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Identifying core topics in technology and innovation management studies: a topic model approach

• Published: 11 February 2017
• Volume 43 , pages 1291–1317, ( 2018 )

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• Hakyeon Lee 1 &
• Pilsung Kang 2  

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The study of technology and innovation management (TIM) has continued to evolve and expand with great speed over the last three decades. This research aims to identify core topics in TIM studies and explore their dynamic changes. The conventional approach, based on discrete assignments by subjective judgment with predetermined categories, cannot effectively capture latent topics from large volumes of scholarly data. Hence, this study adopts the topic model approach, which automatically discovers topics that pervade a large and unstructured collection of documents, to uncover research topics in TIM research. The 50 topics of TIM research are identified through the Latent Dirichlet Allocation model from 11,693 articles published from 1997 to 2016 in 11 TIM journals, and top 10 most popular topics in TIM research are briefly reviewed. We then explore topic trends by examining the changes in topics rankings over different time periods and identifying hot and cold topics of TIM research over the last two decades. For each of the 11 TIM journals, the areas of subspecialty and the effects of editor changes on topic portfolios are also investigated. The findings of this study are expected to provide implications for researchers, journal editors, and policy makers in the field of TIM.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by both the Ministry of Science, ICT, and Future Planning (NRF-2014R1A1A1004648, NRF-2015R1A2A2A04007359) and the Ministry of Education (NRF-2016R1D1A1A09917423, NRF-2016R1D1A1B03930729).

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Lee, H., Kang, P. Identifying core topics in technology and innovation management studies: a topic model approach. J Technol Transf 43 , 1291–1317 (2018). https://doi.org/10.1007/s10961-017-9561-4

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54 Most Interesting Technology Research Topics for 2023

May 30, 2023

Scrambling to find technology research topics for the assignment that’s due sooner than you thought? Take a scroll down these 54 interesting technology essay topics in 10 different categories, including controversial technology topics, and some example research questions for each.

Social technology research topics

Whether you have active profiles on every social media platform, you’ve taken a social media break, or you generally try to limit your engagement as much as possible, you probably understand how pervasive social technologies have become in today’s culture. Social technology will especially appeal to those looking for widely discussed, mainstream technology essay topics.

• How do viewers respond to virtual influencers vs human influencers? Is one more effective or ethical over the other?
• Across social media platforms, when and where is mob mentality most prevalent? How do the nuances of mob mentality shift depending on the platform or topic?
• Portable devices like cell phones, laptops, and tablets have certainly made daily life easier in some ways. But how have they made daily life more difficult?
• How does access to social media affect developing brains? And what about mature brains?
• Can dating apps alter how users perceive and interact with people in real life?
• Studies have proven “doomscrolling” to negatively impact mental health—could there ever be any positive impacts?

Cryptocurrency and blockchain technology research topics

Following cryptocurrency and blockchain technology has been a rollercoaster the last few years. And since Bitcoin’s conception in 2009, cryptocurrency has consistently showed up on many lists of controversial technology topics.

• Is it ethical for celebrities or influential people to promote cryptocurrencies or cryptographic assets like NFTs ?
• What are the environmental impacts of mining cryptocurrencies? Could those impacts ever change?
• How does cryptocurrency impact financial security and financial health?
• Could the privacy cryptocurrency offers ever be worth the added security risks?
• How might cryptocurrency regulations and impacts continue to evolve?
• Created to enable cryptocurrency, blockchain has since proven useful in several other industries. What new uses could blockchain have?

Artificial intelligence technology research topics

We started 2023 with M3GAN’s box office success, and now we’re fascinated (or horrified) with ChatGPT , voice cloning , and deepfakes . While people have discussed artificial intelligence for ages, recent advances have really pushed this topic to the front of our minds. Those searching for controversial technology topics should pay close attention to this one.

• OpenAI –the company behind ChatGPT–has shown commitment to safe, moderated AI tools that they hope will provide positive benefits to society. Sam Altman, their CEO, recently testified before a US Senate He described what AI makes possible and called for more regulation in the industry. But even with companies like OpenAI displaying efforts to produce safe AI and advocating for regulations, can AI ever have a purely positive impact? Are certain pitfalls unavoidable?
• In a similar vein, can AI ever actually be ethically or safely produced? Will there always be certain risks?
• How might AI tools impact society across future generations?
• Countless movies and television shows explore the idea of AI going wrong, going back all the way to 1927’s Metropolis . What has a greater impact on public perception—representations in media or industry developments? And can public perception impact industry developments and their effectiveness?

Beauty and anti-aging technology 

Throughout human history, people in many cultures have gone to extreme lengths to capture and maintain a youthful beauty. But technology has taken the pursuit of beauty and youth to another level. For those seeking technology essay topics that are both timely and timeless, this one’s a gold mine.

• With augmented reality technology, companies like Perfect allow app users to virtually try on makeup, hair color, hair accessories, and hand or wrist accessories. Could virtual try-ons lead to a somewhat less wasteful beauty industry? What downsides should we consider?
• Users of the Perfect app can also receive virtual diagnoses for skin care issues and virtually “beautify” themselves with smoothed skin, erased blemishes, whitened teeth, brightened under-eye circles, and reshaped facial structures. How could advancements in beauty and anti-aging technology affect self-perception and mental health?
• What are the best alternatives to animal testing within the beauty and anti-aging industry?
• Is anti-aging purely a cosmetic pursuit? Could anti-aging technology provide other benefits?
• Could people actually find a “cure” to aging? And could a cure to aging lead to longer lifespans?
• How might longer human lifespans affect the Earth?

Geoengineering technology research topics

An umbrella term, geoengineering refers to large-scale technologies that can alter the earth and its climate. Typically, these types of technologies aim to combat climate change. Those searching for controversial technology topics should consider looking into this one.

• What benefits can solar geoengineering provide? Can they outweigh the severe risks?
• Compare solar geoengineering methods like mirrors in space, stratospheric aerosol injection, marine cloud brightening, and other proposed methods. How have these methods evolved? How might they continue to evolve?
• Which direct air capture methods are most sustainable?
• How can technology contribute to reforestation efforts?
• What are the best uses for biochar? And how can biochar help or harm the earth?
• Out of all the carbon geoengineering methods that exist or have been proposed, which should we focus on the most?

Creative and performing arts technology topics

While tensions often arise between artists and technology, they’ve also maintained a symbiotic relationship in many ways. It’s complicated. But of course, that’s what makes it interesting. Here’s another option for those searching for timely and timeless technology essay topics.

• How has the relationship between art and technology evolved over time?
• How has technology impacted the ways people create art? And how has technology impacted the ways people engage with art?
• Technology has made creating and viewing art widely accessible. Does this increased accessibility change the value of art? And do we value physical art more than digital art?
• Does technology complement storytelling in the performing arts? Or does technology hinder storytelling in the performing arts?
• Which current issues in the creative or performing arts could potentially be solved with technology?

Cellular agriculture technology research topics

And another route for those drawn to controversial technology topics: cellular agriculture. You’ve probably heard about popular plant-based meat options from brands like Impossible and Beyond Meat . While products made with cellular agriculture also don’t require the raising and slaughtering of livestock, they are not plant-based. Cellular agriculture allows for the production of animal-sourced foods and materials made from cultured animal cells.

• Many consumers have a proven bias against plant-based meats. Will that same bias extend to cultured meat, despite cultured meat coming from actual animal cells?
• Which issues can arise from patenting genes?
• Does the animal agriculture industry provide any benefits that cellular agriculture may have trouble replicating?
• How might products made with cellular agriculture become more affordable?
• Could cellular agriculture conflict with the notion of a “ circular bioeconomy ?” And should we strive for a circular bioeconomy? Can we create a sustainable relationship between technology, capitalism, and the environment, with or without cellular agriculture?

Transportation technology research topics

For decades, we’ve expected flying cars to carry us into a techno-utopia, where everything’s shiny, digital, and easy. We’ve heard promises of super fast trains that can zap us across the country or even across the world. We’ve imagined spring breaks on the moon, jet packs, and teleportation. Who wouldn’t love the option to go anywhere, anytime, super quickly? Transportation technology is another great option for those seeking widely discussed, mainstream technology essay topics.

• Once upon a time, Lady Gaga was set to perform in space as a promotion for Virgin Galactic . While Virgin Galactic never actually launched the iconic musician/actor, soon, they hope to launch their first commercial flight full of civilians–who paid $450,000 a pop–on a 90-minute trip into the stars. And if you think that’s pricey, SpaceX launched three businessmen into space for $55 million in April, 2022 (though with meals included, this is actually a total steal). So should we be launching people into space just for fun? What are the impacts of space tourism?
• Could technology improve the way hazardous materials get transported?
• How can the 5.9 GHz Safety Band affect drivers?
• Which might be safer: self-driving cars or self-flying airplanes?
• Compare hyperloop and maglev Which is better and why?
• Can technology improve safety for cyclists?

Gaming technology topics

A recent study involving over 2000 children found links between video game play and enhanced cognitive abilities. While many different studies have found the impacts of video games to be positive or neutral, we still don’t fully understand the impact of every type of video game on every type of brain. Regardless, most people have opinions on video gaming. So this one’s for those seeking widely discussed, mainstream, and controversial technology topics.

• Are different types or genres of video games more cognitively beneficial than others? Or are certain gaming consoles more cognitively beneficial than others?
• How do the impacts of video games differ from other types of games, such as board games or puzzles?
• What ethical challenges and safety risks come with virtual reality gaming?
• How does a player perceive reality during a virtual reality game compared to during other types of video games?
• Can neurodivergent brains benefit from video games in different ways than neurotypical brains?

Medical technology 

Advancements in healthcare have the power to change and save lives. In the last ten years, countless new medical technologies have been developed, and in the next ten years, countless more will likely emerge. Always relevant and often controversial, this final technology research topic could interest anyone.

• Which ethical issues might arise from editing genes using CRISPR-Cas9 technology? And should this technology continue to be illegal in the United States?
• How has telemedicine impacted patients and the healthcare they receive?
• Can neurotechnology devices potentially affect a user’s agency, identity, privacy, and/or cognitive liberty?
• How could the use of medical 3-D printing continue to evolve?
• Are patients more likely to skip digital therapeutics than in-person therapeutic methods? And can the increased screen-time required by digital therapeutics impact mental health

What do you do next?

Now that you’ve picked from this list of technology essay topics, you can do a deep dive and immerse yourself in new ideas, new information, and new perspectives. And of course, now that these topics have motivated you to change the world, look into the best computer science schools , the top feeders to tech and Silicon Valley , the best summer programs for STEM students , and the best biomedical engineering schools .

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• Review article
• Open access
• Published: 28 August 2020

Technology-supported management education: a systematic review of antecedents of learning effectiveness

• Fabian Alexander Müller   ORCID: orcid.org/0000-0003-3071-7590 1 &
• Torsten Wulf 1  

International Journal of Educational Technology in Higher Education volume  17 , Article number:  47 ( 2020 ) Cite this article

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This paper provides a systematic, multidisciplinary review of antecedents of the effectiveness of technology-supported management learning and highlights potential directions for future research. Passive knowledge acquisition in physical classrooms is no longer the hallmark of higher education. Instead, the introduction of new technologies allows for active knowledge construction in increasingly virtual spaces. Such changes in the learning environment affect the education of the managers of tomorrow. Nevertheless, research on technology-supported management learning and its implications for management educators is fragmented and inconsistent across research areas. This paper uses a systematic approach to structure and integrate results from the fields of educational psychology, educational technology, higher education, and management education. This allows us to derive a comprehensive overview of the antecedents of the effectiveness of technology-supported management learning from the various disciplines. Our work reveals several areas that require further investigation, including: (i) the best way to blend and flip formats for different management disciplines and content types, (ii) the selection, design, and richness of the technologies used, (iii) the instructor’s teaching style, including feedback and deliberate confusion, and (iv) learners’ affective states, such as their motivations and emotions, and the role of prior knowledge.

Introduction

Technology has reshaped management education—in contrast to the traditional format of passive knowledge acquisition in synchronous and analog classrooms, much of management education now involves active knowledge construction in increasingly asynchronous and virtual learning spaces (Arbaugh, 2000c ; Garrison & Kanuka, 2004 ). The formerly prevalent objectivist model of learning assumes that there is an objective reality that can be transferred, which supports the traditional lecture format (Leidner & Jarvenpaa, 1995 ). In contrast, the constructivist model of learning posits several representations of reality, and assumes that students learn better when they construct knowledge themselves by actively engaging with and making sense of information (Arbaugh & Benbunan-Fich, 2006 ). The constructivist model is typically facilitated by technology. Sun, Tsai, Finger, Chen, and Yeh ( 2008 ) thus regard technology-supported management learning as the “paradigm of modern education.”

This technological penetration of management education has triggered a substantial amount of research into management learning beyond the traditional classroom (Arbaugh, 2014 ; Arbaugh & Duray, 2002 ; Redpath, 2012 ). Both conceptual and empirical work has been conducted in various disciplines. For instance, research has emerged in the fields of educational psychology (Leutner, 2014 ; Mayer, 2002 ; Moreno & Mayer, 2007 ; Park, Plass, & Brünken, 2014 ), educational technology (Alavi, 1994 ; Evans, 2008 ; Piccoli, Ahmad, & Ives, 2001 ; Selim, 2003 , 2007 ; Sun et al., 2008 ), higher education (Liu, 2012 ; O’Neill & Sai, 2014 ; Snowball, 2014 ; Xu & Jaggars, 2014 ), and management education (Alavi & Gallupe, 2003 ; Arbaugh & Benbunan-Fich, 2006 ; Arbaugh, DeArmond, & Rau, 2013 ). According to Arbaugh et al. ( 2009 ), “the volume and quality of research in online and blended business education has increased dramatically during the past decade.”

However, the different research areas pursue different objectives and approaches. For example, educational psychologists, on the one hand, tend to follow a learner-centered approach : They investigate how learning occurs through the human cognitive architecture and they propose technical applications to facilitate related processes. Educational technology scholars, on the other hand, take a technology-centered approach in which they suggest pushing technological innovations into the classroom while expecting learners to adapt (Mayer, 2002 ). Moreover, the extant research shows that some antecedents of technology-supported management learning have similar effects across disciplines, while others lead to contradictory outcomes. Thus, the current state of the literature is highly fragmented and partially inconsistent. No literature review that integrates findings from the various fields, much less one with a dedicated focus on management education, is available.

Therefore, this paper addresses the widespread academic discourse on technology-supported management learning by systematically investigating the antecedents of that learning. As Buttner and Black ( 2014 ) note, “no single learning theory accounts for all aspects of learning.” Thus, we contrast and integrate prevailing concepts from educational psychology and educational technology research with central themes in the management education and higher education literature. In addition, this paper enriches established theories with more recent research topics, such as confusion and emotions (D’Mello, Lehman, Pekrun, & Graesser, 2014 ; Dindar & Akbulut, 2016 ; Knoerzer, Bruenken, & Park, 2016 ).

Our paper makes two contributions. First, by conducting a systematic, interdisciplinary review of the extant literature, we integrate the dispersed knowledge on the antecedents of the effectiveness of technology-supported management learning from the various disciplines. Second, we critically reflect on conceptual and empirical findings from prior work, and we derive an agenda for future research based on the identified commonalities, inconsistencies, and research gaps. On this basis, we encourage scholars to explore different ways of blending and flipping management learning environments to identify the ideal instruction formats for the different management disciplines and content types. This includes an in-depth study of the impact of collaboration and interaction. In addition, we ask researchers to examine different technology applications and related features to more systematically and effectively select and design learning technologies. We also emphasize the importance of additional research on instructors’ teaching styles in technology-supported management education, as instructors continue to play a critical but changing role. This examination includes feedback and deliberate confusion. Moreover, we call for more research on the prior knowledge and affective states of learners, particularly regarding motivation and emotions, which are still under-researched but can be expected to play an important mediating and/or moderating role in learning outcomes.

Background on the research topic

Management education research is a subdiscipline of the business sciences. According to Arbaugh and Hwang ( 2015 ), it can be defined as “formal business and management education learning in the context of higher education in academic institutions.” Even though precursors of the Journal of Education for Business date back to 1928, today’s predominant publication outlet, the Academy of Management Learning and Education , only came into existence in 2002. The most-cited articles in this field were published during the last 20 years (Arbaugh & Hwang, 2015 ). Hence, management education is an emerging research area.

One stream of research in the management education literature investigates the importance of information technologies and attempts to bring them into the management learning space (Arbaugh, 2000b ; Arbaugh & Duray, 2002 ). Publications include narratives by instructors, examinations of learner perceptions, and experiments with different formats and technologies. Experimental conditions range from technological advances in traditional lectures (Alavi, 1994 ) to flipped environments (Lancellotti, Thomas, & Kohli, 2016 ) to full online programs (Eom, Wen, & Ashill, 2006 ). Given the limited history of the field of management education (Arbaugh & Hwang, 2015 ) and the lack of dedicated scholars of management learning and education (Arbaugh, 2016 ), the respective studies build on research from related disciplines, such as educational psychology (Mayer, 2002 ; Moreno & Mayer, 2007 ), education technology (Selim, 2007 ; Sun et al., 2008 ), and higher education (Liu, 2012 ; Snowball, 2014 ).

Educational psychology research follows a learner-centered approach (Mayer, 2002 ). It assumes that the human system for information processing remains constant in different learning environments (Mayer, 2003 ). Therefore, educational psychologists study how learning occurs in the human cognitive system, explore the cognitive processes behind selected learner characteristics, and propose technical applications to facilitate these processes. Research results indicate that cognitive and affective factors, such as learner attitude (Scheiter & Gerjets, 2007 ), motivation (Mayer, 2014 ), metacognition (Moreno & Mayer, 2007 ), and emotions (Leutner, 2014 ), as well as prior knowledge (Seufert, 2003 ) are important for learning effectiveness independent of the learning environment. These learner characteristics can partially be influenced by the instructor’s teaching style, guidance and feedback behavior (D’Mello et al., 2014 ; Mayer & Moreno, 2003 ; Park, Moreno, Seufert, & Brünken, 2011 ).

Educational technology research, on the other hand, follows a technology-centered approach , which attempts to bring technological innovations into the classroom, while learners are expected to adapt (Mayer, 2002 ). It primarily examines the role of technology characteristics based on the technology acceptance model (TAM) developed by Davis ( 1986 ) and the task-technology fit (TTF) proposed by Goodhue and Thompson ( 1995 ). Frequently analyzed factors resulting from these concepts are perceived ease of use, perceived usefulness, technology quality, technology reliability, and technology richness (Huang, 2014 ; McGill & Klobas, 2009 ; Selim, 2003 ; Song, Singleton, Hill, & Koh, 2004 ). The effects of these technology characteristics are further differentiated based on learner characteristics, such as demographics, prior experiences, and motivation (López-Pérez, Pérez-López, & Rodríguez-Ariza, 2011 ; Woo, 2014 ), instructor characteristics, such as attitude, control over the technology, and teaching style (Selim, 2007 ; Webster & Hackley, 1997 ), and format characteristics, such as flexibility, interaction, and assessment diversity (Concannon, Flynn, & Campbell, 2005 ; Sun et al., 2008 ).

Higher education research on technology-supported learning environments builds on these two approaches and examines learners’ perceptions and their engagement with different formats of instruction, i.e., different levels of technology use in higher education (Carini, Kuh, & Klein, 2006 ; Ituma, 2011 ; Zhao & Kuh, 2004 ). This includes an investigation of the opinions of learners who are in favor of or against technology-supported learning (O’Neill & Sai, 2014 ; Snowball, 2014 ). Furthermore, scholars examine the impact of different learner characteristics, such as demographics, motivation, and learning approaches (Haggis, 2009 ; Xu & Jaggars, 2014 ), format characteristics, such as flexibility and community (Reed & Reay, 2015 ; Zhao & Kuh, 2004 ), and technology characteristics, such as technology selection and quality (Kintu, Zhu, & Kagambe, 2017 ). In addition, higher education research places particular emphasis on student engagement (Carini et al., 2006 ; Ituma, 2011 ).

