they don’t tell the full story. The task of research should be to understand what patterns of digital-device and social-media use can lead to beneficial versus harmful effects 7 , and to inform evidence-based approaches to policy, education and regulation.

Long-standing problems have hampered our efforts to improve access to, and the quality of, mental-health services and support. Digital technology has the potential to address some of these challenges. For instance, consider the challenges associated with collecting data on human behaviour. Assessment in mental-health care and research relies almost exclusively on self-reporting, but the resulting data are subjective and burdensome to collect. As a result, assessments are conducted so infrequently that they do not provide insights into the temporal dynamics of symptoms, which can be crucial for both diagnosis and treatment planning.

By contrast, mobile phones and other Internet-connected devices provide an opportunity to continuously collect objective information on behaviour in the context of people’s real lives, generating a rich data set that can provide insight into the extent and timing of mental-health needs in individuals 8 , 9 . By building apps that can track our digital exhaust (the data generated by our everyday digital lives, including our social-media use), we can gain insights into aspects of behaviour that are well-established building blocks of mental health and illness, such as mood, social communication, sleep and physical activity.

Stress and the city

These data can, in turn, be used to empower individuals, by giving them actionable insights into patterns of behaviour that might otherwise have remained unseen. For example, subtle shifts in patterns of sleep or social communication can provide early warning signs of deteriorating mental health. Data on these patterns can be used to alert people to the need for self-management before the patterns — and the associated symptoms — become more severe. Individuals can also choose to share these data with health professionals or researchers. For instance, in the Our Data Helps initiative, individuals who have experienced a suicidal crisis, or the relatives of those who have died by suicide, can donate their digital data to research into suicide risk.

Because mobile devices are ever-present in people’s lives, they offer an opportunity to provide interventions that are timely, personalized and scalable. Currently, mental-health services are mainly provided through a century-old model in which they are made available at times chosen by the mental-health practitioner, rather than at the person’s time of greatest need. But Internet-connected devices are facilitating the development of a wave of ‘just-in-time’ interventions 10 for mental-health care and support.

A compelling example of these interventions involves short-term risk for suicide 9 , 11 — for which early detection could save many lives. Most of the effective approaches to suicide prevention work by interrupting suicidal actions and supporting alternative methods of coping at the moment of greatest risk. If these moments can be detected in an individual’s digital exhaust, a wide range of intervention options become available, from providing information about coping skills and social support, to the initiation of crisis responses. So far, just-in-time approaches have been applied mainly to behaviours such as eating or substance abuse 8 . But with the development of an appropriate research base, these approaches have the potential to provide a major advance in our ability to respond to, and prevent, mental-health crises.

These advantages are particularly relevant to teenagers. Because of their extensive use of digital devices, adolescents are especially vulnerable to the devices’ risks and burdens. And, given the increases in mental-health problems in this age group, teens would also benefit most from improvements in mental-health prevention and treatment. If we use the social and data-gathering functions of Internet-connected devices in the right ways, we might achieve breakthroughs in our ability to improve mental health and well-being.

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Competing Interests

N.A. has an equity interest in Ksana Health, a company he co-founded and which has the sole commercial licence for certain versions of the Effortless Assessment of Risk States (EARS) mobile-phone application and some related EARS tools. This intellectual property was developed as part of his research at the University of Oregon’s Center for Digital Mental Health (CDMH).

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Essay on Technology – A Boon or Bane for Students

500+ words essay on technology for students.

In this essay on technology, we are going to discuss what technology is, what are its uses, and also what technology can do? First of all, technology refers to the use of technical and scientific knowledge to create, monitor, and design machinery. Also, technology helps in making other goods that aid mankind.

Essay on Technology – A Boon or Bane?

Experts are debating on this topic for years. Also, the technology covered a long way to make human life easier but the negative aspect of it can’t be ignored. Over the years technological advancement has caused a severe rise in pollution . Also, pollution has become a major cause of many health issues. Besides, it has cut off people from society rather than connecting them. Above all, it has taken away many jobs from the workers class.

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As they are completely different fields but they are interdependent on each other. Also, it is due to science contribution we can create new innovation and build new technological tools. Apart from that, the research conducted in laboratories contributes a lot to the development of technologies. On the other hand, technology extends the agenda of science.

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Negative Aspect of Technology

Although technology is a good thing, everything has two sides. Technology also has two sides one is good and the other is bad. Here are some negative aspects of technology that we are going to discuss.

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With new technology the industrialization increases which give birth to many pollutions like air, water, soil, and noise. Also, they cause many health-related issues in animals, birds, and human beings.

Exhaustion of Natural Resources

New technology requires new resources for which the balance is disturbed. Eventually, this will lead to over-exploitation of natural resources which ultimately disturbs the balance of nature.

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A single machine can replace many workers. Also, machines can do work at a constant pace for several hours or days without stopping. Due to this, many workers lost their job which ultimately increases unemployment .

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Industrial Technology

This technology organizes engineering and manufacturing technology for the manufacturing of machines. Also, this makes the production process easier and convenient.

Creative Technology

This process includes art, advertising, and product design which are made with the help of software. Also, it comprises of 3D printers , virtual reality, computer graphics, and other wearable technologies.

Information Technology

This technology involves the use of telecommunication and computer to send, receive and store information. Internet is the best example of Information technology.

FAQs on Essay on Technology

Q.1 What is Information technology?

A –  It is a form of technology that uses telecommunication and computer systems for study. Also, they send, retrieve, and store data.

Q.2 Is technology harmful to humans?

 A – No, technology is not harmful to human beings until it is used properly. But, misuses of technology can be harmful and deadly.

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Feb 13, 2023

200-500 Word Example Essays about Technology

Got an essay assignment about technology check out these examples to inspire you.

Technology is a rapidly evolving field that has completely changed the way we live, work, and interact with one another. Technology has profoundly impacted our daily lives, from how we communicate with friends and family to how we access information and complete tasks. As a result, it's no surprise that technology is a popular topic for students writing essays.

But writing a technology essay can be challenging, especially for those needing more time or help with writer's block. This is where Jenni.ai comes in. Jenni.ai is an innovative AI tool explicitly designed for students who need help writing essays. With Jenni.ai, students can quickly and easily generate essays on various topics, including technology.

This blog post aims to provide readers with various example essays on technology, all generated by Jenni.ai. These essays will be a valuable resource for students looking for inspiration or guidance as they work on their essays. By reading through these example essays, students can better understand how technology can be approached and discussed in an essay.

