Machine Behaviourism: Future Visions of ‘Learnification’ and ‘Datafication’ across Humans and Digital Technologies
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This paper examines visions of ‘learning’ across humans and machines in a near-future of intensive data analytics. Building upon the concept of ‘learnification’, practices of ‘learning’ in emerging big data-driven environments are discussed in two significant ways: the training of machines, and the nudging of human decisions through digital choice architectures. Firstly, ‘machine learning’ is discussed as an important example of how data-driven technologies are beginning to influence educational activity, both through sophisticated technical expertise and a grounding in behavioural psychology. Secondly, we explore how educational software design informed by behavioural economics is increasingly intended to frame learner choices to influence and ‘nudge’ decisions towards optimal outcomes. Through the growing influence of ‘data science’ on education, behaviourist psychology is increasingly and powerfully invested in future educational practices. Finally, it is argued that future education may tend toward very specific forms of behavioural governance – a ‘machine behaviourism’ – entailing combinations of radical behaviourist theories and machine learning systems, that appear to work against notions of student autonomy and participation, seeking to intervene in educational conduct and shaping learner behaviour towards predefined aims.
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The powerful transformative potential of AI and VR technologies could offer notable benefits for students with disabilities once integrated into the educational framework [60,61].
“The powerful transformative potential of AI and VR technologies could offer notable benefits for students with disabilities, once integrated into the educational framework [60,61].”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [61]
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225 · see citing works
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,263 · see citing works
Nudge: Improving Decisions About Health, Wealth and Happiness
Adkisson, R. V. (2008) · The Social Science Journal · doi:10.1016/j.soscij.2008.09.003 · Cited by 5,680 · see citing works
Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
Lebovits, H. (2018) · Public Integrity · doi:10.1080/10999922.2018.1511671 · Cited by 3,318 · see citing works
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Doyle, T. (2017) · The Information Society · doi:10.1080/01972243.2017.1354593 · Cited by 3,110 · see citing works
Algorithms of Oppression: How Search Engines Reinforce Racism
Noble, S. U. (2020) · doi:10.2307/j.ctt1pwt9w5 · Cited by 2,709 · see citing works
(2019) · Cited by 2,637 · see citing works
Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16001837 · Cited by 2,550 · see citing works
(2016) · Cited by 2,334 · see citing works
The age of surveillance capitalism: the fight for a human future at the new frontier of power
Shandler, R. (2019) · Journal of Cyber Policy · doi:10.1080/23738871.2019.1637914 · Cited by 2,113 · see citing works
The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences
Kitchin, R. (2014) · doi:10.4135/9781473909472 · Cited by 1,469 · cited 2× · see citing works
“Therefore, accompanying the ‘ re-emergence of empiricism ’ ushered in by the ‘ data revolution ’ (Kitchin 2014), has been radical behaviourism, with which the work of B.F. Skinner ‘ has been making a comeback ’ (Friesen 2018, 3).”
BackgroundLearning analytics: drivers, developments and challenges
Ferguson, R. (2012) · International Journal of Technology Enhanced Learning · doi:10.1504/ijtel.2012.051816 · Cited by 1,357 · see citing works
Learning Analytics: The Emergence of a Discipline
Siemens, G. (2013) · American Behavioral Scientist · doi:10.1177/0002764213498851 · Cited by 1,284 · see citing works
NMC Horizon Report: 2017 Higher Education Edition
Becker, S. A., Brown, M., Dahlstrom, E., Davis, A., DePaul, K., Díaz, V., & Pomerantz, J. (2017) · Cited by 1,243 · see citing works
Beyond Learning: Democratic Education for a Human Future
Biesta, G. (2006) · Cited by 1,206 · see citing works
Learning Analytics: Ethical Issues and Dilemmas
Slade, S., & Prinsloo, P. (2013) · American Behavioral Scientist · doi:10.1177/0002764213479366 · Cited by 1,078 · see citing works
Let’s not forget: Learning analytics are about learning
Gašević, D., Dawson, S., & Siemens, G. (2015) · TechTrends · doi:10.1007/s11528-014-0822-x · Cited by 1,049 · see citing works
The social power of algorithms
Beer, D. (2017) · Information, Communication & Society · doi:10.1080/1369118x.2016.1216147 · Cited by 945 · see citing works
‘Hypernudge’: big Data as a mode of regulation by design
Yeung, K. (2017) · Information, Communication & Society · doi:10.1080/1369118x.2016.1186713 · Cited by 868 · see citing works
Morozov, E. (2013) · Cited by 591 · see citing works
Academic Analytics: A New Tool for a New Era.
Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007) · Educational Review · Cited by 505 · see citing works
The happiness industry: how the government and big business sold us well-being
(2015) · Choice Reviews Online · doi:10.5860/choice.191819 · Cited by 451 · see citing works
Giving Teaching Back to Education: Responding to the Disappearance of the Teacher
Biesta, G. (2013) · Phenomenology & Practice · doi:10.29173/pandpr19860 · Cited by 394 · see citing works
Emotional AI: The Rise of Empathic Media
McStay, A. (2018) · doi:10.4135/9781526451293 · Cited by 385 · see citing works
Against learning. Reclaiming a language for education in an age of learning
Biesta, G. (2004) · Nordic Studies in Education · doi:10.18261/issn1891-5949-2004-01-06 · Cited by 302 · see citing works
Alpaydın, E. (2016) · Cited by 287 · see citing works
The production of prediction: What does machine learning want?
Mackenzie, A. (2015) · European Journal of Cultural Studies · doi:10.1177/1367549415577384 · Cited by 258 · see citing works
Mackenzie, A. (2017) · The MIT Press eBooks · doi:10.7551/mitpress/10302.001.0001 · Cited by 242 · see citing works
Tsai, Y.-S., & Gasevic, D. (2017) · Proceedings of the Seventh International Learning Analytics & Knowledge Conference · doi:10.1145/3027385.3027400 · Cited by 211 · cited 1× · see citing works
“Learning analytics has garnered signi fi cant attention in education, following high-pro fi le research (see Lang et al. 2017) and policy agendas (see Tsai and Gasevic 2017), as well as consistent predictions of its impending disruption of formal education (for example Johnson et al. 2016; Adams…”
BackgroundStudent privacy in learning analytics: An information ethics perspective
Rubel, A., & Jones, K. M. L. (2014) · The Information Society · doi:10.1080/01972243.2016.1130502 · Cited by 203 · see citing works
Ferguson, R., & Clow, D. (2017) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3027385.3027396 · Cited by 170 · see citing works
Jones, R., Pykett, J., & Whitehead, M. (2013) · Edward Elgar Publishing eBooks · doi:10.4337/9780857936882 · Cited by 149 · see citing works
Interrupting the Politics of Learning
Biesta, G. (2013) · Power and Education · doi:10.2304/power.2013.5.1.4 · Cited by 139 · see citing works
John, P. C. (2018) · Edward Elgar Publishing eBooks · doi:10.4337/9781786430557 · Cited by 134 · see citing works
Cope, B., & Kalantzis, M. (2016) · AERA Open · doi:10.1177/2332858416641907 · Cited by 133 · see citing works
Machine Learners: Archaeology of a Data Practice
Mackenzie, A. (2017) · Cited by 125 · see citing works
Learning analytics: challenges and limitations
Wilson, A. N., Watson, C., Thompson, T. L., Drew, V., & Doyle, S. (2017) · Teaching in Higher Education · doi:10.1080/13562517.2017.1332026 · Cited by 116 · see citing works
Neuroliberalism: Behavioural Government in the Twenty-First Century
Whitehead, M., Jones, R. A., Lilley, R., Pykett, J., & Howell, R. (2017) · Routledge eBooks · doi:10.4324/9781315684772 · Cited by 74 · see citing works
Revising rationality: the use of ‘Nudge’ approaches in neoliberal education policy
Bradbury, A., McGimpsey, I., & Santori, D. (2012) · Journal of Education Policy · doi:10.1080/02680939.2012.719638 · Cited by 71 · see citing works
D’Mello, S. K. (2017) · Society for Learning Analytics Research (SoLAR) eBooks · doi:10.18608/hla17.010 · Cited by 71 · see citing works
Knowledge for Sale: The Neoliberal Takeover of Higher Education
Busch, L. (2017) · Cited by 53 · see citing works
Affective capture in digital school spaces and the modulation of student subjectivities
Nemorin, S. (2017) · Emotion, space and society · doi:10.1016/j.emospa.2017.05.007 · Cited by 51 · see citing works
A Framework for Learning Analytics Using Commodity Wearable Devices
Lu, Y., Zhang, S., Zhang, Z., Xiao, W., & Yu, S. (2017) · Sensors · doi:10.3390/s17061382 · Cited by 49 · see citing works
Deep learning, education and the final stage of automation.