Across these disciplines, online activity (Asarta & Schmidt, 2013 ; Fritz, 2011 ), technology self-efficacy (Piccoli et al., 2001 ; Webster & Hackley, 1997 ), cognitive processing (Mayer, 2003 ; Mayer & Moreno, 2003 ), perceived learning (Arbaugh, 2000a ; Evans, 2008 ), test performance (Arbaugh, 2000c ; Krentler & Willis-Flurry, 2005 ), satisfaction (Concannon et al., 2005 ; Wu, Tennyson, & Hsia, 2010 ), and dropout rates (Deschacht & Goeman, 2015 ; López-Pérez et al., 2011 ) are commonly used as measures of effectiveness.

The brief overview of research activities in the fields of management education, educational psychology, educational technology, and higher education highlights that the antecedents of technology-supported management learning effectiveness can be classified into four dimensions: learner, instructor, format, and technology characteristics. These dimensions are illustrated in Fig.  1 and serve as the basis for our work.

Dimensions of Antecedents of Effectiveness of Technology-Supported Management Learning

Methodology

The search for relevant literature was carried out in three steps as illustrated in Fig.  2 . First, we identified potentially relevant publications through a database search and snowballing. Second, those publications were prioritized by skimming abstracts and full texts. Third, prioritized publications were classified according to their analytical focus.

Systematic Literature Search Process

In the first step, we conducted a keyword search for leading peer-reviewed publications to ensure the relevance and quality of potential sources. We searched the EBSCO Academic Search Premier and EBSCO Business Source Premier databases for the following journals in the educational psychology, educational technology, higher education, and management education fields: Academy of Management Learning and Education, British Journal of Educational Technology, Computers and Education, Decision Sciences Journal of Innovative Education, Educational Psychologist, Educational Psychology Review, Educational Technology Research and Development, Higher Education, Information Systems Research, Innovative Higher Education, International Journal of Management Education, Internet and Higher Education, Journal of Computer Assisted Learning, Journal of Education for Business, Journal of Educational Psychology, Journal of Educational Technology and Society, Journal of Higher Education, Journal of Management Education, Learning and Instruction, Management Learning, MIS Quarterly, Research in Higher Education, and Studies in Higher Education . We then searched the abstracts in these journals for keywords related to student learning (i.e., education, learner, learning, student), learning effectiveness (i.e., achievement, effective, effectiveness, outcome, performance, success), technology support (i.e., computer, digital, electronic, internet, multimedia, online, technology), and management (i.e., accounting, business, economics, finance, management, marketing). Literature with abstracts containing any of the following terms was excluded, as it typically does not focus on technology-supported management education: children, knowledge management, machine learning, organizational learning, school. In addition, we searched the reference lists of the identified articles to uncover any frequently cited scholars and publications that had not yet been found. We repeated this process several times. A total of 317 potentially relevant publications were identified.

In the second step, the abstracts of the identified publications were reviewed to determine whether the findings were related to this paper’s objective. Papers had to meet five criteria for inclusion in our review: investigate human learning rather than organizational learning, study learning effectiveness, go beyond the traditional lecture mode to take technology support into account, focus on higher education situations in which management is taught, and enable a transfer of findings to management education if the findings were not already related to management. If the abstracts appeared to indicate that the focal paper was insufficient for evaluation, full texts were searched. As a result, we selected 79 publications for this review.

In the third step, the selected publications were classified for a detailed review. Based on their analytical focus, the articles were assigned to one or more of the previously identified dimensions of antecedents of the effectiveness of technology-supported management learning: learner, instructor, format, and technology . The selected publications and their key findings are listed in Table  1 .

Antecedents of effectiveness of technology-supported management learning

Technology characteristics.

The integration of technologies into learning environments has been studied for about 30 years. Davis ( 1986 ) developed the first version of the technology acceptance model (TAM) to examine antecedents of a technology’s acceptance. He proposed that the capabilities of a technology trigger learners’ motivation to use it, which in turn leads to actual use. More specifically, the features of a technology are assumed to affect perceived ease of use and perceived usefulness , which then affect attitudes toward using that technology and, thus, actual use. Although this model is not explicitly tailored to learning, it has evolved as a basis for educational technology research. Several studies of technology-supported management learning show that perceived ease of use and perceived usefulness affect satisfaction but do not directly predict perceived learning (Arbaugh, 2000a , 2000b ; Huang, 2014 ). Terpend et al. ( 2014 ) find that perceived ease of use predicts technology adoption. Selim ( 2003 ) also provides evidence that perceived ease of use and usefulness predict technology acceptance, and reveals that ease of use is mostly mediated by usefulness. Sun et al. ( 2008 ) conclude that ease of use enables e-learners to focus on the content rather than the technology.

Goodhue and Thompson ( 1995 ) introduce task-technology fit (TTF) and argue that “for an information technology to have a positive impact on individual performance, the technology must be utilized and must be a good fit with the tasks it supports.” Related antecedents of technology-supported management learning effectiveness that are frequently analyzed include technology quality and technology reliability . In an early experiment with synchronous technology-supported distance learning based on online lectures and videos, Webster and Hackley ( 1997 ) find that both variables influence attitude toward the format and the technology, and that technology quality also influences the relative advantage of the format (i.e., perceived learning). They argue that reliable, efficient, and effective technology interfaces promote learner motivation, while technical complications have the opposite effect. However, they do not find relationships with involvement and participation, cognitive engagement, technology-self-efficacy, or usefulness of the technology. Song et al. ( 2004 ) confirm that technical problems are perceived as disadvantages for online learning. Sun et al. ( 2008 ) examine technology and internet quality in e-learning but find no effects on the satisfaction of management students. Notably, internet quality may be taken for granted. McGill and Klobas ( 2009 ) examine the role of learning management systems and provide empirical evidence that TTF strongly influences perceived learning and weakly affects actual learning. They also show an indirect relationship between TTF and perceived learning through learners’ attitudes toward technology utilization and actual use. Interestingly, they also reveal an effect of TTF on the expected consequences of technology use, although this does not affect actual usage.

Webster and Hackley ( 1997 ) note that technology richness has a positive impact on involvement and participation, cognitive engagement, technology self-efficacy, perceived usefulness, attitudes toward technology and format, and perceived learning. They argue that technology richness supports the accessibility of instructors and their feedback, which moderates learner motivation, thereby predicting technology use and perceived learning. Yourstone et al. ( 2008 ) state that immediate feedback technologies, such as clickers, can have a positive impact on learning outcomes. Work by Snowball ( 2014 ) confirms that passive online activities, such as videos, can be useful for introducing new concepts, while more active components, such as quizzes, are more beneficial for learning. Sloan and Lewis ( 2014 ) suggest that lecture-capture videos are related to higher exam scores. Kember et al. ( 2010 ) find that technological features that promote constructive dialogue and interactive learning improve understanding. Volery and Lord ( 2000 ) and Wu et al. ( 2010 ) note that the design and functionality of a learning management system predict perceived learning. Arbaugh and Rau ( 2007 ) investigate online learning with different systems and, interestingly, find a negative relationship between technology variety and perceived learning but a positive relationship between technology variety and satisfaction. In addition, Huang ( 2014 ) identifies a positive relationship between technology playfulness and satisfaction in a mobile learning environment. He finds that learners’ self-management skills moderate the effects of usefulness and playfulness on satisfaction. These technology-related antecedents of the effectiveness of technology-supported management learning are summarized in Fig.  3 .

Technology-Related Antecedents

Format characteristics

While the format of instruction has traditionally been based on the physical classroom, the advent of technologies in management education allows for the emergence of new settings. Higher education research proposes a blended learning environment that is independent from the technology employed. According to Garrison and Kanuka ( 2004 ), this format is an “integration of face-to-face and online learning experiences – not a layering of one on top of the other.” López-Pérez et al. ( 2011 ) show that blended environments that combine face-to-face classes with online activities (e.g., crosswords, matching, fill in the blank, multiple-choice tests, wikis, forums) reduce dropout rates and improve exam performance. In line with TAM, they show that the perceived utility of online learning is correlated with the motivation generated by the technology, which in turn predicts satisfaction. However, they find that actual learning mainly depends on variables unrelated to blended environments, such as learners’ age, class attendance, or prior experiences—perceived utility and satisfaction do not predict actual learning. Notably, according to Grabe and Christopherson ( 2008 ), a lack of class attendance may be offset through online resources. Deschacht and Goeman ( 2015 ) find better exam performance for blended environments that integrate self-study, online collaboration, and classroom teaching. However, they also find that these environments are associated with higher dropout rates. They argue that the learning effect may be subject to survivorship bias. McLaren ( 2004 ) demonstrates that persistence in online delivery is significantly lower, while learning performance is independent of the format.

Although blended learning environments capture the benefits of technological innovations, such as flexibility in terms of time and place and learner control over pace and content, they also capture the benefits of physical classrooms (i.e., personal interaction through collaboration and community) (Arbaugh, 2014 ; Concannon et al., 2005 ). Educational technology research has found that course flexibility leads to e-learning satisfaction (Arbaugh, 2000b ; Sun et al., 2008 ). The rationale is that flexibility allows learners to balance their personal commitments, such as work, family, and other activities, with their studies. Higher education research suggests that learner independence is crucial for building critical thinking skills (Garrison & Kanuka, 2004 ). Educational psychology research emphasizes that learner control over materials can have a positive impact on cognitive processing due to the possibility of pacing (Mayer et al., 2003 ; Moreno & Mayer, 2007 ). Pacing refers to a flexible presentation speed that encompasses pause, rewind, and fast-forward options. While pausing allows learners to restrict cognitive processing at a certain point of time, rewinding can intensify cognitive processing because the learner repeatedly receives the same information. The fast-forward option allows for certain sections to be skipped so that learners end up with shorter sections, which also benefit cognitive processing. The presentation of information in separate parts gives learners the opportunity to gradually build multiple mental representations that can be integrated later (Mayer & Chandler, 2001 ). Scheiter and Gerjets ( 2007 ) note that learner control in multimedia environments stimulates interest and motivation and, thereby, triggers more active and constructive processing. While Arbaugh and Duray ( 2002 ) show positive relationships between flexibility and both perceived learning and satisfaction in web-based environments, Arbaugh ( 2000a ) finds no direct relationship between flexibility and perceived learning.

In blended learning environments, the flexibility of online learning is integrated with the preeminent characteristic of classroom teaching: interaction . Alavi ( 1994 ) finds that technology-supported learner collaboration and the associated interaction lead to greater satisfaction, self-reported learning, and enhanced exam performance. Collaboration can empower the structuring and sharing of information, leading to exposure to different views and opinions. This requires reiterating prior information when explaining knowledge to others, resolving opposing perspectives through discussions, and internalizing explanations from more knowledgeable peers. Eventually, this leads to more active knowledge processing and construction (Kreijns et al., 2013 ).

Eid and Al-Jabri ( 2016 ) provide evidence that online discussions and chats promote the exchange of knowledge that predicts perceived learning. Furthermore, networking via discussion forums leads to better performance (Walker et al., 2013 ). Arbaugh ( 2000a ) also finds connections between perceived learning and interaction ease, interaction emphasis, and classroom dynamics. Arbaugh and Benbunan-Fich ( 2006 ) investigate online learning among 579 MBA students and find that group learning leads to higher perceived learning and satisfaction than individual learning. While group learning is moderated by an objectivist teaching approach, individual learning is moderated by constructivist instruction. Song et al. ( 2004 ) find that a perceived lack of community is detrimental to perceived online learning. In contrast, Eom et al. ( 2006 ) state that distance interactions lead to an adaptation of information that assists learners in overcoming feelings of remoteness. They find that interaction predicts satisfaction with online learning, which in turn fosters perceived learning. However, they do not find a direct link between interaction and perceived learning. Concannon et al. ( 2005 ) also find that interaction affects the satisfaction of e-learners, while Sun et al. ( 2008 ) find no relationship. Eom and Ashill ( 2018 ) find direct relationships between both learner-learner and learner-instructor interaction and perceived online learning. They also show that peer interactions in e-learning are beneficial for the self-regulation that predicts perceived learning. Perceived learning, in turn, causes satisfaction (Wu et al., 2010 ). Hazari et al. ( 2013 ) suggest that peer interactions via blogs lead to constructive feedback and self-assessments. On the other hand, Arbaugh and Rau ( 2007 ) find that peer interaction in online courses can negatively influence satisfaction, while it can positively affect perceived learning. Wu et al. ( 2010 ) reveal that the learning climate in a blended environment mediates the effect of interaction on satisfaction. According to Solimeno et al. ( 2008 ), online interaction can be even more beneficial for learning than personal interaction, as the former overcomes much of the interpersonal noise.

A variant of blended environments is flipped learning . According to higher education research, there is no single approach to flipped learning. However, the most important aspects include the provision of content in advance and higher-order learning during face time (O’Flaherty & Phillips, 2015 ). Therefore, introductions, explanations, and theories are studied individually and asynchronously at each student’s own pace, typically facilitated by a learning management system, while application and transfer problems are handled during class time. Solimeno et al. ( 2008 ) emphasize the benefits of asynchronous preparation, including flexibility in consulting materials and reviewing online comments from peers. Such a shift in the individual workload from reworking to preparing fosters ownership before class and enables deeper discussions in class that can be initiated by the learners themselves (O’Flaherty & Phillips, 2015 ). Flipped learning also supports the pretraining effect proposed in educational psychology research (Moreno & Mayer, 2007 ). The aim in this regard is to provide learners with relevant prior knowledge or to reactivate it if it is already available. This prepares the human memory with selected knowledge, which can later be integrated with new information. Consequently, pretraining facilitates meaning making and improves cognitive processing (Moreno & Mayer, 2007 ).

Educational technology research finds that assessment diversity in online environments increases satisfaction, as it enables multiple forms of feedback (Sun et al., 2008 ). Concannon et al. ( 2005 ) suggest that the use of some online tests during a semester reshapes study patterns by triggering continuous review and feedback. These format-related antecedents of the effectiveness of technology-supported management learning are outlined in Fig.  4 .

Format-Related Antecedents

Instructor characteristics

Instructors play a central role in any learning environment (Webster & Hackley, 1997 ). This role remains important in technology-supported management education, but it is changing (Daspit & D’Souza, 2012 ; Volery & Lord, 2000 ). Therefore, examinations of instructor characteristics should consider not only the personalities of instructors but also their roles, particularly with regard to learner-instructor interactions.

Research on instructors’ personality in technology-supported environments mainly focuses on instructors’ attitudes toward and control over the technology. Webster and Hackley ( 1997 ) find that the instructor’s attitude toward the technology affects learners’ attitudes toward the format and technology, technology self-efficacy, and perceived learning. In turn, learners’ technology self-efficacy predicts perceived learning (Wu et al., 2010 ). However, they find no relationship between the instructor’s attitude toward the technology and learners’ involvement and participation, cognitive engagement, or perceived usefulness of the technology. Concannon et al. ( 2005 ) find a positive relationship between the instructor’s attitude toward the technology and e-learners’ motivation to use that technology. López-Pérez et al. ( 2011 ) show that learner motivation influences actual learning in both the physical and virtual elements of blended environments. In addition, Sun et al. ( 2008 ) show a positive effect of the instructor’s attitude on the satisfaction of e-learners. They also emphasize the importance of the instructor’s technical competence.

Webster and Hackley ( 1997 ) demonstrate that the instructor’s control over the technology has a positive impact on learners’ attitudes toward a technology, its perceived usefulness, cognitive engagement, and perceived learning. However, they do not find relationships with involvement and participation or technology self-efficacy. Selim ( 2007 ) confirms that both attitudes toward and control over the technology affect business students’ e-learning satisfaction.

While the purpose of a traditional lecture is to deliver knowledge, instructors in a technology-supported environment should support active learning as facilitators and mentors (Solimeno et al., 2008 ). Markel ( 1999 ) proposes a change from “a sage on the stage into a guide on the side,” while Volery and Lord ( 2000 ) expect the role of the instructor to shift toward being “a learning catalyst and knowledge navigator.” Webster and Hackley ( 1997 ) find that such an interactive teaching style has a positive impact on learners’ involvement and participation, cognitive engagement, and attitudes toward format and technology. They find no relationships between an interactive teaching style and the perceived usefulness of the technology, technology self-efficacy, or perceived learning. However, Arbaugh ( 2000a ) shows that efforts to create an interactive online environment predict perceived learning, and that the emphasis on interaction is directly related to satisfaction (Arbaugh, 2000b ). Selim ( 2007 ) also shows that instructor characteristics, including the teaching style, influence business students’ satisfaction with e-learning.

Interactions between learners and instructors comprise both guidance (i.e., process input) and feedback (i.e., essential input) (Moreno & Mayer, 2007 ). On the one hand, process-related input promotes learners’ engagement in the right activities, especially the selection, organization, and integration of relevant information that strengthens relevant cognitive processing (Mayer & Moreno, 2003 ). On the other hand, essential input reduces learners’ extraneous cognitive processing by replacing misconceptions in the human memory (Moreno & Mayer, 2007 ). Extraneous processing refers to cognitive processes that are irrelevant for making sense of information and, thus, should be minimized. However, feedback must be well designed to avoid additional extraneous processing. For technology-supported environments, Demetriadis et al. ( 2008 ) suggest that scaffolding , a technique of appropriate questioning, can trigger learner reflection and deeper processing. They find that scaffolding leads to more knowledge acquisition and knowledge transfer. Moreno and Mayer ( 2007 ) confirm that reflection on prior information leads to more active organization and integration of new information. According to Eom et al. ( 2006 ), both guidance and feedback increase learner satisfaction, but only feedback improves perceived learning in an online environment. Hwang and Arbaugh ( 2006 ) show that feedback does not influence actual learning in blended environments. However, if the search for feedback is triggered by a competitive attitude (i.e., getting ahead of others or preventing others from getting ahead of oneself), it has a positive impact on actual learning. Sun et al. ( 2008 ) show that the timeliness of an instructor’s response has no influence on satisfaction with e-learning.

Instructor feedback in technology-supported environments has also been studied in connection with learners’ prior knowledge. Seufert ( 2003 ) finds that feedback in a computer-based learning task barely affects learners with a high level of prior knowledge. However, it positively moderates the comprehension of learners with intermediate prior knowledge, presumably due to its summarizing and repetitive nature. At the same time, feedback negatively moderates the recall performance of learners with little prior knowledge. Interestingly, in a computer-based simulation, Nihalani et al. ( 2011 ) find that learners with low prior knowledge learn better with the support of the instructor than in cooperation with other beginners and that feedback is disadvantageous for learners with high levels of prior knowledge.

As a variant of feedback, educational psychology scholars study confusion in online environments, which is defined as “the result of contradictions, conflicts, anomalies, erroneous information, and other discrepant events” (Park et al., 2014 ). They propose that when confusion is “induced, regulated, and resolved appropriately,” it can positively influence learning. D’Mello et al. ( 2014 ) find that knowledge and transfer are higher when confusion is deliberately triggered and successfully resolved. Learners’ prior knowledge has small moderation effects. Confusion is assumed to lead to deeper engagement with new information, thereby improving learning (Leutner, 2014 ).