Moreover, by signing up for a free trial with Jenni.ai, students can take advantage of this innovative tool and receive even more support as they work on their essays. Jenni.ai is designed to help students write essays faster and more efficiently, so they can focus on what truly matters – learning and growing as a student. Whether you're a student who is struggling with writer's block or simply looking for a convenient way to generate essays on a wide range of topics, Jenni.ai is the perfect solution.

The Impact of Technology on Society and Culture

Introduction:.

Technology has become an integral part of our daily lives and has dramatically impacted how we interact, communicate, and carry out various activities. Technological advancements have brought positive and negative changes to society and culture. In this article, we will explore the impact of technology on society and culture and how it has influenced different aspects of our lives.

Positive impact on communication:

Technology has dramatically improved communication and made it easier for people to connect from anywhere in the world. Social media platforms, instant messaging, and video conferencing have brought people closer, bridging geographical distances and cultural differences. This has made it easier for people to share information, exchange ideas, and collaborate on projects.

Positive impact on education:

Students and instructors now have access to a multitude of knowledge and resources because of the effect of technology on education . Students may now study at their speed and from any location thanks to online learning platforms, educational applications, and digital textbooks.

Negative impact on critical thinking and creativity:

Technological advancements have resulted in a reduction in critical thinking and creativity. With so much information at our fingertips, individuals have become more passive in their learning, relying on the internet for solutions rather than logic and inventiveness. As a result, independent thinking and problem-solving abilities have declined.

Positive impact on entertainment:

Technology has transformed how we access and consume entertainment. People may now access a wide range of entertainment alternatives from the comfort of their own homes thanks to streaming services, gaming platforms, and online content makers. The entertainment business has entered a new age of creativity and invention as a result of this.

Negative impact on attention span:

However, the continual bombardment of information and technological stimulation has also reduced attention span and the capacity to focus. People are easily distracted and need help focusing on a single activity for a long time. This has hampered productivity and the ability to accomplish duties.

The Ethics of Artificial Intelligence And Machine Learning

The development of artificial intelligence (AI) and machine learning (ML) technologies has been one of the most significant technological developments of the past several decades. These cutting-edge technologies have the potential to alter several sectors of society, including commerce, industry, healthcare, and entertainment. 

As with any new and quickly advancing technology, AI and ML ethics must be carefully studied. The usage of these technologies presents significant concerns around privacy, accountability, and command. As the use of AI and ML grows more ubiquitous, we must assess their possible influence on society and investigate the ethical issues that must be taken into account as these technologies continue to develop.

What are Artificial Intelligence and Machine Learning?

Artificial Intelligence is the simulation of human intelligence in machines designed to think and act like humans. Machine learning is a subfield of AI that enables computers to learn from data and improve their performance over time without being explicitly programmed.

The impact of AI and ML on Society

The use of AI and ML in various industries, such as healthcare, finance, and retail, has brought many benefits. For example, AI-powered medical diagnosis systems can identify diseases faster and more accurately than human doctors. However, there are also concerns about job displacement and the potential for AI to perpetuate societal biases.

The Ethical Considerations of AI and ML

A. Bias in AI algorithms

One of the critical ethical concerns about AI and ML is the potential for algorithms to perpetuate existing biases. This can occur if the data used to train these algorithms reflects the preferences of the people who created it. As a result, AI systems can perpetuate these biases and discriminate against certain groups of people.

B. Responsibility for AI-generated decisions

Another ethical concern is the responsibility for decisions made by AI systems. For example, who is responsible for the damage if a self-driving car causes an accident? The manufacturer of the vehicle, the software developer, or the AI algorithm itself?

C. The potential for misuse of AI and ML

AI and ML can also be used for malicious purposes, such as cyberattacks and misinformation. The need for more regulation and oversight in developing and using these technologies makes it difficult to prevent misuse.

The developments in AI and ML have given numerous benefits to humanity, but they also present significant ethical concerns that must be addressed. We must assess the repercussions of new technologies on society, implement methods to limit the associated dangers, and guarantee that they are utilized for the greater good. As AI and ML continue to play an ever-increasing role in our daily lives, we must engage in an open and frank discussion regarding their ethics.

The Future of Work And Automation

Rapid technological breakthroughs in recent years have brought about considerable changes in our way of life and work. Concerns regarding the influence of artificial intelligence and machine learning on the future of work and employment have increased alongside the development of these technologies. This article will examine the possible advantages and disadvantages of automation and its influence on the labor market, employees, and the economy.

The Advantages of Automation

Automation in the workplace offers various benefits, including higher efficiency and production, fewer mistakes, and enhanced precision. Automated processes may accomplish repetitive jobs quickly and precisely, allowing employees to concentrate on more complex and creative activities. Additionally, automation may save organizations money since it removes the need to pay for labor and minimizes the danger of workplace accidents.

The Potential Disadvantages of Automation

However, automation has significant disadvantages, including job loss and income stagnation. As robots and computers replace human labor in particular industries, there is a danger that many workers may lose their jobs, resulting in higher unemployment and more significant economic disparity. Moreover, if automation is not adequately regulated and managed, it might lead to stagnant wages and a deterioration in employees' standard of life.

The Future of Work and Automation

Despite these difficulties, automation will likely influence how labor is done. As a result, firms, employees, and governments must take early measures to solve possible issues and reap the rewards of automation. This might entail funding worker retraining programs, enhancing education and skill development, and implementing regulations that support equality and justice at work.

IV. The Need for Ethical Considerations

We must consider the ethical ramifications of automation and its effects on society as technology develops. The impact on employees and their rights, possible hazards to privacy and security, and the duty of corporations and governments to ensure that automation is utilized responsibly and ethically are all factors to be taken into account.

Conclusion:

To summarise, the future of employment and automation will most certainly be defined by a complex interaction of technological advances, economic trends, and cultural ideals. All stakeholders must work together to handle the problems and possibilities presented by automation and ensure that technology is employed to benefit society as a whole.

The Role of Technology in Education

Introduction.

Nearly every part of our lives has been transformed by technology, and education is no different. Today's students have greater access to knowledge, opportunities, and resources than ever before, and technology is becoming a more significant part of their educational experience. Technology is transforming how we think about education and creating new opportunities for learners of all ages, from online courses and virtual classrooms to instructional applications and augmented reality.

Technology's Benefits for Education

The capacity to tailor learning is one of technology's most significant benefits in education. Students may customize their education to meet their unique needs and interests since they can access online information and tools. 

For instance, people can enroll in online classes on topics they are interested in, get tailored feedback on their work, and engage in virtual discussions with peers and subject matter experts worldwide. As a result, pupils are better able to acquire and develop the abilities and information necessary for success.