Peters, M. A. (2018) · Educational Philosophy and Theory · doi:10.1080/00131857.2017.1348928 · Cited by 39 · see citing works
Yang, Y.-O. (2016) · Nursing Science Quarterly · doi:10.1177/0894318416647779 · Cited by 26 · see citing works
How Far to Nudge?: Assessing Behavioural Public Policy
John, P. C. (2018) · Cited by 24 · see citing works
Prolegomenon to a Media Theory of Machine Learning: Compute-Computing and Compute-Computed
Berry, D. M. (2017) · Media theory. · doi:10.70064/mt.v1i1.565 · Cited by 5 · see citing works
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Cited by
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Historical threads, missing links, and future directions in AI in education
Williamson, B., & Eynon, R. (2020) · Learning, Media and Technology · doi:10.1080/17439884.2020.1798995 · Cited by 981 · see citing works
Post-Covid-19 Education and Education Technology ‘Solutionism’: a Seller’s Market
Teräs, M., Suoranta, J., Teräs, H., & Curcher, M. (2020) · Postdigital Science and Education · doi:10.1007/s42438-020-00164-x · Cited by 638 · see citing works
The datafication of teaching in Higher Education: critical issues and perspectives
Williamson, B., Bayne, S., & Shay, S. (2020) · Teaching in Higher Education · doi:10.1080/13562517.2020.1748811 · Cited by 374 · see citing works
Agricultural policy in the era of digitalisation
Ehlers, M., Huber, R., & Finger, R. (2021) · Food Policy · doi:10.1016/j.foodpol.2020.102019 · Cited by 233 · see citing works
Developing capabilities: Lifelong learning in the age of AI
Poquet, O., & de Laat, M. F. (2021) · British Journal of Educational Technology · doi:10.1111/bjet.13123 · Cited by 164 · see citing works
Chalkiadakis, A., Seremetaki, A., Kanellou, A., Kallishi, M., Morfopoulou, A., Moraitaki, M., & Mastrokoukou, S. (2024) · Education Sciences · doi:10.3390/educsci14111223 · Cited by 106 · see citing works
Castañeda, L., & Williamson, B. (2021) · Journal of New Approaches in Educational Research · doi:10.7821/naer.2021.1.703 · Cited by 108 · see citing works
Kurian, N. C. (2024) · Learning Media and Technology · doi:10.1080/17439884.2024.2367052 · Cited by 95 · see citing works
What is ‘critical’ in critical studies of edtech? Three responses
Macgilchrist, F. (2021) · Learning Media and Technology · doi:10.1080/17439884.2021.1958843 · Cited by 85 · see citing works
Governed by Edtech? Valuing Pedagogical Autonomy in a Platform Society
Kerssens, N., & van Dijck, J. (2022) · Harvard Educational Review · doi:10.17763/1943-5045-92.2.284 · Cited by 81 · see citing works
Employees’ acceptance of wearable devices: Towards a predictive model
Magni, D., Scuotto, V., Pezzi, A., & Giudice, M. D. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121022 · Cited by 67 · see citing works
Suoranta, J., Teräs, M., Teräs, H., Jandrić, P., Ledger, S., Macgilchrist, F., & Prinsloo, P. (2021) · Postdigital Science and Education · doi:10.1007/s42438-021-00260-6 · Cited by 79 · see citing works
Sperling, K., Stenliden, L., Nissen, J., & Heintz, F. (2022) · European Journal of Education · doi:10.1111/ejed.12526 · Cited by 63 · see citing works
Baker, B., Mills, K. A., McDonald, P., & Wang, L. (2023) · Teachers College Record The Voice of Scholarship in Education · doi:10.1177/01614681231191291 · Cited by 61 · see citing works
Allison, J., Hwang, G., Mayer, R. E., Πέλλας, Ν., Karnalim, O., de Freitas, S., Ng, O., Huang, Y., Hooshyar, D., Seidman, R. H., et al. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251359964 · Cited by 71 · see citing works
Rahm, L., & Skågeby, J. (2023) · British Journal of Educational Technology · doi:10.1111/bjet.13319 · Cited by 57 · see citing works
Fawns, T., Aitken, G., & Jones, D. (2020) · Postdigital Science and Education · doi:10.1007/s42438-020-00109-4 · Cited by 58 · see citing works
Artificial Intelligence in Education