Although feedback embodies interaction between instructors and learners, the physical presence of the instructor is not essential for improving cognitive processing (Redpath, 2012 ). Personal interaction can occur through a collaborative online environment or personalized online communication (Arbaugh, 2000c ). Mayer ( 2002 ) proposes the personalization principle, which posits more effective processing for a conversational communication style in learning materials than for a formal communication style. This increases learners’ attention and encourages them to refer content to themselves (Moreno, 2006 ). In addition, Beege et al. ( 2017 ) find that frontal, as opposed to lateral, instructor orientation in learning videos promotes retention, as para-social interactions can trigger deeper cognitive processing and beneficial affective states. The lack of body language in online settings can be addressed through the use of humor, anecdotes, or emoticons (Whitaker, New, & Ireland, 2016 ). Guo et al. ( 2014 ) find that instructors who speak faster and with more enthusiasm in learning videos increase learner engagement. These instructor-related antecedents of technology-supported management learning effectiveness are illustrated in Fig.  5 .

Instructor-Related Antecedents

Learner characteristics

The learners themselves play an important role in the effectiveness of technology-supported management learning. Educational technology research initially examined the demographic background and prior experience of learners in technology-supported formats. While it is unclear whether gender predicts perceived learning in an online environment (Arbaugh, 2000a , 2008 ; Volery & Lord, 2000 ), both Arbaugh ( 2000b ) and Arbaugh ( 2008 ) find that gender does not influence satisfaction. Furthermore, Lancellotti et al. ( 2016 ) find no connection between gender and actual learning. Age does not influence perceived e-learning (Arbaugh, 2000a ), but it positively predicts actual learning in the physical and virtual settings of a blended environment (López-Pérez et al., 2011 ).

Prior technological experience also influences actual online learning (López-Pérez et al., 2011 ), while its relationships with perceived learning and satisfaction are not always significant (Arbaugh, 2000a , 2008 ; Arbaugh & Rau, 2007 ; Selim, 2007 ; Song et al., 2004 ; Volery & Lord, 2000 ). Piccoli et al. ( 2001 ) examine 146 management students and posit that previous technology experience can be beneficial, while a lack of such experience can promote feelings of anxiety and isolation. Sun et al. ( 2008 ) find that computer anxiety has a negative impact on satisfaction with e-learning, as it can hamper a learner’s attitude, which is essential for technology-supported learning (Scheiter & Gerjets, 2007 ). Solimeno et al. ( 2008 ) show that technology promotes perceived and actual learning among learners with low computer anxiety.

In addition to previous technological experience, research has examined the role of prior academic achievements . Nemanich et al. ( 2009 ) and Palocsay and Stevens ( 2008 ) find that learners’ academic abilities are associated with learning outcomes, particularly in online environments. Scheiter and Gerjets ( 2007 ) assume that a high level of prior knowledge moderates learning in multimedia environments. Asarta and Schmidt ( 2017 ) show that blended formats have a positive influence on exam performance for learners with high prior performance, while weaker students perform better in traditional formats. Owston et al. ( 2013 ) find that high achievers show the highest satisfaction with blended learning environments because they view blended learning as more convenient and engaging, and they feel that they learn key concepts better than in traditional classes.

Educational psychology scholars have considered affective aspects, such as learner motivation and emotions (Park et al., 2014 ). Motivation is defined as an “internal state that initiates, maintains, and energizes the learner’s effort to engage in learning processes” (Mayer, 2014 ). The corresponding work is based on the assumption that motivational factors can mediate learning by increasing or decreasing cognitive engagement (Moreno & Mayer, 2007 ). Selim ( 2007 ) shows that motivation affects e-learning acceptance and satisfaction. According to Song et al. ( 2004 ), e-learners expect their motivation to be related to learning. López-Pérez et al. ( 2011 ) find that motivation predicts actual learning in both the physical and virtual settings of a blended environment. Woo ( 2014 ) confirms the correlation between motivation and actual online learning. Eom et al. ( 2006 ) also find that motivation in an online environment affects satisfaction, although they do not find a direct link to perceived learning.

Plass et al. ( 2014 ) and Um et al. ( 2012 ) investigate emotions induced by videos in online learning, and find that positive emotions can promote comprehension and transfer. Their findings suggest that round, face-like shapes and warm colors reinforce the positive emotions that not only reduce the perceived difficulty of the task but also increase motivation and cognitive processing. This effect of emotions on performance can be mediated by motivation and/or moderated by prior knowledge (Leutner, 2014 ). In contrast, Knoerzer et al. ( 2016 ) find that positive emotions induced through music and autobiographic recall reduce actual online learning, possibly because they distract learners from the focal material. However, they find that negative emotions increase learning, possibly due to a perceived need for deeper information processing. They find no connection between emotions and motivation.

Educational psychology research on multimedia learning further posits that “metacognitive factors mediate learning by regulating cognitive processing and affect” (Moreno & Mayer, 2007 ). Metacognition mainly occurs in the form of self-regulation and reflection during the organization and integration of new information. Moreno and Mayer ( 2007 ) find that reflection is beneficial for cognitive processing, which leads to better learning outcomes. Eom and Ashill ( 2018 ) show that self-regulation in an e-learning environment mediates the relationship between motivation and perceived learning, which is related to satisfaction. Metacognition seems to be particularly important for non-interactive (i.e., distance) phases in which it is not triggered by interactions. However, metacognition is also important in an interactive setting if “the lesson can be performed in a superficial or automatic fashion” (Moreno & Mayer, 2007 ).

According to Fryer and Bovee ( 2016 ), “although a variety of factors influence learning, few are as important as time on task.” Macfadyen and Dawson ( 2010 ) distinguish between online activity and time online, noting that online activity (i.e., written posts, sent messages, completed assessments) indicates learner engagement and predicts actual outcomes, while time online does not. Fritz ( 2011 ) also shows that higher activity in the learning management system affects actual learning, while Asarta and Schmidt ( 2013 ) as well as Buttner and Black ( 2014 ) find no correlation between time online and learning. Based on learning analytics, Zacharis ( 2015 ) finds that four online activities predict 52% of the variance in the final grade: number of files viewed, reading and posting messages, content creation contribution, and quiz efforts. These learner-related antecedents of technology-supported management education are illustrated in Fig.  6 .

Learner-Related Antecedents

In this paper, we have presented a systematic and comprehensive review of peer-reviewed, scientific publications from several research disciplines related to the effectiveness of technology-supported management learning. Although our search for literature was not limited to a specific timeframe, the current relevance of the topic is evident from the identified publications. Research on this topic began to emerge in the 1990s and it has since flourished. With regard to the field of management education, the most cited articles were published in the current millennium (Arbaugh & Hwang, 2015 ). We found that the antecedents of technology-supported management learning effectiveness include more than technological characteristics and learners’ abilities to deal with them. More specifically, the introduction of technologies into the management learning space has implications for formats, instructors, and learner characteristics, all of which are highly interdependent. The desired format of instruction, for example, which is chosen by the instructor, determines the appropriate technology and the role of the instructor. Characteristics of the selected technology, such as quality, reliability, and richness, and characteristics of the instructor, such as attitude, control, and teaching style, impact learners’ perceptions, metacognition, and affect. These relationships are, in turn, moderated by learners’ demographic characteristics and previous experiences. Eventually, all four dimensions—learner, instructor, format, and technology—directly or indirectly influence technology-supported learning effectiveness. These findings are independent from the measurement of effectiveness (i.e., online activity, cognitive processing, perceived learning, satisfaction, actual results, or dropout rates).

These antecedents of technology-supported management learning effectiveness are summarized in Fig.  7 . The subsequent section derives detailed implications for future research based on the identified inconsistencies and interdependencies.

Integrated Perspective on Antecedents of Technology-Supported Management Learning Effectiveness

Implications for future research

In investigating antecedents of technology-supported management learning effectiveness, we have identified several inconsistencies and research gaps in the extant literature. We encourage management education scholars to study these issues in order to develop additional insights into technology-supported management learning. Such research will advance the young field of management education and make a positive contribution to overall management research and education. In Table  2 , we highlight aspects that provide opportunities for further research.

As far as the overall effectiveness of technology-supported formats is concerned, research has produced a number of inconsistent results. For instance, there is disagreement about the impact of blended environments on dropout rates (Deschacht & Goeman, 2015 ; López-Pérez et al., 2011 ). Moreover, whether the use of technology is beneficial for learning remains unclear. Twenty years ago, Arbaugh ( 2000a ) found that the format of instruction is more important than the specific technology employed. To date, theoretical concepts on how to blend and flip learning content in relation to subject areas and content types are still lacking (O’Flaherty & Phillips, 2015 ). Although there might not be a “one-size-fits-all” approach, it is possible to examine which course structures and format features, such as collaboration and interaction, are more appropriate for certain types of content. Due to the wide variety of management disciplines, scholars in management education are predestined to investigate different variants of blended and flipped learning (Arbaugh & Rau, 2007 ). Such studies can reveal connections among content type, optimal course format, and technology use.

Another key question is why learners continue to prefer face-to-face classes to online courses (O’Neill & Sai, 2014 ) even though they regularly use electronic devices and increasingly strive for individualism and flexibility. As technologies are likely to continue to play a central role in society, different learning formats should be studied in relation to specific technologies and their richness of features. Such studies can further investigate whether the use of technology actually equalizes learners’ performance (Krentler & Willis-Flurry, 2005 ). Moreover, Piccoli et al. ( 2001 ) argue that the investigation of new formats and technologies for management education requires an examination of optimal class sizes. They argue for an inverted U-shape relationship between class size and learning effectiveness, as the presence of more learners increases perspectives until a point is reached at which information overload and coordination difficulties outweigh the benefits of additional learners. However, this requires further examination.

Scholars agree that instructors play an important role in technology-supported management education, but how their role will change remains unclear (Arbaugh, 2000a ; Volery & Lord, 2000 ). Some suggest a shift from “a sage on the stage into a guide on the side” (Markel, 1999 ), which implies a shift from an objectivist to a constructivist teaching approach. Nevertheless, collaborative management learning in a technology-supported environment seems to be moderated by an objectivist teaching approach (Arbaugh & Benbunan-Fich, 2006 ), which contradicts the plea for an interactive teaching style (Selim, 2007 ; Webster & Hackley, 1997 ). Furthermore, findings on the role and effects of feedback are inconsistent, particularly with regard to the moderating role of learners’ prior knowledge (Nihalani et al., 2011 ; Seufert, 2003 ). Deliberate confusion, a variant of feedback, has also been under-researched, and there are some indications that learners’ prior knowledge could play a moderating role (D’Mello et al., 2014 ; Leutner, 2014 ). Therefore, the design and impact of teaching style and instructor feedback on cognitive processing and actual learning should be further investigated, especially with regard to potential moderating variables, such as learners’ prior knowledge.

Since Moreno and Mayer ( 2007 ) proposed a cognitive-affective theory of learning with media , it has become clear that learning also depends on affective aspects, such as motivation and emotions. Although the related antecedents have not yet been fully researched, initial results suggest that the design of multimedia materials and interfaces should take into account features that trigger motivation and emotion (Mayer, 2014 ). However, while Plass et al. ( 2014 ) and Um et al. ( 2012 ) find that positive emotions can strengthen comprehension and transfer, Knoerzer et al. ( 2016 ) come to the opposite conclusion when they induce emotions in a different way. Another unresolved aspect of inducing emotions is whether the instructor should be shown speaking in educational videos. While this can create a positive sense of personalization, it may also increase the extraneous load (Kizilcec et al., 2015 ; Mayer, 2003 ). Furthermore, Leutner ( 2014 ) suggests that the effect of emotions on learning might be mediated by motivation or moderated by prior knowledge. As such, the interdependence and effects of motivation and emotions on cognitive processing and actual learning deserve further investigation. In addition, potentially moderating variables, such as learners’ prior knowledge, should be investigated.

Limitations

Although this review followed a systematic procedure, it has some limitations that can be attributed to either our methodology or our research focus. With regard to our methodology, the literature-identification process revealed that numerous publications from a variety of research areas have examined technology-supported learning. Although we have tried to systematically identify all major publications investigating this issue that are relevant for the management context, we cannot guarantee that our results are exhaustive. Furthermore, although we broadened our scope to include publications beyond management education research, we deliberately limited our search to educational psychology, educational technology, and higher education research. These three disciplines appeared to be the most promising during an initial interdisciplinary skimming of the literature. However, we cannot exclude the possibility that relevant research may have been conducted in other disciplines. Moreover, given the interdisciplinary nature of the sources, our literature prioritization and classification revealed that some results were more general in nature, while others were developed explicitly from management education research. In our search in the field of educational technology, we tried to limit our findings to those that came from a management context. Nevertheless, this paper also includes findings from other disciplines when they appeared to be transferable to the management environment. Decisions regarding this transferability were made by the authors.

In terms of the research focus, management is a broad field covering various sub-disciplines, including accounting, economics, finance, marketing, and strategy. Some of these fields are comparable in terms of concepts and terminologies, while others are not. Some fields are rather qualitative, and others are strongly quantitative. In addition, the spectrum of management learners ranges from freshmen in undergraduate programs to highly senior MBA students participating in executive programs. Similarly, the use of technologies in education covers a broad field ranging from traditional classroom teaching sporadically facilitated using electronic devices to programs taught fully online. As our objective was to examine antecedents of management learning in a technology-supported environment as a whole, we did not restrict the learning environment in terms of the technologies employed.

Concluding remarks

This paper has shown that educational technologies are quickly becoming an integral part of management education, both in theory and in practice. Although we have identified a number of research gaps and ideas for further research, educational authorities, institutions, and practitioners should not wait for additional research to be completed. Passive knowledge transfer in synchronous, analogue classroom sessions can no longer be viewed as the most effective educational format. In addition, there are already some indications of what constitutes effective technology-supported management education. In the meantime, researchers from different disciplines should pursue investigations of technology-supported settings in relation to management education and beyond.

Availability of data and materials

Not applicable.

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Top 400 Information Technology Research Topics – Full Guide!

The field of IT is progressive and ever-changing due to the rapid development of hardware, software, and networking technologies. The demand for innovative research in IT has also continued to rise as businesses and organizations embrace digital systems and data-driven solutions. 

Understanding the salient areas of study in IT will help professionals keep up with changes that arise and enable organizations to leverage emerging technologies effectively. 

Cybersecurity, artificial intelligence, cloud computing , and big data analytics have emerged through IT research. These fundamental factors shape the modern technology landscape, giving rise to immense possibilities for boosting productivity, raising efficiency, and improving competitiveness across sectors. 

However, companies wanting to navigate the complexities of today’s digital age and exploit new technological advances must examine some of the latest IT research topics.

Understanding Information Technology Research

Table of Contents

In the world of technology, research is a compass that helps us navigate its convoluted evolutions. For instance, Information Technology (IT) research has been conducted in computer science, software engineering, data analytics, and cybersecurity.

IT research involves systematic inquiry to advance knowledge, problem-solving, and innovation. This includes conducting rigorous experiments and analyzing results to unveil new theories or approaches that improve technologies or bring breakthroughs.

Therefore, interdisciplinarity is at the core of IT research, with collaboration cutting across various disciplines. Whether using AI to reinforce cyber security or big data analytics in healthcare, collaboration leads to solutions to complex problems.

This is because IT research is changing rapidly due to technological advances. Thus, researchers need to be up-to-date to make meaningful contributions.

Ethics are involved so that technology can be responsibly deployed. The researchers grapple with privacy, security, bias, and equity issues to ensure technology benefits society.

As a result of this publication and conferences, which enable dissemination of findings, leading to further innovations, collaboration has supported progress, hence speeding it up.

Understanding IT research is vital for leveraging technology to address societal challenges and foster positive change.

Recommended Readings: “ Top 109+ Media Bias Research Topics | Full Guide! “.

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Choosing a research topic that generates fresh ideas and practical applications is crucial. Your findings should not just add to school talks but also lead to real solutions that can be used in real situations, pushing technology forward and making work smoother.

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Finding Gaps and Unexplored Areas

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By carefully choosing the right research topic, you can open the door to discoveries, push technology forward, and contribute to the constant evolution of the technology information landscape.

Top 400 Information Technology Research Topics

The list of the top 400 information technology research topics is organized into different categories. Let’s examine it. 

Artificial Intelligence (AI) and Machine Learning (ML)

• Easy AI: Explaining and Using
• Group Learning: Getting Better Together
• AI in Health: Diagnosing and Helping
• Robots Learning on Their Own
• Being Fair with Computers
• Talking to Computers in Normal Language
• AI Fighting Bad Guys on the Internet
• AI Driving Cars: How Safe Is It?
• Sharing What We’ve Learned with Other Machines
• AI in Schools: Computers Learning About You

Cybersecurity and Encryption

• Trusting Computers: How to Stay Safe
• Keeping Secrets Safe with Fancy Math
• Secret Codes Computers Use: Safe or Not?
• Spy Games: Watching Out for Bad Stuff
• Keeping Secrets, Even from Friends
• Your Body as Your Password: Is It Safe?
• Fighting Against Computer Ransomers
• Keeping Your Secrets Secret, Even When Sharing
• Making Sure Your Smart Stuff Isn’t Spying on You
• Insuring Against Computer Bad Luck

Data Science and Big Data

• Sharing Secrets: How to Be Safe
• Watching the World in Real-Time
• Big Data: Big Computers Handling Big Jobs
• Making Data Pretty to Look At
• Cleaning Up Messy Data
• Predicting the Future with Numbers
• Finding Patterns in Connected Dots
• Keeping Your Secrets Safe in Big Data
• Sharing Our Secrets Without Telling Anyone
• Helping the Planet with Numbers

Cloud Computing

• Computers Without a Home: Where Do They Live?
• Keeping Computers Close to Home
• Moving Our Stuff to New Homes
• Juggling Many Clouds at Once
• Making Computers That Live in the Cloud
• Keeping Clouds Safe from Bad Guys
• Keeping Clouds Safe from Sneaky Spies
• Making Sure Clouds Do What They’re Supposed To
• Computers Need Energy Too!
• Making the Internet of Things Even Smarter

Internet of Things (IoT)

• Smart Stuff Everywhere: How Does It Work?
• Watching Out for Bad Stuff in Smart Things
• Smart Stuff: Is It Safe?
• Taking Care of Smart Toys
• Making Smart Things That Don’t Need Batteries
• Making Smart Factories Even Smarter
• Smart Cities: Making Cities Better Places to Live
• Your Clothes Can Be Smart, Too!
• Helping Farmers with Smart Farming
• Keeping Secrets Safe in Smart Stuff

Human-Computer Interaction (HCI)

• Magic Glasses: How Do They Work?
• Making Computers Easy to Use
• Making Computers for Everyone
• Talking to Computers with Your Hands
• Making Sure Computers Are Nice to People
• Talking to Computers with Your Voice
• Playing with Computers, You Can Touch
• Trusting Computers to Drive for Us
• Computers That Understand Different People
• Making Computers That Read Our Minds

Software Engineering

• Making Computers Work Together Smoothly
• Building Computers from Tiny Pieces
• Playing Games to Make Computers Better
• Making Sure Computers Work Right
• Making Old Computers New Again
• Making Computers Like to Exercise
• Making Computers Easier to Understand
• Building Computers with Blueprints
• Making Sure Computers Don’t Get Sick
• Sharing Computer Secrets with Everyone

Mobile Computing

• Keeping Phones Safe from Bad Guys
• Making Apps for Every Kind of Phone
• Keeping Phones Safe in the Cloud
• Finding Your Way with Your Phone
• Paying with Your Phone: Safe or Not?
• Checking Your Health with Your Phone
• Seeing the World Through Your Phone
• Wearing Your Phone on Your Wrist
• Learning on the Go with Your Phone
• Making Phones Even Smarter with Clouds

Networking and Communications

• Making Sure Computers Can Talk to Each Other
• Making Computers Work Together Without Wires
• Making the Internet Faster for Everyone
• Getting More Internet Addresses for More Computers
• Cutting the Internet into Pieces
• Making the Internet Even More Invisible
• Talking to Computers with Light
• Making Sure Tiny Computers Talk to Each Other
• Sending Messages Even When It’s Hard
• Making the Radio Smarter for Computers