Challenges and Concerns

Despite the numerous advantages of technology in education, there are also obstacles and considerations to consider. One issue is the growing reliance on technology and the possibility that pupils would become overly dependent on it. This might result in a lack of critical thinking and problem-solving abilities, as students may become passive learners who only follow instructions and rely on technology to complete their assignments.

Another obstacle is the digital divide between those who have access to technology and those who do not. This division can exacerbate the achievement gap between pupils and produce uneven educational and professional growth chances. To reduce these consequences, all students must have access to the technology and resources necessary for success.

In conclusion, technology is rapidly becoming an integral part of the classroom experience and has the potential to alter the way we learn radically. 

Technology can help students flourish and realize their full potential by giving them access to individualized instruction, tools, and opportunities. While the benefits of technology in the classroom are undeniable, it's crucial to be mindful of the risks and take precautions to guarantee that all kids have access to the tools they need to thrive.

The Influence of Technology On Personal Relationships And Communication 

Technological advancements have profoundly altered how individuals connect and exchange information. It has changed the world in many ways in only a few decades. Because of the rise of the internet and various social media sites, maintaining relationships with people from all walks of life is now simpler than ever. 

However, concerns about how these developments may affect interpersonal connections and dialogue are inevitable in an era of rapid technological growth. In this piece, we'll discuss how the prevalence of digital media has altered our interpersonal connections and the language we use to express ourselves.

Direct Effect on Direct Interaction:

The disruption of face-to-face communication is a particularly stark example of how technology has impacted human connections. The quality of interpersonal connections has suffered due to people's growing preference for digital over human communication. Technology has been demonstrated to reduce the usage of nonverbal signs such as facial expressions, tone of voice, and other indicators of emotional investment in the connection.

Positive Impact on Long-Distance Relationships:

Yet there are positives to be found as well. Long-distance relationships have also benefited from technological advancements. The development of technologies such as video conferencing, instant messaging, and social media has made it possible for individuals to keep in touch with distant loved ones. It has become simpler for individuals to stay in touch and feel connected despite geographical distance.

The Effects of Social Media on Personal Connections:

The widespread use of social media has had far-reaching consequences, especially on the quality of interpersonal interactions. Social media has positive and harmful effects on relationships since it allows people to keep in touch and share life's milestones.

Unfortunately, social media has made it all too easy to compare oneself to others, which may lead to emotions of jealousy and a general decline in confidence. Furthermore, social media might cause people to have inflated expectations of themselves and their relationships.

A Personal Perspective on the Intersection of Technology and Romance

Technological advancements have also altered physical touch and closeness. Virtual reality and other technologies have allowed people to feel physical contact and familiarity in a digital setting. This might be a promising breakthrough, but it has some potential downsides. 

Experts are concerned that people's growing dependence on technology for intimacy may lead to less time spent communicating face-to-face and less emphasis on physical contact, both of which are important for maintaining good relationships.

In conclusion, technological advancements have significantly affected the quality of interpersonal connections and the exchange of information. Even though technology has made it simpler to maintain personal relationships, it has chilled interpersonal interactions between people. 

Keeping tabs on how technology is changing our lives and making adjustments as necessary is essential as we move forward. Boundaries and prioritizing in-person conversation and physical touch in close relationships may help reduce the harm it causes.

The Security and Privacy Implications of Increased Technology Use and Data Collection

The fast development of technology over the past few decades has made its way into every aspect of our life. Technology has improved many facets of our life, from communication to commerce. However, significant privacy and security problems have emerged due to the broad adoption of technology. In this essay, we'll look at how the widespread use of technological solutions and the subsequent explosion in collected data affects our right to privacy and security.

Data Mining and Privacy Concerns

Risk of Cyber Attacks and Data Loss

The Widespread Use of Encryption and Other Safety Mechanisms

The Privacy and Security of the Future in a Globalized Information Age

Obtaining and Using Individual Information

The acquisition and use of private information is a significant cause for privacy alarm in the digital age. Data about their customers' online habits, interests, and personal information is a valuable commodity for many internet firms. Besides tailored advertising, this information may be used for other, less desirable things like identity theft or cyber assaults.

Moreover, many individuals need to be made aware of what data is being gathered from them or how it is being utilized because of the lack of transparency around gathering personal information. Privacy and data security have become increasingly contentious as a result.

Data breaches and other forms of cyber-attack pose a severe risk.

The risk of cyber assaults and data breaches is another big issue of worry. More people are using more devices, which means more opportunities for cybercriminals to steal private information like credit card numbers and other identifying data. This may cause monetary damages and harm one's reputation or identity.

Many high-profile data breaches have occurred in recent years, exposing the personal information of millions of individuals and raising serious concerns about the safety of this information. Companies and governments have responded to this problem by adopting new security methods like encryption and multi-factor authentication.

Many businesses now use encryption and other security measures to protect themselves from cybercriminals and data thieves. Encryption keeps sensitive information hidden by encoding it so that only those possessing the corresponding key can decipher it. This prevents private information like bank account numbers or social security numbers from falling into the wrong hands.

Firewalls, virus scanners, and two-factor authentication are all additional security precautions that may be used with encryption. While these safeguards do much to stave against cyber assaults, they are not entirely impregnable, and data breaches are still possible.

The Future of Privacy and Security in a Technologically Advanced World

There's little doubt that concerns about privacy and security will persist even as technology improves. There must be strict safeguards to secure people's private information as more and more of it is transferred and kept digitally. To achieve this goal, it may be necessary to implement novel technologies and heightened levels of protection and to revise the rules and regulations regulating the collection and storage of private information.

Individuals and businesses are understandably concerned about the security and privacy consequences of widespread technological use and data collecting. There are numerous obstacles to overcome in a society where technology plays an increasingly important role, from acquiring and using personal data to the risk of cyber-attacks and data breaches. Companies and governments must keep spending money on security measures and working to educate people about the significance of privacy and security if personal data is to remain safe.

In conclusion, technology has profoundly impacted virtually every aspect of our lives, including society and culture, ethics, work, education, personal relationships, and security and privacy. The rise of artificial intelligence and machine learning has presented new ethical considerations, while automation is transforming the future of work. 

In education, technology has revolutionized the way we learn and access information. At the same time, our dependence on technology has brought new challenges in terms of personal relationships, communication, security, and privacy.

Jenni.ai is an AI tool that can help students write essays easily and quickly. Whether you're looking, for example, for essays on any of these topics or are seeking assistance in writing your essay, Jenni.ai offers a convenient solution. Sign up for a free trial today and experience the benefits of AI-powered writing assistance for yourself.