Gràcia, X. G., & Gil, J. M. S. (2021) · Seminar net · doi:10.7577/seminar.4281 · Cited by 62 · see citing works
Alwahaby, H., Cukurova, M., Papamitsiou, Z. K., & Giannakos, M. N. (2022) · Springer eBooks · doi:10.1007/978-3-031-08076-0_12 · Cited by 67 · see citing works
Wise, A. F., Sarmiento, J. P., & Boothe, M. (2021) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3448139.3448210 · Cited by 46 · see citing works
Data-driven digital nudging: a systematic literature review and future agenda
Sadeghian, A. H., & Otarkhani, A. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2286535 · Cited by 56 · see citing works
Education big data and learning analytics: a bibliometric analysis
Samsul, S. A., Yahaya, N., & Abuhassna, H. (2023) · Humanities and Social Sciences Communications · doi:10.1057/s41599-023-02176-x · Cited by 65 · see citing works
Matthews, A. (2020) · Learning Media and Technology · doi:10.1080/17439884.2021.1864398 · Cited by 43 · see citing works
“We called that a behavior”: The making of institutional data
Whitman, M. (2020) · Big Data & Society · doi:10.1177/2053951720932200 · Cited by 44 · see citing works
Educating for the future? Mapping the emerging lines of precision education governance
Mertanen, K., Vainio, S., & Brunila, K. (2021) · Policy Futures in Education · doi:10.1177/14782103211049914 · Cited by 40 · see citing works
Where does AI-driven Education, in the Chinese Context and Beyond, go next?
Yuan, L. Y. (2023) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-023-00341-6 · Cited by 47 · see citing works
La Inteligencia Artificial en la educación: Big data, cajas negras y solucionismo tecnológico
Gràcia, X. G., & Gil, J. M. S. (2022) · RELATEC Revista Latinoamericana de Tecnología Educativa · doi:10.17398/1695-288x.21.1.129 · Cited by 64 · see citing works
Kumar, S., Gaur, V., & Wu, C. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-10403-z · Cited by 38 · see citing works
Chunyan, T., & Ren, C. (2025) · Scientific Reports · doi:10.1038/s41598-025-10497-x · Cited by 39 · see citing works
Aroles, J., & Kuepers, W. M. (2021) · Management Learning · doi:10.1177/13505076211053871 · Cited by 38 · see citing works
Fawns, T. (2023) · Springer eBooks · doi:10.1007/978-3-031-35469-4_52-1 · Cited by 38 · see citing works
Turning universities into data-driven organisations: seven dimensions of change
Komljenovič, J., Sellar, S., & Birch, K. (2024) · Higher Education · doi:10.1007/s10734-024-01277-z · Cited by 37 · see citing works
Shava, E. (2022) · Journal of Culture and Values in Education · doi:10.46303/jcve.2022.7 · Cited by 36 · see citing works
Digital Disruption In Teaching And Testing
Wyatt‐Smith, C., Lingard, B., & Heck, E. (2021) · Routledge eBooks · doi:10.4324/9781003045793 · Cited by 37 · see citing works
Kyambade, M., Namatovu, A., & Ssentumbwe, A. M. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2505297 · Cited by 53 · see citing works
The 2016 Manifesto for Teaching Online
(2020) · The MIT Press eBooks · doi:10.7551/mitpress/11840.003.0001 · Cited by 34 · see citing works
Decuypere, M., & Hartong, S. (2022) · Learning Media and Technology · doi:10.1080/17439884.2022.2086261 · Cited by 31 · see citing works
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Balcıoğlu, Y. S., & Artar, M. (2023) · Information Development · doi:10.1177/02666669231213023 · Cited by 30 · see citing works
Verwiebe, R., & Hagemann, S. (2024) · Information Communication & Society · doi:10.1080/1369118x.2024.2358170 · Cited by 50 · see citing works
Bock, A., Breiter, A., Hartong, S., Jarke, J., Jornitz, S., Lange, A., & Macgilchrist, F. (2023) · Springer eBooks · doi:10.1007/978-3-658-38651-1 · Cited by 31 · see citing works
Digital citizenship at school: Democracy, pragmatism and RRI
Vallès-Peris, N., & Domènech, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102448 · Cited by 29 · see citing works