Bioinformatics and Computational Biology

• Reading Your DNA with Computers
• Making Medicine Just for You
• Meeting the Microscopic World with Computers
• Building Computer Models of Living Things
• Finding New Medicine with Computers
• Building Computer Models of Tiny Machines
• Making Family Trees for Living Things
• Counting Germs with Computers
• Making Big Lists of Living Things
• Making Computers Think Like Brains

Quantum Computing

• Making Computers Better at Some Math Problems
• Keeping Computers Safe from Small Mistakes
• Making Computers Even Harder to Spy On
• Making Computers Learn Faster with Quantum Tricks
• Making Fake Worlds for Computers to Explore
• Building Computers from Super-Cold Stuff
• Making Computers Cold to Think Better
• Making Computers Think Like Chemists
• Making the Internet Even Safer with Computers
• Showing Off What Computers Can Do Best

Green Computing

• Saving Energy with Computers
• Using Wind and Sun to Power Computers
• Making Phones Last Longer Without Plugging In
• Making Computers Kinder to the Planet
• Recycling Old Computers to Save the Earth
• Computers That Care About Their Trash
• Saving Energy in Big Rooms Full of Computers
• Making Computers Save Energy and Work Faster
• Counting the Trash from Computers
• Making Computers Kinder to the Planet’s Air

Information Systems

• Making Computers Work Together in Big Companies
• Making Computers Remember Their Friends
• Making Computers Share What They Know
• Making Computers Smart About Money
• Making Computers Send Presents to Their Friends
• Helping Computers Make Big Decisions
• Making Government Computers Talk to Each Other
• Making Computers Count Likes and Shares
• Assisting computers to Find What You Asked For
• Assisting companies to Keep Their Friends Happy

Semantic Web and Linked Data

• Making Computers Understand Each Other Better
• Making Computers Talk About Themselves
• Making the Internet More Friendly for Computers
• Helping Computers Find What They Need
• Making Computers Smarter by Talking to Each Other
• Making Computers Friends with Different Languages
• Making Computers Understand Different Ideas
• Making Computers Think Like Us
• Making Computers Smarter About Old Stuff
• Making Computers Share Their Secrets Safely

Social Computing and Online Communities

• Making Friends on the Internet
• Getting Good Suggestions from the Internet
• Making Computers Work Together to Solve Problems
• Learning from Your Friends on the Internet
• Stopping Fake News on the Internet
• Knowing How People Feel on the Internet
• Helping Each Other on the Internet During Emergencies
• Making Sure Computers Are Nice to Everyone
• Keeping Secrets on the Internet
• Making the Internet a Better Place for Everyone

Game Development and Virtual Worlds

• Making Games That Play Fair
• Letting Computers Make Their Fun
• Making Fake Worlds for Fun
• Learning with Games
• Making the Rules for Fun
• Watching How People Play Together
• Seeing Things That Aren’t There
• Letting Lots of People Play Together
• Making the Engines for Fun
• Playing Games to Learn

E-Learning and Educational Technology

• Making Learning Easy for Everyone
• Taking Classes on the Internet
• Learning from Your Computer’s Teacher
• Learning from What Computers Know
• Learning Anywhere with Your Computer
• Making Learning Fun with Games
• Learning Without a Real Lab
• Learning with Free Stuff on the Internet
• Mixing School with Your Computer
• Making School More Fun with Your Computer

Digital Forensics and Incident Response

• Solving Computer Mysteries
• Looking for Clues in Computers
• Finding Bad Guys on the Internet
• Looking for Clues on Phones and Tablets
• Hiding Clues on Computers
• Helping When Computers Get Sick
• Solving Mysteries While the Computer Is On
• Finding Clues on Your Smart Watch
• Finding Tools for Finding Clues
• Following the Rules When Solving Mysteries

Wearable Technology and Smart Devices

• Keeping Healthy with Smart Watches
• Making Clothes That Talk to Computers
• Listening to the Earth with Your Shirt
• Wearing Glasses That Show Cool Stuff
• Making Your Home Smarter with Your Phone
• Using Your Body to Unlock Your Phone
• Helping People Move with Special Shoes
• Assisting people to See with Special Glasses
• Making Your Clothes Do More Than Keep You Warm
• Keeping Secrets Safe on Your Smart Stuff

Robotics and Automation

• Making Friends with Robots
• Letting Robots Do the Hard Work
• Robots That Work Together Like Ants
• Learning Tricks from People
• Robots That Feel Like Jelly
• Helping Doctors and Nurses with Robots
• Robots That Help Farmers Grow Food
• Making Cars Without People
• Teaching Robots to Recognize Things
• Robots That Learn from Animals

Health Informatics

• Computers That Help Doctors Keep Track of Patients
• Sharing Secrets About Your Health with Other Computers
• Seeing the Doctor on Your Computer
• Keeping Track of Your Health with Your Phone
• Making Medicine Better with Computers
• Keeping Your Health Secrets Safe with Computers
• Learning About Health with Computers
• Keeping Health Secrets Safe on the Internet
• Watching Out for Germs with Computers
• Making Sure the Doctor’s Computer Plays Nice

Geographic Information Systems (GIS)

• Watching the World Change with Computers
• Making Maps on the Internet
• Seeing the World from Very Far Away
• Finding Hidden Patterns with Computers
• Making Cities Better with Computers
• Keeping Track of the Earth with Computers
• Keeping Track of Wild Animals with Computers
• Making Maps with Everyone’s Help
• Seeing the World in 3D
• Finding Things on the Map with Your Phone

Knowledge Management

• Helping Computers Remember Things
• Making Computers Talk About What They Know
• Finding Secrets in Big Piles of Data
• Helping Companies Remember What They Know
• Sharing Secrets with Computers at Work
• Making Computers Learn from Each Other
• Making Computers Talk About Their Friends
• Making Companies Remember Their Secrets
• Keeping Track of What Companies Know

Computational Linguistics and Natural Language Processing (NLP)

• Finding Out How People Feel on the Internet
• Finding Names and Places in Stories
• Making Computers Talk to Each Other
• Making Computers Answer Questions
• Making Summaries for Busy People
• Making Computers Understand Stories
• Making Computers Understand Pictures and Sounds
• Making Computers Learn New Words
• Making Computers Remember What They Read
• Making Sure Computers Aren’t Mean to Anyone

Information Retrieval and Search Engines

• Finding Stuff on the Internet
• Getting Suggestions from the Internet
• Finding Stuff at Work
• Helping Computers Find Stuff Faster
• Making Computers Understand What You Want
• Finding Stuff on Your Phone
• Finding Stuff When You’re Moving
• Finding Stuff Near Where You Are
• Making Sure Computers Look Everywhere for What You Want

Computer Vision

• Finding Stuff in Pictures
• Cutting Up Pictures
• Watching Videos for Fun
• Learning from Lots of Pictures
• Making Pictures with Computers
• Finding Stuff That Looks Like Other Stuff
• Finding Secrets in Medical Pictures
• Finding Out If Pictures Are Real
• Looking at People’s Faces to Know Them

Quantum Information Science

• Making Computers Learn Faster with Tricks

Social Robotics

• Robots That Help People Who Have Trouble Talking
• Robots That Teach People New Things
• Making Robots Work with People
• Helping Kids Learn with Robots
• Making Sure Robots Aren’t Mean to Anyone
• Making Robots Understand How People Feel
• Making Friends with Robots from Different Places
• Making Sure Robots Respect Different Cultures
• Helping Robots Learn How to Be Nice

Cloud Robotics

• Making Robots Work Together from Far Away
• Making Robots Share Their Toys
• Making Robots Do Hard Jobs in Different Places
• Making Robots Save Energy
• Making Robots Play Together Nicely
• Making Robots Practice Being Together
• Making Sure Robots Play Fair
• Making Robots Follow the Rules

Cyber-Physical Systems (CPS)

• Making Robots Work Together with Other Things
• Keeping Robots Safe from Small Mistakes
• Keeping Factories Safe from Bad Guys
• Making Sure Robots Respect Different People
• Making Sure Robots Work Well with People
• Keeping Robots Safe from Bad Guys
• Making Sure Robots Follow the Rules

Biomedical Imaging

• Taking Pictures of Inside You with Computers
• Seeing Inside You with Computers
• Cutting Up Pictures of Inside You
• Finding Problems Inside You with Computers
• Cutting Up Pictures and Putting Them Together
• Counting Inside You with Pictures
• Making Pictures to Help Doctors
• Making Lists from Pictures Inside You
• Making Sure Pictures of You Are Safe

Remote Sensing

• Watching Earth from Far Away with Computers
• Making Pictures of Earth Change
• Taking Pictures from Very High Up
• Watching Crops Grow with Computers
• Watching Cities Grow with Computers
• Watching Earth Change with Computers
• Watching Earth from Far Away During Emergencies
• Making Computers Work Together to See Earth
• Putting Pictures of Earth Together
• Making Sure Pictures of Earth Are Safe

Cloud Gaming

• Playing Games from Far Away
• Making Games Work Faster from Far Away
• Keeping Games Safe from Bad Guys
• Making Sure Everyone Can Play Together
• Making Games Faster from Far Away
• Watching People Play Games from Far Away
• Making Sure Games Look Good from Far Away
• Watching Games Get More Popular

Augmented Reality (AR)

• Making Glasses That Show Cool Stuff
• Making Cool Stuff for Glasses to Show
• Watching Glasses Follow You
• Watching Phones Show Cool Stuff
• Making Cool Stuff to Show with Phones
• Making Places Even Better with Phones
• Making Factories Even Better with Glasses
• Making Places Even Better with Glasses
• Making Sure Glasses Don’t Scare Anyone

Virtual Reality (VR)

• Making Glasses That Show Different Worlds
• Making Glasses That Follow Your Hands
• Making Therapy Fun with Glasses
• Making Learning Fun with Glasses
• Making Glasses That Make Jobs Safer
• Making Glasses That Show Your Friends
• Making Sure Glasses Are Friendly
• Making Glasses That Make Buildings Better
• Making Sure Glasses Aren’t Scary

Digital Twins

• Making Computers That Copy the Real World
• Making People Better with Computers
• Making Flying Safer with Computers
• Making Cars Safer with Computers
• Making Energy Better with Computers
• Making Buildings Better with Computers
• Making Cities Safer with Computers
• Making Sure Computers Copy the Real World Safely
• Making Computers Follow the Rules

Edge Computing

• Making Computers Work Faster Near You
• Keeping Computers Safe Near You
• Making Computers Work with Far-Away Computers
• Making Computers Work Fast with You
• Making Computers Work Together Near You
• Making Phones Work Faster Near You
• Making Computers Work Near You
• Making Computers Work in Busy Places

Explainable AI (XAI)

• Making Computers Explain What They Do
• Making Medicine Safer with Computers
• Making Money Safer with Computers
• Making Computers Safe to Drive Cars
• Making Computers Fair to Everyone
• Making Computers Explain What They Think
• Making Computers Easy to Understand

Blockchain and Distributed Ledger Technology (DLT)

• Making Secret Codes Computers Use
• Making Contracts Computers Can Understand
• Making Computers Share Secrets Safely
• Making Money Safe with Computers
• Making Computers Work Together Nicely
• Making Computers Keep Secrets Safe
• Making Computers Work Together Fairly
• Making Stuff Move Safely with Computers

Quantum Communication

• Making Computers Talk to Each Other Safely
• Making Computers Talk to Each Other from Far Away
• Making Computers Talk to Each Other in Secret
• Making Money Move Safely with Computers

This list covers a broad spectrum of topics within Information Technology, ranging from foundational concepts to cutting-edge research areas. Feel free to choose any topic that aligns with your interests and expertise for further exploration and study!

Emerging Trends in Information Technology Research

In the rapidly changing world of Computer Studies, keeping up with the latest trends is indispensable. Technology keeps changing, and so does research in computer studies. From awesome things like clever robots to how we can safeguard our online information, computer studies research is always discovering new ways to improve our lives. Therefore, let us delve into some of the most exciting new trends shaping computer studies’ future.

• Smart Computers:

Right now, smart computers are a hot item. They can learn from experience, recognize patterns, and even understand language like humans do. This helps in many areas, such as healthcare or finance. So researchers are working on making smart computers smarter yet so that they can make decisions alone and be fair to everyone.

• Fast Computing:

As more devices connect to the Internet, we need ways to process information quickly. Fast computing helps bring processing power closer to where the information comes from, making things quicker and more efficient. Thus, researchers have been figuring out how to improve fast computing, especially for analyzing real-time data.

• Keeping Things Safe:

With all the cool tech around, keeping our information safe from bad guys is important. We must develop methods to safeguard our data and networks from cyber attackers. In addition, they have also been considering how to ensure the privacy of our personal information so that only authorized individuals can access it.

• Fancy Computers:

The next big thing in computing is quantum computers. They can do calculations at a high speed that ordinary ones cannot. Researchers are working hard to achieve quantum computing because it could be useful in cracking codes and creating new drugs.

• New Ways of Doing Things Together:

Blockchain is an exciting technology that allows us to collaborate without a central authority. Its use in cryptocurrencies is quite popular but it has other applications too. Blockchain can be applied for purposes such as helping us discover where products come from, proving who we are on the internet, and making contracts that cannot be changed later on.

• Virtual Reality Adventures:

Entering a completely different world is what Virtual Reality (VR) and Augmented Reality (AR) do. The feeling of being in reality is what these two technologies create, which is not real. These researchers are working hard on making VRs and ARs better so that they can be used for learning, training, and amusement in more innovative ways.

In summary, computer studies research keeps changing with new trends such as smart computers, rapid computing, cybersecurity issues, high-end computers, collaboration platforms and immersive games or virtual reality escapades. 

By exploring these trends and developing new ideas, researchers ensure that technology keeps improving and making our lives easier and more exciting.

How can I brainstorm research topics in information technology?

Start by identifying your areas of interest and exploring recent advancements in the field. Consider consulting with mentors or peers for suggestions and feedback.

What are some ethical considerations in AI research?

Ethical considerations in AI research include fairness, transparency, accountability, and privacy. Researchers should ensure their algorithms and models do not perpetuate bias or harm individuals.

How can I stay updated on emerging trends in IT research?

Follow reputable journals, conferences, and online forums dedicated to information technology. Engage with the academic community through discussions and networking events.

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Top 150 Project Management Dissertation Topics [Updated]

Project management is like the conductor of an orchestra, harmonizing various elements to achieve a masterpiece. Dissertation topics in this field are crucial as they delve into the heart of managing projects effectively. Whether you’re a budding project manager or a seasoned professional looking to deepen your understanding, choosing the right project management dissertation topic is paramount. Let’s embark on a journey to explore some intriguing project management dissertation topics that could spark your interest and contribute to this dynamic field.

How To Pick A Dissertation Topic?

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Picking what you’ll study for your big research project (dissertation) is a really important choice. Take your time and think about it carefully. Here are some steps to help you pick the right topic:

• Reflect on your interests: Consider topics that genuinely interest you and align with your passion and expertise. Your enthusiasm will sustain you through the research process.
• Review existing literature: Conduct a thorough review of literature in your field to identify gaps, unanswered questions, or emerging trends that could form the basis of your research.
• Consider practical relevance: Choose a topic that has practical relevance and real-world implications for your field, industry, or community. Aim to address pressing issues or challenges faced by practitioners or organizations.
• Consult with advisors and peers: Seek feedback from your academic advisors, mentors, or peers to get their perspectives on potential topics. They can give you good advice and assist you in making your ideas better.
• Narrow down your focus: Once you have a broad topic in mind, narrow it down to a specific research question or area of investigation. Make sure your topic is manageable within the scope of your dissertation and aligns with the available resources and timeline.
• Evaluate feasibility: Figure out if your topic is doable by checking if you can find enough information, if you have the right tools to study it, if it’s morally okay, and if there are any real-life limits that might get in the way. Ensure that you have access to the necessary resources and support to conduct your research effectively.
• Stay flexible: Stay ready to change or improve your topic as you learn more during your research and find out new things. Your dissertation topic might change as you go, so it’s important to be open to that and be able to adjust along the way.
• Consider your long-term goals: Think about how your dissertation topic aligns with your long-term academic or career goals. Choose a topic that will allow you to develop valuable skills, make meaningful contributions to your field, and position yourself for future opportunities.

150 Project Management Dissertation Topics: Category Wise

Traditional vs. agile methodologies.

• A comparative analysis of traditional waterfall and agile project management methodologies.
• Evaluating the effectiveness of agile methodologies in software development projects.
• Implementing agile practices in non-IT industries: challenges and opportunities.
• The role of project management maturity models in transitioning from traditional to agile methodologies.
• Agile project management in dynamic and uncertain environments: case studies from various industries.
• Integrating hybrid project management approaches: combining elements of traditional and agile methodologies.
• Assessing the impact of agile project management on team dynamics and collaboration.
• Agile project management in large-scale and complex projects: lessons learned and best practices.
• Overcoming resistance to agile adoption: strategies for organizational change management.
• The future of project management: trends and innovations in agile methodologies.

Project Management Tools and Software

• Evaluating the effectiveness of project management software in improving project outcomes.
• Adoption and implementation of project management tools: a case study approach.
• Comparing different project management software solutions: features, benefits, and limitations.
• Customization vs. out-of-the-box implementation: factors influencing the choice of project management software.
• The impact of cloud-based project management tools on remote team collaboration.
• Enhancing project management efficiency through the integration of collaboration platforms and project management software.
• Project management software usability and user experience: implications for adoption and usage.
• Assessing the security and data privacy risks associated with project management software.
• Trends in project management software development: artificial intelligence, automation, and predictive analytics.
• The role of project management software vendors in driving innovation and industry standards.

Project Risk Management

• Identifying and prioritizing project risks: a systematic approach.
• Quantitative vs. qualitative risk analysis: comparing methods and outcomes.
• Risk management strategies for high-risk industries: construction, aerospace, and defense.
• The role of project risk management in achieving project success: evidence from case studies.
• Incorporating risk management into project planning and decision-making processes.
• Stakeholder engagement in project risk management: challenges and best practices.
• Resilience and adaptability: building a risk-aware project culture.
• Emerging risks in project management: cybersecurity threats, geopolitical instability, and climate change.
• Risk management in agile projects: adapting traditional approaches to dynamic environments.
• The future of project risk management: predictive analytics, big data, and machine learning.

Project Scheduling and Planning

• Critical path analysis and its applications in project scheduling.
• Resource leveling techniques for optimizing project schedules and resource allocation.
• The role of project management offices (PMOs) in project scheduling and planning.
• Earned value management (EVM) as a performance measurement tool in project scheduling.
• Lean project management principles: minimizing waste and maximizing efficiency in project schedules.
• Agile project planning techniques: iterative planning, sprint planning, and release planning.
• Time management strategies for project managers: prioritization, delegation, and timeboxing.
• The impact of schedule compression techniques on project duration and cost.
• Project scheduling under uncertainty: probabilistic scheduling models and Monte Carlo simulation.
• Real-time scheduling and adaptive planning: harnessing technology for dynamic project environments.

Leadership and Team Management

• Transformational leadership in project management: inspiring vision and empowering teams.
• The role of emotional intelligence in project leadership and team performance.
• Cross-cultural leadership in multinational project teams: challenges and strategies.
• Building high-performing project teams: recruitment, training, and team development.
• Distributed leadership in virtual project teams: fostering collaboration and trust.
• Conflict resolution strategies for project managers: mediation, negotiation, and arbitration.
• Motivating project teams: rewards, recognition, and intrinsic motivation.
• The impact of leadership styles on project outcomes: autocratic, democratic, and laissez-faire.
• Gender diversity in project teams: implications for leadership and team dynamics.
• Team resilience and psychological safety: creating a supportive and inclusive project environment.