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Argumentative Essay

Argumentative Essay About Technology

Last updated on: Mar 25, 2024

Make Your Argumentative Essay About Technology Unbeatable: Examples and Tips

By: Barbara P.

15 min read

Reviewed By: Melisa C.

Published on: Mar 9, 2023

Are you feeling overwhelmed by the task of writing an argumentative essay about technology? Don't worry – you're not alone. 

Technology is a vast and rapidly evolving field, making it a challenging topic to tackle. But fear not!  With the right structure, examples, and tips, you'll be equipped to create a persuasive and captivating essay that will impress your readers.

In this blog, we're here to guide you through the process, providing you with engaging examples and essential guidelines. With our help, you'll be able to create an argument that is both persuasive and well-supported by evidence.

So read on and make sure your argumentative essay about technology is unbeatable! 

On this Page

How to Write an Argumentative Essay About Technology?

Now you know what argumentative essays about technology are and why they're important? 

Let's look at how to write a compelling argument. 

Pick a Title

The title of your essay should capture the attention of your reader and summarize the main points of your argument. 

Think carefully about how you want to frame your argument in order to create an effective title. It should be short and catchy, but also accurately reflect the main arguments or ideas in your essay. 

Form an Outline 

After deciding on a title for your essay, it’s important to form an outline of the key points and arguments you will make in each paragraph. This will help keep you organized during the writing process and ensure that all of your ideas are connected. 

Make sure there is good flow between each section so that readers can follow along easily. 

Here is an outline template for argumentative essay about technology:

Write an Introduction 

Your introduction is where you set up the context for your essay and explain what it is that you will be arguing throughout the rest of the text. 

Include relevant background information, as well as any interesting facts or anecdotes that could help engage readers from the beginning. 

Be sure to end with a thesis statement that clearly lays out which side you are taking in this debate and what evidence will be used to support it.

Write Body Paragraphs 

Your body paragraphs are where most of your research comes into play! 

Ensure these paragraphs contain detailed evidence from reliable sources that supports each point being made in each paragraph. 

Additionally, be sure to use transition words throughout these sections so that readers can follow along easily from one point to another.  

Write a Conclusion

Your conclusion should briefly outline the key points and evidence used throughout your paper. While reiterating why this particular topic is so important and relevant today. 

Your conclusion should leave readers with something thought-provoking! 

Perhaps something they hadn’t considered before rather than just summarizing everything they have already read in previous paragraphs.

Looking for guidance on crafting powerful arguments? Look no further than our argumentative essay guide! 

Check out this informative video to learn how to construct a persuasive argumentative essay!

Examples of Argumentative Essay About Technology

Now that you know how to write an argumentative essay about technology, let's look at some examples.

These examples will help you get a better understanding of the argumentative essay structure and what types of arguments you can make. 

Argumentative Essay About Advantages and Disadvantages of Technology

Let’s take a look:

Paper Due? Why Suffer? That's our Job!

Argumentative Essay On Technology And Society

Here is a short argumentative essay on technology and society: 

Example of a Research-Based Argumentative Essay About Technology

Argumentative essay examples are a great way to gain a better understanding of how technology is affecting our lives - both positively and negatively. 

To help illustrate this argument, this essay will look at the evidence for an argumentative essay about technology.

Here are some additional examples for you to get inspired!

Argumentative Essay About Technology And Social Media

Argumentative Essay About Technology In Education

Argumentative Essay About Technology A Friend Or A Foe

Argumentative Essay About Technology Make Us Alone

Is Technology Good Or Bad Argumentative Essay

5 Paragraph Argumentative Essay About Technology

If you're searching for the determination to create a persuasive essay, our blog of argumentative essay examples is just what you need!

Good Argumentative Essay About Technology Topics

When writing argumentative essays about technology, it's important to identify a topic that is relevant and argumentative.

The following are some good argumentative essay topics related to technology: 

• Will AI bring more benefits or risks to society?
• Is social media a positive or negative influence on society?
• How can individuals and organizations better protect themselves from cyber threats?
• Should individuals have more control over their personal data online?
• Will automation lead to mass unemployment or create new job opportunities?
• Is VR technology more beneficial for entertainment or educational purposes?
• Should governments have the authority to regulate and censor online content?
• What are the advantages and disadvantages of widespread 5G implementation?
• Is the use of biometric data for identification and security purposes ethical?
• How can technology be effectively integrated into classrooms to enhance learning outcomes?

Want to write an essay that will grab your readers' attention? Explore our blog for more thrilling argumentative essay topics !

Summarizing it all,  argumentative essay examples about technology can help to illustrate the argument for or against its use in our lives. By exploring various argumentative essay topics related to technology, you can gain a better understanding of the benefits and drawbacks of its use. 

So, take a look at the argumentative essay topics provided above and create your argumentative essay today! 

And if you are still seeking help with your argumentative essay, contact our essay writer today!

Our argumentative essay writer has the knowledge and experience to write the best argumentative essay for you. 

So request “ write my paper ” today and we guarantee that your essay will be well-structured, argumentative, and insightful. 

So don't hesitate - to contact our argumentative essay writing service today! 

Literature, Marketing

Dr. Barbara is a highly experienced writer and author who holds a Ph.D. degree in public health from an Ivy League school. She has worked in the medical field for many years, conducting extensive research on various health topics. Her writing has been featured in several top-tier publications.

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• Technology Essay

Essay on Technology

The word "technology" and its uses have immensely changed since the 20th century, and with time, it has continued to evolve ever since. We are living in a world driven by technology. The advancement of technology has played an important role in the development of human civilization, along with cultural changes. Technology provides innovative ways of doing work through various smart and innovative means. 

Electronic appliances, gadgets, faster modes of communication, and transport have added to the comfort factor in our lives. It has helped in improving the productivity of individuals and different business enterprises. Technology has brought a revolution in many operational fields. It has undoubtedly made a very important contribution to the progress that mankind has made over the years.

The Advancement of Technology:

Technology has reduced the effort and time and increased the efficiency of the production requirements in every field. It has made our lives easy, comfortable, healthy, and enjoyable. It has brought a revolution in transport and communication. The advancement of technology, along with science, has helped us to become self-reliant in all spheres of life. With the innovation of a particular technology, it becomes part of society and integral to human lives after a point in time.

Technology is Our Part of Life:

Technology has changed our day-to-day lives. Technology has brought the world closer and better connected. Those days have passed when only the rich could afford such luxuries. Because of the rise of globalisation and liberalisation, all luxuries are now within the reach of the average person. Today, an average middle-class family can afford a mobile phone, a television, a washing machine, a refrigerator, a computer, the Internet, etc. At the touch of a switch, a man can witness any event that is happening in far-off places.  

Benefits of Technology in All Fields: 

We cannot escape technology; it has improved the quality of life and brought about revolutions in various fields of modern-day society, be it communication, transportation, education, healthcare, and many more. Let us learn about it.

Technology in Communication:

With the advent of technology in communication, which includes telephones, fax machines, cellular phones, the Internet, multimedia, and email, communication has become much faster and easier. It has transformed and influenced relationships in many ways. We no longer need to rely on sending physical letters and waiting for several days for a response. Technology has made communication so simple that you can connect with anyone from anywhere by calling them via mobile phone or messaging them using different messaging apps that are easy to download.

Innovation in communication technology has had an immense influence on social life. Human socialising has become easier by using social networking sites, dating, and even matrimonial services available on mobile applications and websites.

Today, the Internet is used for shopping, paying utility bills, credit card bills, admission fees, e-commerce, and online banking. In the world of marketing, many companies are marketing and selling their products and creating brands over the internet. 

In the field of travel, cities, towns, states, and countries are using the web to post detailed tourist and event information. Travellers across the globe can easily find information on tourism, sightseeing, places to stay, weather, maps, timings for events, transportation schedules, and buy tickets to various tourist spots and destinations.

Technology in the Office or Workplace:

Technology has increased efficiency and flexibility in the workspace. Technology has made it easy to work remotely, which has increased the productivity of the employees. External and internal communication has become faster through emails and apps. Automation has saved time, and there is also a reduction in redundancy in tasks. Robots are now being used to manufacture products that consistently deliver the same product without defect until the robot itself fails. Artificial Intelligence and Machine Learning technology are innovations that are being deployed across industries to reap benefits.

Technology has wiped out the manual way of storing files. Now files are stored in the cloud, which can be accessed at any time and from anywhere. With technology, companies can make quick decisions, act faster towards solutions, and remain adaptable. Technology has optimised the usage of resources and connected businesses worldwide. For example, if the customer is based in America, he can have the services delivered from India. They can communicate with each other in an instant. Every company uses business technology like virtual meeting tools, corporate social networks, tablets, and smart customer relationship management applications that accelerate the fast movement of data and information.

Technology in Education:

Technology is making the education industry improve over time. With technology, students and parents have a variety of learning tools at their fingertips. Teachers can coordinate with classrooms across the world and share their ideas and resources online. Students can get immediate access to an abundance of good information on the Internet. Teachers and students can access plenty of resources available on the web and utilise them for their project work, research, etc. Online learning has changed our perception of education. 

The COVID-19 pandemic brought a paradigm shift using technology where school-going kids continued their studies from home and schools facilitated imparting education by their teachers online from home. Students have learned and used 21st-century skills and tools, like virtual classrooms, AR (Augmented Reality), robots, etc. All these have increased communication and collaboration significantly. 

Technology in Banking:

Technology and banking are now inseparable. Technology has boosted digital transformation in how the banking industry works and has vastly improved banking services for their customers across the globe.

Technology has made banking operations very sophisticated and has reduced errors to almost nil, which were somewhat prevalent with manual human activities. Banks are adopting Artificial Intelligence (AI) to increase their efficiency and profits. With the emergence of Internet banking, self-service tools have replaced the traditional methods of banking. 

You can now access your money, handle transactions like paying bills, money transfers, and online purchases from merchants, and monitor your bank statements anytime and from anywhere in the world. Technology has made banking more secure and safe. You do not need to carry cash in your pocket or wallet; the payments can be made digitally using e-wallets. Mobile banking, banking apps, and cybersecurity are changing the face of the banking industry.

Manufacturing and Production Industry Automation:

At present, manufacturing industries are using all the latest technologies, ranging from big data analytics to artificial intelligence. Big data, ARVR (Augmented Reality and Virtual Reality), and IoT (Internet of Things) are the biggest manufacturing industry players. Automation has increased the level of productivity in various fields. It has reduced labour costs, increased efficiency, and reduced the cost of production.

For example, 3D printing is used to design and develop prototypes in the automobile industry. Repetitive work is being done easily with the help of robots without any waste of time. This has also reduced the cost of the products. 

Technology in the Healthcare Industry:

Technological advancements in the healthcare industry have not only improved our personal quality of life and longevity; they have also improved the lives of many medical professionals and students who are training to become medical experts. It has allowed much faster access to the medical records of each patient. 

The Internet has drastically transformed patients' and doctors’ relationships. Everyone can stay up to date on the latest medical discoveries, share treatment information, and offer one another support when dealing with medical issues. Modern technology has allowed us to contact doctors from the comfort of our homes. There are many sites and apps through which we can contact doctors and get medical help. 

Breakthrough innovations in surgery, artificial organs, brain implants, and networked sensors are examples of transformative developments in the healthcare industry. Hospitals use different tools and applications to perform their administrative tasks, using digital marketing to promote their services.

Technology in Agriculture:

Today, farmers work very differently than they would have decades ago. Data analytics and robotics have built a productive food system. Digital innovations are being used for plant breeding and harvesting equipment. Software and mobile devices are helping farmers harvest better. With various data and information available to farmers, they can make better-informed decisions, for example, tracking the amount of carbon stored in soil and helping with climate change.

Disadvantages of Technology:

People have become dependent on various gadgets and machines, resulting in a lack of physical activity and tempting people to lead an increasingly sedentary lifestyle. Even though technology has increased the productivity of individuals, organisations, and the nation, it has not increased the efficiency of machines. Machines cannot plan and think beyond the instructions that are fed into their system. Technology alone is not enough for progress and prosperity. Management is required, and management is a human act. Technology is largely dependent on human intervention. 

Computers and smartphones have led to an increase in social isolation. Young children are spending more time surfing the internet, playing games, and ignoring their real lives. Usage of technology is also resulting in job losses and distracting students from learning. Technology has been a reason for the production of weapons of destruction.

Dependency on technology is also increasing privacy concerns and cyber crimes, giving way to hackers.

FAQs on Technology Essay

1. What is technology?

Technology refers to innovative ways of doing work through various smart means. The advancement of technology has played an important role in the development of human civilization. It has helped in improving the productivity of individuals and businesses.

2. How has technology changed the face of banking?

Technology has made banking operations very sophisticated. With the emergence of Internet banking, self-service tools have replaced the traditional methods of banking. You can now access your money, handle transactions, and monitor your bank statements anytime and from anywhere in the world. Technology has made banking more secure and safe.

3. How has technology brought a revolution in the medical field?

Patients and doctors keep each other up to date on the most recent medical discoveries, share treatment information, and offer each other support when dealing with medical issues. It has allowed much faster access to the medical records of each patient. Modern technology has allowed us to contact doctors from the comfort of our homes. There are many websites and mobile apps through which we can contact doctors and get medical help.