Project Governance and Stakeholder Management

• Project governance frameworks: roles, responsibilities, and decision-making structures.
• Stakeholder identification and analysis: mapping stakeholder interests, influence, and expectations.
• Effective communication strategies for project stakeholders: stakeholder engagement plans and communication channels.
• Managing stakeholder conflicts and competing interests in projects.
• Make sure companies do good things for the community and talk to the people affected by their projects.
• Look at how the big bosses of a project make decisions and handle the people involved.
• Accountability and transparency in project governance: reporting mechanisms and performance metrics.
• Regulatory compliance in project management: legal requirements and industry standards.
• Balancing stakeholder interests in project decision-making: ethical considerations and social responsibility.
• Continuous improvement in project governance: lessons learned and best practices.

Project Finance and Cost Management

• Project budgeting and cost estimation techniques: top-down vs. bottom-up approaches.
• Cost-benefit analysis and return on investment (ROI) in project decision-making.
• Earned value management (EVM) as a cost control tool in project management.
• Managing project financial risks: budget overruns, resource constraints, and market fluctuations.
• Project procurement and contract management: negotiating contracts, vendor selection, and performance monitoring.
• Life cycle costing in project evaluation: considering long-term costs and benefits.
• Value engineering and value management: optimizing project value while minimizing costs.
• Financial modeling and scenario analysis in project finance: assessing project feasibility and viability.
• Funding sources for project financing: equity, debt, grants, and public-private partnerships.
• Project finance in emerging markets: challenges and opportunities for investment.

Project Quality Management

• Total quality management (TQM) principles in project management: continuous improvement and customer focus.
• Quality planning and assurance processes: setting quality objectives and quality standards.
• Quality control techniques in project management: inspection, testing, and quality audits.
• Six Sigma methodology and its applications in project quality management.
• Lean principles in project management: eliminating waste and optimizing processes.
• Measuring project quality performance: key performance indicators (KPIs) and quality metrics.
• Building a culture of quality excellence in project teams: training, empowerment, and recognition.
• Supplier quality management in project procurement: ensuring supplier compliance and performance.
• Benchmarking and best practices in project quality management.
• Continuous improvement in project quality: feedback loops, lessons learned, and process optimization.

Project Stakeholder Engagement and Communication

• Stakeholder engagement strategies in project management: stakeholder analysis, mapping, and engagement plans.
• Effective communication techniques for project managers: verbal, written, and nonverbal communication.
• Managing virtual project teams: communication tools, technologies, and best practices.
• Conflict resolution strategies for project stakeholders: negotiation, mediation, and collaboration.
• Stakeholder communication in crisis situations: managing stakeholder expectations and maintaining trust.
• Building trust and credibility with project stakeholders: transparency, integrity, and responsiveness.
• Cultural sensitivity and communication in multicultural project teams.
• The role of project managers as communication facilitators and mediators.
• Communication challenges in cross-functional project teams: aligning diverse perspectives and priorities.
• Measuring stakeholder satisfaction and feedback: surveys, interviews, and feedback mechanisms.

Project Human Resource Management

• Human resource planning in project management: resource allocation, skills assessment, and capacity planning.
• Talent management strategies for project teams: recruitment, training, and career development.
• Team-building techniques for project managers: icebreakers, team-building exercises, and bonding activities.
• Performance management in project teams: setting objectives, providing feedback, and evaluating performance.
• Conflict resolution strategies for project managers: negotiation, mediation, and conflict coaching.
• Diversity and inclusion in project teams: fostering a culture of equity, diversity, and inclusion.
• Leadership development in project management: training, coaching, and mentorship programs.
• Managing virtual project teams: communication, collaboration, and team cohesion.
• Building resilience and well-being in project teams: managing stress, burnout, and work-life balance.

Project Procurement and Contract Management

• Procurement planning and strategy development: make-or-buy decisions, sourcing options, and procurement methods.
• Contract types and structures in project procurement: fixed-price, cost-reimbursable, and time-and-material contracts.
• Supplier selection criteria and evaluation methods: vendor qualifications, bid evaluation, and supplier performance metrics.
• Negotiation techniques for project managers: win-win negotiation, BATNA analysis, and concessions management.
• Managing contracts and contractor relationships: contract administration, performance monitoring, and dispute resolution.
• Outsourcing and offshoring in project procurement: risks, benefits, and best practices.
• Legal and regulatory considerations in project procurement: compliance with procurement laws, standards, and regulations.
• Contractual risk management: mitigating contract risks through indemnification clauses, insurance, and contingency planning.
• Ethical considerations in project procurement: fairness, transparency, and integrity in procurement processes.
• Continuous improvement in procurement and contract management: lessons learned, process optimization, and supplier feedback.

Project Sustainability and Social Responsibility

• Integrating sustainability principles into project management: environmental stewardship, social equity, and economic viability.
• Sustainable project planning and design: minimizing environmental impacts, maximizing resource efficiency, and promoting resilience.
• Social impact assessment in project management: stakeholder engagement, community consultation, and social license to operate.
• Sustainable procurement practices: ethical sourcing, fair trade, and supply chain transparency.
• Green project management: reducing carbon emissions, conserving natural resources, and promoting renewable energy.
• Corporate social responsibility (CSR) in project management: philanthropy, community development, and stakeholder engagement.
• Sustainable infrastructure development: green buildings, sustainable transportation, and eco-friendly urban planning.
• Environmental risk management in projects: assessing and mitigating environmental impacts and regulatory compliance.
• Sustainable project financing: green bonds, impact investing, and sustainable finance mechanisms.
• Sustainability reporting and disclosure: communicating project sustainability performance to stakeholders.

Project Innovation and Technology Management

• Innovation management in project-based organizations: fostering a culture of creativity, experimentation, and learning.
• Technology adoption and diffusion in project management: factors influencing technology acceptance and implementation.
• Managing innovation projects: from ideation to commercialization, stage-gate processes, and innovation ecosystems.
• Open innovation and collaborative project management: partnerships, co-creation, and knowledge sharing.
• Digital transformation in project management: leveraging emerging technologies for project delivery and collaboration.
• Artificial intelligence and machine learning in project management: predictive analytics, automation, and decision support systems.
• Blockchain technology in project management: decentralized project governance, smart contracts, and supply chain transparency.
• Virtual reality and augmented reality in project management: immersive training, visualization, and virtual collaboration.
• Internet of Things (IoT) applications in project management: real-time monitoring, predictive maintenance, and asset tracking.
• Data-driven project management: leveraging big data, analytics, and business intelligence for project insights and decision-making.

Project Governance and Compliance

• Regulatory compliance in project management: legal requirements, industry standards, and certification programs.
• Ethics and integrity in project governance: code of conduct, conflict of interest policies, and whistleblowing mechanisms.
• Corporate governance and project management: alignment with organizational objectives, risk management, and performance oversight.
• Internal controls and assurance mechanisms in project governance: auditing, monitoring, and accountability.
• Project portfolio governance: prioritization, resource allocation, and strategic alignment.
• Regulatory reporting and disclosure requirements: compliance with regulatory agencies, stakeholders, and investors.
• Project audits and reviews: evaluating project performance, compliance, and lessons learned.
• Governance of public-private partnerships (PPPs): contractual arrangements, risk allocation, and stakeholder engagement.
• Continuous improvement in project governance: feedback loops, lessons learned, and process optimization.

Project Resilience and Change Management

• Building project resilience: risk management, contingency planning, and adaptive strategies.
• Change management in project management: managing resistance, communication, and stakeholder engagement.
• Organizational resilience and project management: lessons from crisis management, business continuity planning, and disaster recovery.
• Agile project management and organizational agility: responsiveness to change, iterative planning, and adaptive leadership.
• Innovation and creativity in project management: fostering a culture of experimentation, learning, and adaptation.
• Anticipatory project management: scenario planning, risk assessment, and proactive decision-making.
• Crisis leadership and project management: decision-making under pressure, communication, and stakeholder management .
• Change readiness assessment in project management: organizational culture, capacity building, and change champions.
• Learning from failure: post-mortem analysis, root cause analysis, and continuous improvement.
• Resilience in project teams: psychological safety, emotional intelligence, and well-being.

In conclusion, selecting the right project management dissertation topics is essential for exploring new frontiers, addressing pressing challenges, and making meaningful contributions to the field. By choosing a topic that aligns with your interests, expertise, and aspirations, you can embark on a rewarding journey of discovery and innovation in project management.

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450+ Technology Research Topics & Ideas for Your Paper

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Technology is like a massive puzzle where each piece connects to form the big picture of our modern lives. Be it a classroom, office, or a hospital, technology has drastically changed the way we communicate and do business. But to truly understand its role, we need to explore different technology research topics.

And that's where this blog will be handy! Powered by solid experience, our professional term paper writers gathered multiple technology research paper topics in literally any direction. Whether you're a student looking for an intriguing subject for your project or just a tech enthusiast trying to broaden your understanding, we've got your back. Dive into this collection of tech topics and see how technological progress is shaping our world.

What Are Technology Topics?

Technology is the application of scientific knowledge for practical purposes. It's the smartphone in your hand, the electric car on your street, and the spacecraft exploring Mars. It might also be the code that protects your online privacy and the microscope that uncovers mysteries of the human cell.

Technology permeates our lives, revolutionizing the way we communicate, learn, work, and play. But, beyond the gadgets and gizmos, there's a world of diverse technology research topics, ideas, concepts, and challenges.

Technology topics zoom in on these ideas, peeling back the layers of the tech universe. As a researcher, you might study how AI is changing healthcare, explore the ethical implications of robotics, or investigate the latest innovations in renewable energy. Your project should probe into the 'how,' the 'why,' and the 'what next' of the technology that is reshaping our world. So, whether you're dissecting the impact of EdTech on traditional learning or predicting the future of space exploration, research topics in technology are limitless.

Branches of Technology Research Paper Topics

Undoubtedly, the reach of technology is extensive. It's woven its way into almost every corner of our lives. Before we move to technological research topics, let’s first see just where technology has left its mark. So, here are some areas where technology is really shaking things up:

• Government services: E-governance, digital IDs, and digital voting are just a few examples of technology's application in government services.
• Finance: Fintech innovations include cryptocurrencies, mobile banking, robo-advising, and contactless payments.
• Education: Technology is used in a wide variety of educational contexts, from e-learning platforms and digital textbooks to educational games and virtual classrooms.
• Communication: Social media, video conferencing, instant messaging, and email are all examples of tech's role in communication.
• Healthcare: From electronic medical records and telemedicine to advanced imaging technology and robotic surgery, technology is surely transforming healthcare.
• Agriculture: Technological advancements are revolutionizing agriculture through precision farming, automated machinery, drones, and genetic engineering.
• Retail: It also influences retail through e-commerce, mobile payments, virtual fitting rooms, and personalized shopping experiences.
• Environment: Tech is used in climate modeling, conservation efforts, renewable energy, and pollution control.

These are far from all sectors where technology can be applied. But this list shows how diverse topics in technology can be.

How to Choose a Technology Research Topic?

Before you select any idea, it’s important to understand what a good technology research topic is. In a nutshell, a decent topic should be interesting, relevant, and feasible to research within your available resources and time. Make sure it’s specific enough, but not to narrow so you can find enough credible resources. 

Your technology topic sets the course of your research. It influences the type and amount of information you'll search for, the methods you'll use to find it, and the way you'll interpret it. Ultimately, the right topic can make your research process not only more manageable but also more meaningful. But how to get started, you may ask. Don’t worry! Below we are going to share valuable tips from our thesis writers on how to choose a worthy topic about technology.

• Make research Study the latest trends and explore relevant technology news. Your task is to come up with something unique that’s not been done before. Try to look for inspiration in existing literature, scientific articles, or in past projects.
• Recognize your interests Start with what you are genuinely curious about in the field of technology. Passion can be a great motivator during the research process.
• Consider the scope You want a topic that is neither too broad nor too narrow. It should provide enough material to explore without being overwhelming.
• Check availability of resources Ensure there are sufficient trustworthy resources available for your chosen topic.
• Evaluate the relevance Your technology research idea should be pertinent to your field of study and resonate with current trends. This can make your research more valuable and engaging for your audience.

Top List of Technology Research Topics

Are you looking for the best research topics about technology? Stop by! Here, we’ve carefully collected the topic ideas to ignite your curiosity and support your research. Each topic offers various data sources, allowing you to construct well-supported arguments. So, let's discover these fascinating subjects together!

• AI's influence on healthcare.
• Challenges of cybersecurity in a connected world.
• Role of drones in modern agriculture.
• Could renewable energy replace fossil fuels?
• Impact of virtual reality on education.
• Blockchain's potential beyond cryptocurrencies.
• Ethical considerations in biotechnology.
• Can smart cities enhance quality of life?
• Autonomous vehicles – opportunities and threats.
• Robotics in manufacturing.
• Is big data changing decision-making processes?
• E-waste : Challenges and solutions.
• Role of IoT in smart homes.
• Implications of 5G technology.
• EdTech: A revolution in learning?

Good Technology Research Topics

Ready for another batch of inspiration? Get ready to discover great technology topics for a research paper across various disciplines. These ideas are designed to stimulate your creativity and provide substantial information for your research. So, let's explore these exciting themes together!

• Impact of nanotechnology on medicine.
• Harnessing quantum computing potential.
• Augmented reality in tourism.
• Can bioinformatics revolutionize disease prediction?
• Sustainability in tech product design.
• Darknet : A hidden side of the internet.
• How does technology influence human behavior?
• Assistive technology in special education.
• Are smart textiles transforming the fashion industry?
• Role of GIS in urban planning.
• Space tourism: A reality or fantasy?
• Potential of digital twins in engineering.
• How is telemedicine shaping healthcare delivery?
• Green IT : Addressing environmental issues.
• Impact of machine learning on finance.

Interesting Technology Research Paper Topics

For those craving intriguing angles and fresh ideas, we present these interesting topics in technology. This collection is filled with thought-provoking subjects that cover the lesser-known areas of technology. Each topic is concise, clear, and ready to spark a fascinating research journey!

• Cyber-physical systems in industry 4.0.
• Social implications of deepfake technology.
• Can gamification enhance learning outcomes?
• Neuromorphic computing: Emulating the human brain.
• Li-Fi : Light-based communication technology.
• Health risks of prolonged screen time.
• Quantum cryptography and secure communication.
• Role of technology in sustainable agriculture.
• Can we predict earthquakes with AI?
• Virtual influencers: A new trend in marketing.
• Tech solutions for wildlife conservation.
• Role of 3D printing in organ transplantation.
• Impact of automation on the job market.
• Cloud gaming: A new era in the gaming industry.
• Genomic editing: Possibilities and ethical concerns.

New Technology Research Topics

Understanding the fast-paced world of technology requires us to keep up with the latest developments. Hence, we bring you burning  technology research paper topics. These ideas reflect the most recent trends and advances in technology, offering fresh perspectives for your research. Let's take a look at these compelling subjects!

• Potential of hyper automation in business processes.
• How is AI changing digital marketing?
• Brain-computer interfaces: The future of communication?
• Quantum supremacy : Fact or fiction?
• 5D data storage: Revolutionizing data preservation.
• Rise of voice technology in consumer applications.
• Using AI for mental health treatment.
• Implications of edge computing for IoT devices.
• Personalized learning with AI in education.
• Role of technology in reducing food waste.
• Digital twin technology in urban development.
• Impact of AI on patent law.
• Cybersecurity in the era of quantum computing.
• Role of VR in disaster management training.
• AI in talent recruitment: Pros and cons.

Unique Technology Research Topics

For those wanting to stand out with truly original research, we offer 100% authentic topics about technology. We understand that professors highly value unique perspectives. Below we've meticulously selected these technology paper topics to offer you something different. These are not your everyday technology subjects but rather unexpected gems ready to be explored.

• Digital ethics in AI application.
• Role of technology in countering climate change.
• Is there a digital divide in developing countries?
• Role of drones in disaster management.
• Quantum internet: Possibilities and challenges.
• Digital forensic techniques in cybersecurity.
• Impact of technology on traditional art forms.
• Biohacking: Can we really upgrade ourselves?
• Technology and privacy: An inevitable trade-off?
• Developing empathy through virtual reality.
• AI and creativity: Can machines be artists?
• Technology's impact on urban gardening.
• Role of technology in accessible tourism.
• Quantum biology: A frontier of science.
• Unmanned underwater vehicles: Opportunities and threats.

Informative Research Topics in Technology

If you are seeking comprehensive information on technologies, this selection will definitely provide you with insights. As you may know, every study should be backed up by credible sources. Technology topics for research papers below are very easy to investigate, so you will surely find a bunch of academic resources.

• Exploring  adaptive learning systems in online education.
• Role of technology in modern archaeology.
• Impact of immersive technology on journalism.
• The rise of telehealth services.
• Green data centers: A sustainable solution?
• Cybersecurity in mobile banking.
• 3D bioprinting : A revolution in healthcare?
• How technology affects sleep quality.
• AI in music production: A new era?
• Technology's role in preserving endangered languages.
• Smart grids for sustainable energy use.
• The future of privacy in a digital world.
• Can technology enhance sports performance?
• Role of AR in interior design.
• How technology is transforming public libraries.

Controversial Research Topics on Technology

Technological field touches upon areas where technology, ethics, and society intersect and often disagree. This has sparked debates and, sometimes, conspiracy theories, primarily because of the profound implications technologies have for our future. Take a look at these ideas, if you are up to a more controversial research topic about technology:

• Facial recognition technology: Invasion of privacy?
• Tech addiction: Myth or reality?
• The ethics of AI in warfare.
• Should social media platforms censor content?
• Are cryptocurrencies a boon or a bane?
• Is technology causing more harm than good to our health?
• The bias in machine learning algorithms.
• Genetic engineering: Playing God or advancing science?
• Will AI replace human jobs?
• Net neutrality: Freedom of internet or control?
• The risk of AI superintelligence.
• Tech companies' monopoly: Beneficial or detrimental?
• Are we heading towards a surveillance society?
• AI in law enforcement: Safeguard or threat?
• Do we rely too much on technology?

Easy Technology Research Paper Topics

Who ever thought the tech field was only for the tech-savvy? Well, it's time to dispel that myth. Here in our collection of simple technology research topics, we've curated subjects that break down complex tech concepts into manageable chunks. We believe that every student should get a chance to run a tech related project without any hurdles.

• Impact of social media on interpersonal communication.
• Smartphones: A boon or a bane?
• How technology improves accessibility for people with disabilities.
• E-learning versus traditional learning.
• Impact of technology on travel and tourism.
• Pros and cons of online shopping.
• How has technology changed entertainment?
• Technology's role in boosting productivity at work.
• Online safety: How to protect ourselves?
• Importance of digital literacy in today's world.
• How has technology influenced the music industry?
• E-books vs printed books: A tech revolution?
• Does technology promote loneliness?
• Role of technology in shaping modern communication.
• The impact of gaming on cognitive abilities.

Technology Research Topics Ideas for Students

As an experienced paper writing service online that helps students all the time, we understand that every learner has unique academic needs. With this in mind, the next section of our blog is designed to cater specifically to different academic levels. Whether you're a high school student just starting to explore technology or a doctoral candidate delving deep into a specialized topic, we've got different technology topics arranged by complexity.

Technology Research Topics for High School Students

High school students are expected to navigate complex topics, fostering critical thinking and promoting in-depth exploration. The proposed research paper topics on technology will help students understand how tech advancements shape various sectors of society and influence human life.

• How have smartphones changed our communication?
• Does virtual reality in museums enhance visitor experience?
• Understanding privacy issues in social media.
• How has technology changed the way we listen to music?
• Role of technology in promoting fitness and healthy lifestyle.
• Advantages and disadvantages of online learning.
• Does excessive screen time affect sleep quality?
• Do video games affect academic performance?
• How do GPS systems work?
• How has technology improved animation in films?
• Pros and cons of using smart home devices.
• Are self-driving cars safe?
• Technology's role in modernizing local libraries.
• Can technology help us lead more sustainable lifestyles?
• Can technology help improve road safety for teenagers?