4. Are we dependent on technology?

Yes, today, we are becoming increasingly dependent on technology. Computers, smartphones, and modern technology have helped humanity achieve success and progress. However, in hindsight, people need to continuously build a healthy lifestyle, sorting out personal problems that arise due to technological advancements in different aspects of human life.

• Essay On Technology

Essay on Technology

500+ words essay on technology.

The word technology comes from the two Greek words, ‘techne’ and ‘logos’. Techne means art, skills, or craft, and Logos means a word, saying, or expression that expresses inward thought. Thus, technology means the skill to convey an idea to reach a goal. But nowadays, the term technology mainly signifies the knowledge of tools, machines, techniques, crafts, systems, and organisation methods to solve a problem. Today, technological advancement has provided the human race with the ability to control and adapt to their natural environment. In this Essay on Technology, students will know the importance of technology, its advantages and disadvantages and the future of technology.

How Has Technology Changed Our Lives?

Various innovations and development took place in the field of technology which has made a significant impact on our lives in different ways. With the invention of technology, we become more powerful. We have the ability to transform the environment, extend our lifetime, create big and interconnected societies and even explore various new things about the universe. Today, we use technology from morning to evening, from the simplest nail cutter to television and personal laptop. Technology has touched all aspects of our lives, whether it is mobile phones, kettles, kitchen microwaves, electric cookers, television, water heaters, remote control, fridge, and other larger communication systems such as internet facilities, railways, air routes, and so on. Thus, technology plays an extremely crucial role in the lives of human beings.

Advantages of Technology

The advancement in technology has made our lives easier, more comfortable and enjoyable. It has reduced the effort and time required to complete a task, thus enhancing the quality and efficiency of work. Technology has become a part of our life and benefited us in many ways. Today, we can communicate with people living in any city or country. Communication has become much faster and easier as we are just a click away from people. In education, technology has played a vital role, especially during the COVID-19 breakdown period. It has brought virtual and online classes for students and teachers across the globe to share knowledge, ideas and resources online. Moreover, technology has made it easier for students to understand complex concepts with the help of virtualisation, graphics, 3D animation and diagrams.

Technology is considered to be the driving force behind improvements in the medical and healthcare field. Modern machines have helped doctors to perform operations successfully. Due to technology, the lifespan of the common person has increased. There are many more sectors, such as banking, automation, automobile, and various industries, where technology is making significant changes and helping us.

Disadvantages of Technology

Although we have so many advantages of technology, there are also disadvantages. Robots and machines have taken over the job of many people. Instead of bringing people together, technology has made them socially isolated. People now spend most of their time on smartphones or computers rather than interacting with other people. Technology in education has reduced the intellectual and analytical ability of students. It is like spoon-feeding to students as they don’t have the reasoning and aptitude skills to think differently. Technology has raised the issue of internet privacy. So, one has to be very careful while using banking passwords to make online transactions.

Future of Technology

The future of technology seems to be exciting but also scary. Futuristic predictions in technology can dish out some exciting or scary visions for the future of machines and science. Technology will either enhance or replace the products and activities that are near and dear to us. The answer to our technological dilemma about what will be the upcoming technological innovation in the future is not surprising. In the past, technology was mainly focused on retaining more information and efficient processing, but in the future, it will be based on industrial robots, artificial intelligence, machine learning, etc.

Technology alone cannot help in building a better world. The collateral collaboration of machines and human effort is required for the progress and prosperity of the nation. We need to develop a more robust management system for the efficient functioning of technology.

Practise CBSE Essays on more topics to improve the writing section. Students can get the latest updates on CBSE/ICSE/State Board/Competitive Exams at BYJU’S website. They can also download the BYJU’S App for interactive study videos.

Frequently Asked Questions on Technology Essay

What is the simple definition of technology.

The real-time application of science and knowledge is how technology can be defined in simple terms.

Which country is ranked first in technological advancement?

Finland ranks top in technological advancement ahead of the USA according to the UNDP.

Why is the development of technology important?

Technology has now become an important part of our lives and thus technical and technological advancements are essential to take us forward in all aspects.

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Counselling

Letter from the CIO

Rob Groome is the Chief Information Officer (CIO) at USC Institute for Creative Technologies, overseeing both the Information Technology and Facilities teams. Previously, Groome was the Head of IT and Information Security Officer at BlueOcean, the brandtech AI-powered decision intelligence company, headquartered in San Francisco. Here he talks about joining ICT in 2000, staying for 16 years – and then returning in 2023, after working on main campus, and taking a detour into entrepreneurship – as our first ever CIO. 

ICT has seen major changes since its inception in 1999.  Originally housed in 2 ½ floors in a building in Marina del Rey, it eventually occupied the entire space. The original “annex” on Redwood Drive which moved to McConnell Ave. Then to our current HQ in Playa Vista.  

By 2009, ICT was bulging at the seams and needed to look for a new home.  Enter Waterfront Drive, ICT’s current home and one of the greatest achievements of my career.  

When the idea of a new “campus” came about, we set out to build something incredible that would help change the course of the research, support the growth, and showcase what a truly amazing place ICT is. My involvement with making ICT’s new space a reality was all encompassing.  From architecting the network, identifying the requirements for power, or designing a place to showcase the work that our incredible researchers do, we all tried to get it right.  

How I Came to ICT

I came to ICT in a very different manner than most. In 2001. After a layoff, and caring for my infant daughter, a friend (who had just interviewed at ICT), suggested I apply for the role of the IT Manager (because I was a better fit than they). 

Intrigued, I delved into ICT’s groundbreaking work and was determined to join. Fast forward to the interview – and I was captivated. 

In Nov 2001, I joined ICT and stayed for 16+ remarkable years. From the groundbreaking VR Theater that housed the Mission Rehearsal Exercise and those famous words: “What happened here?” “There was an accident Sir,” to the amazing work with The Shoah Foundation to preserve the stories of holocaust survivors – there has never been a dull moment.  

Projects and Research

Over 25 years, ICT has achieved remarkable milestones and done groundbreaking research. 

Two projects particularly resonate to me: witnessing firsthand the life-saving impact of our training systems at Camp Pendleton, and contributing to the New Dimensions in Testimony project. 

The incident at Camp Pendleton served as a powerful reminder of my purpose, my “why”. While observing a squad undergoing training with the Mobile Counter IED Trainer (MCIT), I witnessed some soldiers not taking the exercise seriously. Their commanding officer intervened sternly, declaring, “You think this is (deleted expletive) funny?! This training system has saved my life and is why I am still here today! Pay attention to this, do you understand me?”

Immediately, the soldiers adjusted their demeanor, responding with a crisp “Yes, Sir,” and resumed training. Later, the officer approached me, inquiring about my presence. I explained that I was from ICT, installing another training system. He then expressed gratitude, remarking: 

“I hope you realize how impactful this really is. Thank you for your help in keeping us safe.” 

This encounter left a profound impression on me, highlighting the importance of our work even for those of us less directly engaged with our customer base.

The second project that I was very involved with was the New Dimensions in Testimony project, a collaboration with ICT and the Shoah Foundation to capture the stories of holocaust survivors before they were lost forever.  While working with one of the survivors, the Shoah Foundation team asked me if I would like my kids to come interview one of the survivors. I asked my kids, 12 and 9 at the time, if they would like to do it and they said yes, absolutely, but can we read about who we are going to interview?  

They took the time to really understand who the subject of the interview that day, what he went through, and how he made it through.  When the time came to do the interview, I couldn’t have been more impressed with my kids, and everyone involved.

It’s a memory I will never forget.  

Leaving ICT – and Returning

In 2018, I left ICT to take on new challenges and gain different experiences. I moved over to the Office of the CISO at USC before venturing into the realm of entrepreneurship, where I played a pivotal role in building a company from the ground up. 

However, in August 2023, as I found myself contemplating my next steps, ICT reached out to me. Over a memorable lunch with Cheryl Birch and Bill Swartout , they proposed the idea of my return. Instantly intrigued, I eagerly sought more details about the opportunity and the institute’s needs. By the time I left the meeting and returned home, I was already envisioning my comeback and planning my role. 

When I shared the opportunity with my family, their unanimous response was, “This just feels right.” Indeed, it resonated with me too. I’m immensely proud to be back at ICT, now leading the Information Technology and Facilities teams, and eager to contribute to its continued success.

Returning to ICT fills me with pride, having been part of its journey for much of its initial 25 years – especially when I think about the challenges we are now addressing, in terms of cybersecurity, upgrading the built environment, and celebrating our 25th anniversary this August. 

ICT has always been at the forefront of the evolution in the way that technology, security, research, and academia have had to learn to interact and work together. In the early 2000s, a culture of transparency, collaboration, and openness prevailed.  As cybercrime became more prevalent and the DoD was more and more of a target, more stringent security requirements began to surface for any government contractors.  The balance of sharing and collaboration became more difficult with the requirements to control, identify, and protect and ICT was at the heart of it because of our contracts.  

Now, as we embark on the next 25, our focus remains on staying ahead of trends, breaking new ground, and empowering our research teams to push boundaries and lead in the ever-expanding technological landscape. Technology is evolving rapidly, and our interactions with it are changing. As we embrace concepts like cloud computing and artificial intelligence, ICT stands out as a place where uniqueness is not just embraced but celebrated—an environment poised to change the world once again.

Rob Groome is the Chief Information Officer (CIO) at USC Institute for Creative Technologies, overseeing both the Information Technology and Facilities teams. Previously, Groome was the Head of IT and Information Security Officer at BlueOcean, the brandtech AI-powered decision intelligence company, headquartered in San Francisco. Groome has spent much of his career at University of Southern California (USC), joining ICT initially in 2001, as IT Manager, before being promoted to Director, IT. After almost 17 years with ICT, Groome took a promotion on the main campus, heading up the Security Operations Team within USC’s Information Technology Services (ITS) division for several years, before leaving academia for the world of Silicon Valley start-ups (BlueOcean). He re-joined ICT in 2023 as our first-ever CIO. 

Center for Environmental Research and Technology

We Engineer Excellence

Join us for a presentation and defense by Ryan Drover, as he defends his Ph.D. thesis at the Center for Environmental Research and Technology (CE-CERT). Let's come together to support Ryan in this significant milestone of his academic journey.

Time: 04/09/2024 (Tuesday) 1:00 pm

Location: CE-CERT room 105

Name: Ryan Drover

Title: Bridging Traditional Understandings of Aerosol Dynamics to Real-World Maritime Emissions and Respiratory Health Delivery Methods

Abstract: Advancements in air quality research and the demand for more accurate environmental health assessments have highlighted the need for methodologies that bridge the gap between laboratory findings and real-world conditions. This dissertation includes a retrospective of maritime emissions, utilizes complete vessel operational and emissions parameters on active container ships, and provides evaluation to establish a novel aerosol delivery method for health studies, collectively aiming to enhance the management of air pollution and its health implications. 

A major global fuel consumer and emissions source, maritime shipping has been historically understudied, and so emissions controls and policy have been misapplied. A historic technical review was conducted, utilizing an extensive internal dataset to develop new insights into the emissions profile of ocean-going vessels (OGVs). This analysis provides insight into the pollutants released by these ships across decades of regulatory changes and yields operational insights, suggesting pathways for more effective regulatory strategies. 

In the subsequent chapter, this work applies GPS monitoring on active container ships, combined with in-use engine operational data and emissions testing, to develop an understanding of how vessel operations modify the contributions to air pollution. This approach offers a significant advancement over traditional engine load-based emission estimations, providing guidance to improve the accounting of emissions in real-time and historically, under real-world operating conditions, and identifying areas of regulatory oversight. This granularity enables the identification of specific maneuvers and activities, particularly in sensitive areas, that disproportionately affect emission levels.

The final chapter evaluates a recently introduced method for aerosol delivery in biomedical studies, designed to mimic real-world respiratory exposure to pollutants more accurately than traditional laboratory techniques. In simulating representative conditions under which subjects are exposed to aerosols, the physical deposition of particles in the lung and the resulting inflammatory response enable a clearly quantified improvement in methodology. 

School of Chemistry & Biochemistry

College of sciences, 12 grad students named as finalists for 2024 three minute thesis competition.

Mar 26, 2024

After six intense preliminary rounds, twelve exceptional scholars have emerged from a pool of 65 talented candidates, earning their place as finalists in Georgia Tech's highly anticipated annual Three Minute Thesis (3MT) competition. On Friday, April 5, 2024, these finalists will hit the stage, harnessing their research expertise, to deliver compelling presentations in a three-minute format.