Technology Research Topics for College Students

Think technology research topics for college are all about rocket science? Think again! Our compilation of college-level tech research topics brings you a bunch of intriguing, conversation-stirring, and head-scratching questions. They're designed to let you sink into the world of technology while also pushing your academic boundaries. Time to dive in, explore, question, and take your own unique stance on hot-button issues.

• Biometrics in identity verification: A privacy risk?
• Impact of 5G on mobile gaming.
• Are wearable fitness devices a true reflection of health?
• Can machine learning help predict climate change effects?
• Are digital currencies disrupting traditional finance?
• Use of drones in search and rescue operations.
• Impact of e-learning on academic performance.
• Does artificial intelligence have a place in home security?
• What are the ethical issues surrounding robotic surgery?
• Are e-wallets a safer option for online transactions?
• How has technology transformed news dissemination?
• AI in language translation: How accurate can it be?
• Personalized advertising: Boon or bane for online users?
• Are smart classes making learning more interactive?
• Influence of technology on homemade crafts and DIY culture.

Technology Research Topics for University Students

Are you browsing for university technology research ideas? We've got you covered. Whether you're about to dig deep into high-tech debates, or just taking your first steps, our list of technology research questions is your treasure chest.

• Blockchain applications in ensuring academic integrity.
• Impact of quantum computing on data security.
• Are brain-computer interfaces a future communication tool?
• Does digital currency pose a threat to the global economy?
• Use of AI in predicting and managing natural disasters.
• Can biometrics replace traditional identification systems?
• Role of nanotechnology in waste management.
• Machine learning's influence on climate change modeling.
• Edge computing: Revolutionizing data processing?
• Is virtual reality in psychological therapy a viable option?
• Potential of synthetic biology in medical research.
• Quantum cryptography: An uncrackable code?
• Is space tourism achievable with current technology?
• Ethical implications of gene editing technologies.
• Artificial intelligence in governance.

Technology Research Paper Topics in Different Areas

In the next section, we've arranged a collection of technology research questions related to different areas like computer science, biotechnology, and medicine. Find an area you are interested in and look through subject-focused ideas and topics for a research paper on technology.

Technology Research Topics on Computer Science

Computer science is a field that has rapidly developed over the past decades. It deals with questions of technology's influence on society, as well as applications of cutting-edge technologies in various industries and sectors. Here are some computer science research topics on technology to get started:

• Prospects of machine learning in malware detection.
• Influence of cloud computing on business operations.
• Quantum computing: potential impacts on cryptography.
• Role of big data in personalized marketing.
• Can AI models effectively simulate human decision-making?
• Future of mobile applications: Towards augmented reality?
• Pros and cons of open source software development.
• Role of computer science in advancing virtual reality.
• Natural language processing: Transforming human-computer interaction?
• Developing secure e-commerce platforms: Challenges and solutions.
• Green computing : solutions for reducing energy consumption.
• Data mining in healthcare: An untapped opportunity?
• Understanding cyber threats in the internet of things.
• Algorithmic bias: Implications for automated decision-making.
• Role of neural networks in image recognition.

Information Technology Research Topics

Information technology is a dynamic field that involves the use of computers and software to manage and process information. It's crucial in today's digital era, influencing a range of industries from healthcare to entertainment. Here are some captivating information technology related topics:

• Impact of cloud technology on data management.
• Role of information technology in disaster management.
• Can artificial intelligence help improve data accuracy?
• Cybersecurity measures for protecting personal information.
• Evolving role of IT in healthcare administration.
• Adaptive learning systems: A revolution in education?
• E-governance : Impact on public administration.
• Role of IT in modern supply chain management.
• Bioinformatics and its role in personalized medicine.
• Is data mining an invasion of privacy?
• Can virtual reality enhance training and development programs?
• Role of IT in facilitating remote work.
• Smart devices and data security: A potential risk?
• Harnessing IT for sustainable business practices.
• How can big data support decision-making processes?

Technology Research Topics on Artificial Intelligence

Artificial Intelligence, or AI as we fondly call it, is all about creating machines that mimic human intelligence. It's shaping everything from how we drive our cars to how we manage our calendars. Want to understand the mind of a machine? Choose a topic about technology for a research paper from the list below:

• AI's role in detecting fake news.
• Chatbots in customer service: Are humans still needed?
• Algorithmic trading: AI's impact on financial markets.
• AI in agriculture: a step towards sustainable farming?
• Facial recognition systems: an AI revolution or privacy threat?
• Can AI outperform humans in creative tasks?
• Sentiment analysis in social media: how effective is AI?
• Siri, Alexa, and the future of AI.
• AI in autonomous vehicles: safety concern or necessity?
• How AI algorithms are transforming video games.
• AI's potential in predicting and mitigating natural disasters.
• Role of AI in combating cyber threats.
• Influence of AI on job recruitment and HR processes.
• Can AI help in advancing climate change research?
• Can machines make accurate diagnoses?

Technology Research Topics in Cybersecurity Command

Cybersecurity Command focuses on strengthening digital protection. Its goal is to identify vulnerabilities, and outsmart cyber threats. Ready to crack the code of the cybersecurity command? Check out these technology topics for research designed to take you through the tunnels of cyberspace:

• Cybersecurity strategies for a post-quantum world.
• Role of AI in identifying cyber threats.
• Is cybersecurity command in healthcare a matter of life and death?
• Is there any connection between cryptocurrency and cybercrime?
• Cyber warfare : The invisible battleground.
• Mitigating insider threats in cybersecurity command.
• Future of biometric authentication in cybersecurity.
• IoT security: command challenges and solutions.
• Cybersecurity and cloud technology: A secure match?
• Influence of blockchain on cybersecurity command.
• Machine learning's role in malware detection.
• Cybersecurity protocols for mobile devices.
• Ethics in cybersecurity: Hacking back and other dilemmas.
• What are some steps to recovery after a breach?
• Social engineering: Human factor in cybersecurity.

Technology Research Topics on Biotechnology

Biotechnology is an interdisciplinary field that has been gaining a lot of traction in the past few decades. It involves the application of biological principles to understand and solve various problems. The following research topic ideas for technology explore biotechnology's impact on medicine, environment, agriculture, and other sectors:

• Can GMOs solve global hunger issues?
• Understanding biotech's role in developing personalized medicine.
• Using biotech to fight antibiotic resistance.
• Pros and cons of genetically modified animals.
• Biofuels – are they really a sustainable energy solution?
• Ethical challenges in gene editing.
• Role of biotech in combating climate change.
• Can biotechnology help conserve biodiversity?
• Biotech in beauty: Revolutionizing cosmetics.
• Bioluminescence – a natural wonder or a biotech tool?
• Applications of microbial biotechnology in waste management.
• Human organ farming: Possibility or pipe dream?
• Biotech and its role in sustainable agriculture.
• Biotech advancements in creating allergy-free foods.
• Exploring the future of biotech in disease detection.

>> Read more: Biology Topics to Research

Technology Research Paper Topics on Genetic Engineering

Genetic engineering is an area of science that involves the manipulation of genes to change or enhance biological characteristics. This field has raised tremendous ethical debates while offering promising solutions in medicine and agriculture. Here are some captivating topics for a technology research paper on genetic engineering:

• Future of gene editing: Breakthrough or ethical dilemma?
• Role of CRISPR technology in combating genetic diseases.
• Pros and cons of genetically modified crops.
• Impact of genetic engineering on biodiversity.
• Can gene therapy provide a cure for cancer?
• Genetic engineering and the quest for designer babies.
• Legal aspects of genetic engineering.
• Use of genetic engineering in organ transplantation.
• Genetic modifications: Impact on human lifespan.
• Genetically engineered pets: A step too far?
• The role of genetic engineering in biofuels production.
• Ethics of genetic data privacy.
• Genetic engineering and its impact on world hunger.
• Genetically modified insects: Solution for disease control?
• Genetic engineering: A tool for biological warfare?

Reproduction Technology Research Paper Topics

Reproduction technology is all about the science that aids human procreation. It's a field teeming with innovation, from IVF advancements to genetic screening. Yet, it also stirs up ethical debates and thought-provoking technology topics to write about:

• Advances in in Vitro Fertilization (IVF) technology .
• The rise of surrogacy: Technological advancements and implications.
• Ethical considerations in sperm and egg donation.
• Genetic screening of embryos: A step forward or an ethical minefield?
• Role of technology in understanding and improving fertility.
• Artificial Wombs: Progress and prospects.
• Ethical and legal aspects of posthumous reproduction.
• Impact of reproductive technology on the LGBTQ+ community.
• The promise and challenge of stem cells in reproduction.
• Technology's role in preventing genetic diseases in unborn babies.
• Social implications of childbearing technology.
• The concept of 'designer babies': Ethical issues and future possibilities.
• Reproductive cloning: Prospects and controversies.
• Technology and the future of contraception.
• Role of AI in predicting successful IVF treatment.

Medical Technology Topics for a Research Paper

The healthcare field is undergoing massive transformations thanks to cutting-edge medical technology. From revolutionary diagnostic tools to life-saving treatments, technology is reshaping medicine as we know it. To aid your exploration of this dynamic field, we've compiled medical technology research paper topics:

• Role of AI in early disease detection.
• Impact of telemedicine on rural healthcare.
• Nanotechnology in cancer treatment: Prospects and challenges.
• Can wearable technology improve patient outcomes?
• Ethical considerations in genome sequencing.
• Augmented reality in surgical procedures.
• The rise of personalized medicine: Role of technology.
• Mental health apps: Revolution or hype?
• Technology and the future of prosthetics.
• Role of Big Data in healthcare decision making.
• Virtual reality as a tool for pain management.
• Impact of machine learning on drug discovery.
• The promise of medical drones for emergency response.
• Technology's role in combating antimicrobial resistance.
• Electronic Health Records (EHRs): Blessing or curse?

>> More ideas: Med Research Topics

Health Technology Research Topics

Health technology is driving modern healthcare to new heights. From apps that monitor vital stats to robots assisting in surgeries, technology's touch is truly transformative. Take a look at these topics related to technology applied in healthcare:

• Role of mobile apps in managing diabetes.
• Impact of health technology on patient privacy.
• Wearable tech: Fad or future of personal health monitoring?
• How can AI help in battling mental health issues?
• Role of digital tools in promoting preventive healthcare.
• Smart homes for the elderly: Boon or bane?
• Technology and its impact on health insurance.
• The effectiveness of virtual therapy sessions.
• Can health chatbots replace human doctors?
• Technology's role in fighting the obesity epidemic.
• The use of blockchain in health data management.
• Impact of technology on sleep health.
• Social media and its effect on mental health.
• Prospects of 3D printing in creating medical equipment.
• Tele-rehabilitation: An effective solution for physical therapy?

>> View more: Public Health Topics to Research

Communication Technology Research Topics

With technology at the helm, our ways of communicating are changing at an unprecedented pace. From simple text messages to immersive virtual conferences, technology has rewritten the rules of engagement. So, without further ado, let's explore these communication research ideas for technology that capture the essence of this revolution.

• AI chatbots: Re-defining customer service.
• The impact of 5G on global communication.
• Augmented Reality: The future of digital marketing?
• Is 'digital divide' hindering global communication?
• Social media's role in shaping public opinion.
• Can holographic communication become a reality?
• Influence of emojis in digital communication.
• The cybersecurity challenges in modern communication.
• Future of journalism in the digital age.
• How technology is reshaping political communication.
• The influence of streaming platforms on viewing habits.
• Privacy concerns in the age of instant messaging.
• Can technology solve the issue of language barriers?
• The rise of podcasting: A digital renaissance.
• Role of virtual reality in remote communication.

Research Topics on Technology in Transportation

Technology is the driving force behind the dramatic changes in transportation, making journeys safer, more efficient, and eco-friendly. Whether it's autonomous vehicles or the concept of Hyperloop, there are many transportation technology topics for a research paper to choose from:

• Electric vehicles: A step towards sustainable travel.
• The role of AI in traffic management.
• Pros and cons of autonomous vehicles.
• Hyperloop: An ambitious vision of the future?
• Drones in goods delivery: Efficiency vs. privacy.
• Technology's role in reducing aviation accidents.
• Challenges in implementing smart highways.
• The implications of blockchain in logistics.
• Could vertical takeoff and landing (VTOL) vehicles solve traffic problems?
• Impact of GPS technology on transportation.
• How has technology influenced public transit systems?
• Role of 5G in future transportation.
• Ethical concerns over self-driving cars.
• Technology in maritime safety: Progress and hurdles.
• The evolution of bicycle technology: From spokes to e-bikes.

Technology Research Paper Topics on Education

The intersection of technology and education is an exciting frontier with limitless possibilities. From online learning to interactive classrooms, you can explore various technology paper topics about education:

• How does e-learning affect student engagement?
• VR classrooms: A glimpse into the future?
• Can AI tutors revolutionize personalized learning?
• Digital textbooks versus traditional textbooks: A comparison.
• Gamification in education: Innovation or distraction?
• The impact of technology on special education.
• How are Massive Open Online Courses (MOOCs) reshaping higher education?
• The role of technology in inclusive education.
• Cybersecurity in schools: Measures and challenges.
• The potential of Augmented Reality (AR) in classroom learning.
• How is technology influencing homeschooling trends?
• Balancing technology and traditional methods in early childhood education.
• Risks and benefits of student data tracking.
• Can coding be the new literacy in the 21st century?
• The influence of social media on academic performance.

>> Learn more: Education Research Paper Topics

Relationships and Technology Research Topics

In the digital age, technology also impacts our relationships. It has become an integral part of how we communicate, meet people, and sustain our connections. Discover some thought-provoking angles with these research paper topics about technology:

• How do dating apps affect modern relationships?
• The influence of social media on interpersonal communication.
• Is technology enhancing or hindering long-distance relationships?
• The psychology behind online dating: A study.
• How do virtual reality environments impact social interaction?
• Social media friendships: Genuine or superficial?
• How does technology-mediated communication affect family dynamics?
• The impact of technology on work-life balance.
• The role of technology in sustaining long-term relationships.
• How does the 'always connected' culture influence personal boundaries?
• Cyberbullying and its effect on teenage relationships.
• Can technology predict compatibility in relationships?
• The effects of 'ghosting' in digital communication.
• How technology assists in maintaining relationships among elderly populations.
• Social media: A boon or bane for marital relationships?

Agriculture Technology Research Paper Topics

Modern agriculture is far from just tilling the soil and harvesting crops. Technology has made remarkable strides into the fields, innovating and improving agricultural processes. Take a glance at these technology research paper topic ideas:

• Can drone technology transform crop monitoring?
• Precision agriculture: Benefits and challenges.
• Aquaponics and the future of sustainable farming.
• How is artificial intelligence aiding in crop prediction?
• Impact of blockchain technology in food traceability.
• The role of IoT in smart farming.
• Vertical farming : Is it a sustainable solution for urban food supply?
• Innovations in irrigation technology for water conservation.
• Automated farming: A boon or a threat to employment in agriculture?
• How satellite imagery is improving crop disease detection.
• Biotechnology in crop improvement: Pros and cons.
• Nanotechnology in agriculture: Scope and limitations.
• Role of robotics in livestock management.
• Agricultural waste management through technology.
• Is hydroponics the future of farming?

Technological Research Topics on Environment

Our planet is facing numerous environmental challenges, and technology may hold the key to solving many of these. With innovations ranging from renewable energy sources to waste management systems, the realm of technology offers a plethora of research angles. So, if you're curious about the intersection of technology and environment, this list of research topics is for you:

• Innovations in waste management: A technology review.
• The role of AI in predicting climate change impacts.
• Renewable energy: Advancements in solar technology.
• The impact of electric vehicles on carbon emissions.
• Can smart agriculture help solve world hunger?
• Role of technology in water purification and conservation.
• The impact of IoT devices on energy consumption.
• Technology solutions for oil spills.
• Satellite technology in environmental monitoring.
• Technological advances in forest conservation.
• Green buildings: Sustainable construction technology.
• Bioengineering: A solution to soil erosion?
• Impact of nanotechnology on environmental conservation.
• Ocean clean-up initiatives: Evaluating existing technology.
• How can technology help in reducing air pollution?

>> View more: Environmental Science Research Topics

Energy & Power Technology Topics for Research Paper

Energy and power are two pivotal areas where technology is bringing unprecedented changes. You can investigate renewable energy sources or efficient power transmission. If you're excited about exploring the intricacies of energy and power advancements, here are some engaging technology topics for research papers:

• Assessing the efficiency of wind energy technologies.
• Power storage: Current and future technology.
• Solar panel technology: Recent advancements and future predictions.
• Can nuclear fusion be the answer to our energy crisis?
• Smart grid technology: A revolution in power distribution.
• Evaluating the impact of hydropower on ecosystems.
• The role of AI in optimizing power consumption.
• Biofuels vs. fossil fuels: A comparative study.
• Electric vehicle charging infrastructure: Technological challenges and solutions.
• Technology advancements in geothermal power.
• How is IoT technology helping in energy conservation?
• Harnessing wave and tidal energy: Technological possibilities.
• Role of nanotechnology in improving solar cell efficiency.
• Power transmission losses: Can technology provide a solution?
• Assessing the future of coal technology in the era of renewable energy.

Research Topics about Technology in Finance

The finance sector has seen drastic changes with the rise of technology, which has revolutionized the way financial transactions are conducted and services are offered. Consider these research topics in technology applied in the finance sector:

• Rise of cryptocurrency: An evaluation of Bitcoin's impact.
• Algorithmic trading: How does it reshape financial markets?
• Role of AI and machine learning in financial forecasting.
• Technological challenges in implementing digital banking.
• How is blockchain technology transforming financial services?
• Cybersecurity risks in online banking: Identifying solutions.
• FinTech startups: Disrupting traditional finance systems.
• Role of technology in financial inclusion.
• Assessing the impact of mobile wallets on the banking sector.
• Automation in finance: Opportunities and threats.
• Role of big data analytics in financial decision making.
• AI-based robo-advisors vs. human financial advisors.
• The future of insurance technology (InsurTech).
• Can technology solve the issue of financial fraud?
• Impact of regulatory technology (RegTech) in maintaining compliance.

>> More ideas: Finance Research Topics

War Technology Research Paper Topics

The nature of warfare has transformed significantly with the evolution of technology, shifting the battlegrounds from land, sea, and air to the realms of cyber and space. This transition opens up a range of topics to explore. Here are some research topics in the realm of war technology:

• Drones in warfare: Ethical implications.
• Cyber warfare: Assessing threats and defense strategies.
• Autonomous weapons: A boon or a curse?
• Implications of artificial intelligence in modern warfare.
• Role of technology in intelligence gathering.
• Satellite technology and its role in modern warfare.
• The future of naval warfare: Autonomous ships and submarines.
• Hypersonic weapons: Changing the dynamics of war.
• Impact of nuclear technology in warfare.
• Technology and warfare: Exploring the relationship.
• Information warfare: The role of social media.
• Space warfare: Future possibilities and implications.
• Bio-warfare: Understanding technology's role in development and prevention.
• Impact of virtual reality on military training.
• War technology and international law: A critical examination.

Food Technology Topics for Research Papers

Food technology is a field that deals with the study of food production, preservation, and safety. It involves understanding how various techniques can be applied to increase shelf life and improve nutrition value of foods. Check out our collection of food technology research paper topic ideas:

• Lab-grown meats: Sustainable solution or a mere hype?
• How AI is enhancing food safety and quality?
• Precision agriculture: Revolutionizing farming practices.
• GMOs: Assessing benefits and potential risks.
• Role of robotics in food manufacturing and packaging.
• Smart kitchens: Streamlining cooking through technology.
• Nanofood: Tiny technology, big impact.
• Sustainable food systems: Role of technology.
• Food traceability: Ensuring transparency and accountability.
• Food delivery apps: Changing the face of dining out.
• The rise of plant-based alternatives and their production technologies.
• Virtual and augmented reality in culinary experiences.
• Technology in mitigating food waste.
• Innovations in food packaging: Impact on freshness and sustainability.
• IoT in smart farming: Improving yield and reducing waste.

Entertainment Technology Topics

Entertainment technology is reinventing the ways we experience amusement. This industry is always presenting new angles for research and discussion, be it the rise of virtual reality in movies or the influence of streaming platforms on the music industry. Here's a list of unique research topics related to entertainment technology:

• Impact of virtual reality on the movie industry.
• Streaming platforms vs traditional media: A comparative study.
• Technology in music: Evolution and future prospects.
• eSports: Rise of a new form of entertainment.
• Augmented reality in theme parks.
• The transformation of theater with digital technology.
• AI and film editing: Redefining the art.
• The role of technology in the rise of independent cinema.
• Podcasts: Revolutionizing radio with technology.
• Immersive technologies in art exhibitions.
• The influence of technology on fashion shows and design.
• Livestreaming concerts: A new norm in the music industry?
• Drones in entertainment: Applications and ethics.
• Social media as an entertainment platform.
• The transformation of journalism in the era of digital entertainment.

Technology Research Questions

As we navigate the ever-changing landscape of technology, numerous intriguing questions arise. Below, we present new research questions about technology that can fuel your intellectual pursuit.

• What potential does quantum computing hold for resolving complex problems?
• How will advancements in AI impact job security across different sectors?
• In what ways can blockchain technology reform the existing financial systems?
• How is nanotechnology revolutionizing the field of medicine?
• What are the ethical implications surrounding the use of facial recognition technology?
• How will the introduction of 6G change our communication patterns?
• In what ways is green technology contributing to sustainable development?
• Can virtual reality transform the way we approach education?
• How are biometrics enhancing the security measures in today's digital world?
• How is space technology influencing our understanding of the universe?
• What role can technology play in solving the global water crisis?
• How can technology be leveraged to combat climate change effectively?
• How is technology transforming the landscape of modern agriculture?
• Can technological advancements lead to a fully renewable energy-dependent world?
• How does technology influence the dynamics of modern warfare?

Bottom Line on Research Topics in Technology

Technology is a rapidly evolving field, and there's always something new to explore. Whether you're writing for the computer sciences, information technology or food technology realm, there are endless ideas that you can research on. Pick one of these technology research paper topics and jumpstart your project.

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130 Information Technology Research Topics And Quick Writing Prompts

The field of information technology is one of the most recent developments of the 21st century. Scholars argue that we are living in a technological age. Despite this buzz, however, many students still find it challenging to compose an information technology research topic.

Nonetheless, we are here to show you the way and lead you accordingly. Let us explore professional topics in information technology together then.

Quality Information Technology Topics For Research Paper

• The effects of Artificial Intelligence on complex and tedious tasks
• Discuss the development of computational & synthetic biology in research
• What are the limitations to the study of computer architecture in colleges?
• Discuss the evolution of animation, computer graphics, and game science
• Critically analyze how computing is contributing to the development
• What are the emerging fields of study in computer data science?
• How to manage data in the age of the 5G technology
• The impact of human-computer interaction on innovations
• How is machine learning exposing students to more recent opportunities in life?
• Evaluate molecular information systems and their role in biotechnology
• How information technology has contributed to natural language processing
• What are the latest developments in programming languages and software engineering
• Analyze emerging opportunities in the field of Robotics

College Research Paper Topics in Information Technology

• The rising security and privacy concerns with technological advancements
• What are the considerations when setting up systems and networking?
• Discuss the theory of computation and its contribution to information technology
• Why is ubiquitous computing attracting fewer students?
• The role of wireless and sensor systems in making the world a safe place
• Reasons, why cloud computing has helped save on space and efficiency
• Why are most computer students comprised of the male?
• Discuss the essence of amorphous computing in the 21st century
• How has biomedical mining impacted the health sector?
• Can cyborgs relate well with the man?
• How neural networking is making brain surgery a swift process
• The role of swarm intelligence in collaboration and brainstorming
• How are companies maximizing the use of Big Data?

List of Topics For Research Paper in Information Technology

• Discuss how the Internet of Things is transforming how people conduct their activities
• Challenges to software-defined networking
• How are marketers and promoters taking up software as a service?
• The role of augmented reality and virtual reality in healthcare systems
• How intelligent apps are making life easier for man
• The role of information technology in detecting fake news and malicious viral content
• Long term effects of a technologically oriented world
• Technological advancements that made it possible for the SpaceX shuttle to land on the International Space Station
• How technology is making learning more practical and student-centered
• What role has technology played in the spread of world pandemics?
• How are governments able to shut down the Internet for their countries during particular events?
• Does social media make the world a global village or a divided universe?
• Discuss the implications of technological globalization

Unique Information Technology Research Topics

• Discuss the areas of life which have been least exploited using technology
• What are the considerations for setting up an educational curriculum on computer technology?
• Compare and contrast between different computer processing powers
• Why is Random Access Memory so crucial to the functioning of a computer?
• Should computer as a subject be mandatory for all students in college?
• How information technology has helped keep the world together during the quarantine period
• Discuss why most hackers manage to break firewalls of banks
• Are automated teller machine cards a safe way of keeping your bank details?
• Why should every institution incorporate automated systems in its functions?
• Who is more intelligent than the other? Man or Computer systems?
• How is NASA implementing the use of Information technology to explore space?
• The impact of automated message replies on smartphones.
• Do mobile phones contain radiations that cause cancer?

IT Research Topics For High School Students

• How does natural language processing compare with machine learning?
• What is the role of virtual reality in the entertainment industry?
• Discuss the application of computer vision technology in autonomous cars
• How have CCTVs assisted in keeping the world safe?
• Effects of phishing and spying on relationships
• Why cyber espionage is on the rise in the face of the 5G technology
• Compare and contrast between content-based recommendation vs. collaborative filtering
• Evaluate the interconnection between the Internet of things and artificial intelligence
• Analyze the amount of data generated from the Internet of things in devices
• Ethical and legal implications of various technological practices
• How technology has contributed to the formation of Genetically Modified Organisms
• Describe in detail the vaccine development process
• Why nanotechnology may be the only hope left in treating HIV

Hot Topics in IT

• How companies can incorporate information technologies in their policy management systems
• The role of IT in enhancing service delivery in customer care centers
• How IT has made advertising more appealing and authentic to the consumer
• Discuss the innovation of the Next Generation education systems
• Why are there fewer Information Technology colleges and universities in developing countries?
• Discuss WIFI connectivity in developed countries
• What are the considerations when purchasing a Bandwidth Monitor?
• How to create an effective Clinic Management System for intensive care
• Factors that necessitate the development of an Enterprise Level System Information Management
• Is it possible to develop fully functional Intelligent Car Transportation Systems?
• Why the world should adopt E-Waste Management systems ASAP
• Discuss the impact of weather and climate on internet strength and connectivity
• The role of advanced information technologies preserving classified documents

Interesting Information Technology Topics

• Human resource information management systems in large organizations
• Evaluate the effectiveness of online enterprise resource planning
• A critical analysis of object tracking using radial function networks
• How has Bluetooth mobile phone technology developed over time?
• Ethical challenges arising from new media information technologies
• How the computer has developed over the last decade
• The role of social media in enhancing communication strategies
• Why new media technologies have made physical newspapers obsolete
• The impact of the Internet of news sourcing, production, distribution, and sharing
• Discuss the structures of various communication structures
• How social media is making ads easily accessible
• The impact of social networking sites on personal contact
• Discuss the latest content marketing ideas in the wake of information technology

Topics Related To Information Technology

• The impact of media exposure to adolescents and teenagers
• How mass media is slowly but surely taking over the place of personal socialization
• How to use the Internet and interactive media as advertising tools
• Discuss the trends in music marketing in a digital world
• The use of hype in new media technologies
• The impact of using YouTube and video blogs in communication messages
• Discuss the challenges that are arising as a result of new media technologies
• How to build trustful relationships in virtual communication channels
• Why it is impossible to maintain privacy in social media
• Reasons why cyberbullying continues to persist in various communication technologies
• The change in interpersonal communication with the invention of information technology
• Is the future of information technologies right?
• Discuss how sensationalism is persisting in the wake of new media technologies

Research Proposal Topics in Information Technology

• Is it possible to live in a world without social media?
• The impact of mass media on morality and decency in the 21st century
• Advantages and disadvantages of renewable energy sources
• How effective is hydrogen power over others?
• An overview of renewable energy technologies
• The impact of robots in improving food safety
• How are drones useful in keeping large acres of land secure?
• The impact of 3D printing on the practice of medicine
• The effectiveness of having robots in infectious disease units
• The impact of hydroponic farming
• How to improve disease control using technology
• Eliminating poisonous substances in food using technology
• The effectiveness of robotic surgeries

Hot Topics in Computer Science

• Distinguish between virtual reality and human perception
• How are the inventions in the field of computer science transforming the world
• Evaluate the effectiveness of high-dimensional data modeling
• Limitations to the field of computer science
• Are colleges and universities producing competent computer scientists?
• How ethical hacking has turned out to be worse
• The essence of having specialized banking systems
• What is the most effective security measure: A serial code or fingerprint?
• The development of programming languages
• The effect of computational thinking on science
• Is it possible to eliminate stalking?
• Ways of improving patent rights for technological innovations
• An overview of the different types of software security

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The Plight of Platform Workers Under Algorithmic Management in Southeast Asia

Algorithmic management by large online platforms disrupts societal relations. A case study about drivers in Southeast Asia demonstrates the worldwide shifts that are underway.

Introduction

After Uber arrived on the scene and disrupted existing taxi companies, its successful model was quickly replicated in other sectors. A proliferation of new platforms emerged, offering to match demand and supply in all manner of task-based work. As more workers look to online platforms to earn income, the technology powering these platforms is having far-reaching effects beyond simply optimized task matching.

Algorithmic management by large online platforms disrupts existing societal relations. It makes work an individualized endeavor, creates a vacuum in place of established duties and obligations between buyers and suppliers of labor, and produces an intense concentration of power. These shifts are happening worldwide, but already disenfranchised communities lacking institutional support systems face higher risks of disruption.

The individualization of work occurs when platform workers find it difficult to form sustainable connections with their managers, co-workers, and clients. Established labor relations are disrupted when workers are treated as independent contractors yet are dependent on platforms for job access and lack decisionmaking power on pricing and working conditions. Algorithmic management also intensifies platforms’ ability to concentrate power, as information asymmetry and unilateral business decisions create an opaque, extractive, and unaccountable environment.

These effects in turn have tangible impacts on workers’ ability to pursue collective action in hopes of establishing clear employment status, improving their labor conditions, and gaining clarity on the parameters of automated decisionmaking that shape their access to work.

Policy changes addressing effects on societal relations, not just effects on individuals, are needed to mitigate relational shifts and to prompt adjustments to new forms of technology in workplaces. Such policy changes require careful consideration of how societal relations and their attending power structures are impacted by increasing dependence on technology for labor management. To make such changes, it is necessary to go beyond the current emphasis among experts in the governance of artificial intelligence (AI) on individual harms and redress and to also factor in the connections between individuals and how technology changes the ways people relate to each other. 1 This article considers how app-based drivers in Southeast Asia have experienced these issues.

Algorithmic Management of Platform Workers

Algorithmic management has emerged as an area of interest for regulators, civil society watchdogs, and academic researchers. 2 Sara Baiocco and her colleagues define algorithmic management as “the use of computer-programmed procedures for the coordination of labour input in an organization,” covering functions of planning, staffing, commanding, coordinating, and controlling. 3 Using AI, these management functions can be fully or partially taken over by automated decisionmaking, as algorithms learn from large swaths of data collected from within and outside the organization using them. 4

With the rise of digital labor platforms mediating the supply and demand of services, algorithmic management eases the logistical difficulties of coordinating labor transactions between millions of users in a timely manner. Tasks that can be largely automated include job matching between the supply and demand sides, dynamic price setting and incentive or penalty structures for both, and monitoring and quality control of service provision. In Southeast Asia, for example, the Grab app matches drivers and passengers looking for rides, determines an appropriate fare, and monitors the duration of each journey.

Algorithmic management allows platforms to operate at scale and create a virtuous cycle of more users (either clients or workers) and more user-generated data that can lead to more precise predictions and decisionmaking. The resulting efficiency generally results in higher customer satisfaction and lowered barriers of access to new earning opportunities for workers. 5 Platforms, being the intermediaries between the supply and demand sides of labor, are also able to extract economic value from both ends.

Platform Responsibility in Algorithmic Design

It is difficult to separate the impacts of platforms’ business decisions and the consequences of algorithmic management. A business decision to corner the market by forgoing profit in the short term can lead to a pricing strategy that prioritizes user supply over maximizing profit. This can then get translated into algorithms that calculate a lower price range for users. When algorithms like this are opaque—a common complaint—it can be difficult to understand whether algorithmic management aligns with business decisions or simply reflects temporary or arbitrarily set conditions. While users may benefit from this arrangement in the short term, workers may not be so fortunate. This situation can be somewhat rectified if businesses choose to explain their systems to their stakeholders, including workers. 6

The impacts of business decisions and algorithmic management are intertwined. Business decisions underlie algorithmic rules, and successful platforms also hold disproportionate amounts of power when they achieve the status of a monopoly or monopsony. 7 The largest platforms with the biggest networks of workers and consumers become the preferred option for both, minimizing the degree of accountability that users can demand of them and making it difficult for smaller platforms and other players to be competitive.

The Case of App-based Drivers in Southeast Asia

In Southeast Asia, drivers for ride-hailing apps and delivery workers that rely on platforms for work are the ones bearing the brunt of algorithmic management.

In the early 2010s, Grab began to gain traction (originating as MyTeksi, a taxi-hailing app in Malaysia), and Uber entered the Southeast Asian market. Since then, the region’s app-based transportation sector has experienced intense growth. 8 As of 2023, a decade of jostling for market dominance has left the sector with only a few players: the most powerful ones for ride hailing are Grab (which subsumed Uber’s regional business) and the Indonesian firm GoTo (after Gojek and Tokopedia merged), both of which also dominate the food delivery market along with Delivery Hero (which runs Foodpanda). 9

When platforms were growing and needed to recruit drivers, drivers benefited from being in short supply, so they received higher pay and better incentives than in traditional taxi companies and elsewhere in the transport sector. These benefits were not necessarily due to higher fares per ride, but could have been linked to the higher number of tasks available and reduced waiting time between tasks that increased overall pay. 10

When platforms were competing for market share in terms of users then, they were also having aggressive price wars that subsidized customer fees and driver pay, attracting users from both the demand and supply sides. Many of those working in the traditional transport sector transitioned to app-based driving, and app-based driving also became an attractive job opportunity for those who were not originally working within the transport sector. 11

However, as platforms gained popularity and attracted an excess supply of drivers, the drivers no longer had the upper hand. As platforms came under pressure to gain profits, drivers found themselves facing multiple rounds of rising commissions and reduced incentives. 12 As with platforms, drivers face the effects of capitalist forces intertwined with technological impacts. Unlike platforms, they have much less control over their own outcomes.

The opaque and impersonal nature of algorithmic management worsens the circumstances that drivers face. Through the interface of their device screens, drivers across the region have experienced unilateral changes in incentive structures with no consultation. 13 , 14 Those who have had their accounts deactivated unfairly have struggled to find recourse, with one reported case in Malaysia of a driver who had to go through more than two and a half years of litigation to reinstate her account. 15 Drivers lack access to relationships with decisionmakers, as might be the case for a taxi driver whose license has been revoked. They also lack familiarity with the bureaucracy and grievance-filing process that a human resources department might have been able to provide in a less algorithmically driven workplace.

App-based driving is precarious work, due to inadequate social protections and occupational health and safety risks. Workers rush in traffic to obtain high customer ratings, which is often the only performance metric available to them. Drivers also feel pressured to accept unsuitable jobs against their judgment, hoping that the algorithms will in turn rank them higher and provide more access to jobs and better job matching, or that the algorithm-based apps will offer bonuses when the drivers meet targets by completing a high number of jobs. 16

Algorithmic control with little transparency leads to self-disciplining on the part of the workers who work long hours with little rest in between. Since they don’t know exactly how or when they are being assigned tasks, they stay on call for long stretches hoping for work. The information asymmetry on how decisions are made also rouses the distrust of drivers against the job-matching algorithms. For example, drivers complain that the system slows down the assignment of jobs when they are about to achieve their targets, affecting their chances to obtain rewards. 17

Faced with asymmetries in both information and decisionmaking power, algorithmically managed workers have limited options for addressing their grievances. App-based drivers across Southeast Asia have therefore organized demonstrations and strikes (for example by turning off their apps en masse to refuse to work) to protest their low pay and poor working conditions. 18 However, the decentralized nature of the movement, workers’ ambivalence for strikes, and the lack of public support for such actions have made it very difficult for workers to make substantive progress. For instance, in Thailand, a survey of 550 platform workers 19 showed that about half of the respondents did not favor protests and strikes. 20

In general, movements across the region have faced divisions on issues and priorities, as well as political differences, making large-scale organization of collective bargaining very challenging. Adding to these difficulties are the relational impacts of algorithmic management.

The Relational Impacts of Algorithmic Management

Elsewhere, one of us has argued how important it is to consider the negative impacts of AI beyond individual harm , to shift some of our attention toward societal harm , or how certain AI-powered applications change the nature and quality of human relationships. 21 App-based drivers’ deteriorated working conditions under algorithmic management are an instance of individual harm that has been documented extensively. 22 Much less covered, however, are the effects of algorithmic management on societal relations in terms of how algorithms have reshuffled and redefined the ways in which members of society relate to each other.

There are at least three examples of relational impacts resulting from algorithmic management by large online platforms that help illustrate the structural causes of app-based drivers’ plight.

Disintermediation and the Individualization of Work

The first disruption to societal relations is brought about by efforts to commodify labor suppliers—in this case, app-based drivers—as platforms depict drivers as largely faceless and nameless one-off service providers to a big pool of customers. While customers of ride-hailing apps receive driver identification and license plate numbers for their drivers, interactions mostly occur through the app, and encounters are fleeting. Drivers as a labor commodity works for the platforms in the sense that customers return to the app to request further rides, whereas drivers find it difficult to establish a consistent client base outside of the platform and therefore must depend on the platforms for job access. 23

The disintermediation of relationships between customers and drivers is not the only form of isolation for app-based drivers. They also find themselves disconnected from their coworkers—namely, other drivers who are subjected to the same algorithmic control. Besides strikes, app-based drivers in Southeast Asia use other forms of grassroots organization to fulfill the need to connect to their peers. Associations and informal communities of drivers have built networks around a “mutual aid logic” with strong social commitment to support and help each other in times of need. 24

For example, in Indonesia, driver communities form organically when drivers meet physically and congregate at base camps where they rest or wait for orders, and they are digitally connected via WhatsApp groups. In early 2020, Fahmi Panimbang estimated that greater Jakarta had more than 5,000 driver communities, with each group comprising 10 to 100 members. 25 These groups serve various functions such as emergency and rapid response (in the case of accidents, conflicts, or other crises); welfare and mobilization of funding; and information or knowledge sharing. Crucially, for the drivers, a sense of community and solidarity is also fostered through collective action, regular meetings, and leisure activities like weekend trips.