Congratulations to the following twelve finalists:

Karina Bhattacharya MID Industrial Design 

Vinodhini Comandur, Ph.D. Aerospace Engineering 

Mo Jarin, Ph.D. Environmental Engineering 

Anamik Jhunjhunwala, Ph.D. Biomedical Engineering 

Valeria Juarez, Ph.D. Biomedical Engineering 

Alexandra Patterson, Ph.D. Bioengineering 

Jeffrey Pattison, Ph.D. Aerospace Engineering 

Kantwon Rogers, Ph.D. Computer Science 

Mallika Senthil, MS Biomedical Engineering 

Wenting Shi, Ph.D. Chemistry and Biochemistry 

Shreyas Srivathsan, Ph.D. Aerospace Engineering 

Raghav Tandon, Ph.D. Machine Learning 

This year’s 3MT competition takes place on Friday, April 5, 2024, at 5:30 p.m. in the Atlantic Theater in the John Lewis Student Center. The entire Georgia Tech community is encouraged to attend the competition, which occurs as the finale of the 2024 Grad Student Appreciation Week. 3MT will also be streamed online and can be viewed at https://gatech.zoom.us/j/98696536715 .  Audience members and online viewers can vote for their favorite presenter to win the People’s Choice Award.  

Ph.D. winners can win up to $2,000 in research travel grants. The master's winner will receive a $1,000 research travel grant.   

Tech’s 3MT competition is coordinated by the Office of Graduate Education in partnership with the Center for Teaching and Learning (CTL), The Naugle Communications Center, and the Language Institute.  

For more information, visit grad.gatech.edu/3mt . 

Brittani Hill | Marketing and Communications Manager 

Office of Graduate and Postdoctoral Education 

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• The Regulatory Review In Depth

AI Providers Should Not Be Liable for Users’ Securities Violations

Jack solowey.

Policymakers are considering a liability regime that is bad economics and bad law.

If you are a policymaker looking to assert jurisdiction over a hot new sector, you might try to put deep-pocketed players on the hook for harms within your purview.

This strategy could explain a bill introduced in the U.S. Senate Banking Committee —the Financial Artificial Intelligence Risk Reduction (FAIRR) Act—that would make artificial intelligence (AI) providers liable for uses of their tools that violate securities laws, unless those providers take reasonable preventive steps.

This liability regime might be understandable given policymakers’ incentives. Nonetheless, it would produce poor public policy by clumsily assigning blame in a way that clashes with standard economic and legal frameworks for determining when producers should be liable for harms associated with the use of their products.

Ideally, liability rules would discourage violations of individuals’ rights without discouraging the productive enjoyment thereof. Economists try to strike this balance by assigning liability to the “least cost avoider”—the party for whom preventing or ameliorating rights-infringing activity is the cheapest.

It appears unlikely that AI tool providers are the least cost avoiders of securities law violations. If, for example, a registered securities firm, such as a broker-dealer, investment adviser, or investment company, uses a generic AI model, it is far likelier that the firm, not the model developer, would have an advantage in mitigating securities law risks—including through a dedicated compliance team.

It may be more tempting to view the AI provider as the least cost avoider when an individual, not a registered securities firm, uses the tool. But even when that person is no securities law expert, it is still probably cheaper for the individual to handle the legal issues than it would be for the AI provider. Paying for legal advice about a known and specific activity is usually going to be less expensive than devising a compliance program to guard against every possible permutation of securities violation.

This is not to say that policymakers cutting the Gordian knot of AI liability by putting model providers on the hook have nothing going for them. For instance, identifying a clearly liable party could present lower administrative costs for the legal system. Richard Epstein , professor at the New York University School of Law, writes of the “ twin objectives” of legal rules: “reducing administrative costs” and “setting desirable incentives.” When these aims are in tension, though, Epstein observes that the question becomes “whether the savings in administrative costs is dissipated by the creation of inferior incentive structures.”

Making AI providers liable for securities violations generally would produce inferior incentives. Tyler Cowen , economist and professor at George Mason University , argues that “placing full liability on AI providers for all their different kinds of output, and the consequences of those outputs, would probably bankrupt them.” That would reduce valuable AI innovations that benefit securities market participants .

In addition, in situations where an AI user is directly responsible for a securities violation and the AI provider merely failed to prevent that violation, it still would be likely more enticing to launch enforcement and private actions against the AI provider wherever possible, as such a provider would tend to be a higher profile target with the seeming ability to pay a large judgment or settlement. For this reason, making AI firms liable for such securities violations would perversely have those companies regularly pick up the tab for the parties clearly and directly responsible for violations.

AI provider liability for securities violations does not look any better through the lenses of the common law, such as products liability or agency law. Neither doctrine suggests universal AI provider liability for resulting harm is appropriate.

For one, in most of the United States, provider liability for faulty products only covers physical injuries to people and property, not “purely economic losses,” which would typically characterize securities violations. Moreover, important (but not uniformly applied) product liability considerations ask whether the user modified the product or used it in an abnormal fashion , either of which could forestall the provider’s liability. When a user prompts an AI tool to produce a securities violation, there is a reasonable argument that the user engaged in modification or abnormal use. At the very least, this is the type of argument that courts should consider.

Agency law reveals similar issues. The typical rule is that principals (on whose behalf agents act) are liable for acts of their agents that are within the scope of the agents’ employment. In the AI context, even if we assume that the AI provider could be the principal to the digital AI agent, there remains the question of whether the AI agent acted within the scope of “employment.” Because these questions are often litigated with mixed results , a liability regime that ignores them would clash with the time-tested subtleties of the common law.

Key principles of U.S. securities law also weigh against uniform AI provider liability. Specifically, securities laws have varying state of mind requirements. Notably, private fraud actions under the Securities Exchange Act and its implementing regulations have been interpreted by the Supreme Court to require allegations of the defendant’s “intent to deceive, manipulate, or defraud.” The FAIRR Act would circumvent such requirements by deeming the AI provider to have the relevant state of mind. Notably, a recent speech by U.S. Securities and Exchange Commission Chair Gary Gensler interpreted the FAIRR Act as proposing to impose a strict liability standard.

Undermining intent requirements not only would clash with existing law, but it would also reveal the inefficiency of placing blame with AI providers. State-of-mind requirements can, in part, codify important intuitions about whether a party was in any good position to avoid harms. For example, in asking whether harm was foreseeable, the tort law’s negligence standard essentially asks whether it would have made any sense for the defendant to act in a way that would have averted the harm. In removing, or at least downgrading, AI provider state-of-mind requirements for securities violations, the FAIRR Act would allocate liability for conduct in ways that have not previously made sense to policymakers or courts.

Grappling with liability questions in the age of AI is critical. But taking the lazy way out by blaming those building AI tools that all of us stand to benefit from is not the answer, particularly when doing so clashes with both economics and longstanding legal principles.

Jack Solowey is a Policy Analyst at the Cato Institute’s Center for Monetary and Financial Alternatives, focusing on financial technology.

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