These worker initiatives are a means of compensating for the isolating and disempowering effects of algorithmic management. Similar forms of mobilization have been observed in other countries such as Thailand, 26 Malaysia, 27 and Vietnam. 28 Driver communities have also found it important to organize beyond their localities, consolidating or collaborating across groups so as to span wider geographical areas. Some of these groups have become more formalized organizations with stronger institutional capacities such as associations and unions to tackle industry-wide structural issues beyond mutual aid. 29

The Reconfiguration of Roles and Obligations

A key problem that often surfaces related to the working conditions of app-based drivers globally is their unclear employment status as “partners.” Platforms claim that they are merely intermediaries connecting independent workers with jobs, taking a small cut from their earnings. However, this argument starts to fray considering that many workers depend on platforms as their sole source of income. Furthermore, opaque algorithmic management controls their access to clients and limits their autonomy—deciding, for example, when and where they will work and how much to charge for their services.

By not defining drivers as employees, platforms skirt standard labor regulations such as having to provide a minimum wage, paid leave and overtime, and a notice period for dismissal. For some Southeast Asian countries, such as Malaysia, 30 drivers are unable to form unions if they are not employees, hampering their ability to go through a formal collective bargaining process. In such an arrangement, tripartite labor relations established between the state, employers, and worker unions are rendered obsolete, as are the negotiated standards for decent work underlying sustainable development.

Viewed relationally, this can be seen as a way of clearing the slate of the established duties and obligations of each party within an employer/employee relationship as enshrined in employment law. In the place of these obligations and duties is a vacuum without institutional frameworks or support for drivers, whose lack of an employment identity cuts them off from access to labor rights and protections. This does not boil down to a simple solution of defining app-based drivers as employees of platforms, since some drivers prefer the flexibility of nonfixed employment and since not all drivers work fulltime. 31 Clearly, a nuanced way forward must be found to address the needs of different types of workers interacting with these algorithmic management systems.

It is not a clear-cut case that the disruptions caused by platforms are necessarily worse than the status quo. It is important to acknowledge that much of the work available in Southeast Asia is informal to begin with. In the case of Indonesia, for instance, researchers have argued that the existence of Gojek provided the unintended consequence of more opportunities for collective action, enabling motorcycle taxi drivers to organize against a “pseudo-employer” for wage bargaining. 32

However, over the long term, it would be better to establish formal channels and institutionalized processes to clarify the responsibilities of platforms, starting from employment classifications that include app-based workers. The purpose would be to ensure that the gains from workers organizing are enshrined in law and policy processes, so that past efforts at defining roles can be built upon, without workers having to renegotiate terms repeatedly.

The Concentration of Power

By definition, power is relational, and its distribution is very rarely symmetrical or in equilibrium. It is unsurprising to see the use of technology tilt the balance of power in favor of the powerful, especially through the withholding of information and a lack of accountability.

The logic of the first mover advantage and network effects, propelled further by the capitalist business decisions alluded to earlier, also impact the market. A narrowing of market players has disproportionately benefited platforms with the largest number of workers. This reduces worker options in terms of who to work with and how to improve their working conditions and outcomes, thus disenfranchising an already vulnerable group.

In 2021, the leading ride-hailing app in Southeast Asia, Grab, showed remarkable market consolidation. In a consumer survey, 94 percent of respondents in Malaysia named Grab as their preferred ride-hailing app. The firm was also mentioned by 91 percent of respondents in the Philippines, 80 percent in Thailand, 74 percent in Singapore, 73 percent in Vietnam, and 52 percent in Indonesia. Gojek, trailing as a distant second, has become particularly popular in Indonesia. 33

The on-demand food delivery sector also appears to be highly concentrated: GrabFood (Grab), Foodpanda (Delivery Hero), and GoFood (Gojek) had cornered 84.8 percent of the market in 2021, according to one industry report. 34

Algorithmic management also facilitates the consolidation of platform power in two ways. The first is information asymmetry. Platforms justify themselves in collecting tremendous amounts of behavioral and personal data in the name of optimizing algorithms, giving them much more knowledge of the market ecosystem than what individual workers possess. Platforms are thus able to optimize decisionmaking for their own benefit, while workers are left without similar information.

Second, algorithmic management reduces human intervention and agency. The logic of algorithms is supposedly neutral and effective, with decisions made and acted upon swiftly with minimal need for human input or intervention. Thus, workers have little recourse to challenge decisions or file grievances. It is possible that even if drivers are able to report issues or grievances in-app, a slow platform response will increase the likelihood that they accept the decisions of algorithms in the interest of generating income. If this is widely the case, it may reduce workers’ sense of agency and self-determination, which can affect their well-being and could stifle professional development.

Related Policy Developments

Initial policymaking concerns regarding the platform economy were rooted in concerns over customer safety and worker rights to social protections. Southeast Asian governments have made efforts to regulate the ride-hailing sector to address these concerns. 35 For example, countries in the region require that drivers be registered and that vehicles used for ride-sharing jobs meet certain minimum requirements. Also, countries like Malaysia have made it mandatory for ride-hailing drivers to contribute to the country’s national social security plan for self-employed workers. 36

However, these regulations, while important and necessary, do not address the relational impacts of algorithmic management on worker welfare and well-being. Policies that focus more on governing technologies and platforms instead of workers may play a bigger role in tackling these issues.

For example, regulations that specifically address algorithmic management can provide checks and balances in the platform economy. China’s Internet Information Service Algorithmic Recommendation Management Provisions, in force since 2022, deal predominantly with online content but also include regulations for labor management recommendation algorithms, such as those used by food delivery platforms. As a result, in accordance with the law’s requirements, platforms registered their algorithms in China’s algorithm registry and reported taking measures to use algorithms that give drivers more time to deliver orders and allow them to ask for more time if they need to. 37 This example shows that it is possible to nudge platforms to alter the priorities of their algorithms and take responsibility for the decisions made by their technologies, reestablishing their role in labor relations.

Southeast Asian governments could also learn from the two-tiered approach taken by the European Union (EU). Large platforms can be held in check by antitrust regulations or gatekeeper regulations such as the Digital Markets Act, which the EU adopted in 2022. The act requires large online platforms providing core services (known as gatekeepers) to comply with rules aimed at ensuring a fair market. What is important is that not all platforms are held to the same rules. Large platforms with disproportionate influence in the market face stricter rules than smaller platforms. In this way, platforms whose algorithms are likely to affect a large proportion of workers can be regulated more closely. A two-tiered regulatory model could hold larger platforms accountable and allow smaller platforms to innovate and grow.

Presently, platform workers bear the brunt of algorithmic management’s effects, but such management practices are expected to spread into traditional workplaces as big data and automation become more prevalent. 38 The world is just beginning to see how algorithmic management, along with other forms of recommender algorithms, can have harmful impacts on societal relations.

The isolation of workers makes it hard for them to make connections and find solidarity, which can hinder their ability to improve their collective working conditions. The distortion of roles and responsibilities in labor relations undoes years of efforts to codify expectations and develop workers’ rights and social protections. Concentration of power in the hands of corporations deepens social inequalities.

Fortunately, human resilience is already at work in the ways workers are organizing and demanding better working conditions. After all, workers directly experience the relational impacts of the technologies managing their work. As they respond to the effects of these technologies in real time, they should be consulted on policy matters because they are best placed to underline challenges and propose solutions. Measures that support worker organizing and community building may result in creative community-driven solutions and more impactful policies.

Labor and technology policies can also help regulate platforms and corporations seeking to maximize profits at the expense of people by addressing structural and relational impacts as well as individual impacts. Now is the time for innovative approaches such as a two-tiered approach to regulating online platforms and more humane, albeit less profit-maximizing, means of algorithmic management.

1 Nathalie A. Smuha, “Beyond the Individual: Governing AI’s Societal Harm,” Internet Policy Review 10, no. 3 (November 2021): https://papers.ssrn.com/abstract=3941956 .

2 AI Now Institute, “2023 Landscape: Confronting Tech Power,” AI Now Institute, 2023, https://ainowinstitute.org/2023-landscape .

3 Sara Baiocco et al., “The Algorithmic Management of Work and Its Implication in Different Contexts,” International Labour Organisation and the European Commission, Background Paper 9, June 2022, https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/publication/wcms_849220.pdf .

4 This can include behavioral data from users such as workers or clients, as well as data obtained from data brokers.

5 Tech for Good Institute, “The Platform Economy: Southeast Asia’s Digital Growth Catalyst,” Tech for Good Institute and Bain Capital, October 2021, https://techforgoodinstitute.org/research/tfgi-reports/the-platform-economy-southeast-asias-digital-growth-catalyst .

6 An example of such an effort is Meta’s release of system cards to explain how AI systems within their products work. See Meta Transparency Center, “Our Approach to Explaining Ranking,” Meta Transparency Center, December 31, 2023, https://transparency.fb.com/features/explaining-ranking .

7 A monopsony is a market with only one buyer, as opposed to a monopoly, which is a market with only one seller. See William M. Boal and Michael R Ransom, “Monopsony in the Labor Market,” Journal of Economic Literature 35, no. 1 (1997): 86–112.

8 Charles David A. Icasiano and Araz Taeihagh. “Governance of the Risks of Ridesharing in Southeast Asia: An In-Depth Analysis,” Sustainability 13, no. 11 (2021): https://doi.org/10.3390/su13116474 .

9 Statista, “Asia: Most Used Food Delivery Apps by Country,” Statista, 2021, https://www.statista.com/statistics/1394977/asia-most-used-food-delivery-apps-by-country .

10 Fahmi Panimbang, “Solidarity Across Boundaries: A New Practice of Collectivity Among Workers in the App-Based Transport Sector in Indonesia,” Globalizations 18, no. 8 (2021): 1377–1391, https://doi.org/10.1080/14747731.2021.1884789 .

11 Tech for Good Institute, “The Platform Economy.”

12 Panimbang, “Solidarity Across Boundaries.”

13 Kriangsak Teerakowitkajorn and the Just Economy Labor Institute, “Desiring A Strong Movement: Understanding the Discontent of Thai Platform Workers,” Asian Labour Review , September 2022, https://labourreview.org/desiring-a-strong-movement-in-thailand .

14 Faisal Irfani, “A Merger Makes Tokopedia and GoJek Bigger–and the Income of Online Drivers Smaller,” Project Multatuli, August 4, 2021, https://projectmultatuli.org/en/a-merger-makes-tokopedia-and-gojek-bigger-and-the-income-of-online-drivers-smaller .

15 Huei Ting Cheong, “Building Power Through Associations: Experience of Grab Drivers in Malaysia,” Asian Labour Review (blog post), May 31, 2023, https://labourreview.org/malaysia-grab .

16 Baiocco et al., “The Algorithmic Management of Work and Its Implication in Different Contexts.”

17 Baiocco et al., “The Algorithmic Management of Work and Its Implication in Different Contexts.”

18 Ioulia Bessa et al., “A Global Analysis of Worker Protest in Digital Labour Platforms,” International Labour Organisation, June 2022, https://doi.org/10.54394/CTNG4947 .

19 Survey respondents represented four sectors: couriers (including food delivery, transport, and logistics); domestic work; massage therapy; and sex work. While the survey goes beyond app-based drivers, it indicates a general aversion to demonstrations and strikes within Thai culture. As mentioned in the article, striking workers (including app-based drivers) in Thailand do not generally receive a lot of public sympathy.

20 Teerakowitkajorn and the Just Economy Labor Institute, “Desiring A Strong Movement.”

21 Jun-E Tan, “Visualising Societal Harms of AI,” London School of Economics Southeast Asia Blog, October 11, 2023, https://blogs.lse.ac.uk/seac/2023/10/11/visualising-societal-harms-of-ai .

22 See, for example, stories about Grab published by Rest of World at https://restofworld.org/search/grab/ .

23 Jin Li, Scott Duke Kominers, and Lila Shroff, “A Labor Movement for the Platform Economy,” Harvard Business Review , September 24, 2021. https://hbr.org/2021/09/a-labor-movement-for-the-platform-economy .

24 Michele Ford and Vivian Honan, “The Limits of Mutual Aid: Emerging Forms of Collectivity among App-Based Transport Workers in Indonesia.” Journal of Industrial Relations 61, no. 4 (April 2019): https://journals.sagepub.com/doi/full/10.1177/0022185619839428 .

25 Panimbang, “Solidarity Across Boundaries.”

26 Kriangsak Teerakowitkajorn, “Stories From Below: Organic Leaders and Dilemmas of Grassroots Organizing in Thailand,” Asian Labour Review , March 26, 2023, https://labourreview.org/grab-thailand .

27 Cheong, “Building Power Through Associations.”

28 Joe Buckley, “The Labour Politics of App-Based Driving in Vietnam,” Trends in Southeast Asia , Issue 16, ISEAS Yusof Ishak Institute, 2023, https://www.iseas.edu.sg/articles-commentaries/trends-in-southeast-asia/the-labour-politics-of-app-based-driving-in-vietnam-by-joe-buckley .

29 Ford and Honan, “The Limits of Mutual Aid.”

30 Cheong, “Building Power Through Associations.”

31 Edwin Goh, “Responses to Delivery Riders Missing the Bigger Picture,” The Centre, August 30, 2022, https://www.centre.my/post/responses-to-delivery-riders-missing-the-bigger-picture ; and

32 Michele Ford and Vivian Honan, “The Go-Jek Effect,” in Digital Indonesia: Connectivity and Divergence , ed. Edwin Jurriens and Ross Tapsell, (Singapore: ISEAS - Yusof Ishak Institute, 275–288).

33 According to statistics by Statista reflected in a survey of 7,200 respondents in Southeast Asia. See Statista, “Southeast Asia: Most Used Ride-Hailing Apps by Country.” https://www.statista.com/statistics/1294871/sea-most-used-ride-hailing-apps-by-country .

34 “Southeast Asian On-Demand Food Delivery Market, 2021–2030,” Frost and Sullivan, February 15, 2022, https://www.frost.com/news/on-demand-food-delivery-services-next-growth-frontier-in-southeast-asia .

35 Icasiano and Taeihagh, “Governance of the Risks of Ridesharing in Southeast Asia.”

36 “Self-Employed,” Malaysian Social Security Organisation, https://www.perkeso.gov.my/uncategorised/51-social-security-protection/818-self-employment-social-security-scheme.html .

37 Matt Sheehan and Sharon Du, “How Food Delivery Workers Shaped Chinese Algorithm Regulations,” Carnegie Endowment for International Peace, November 2, 2022, https://carnegieendowment.org/2022/11/02/how-food-delivery-workers-shaped-chinese-algorithm-regulations-pub-88310 .

38 Baiocco et al., “The Algorithmic Management of Work and Its Implication in Different Contexts.”

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Professor Emeritus David Lanning, nuclear engineer and key contributor to the MIT Reactor, dies at 96

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David Lanning, MIT professor emeritus of nuclear science and engineering and a key contributor to the MIT Reactor project, passed away on April 26 at the Lahey Clinic in Burlington, Massachusetts, at the age of 96.

Born in Baker, Oregon, on March 30, 1928, Lanning graduated in 1951 from the University of Oregon with a BS in physics. While taking night classes in nuclear engineering, in lieu of an available degree program at the time, he started his career path working for General Electric in Richland, Washington. There he conducted critical-mass studies for handling and designing safe plutonium-bearing systems in separation plants at the Hanford Atomic Products Operation, making him a pioneer in nuclear fuel cycle management.

Lanning was then involved in the design, construction, and startup of the Physical Constants Testing Reactor (PCTR). As one of the few people qualified to operate the experimental reactor, he trained others to safely assess and handle its highly radioactive components.

Lanning supervised experiments at the PCTR to find the critical conditions of various lattices in a safe manner and conduct reactivity measurements to determine relative flux distributions. This primed him to be an indispensable asset to the MIT Reactor (MITR), which was being constructed on the opposite side of the country.

An early authority in nuclear engineering comes to MIT

Lanning came to MIT in 1957 to join what was being called the “MIT Reactor Project” after being recruited by the MITR’s designer and first director, Theos “Tommy” J. Thompson, to serve as one of the MITR’s first operating supervisors. With only a handful of people on the operations team at the time, Lanning also completed the emergency plan and startup procedures for the MITR, which achieved criticality on July 21, 1958.

In addition to becoming a faculty member in the Department of Nuclear Engineering in 1962, Lanning’s roles at the MITR went from reactor operations superintendent in the 1950s and early 1960s, to assistant director in 1962, and then acting director in 1963, when Thompson went on sabbatical.

In his faculty position, Lanning took responsibility for supervising lab subjects and research projects at the MITR, including the Heavy Water Lattice Project. This project supported the thesis work of more than 30 students doing experimental studies of sub-critical uranium fuel rods — including Lanning’s own thesis. He received his PhD in nuclear engineering from MIT in fall 1963.

Lanning decided to leave MIT in July 1965 and return to Hanford as the manager of their Reactor Neutronics Section. Despite not having plans to return to work for MIT, Lanning agreed when Thompson requested that he renew his MITR operator’s license shortly after leaving.

“Because of his thorough familiarity with our facility, it is anticipated that Dr. Lanning may be asked to return to MIT for temporary tours of duty at our reactor. It is always possible that there may be changes in the key personnel presently operating the MIT Reactor and the possible availability of Dr. Lanning to fill in, even temporarily, could be a very important factor in maintaining a high level of competence at the reactor during its continued operation,” Theos J. Thompson wrote in a letter to the Atomic Energy Commission on Sept. 21, 1965

One modification, many changes

This was an invaluable decision to continue the MITR’s success as a nuclear research facility. In 1969 Thompson accepted a two-year term appointment as a U.S. atomic energy commissioner and requested Lanning to return to MIT to take his place during his temporary absence. Thompson initiated feasibility studies for a new MITR core design and believed Lanning was the most capable person to continue the task of seeing the MITR redesign to fruition.

Lanning returned to MIT in July 1969 with a faculty appointment to take over the subjects Thompson was teaching, in addition to being co-director of the MITR with Lincoln Clark Jr. during the redesign. Tragically, Thompson was killed in a plane accident in November 1970, just one week after Lanning and his team submitted the application for the redesign’s construction permit.

Thompson’s death meant his responsibilities were now Lanning’s on a permanent basis. Lanning continued to completion the redesign of the MITR, known today as the MITR-II. The redesign increased the neutron flux level by a factor of three without changing its operating power — expanding the reactor’s research capabilities and refreshing its status as a premier research facility.

Construction and startup tests for the MITR-II were completed in 1975 and the MITR-II went critical on Aug. 14, 1975. Management of the MITR-II was transferred the following year from the Nuclear Engineering Department to its own interdepartmental research center, the Nuclear Reactor Laboratory , where Lanning continued to use the MITR-II for research.

Beyond the redesign

In 1970, Lanning combined two reactor design courses he inherited and introduced a new course in which he had students apply their knowledge and critique the design and economic considerations of a reactor presented by a student in a prior term. He taught these courses through the late 1990s, in addition to leading new courses with other faculty for industry professionals on reactor safety.

Co-author of over 70 papers , many on the forefront of nuclear engineering, Lanning’s research included studies to improve the efficiency, cycle management, and design of nuclear fuel, as well as making reactors safer and more economical to operate.

Lanning was part of an ongoing research project team that introduced and demonstrated digital control and automation in nuclear reactor control mechanisms before any of the sort were found in reactors in the United States. Their research improved the regulatory barriers preventing commercial plants from replacing aging analog reactor control components with digital ones. The project also demonstrated that reactor operations would be more reliable, safe, and economical by introducing automation in certain reactor control systems. This led to the MITR being one of the first reactors in the United States licensed to operate using digital technology to control reactor power.

Lanning became professor emeritus in May 1989 and retired in 1994, but continued his passion for teaching through the late 1990s as a thesis advisor and reader. His legacy lives on in the still-operational MITR-II, with his former students following in his footsteps by working on fuel studies for the next version of the MITR core. 

Lanning is predeceased by his wife of 60 years, Gloria Lanning, and is survived by his two children, a brother, and his many grandchildren .

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