Impact of Artificial Intelligence in Students’ Learning Life
Raja, S., Jebadurai, D. J., Ivan, L., Rudenko, M., Ruslan, K., & Reznik, N. P. (2024) · Studies in systems, decision and control · doi:10.1007/978-3-031-49544-1_1 · Cited by 29 · see citing works
Problems and Risks of Digitalization in Higher Education
Pashkov, M. V., & Pashkova, V. M. (2022) · Высшее образование в России · doi:10.31992/0869-3617-2022-31-22-3-40-57 · Cited by 29 · see citing works
Introduction: AI, Inclusion, and ‘Everyone Learning Everything’
Knox, J., Wang, Y.-C., & Gallagher, M. S. (2019) · Perspectives on rethinking and reforming education · doi:10.1007/978-981-13-8161-4_1 · Cited by 28 · see citing works
The new natural? Authenticity and the naturalization of educational technologies
Dishon, G. (2020) · Learning Media and Technology · doi:10.1080/17439884.2020.1845727 · Cited by 28 · see citing works
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Witzenberger, K., & Gulson, K. Ν. (2021) · Learning Media and Technology · doi:10.1080/17439884.2021.1913181 · Cited by 27 · see citing works
Apps, T., Beckman, K., & Howard, S. K. (2022) · Learning Media and Technology · doi:10.1080/17439884.2022.2160458 · Cited by 39 · see citing works
Fawns, T., & Schaepkens, S. P. C. (2022) · Teaching and Learning in Medicine · doi:10.1080/10401334.2022.2048832 · Cited by 28 · see citing works
Ortegón, C., Decuypere, M., & Williamson, B. (2024) · Research in Education · doi:10.1177/00345237241242990 · Cited by 24 · see citing works
The Impact of Immersive Learning on Teacher Effectiveness: A Systematic Study
Buragohain, D., Deng, C., Sharma, A., & Chaudhary, S. (2024) · IEEE Access · doi:10.1109/access.2024.3373541 · Cited by 24 · see citing works
Postdigital Living and Algorithms of Desire
Lacković, N. (2020) · Postdigital Science and Education · doi:10.1007/s42438-020-00141-4 · Cited by 23 · see citing works
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Forsler, I., Hayes, S., Jandrić, P., Macgilchrist, F., Selwyn, N., & Hansén, S. (2025) · Postdigital Science and Education · doi:10.1007/s42438-025-00601-9 · Cited by 22 · see citing works
Calderwood, S. J. (2025) · Postdigital Science and Education · doi:10.1007/s42438-024-00537-6 · Cited by 29 · see citing works
Education Crisis, Workforce Preparedness, and COVID‐19: Reflections and Recommendations
Krishnamoorthy, R., & Keating, K. (2021) · American Journal of Economics and Sociology · doi:10.1111/ajes.12376 · Cited by 21 · see citing works
Platformed professional(itie)s and the ongoing digital transformation of education
Hartong, S., & Decuypere, M. (2023) · Tertium Comparationis · doi:10.31244/tc.2023.01.01 · Cited by 21 · see citing works
Perrotta, C. (2021) · Journal of New Approaches in Educational Research · doi:10.7821/naer.2021.1.638 · Cited by 19 · see citing works
The construction of (good) parents (as professionals) in/through learning platforms
Hartong, S., & Manolev, J. (2023) · Tertium Comparationis · doi:10.31244/tc.2023.01.05 · Cited by 19 · see citing works
Datafied school life: the hidden commodification of digital learning
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Hummel, S. (2025) · Education Sciences · doi:10.3390/educsci15121594 · Cited by 21 · see citing works
Alwahaby, H., Cukurova, M., Papamitsiou, Z., & Giannakos, M. (2021) · doi:10.35542/osf.io/sd23y · Cited by 15 · see citing works
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Han, A., Krieger, F., & Greiff, S. (2021) · Journal of Learning Analytics · doi:10.18608/jla.2021.7288 · Cited by 16 · see citing works
de Oliveira, E. R., & Rodrigues, P. (2021) · Electronic Journal of Knowledge Management · doi:10.34190/ejkm.19.2.2459 · Cited by 15 · see citing works
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Buchanan, R. (2020) · Policy Futures in Education · doi:10.1177/1478210320910293 · Cited by 15 · see citing works
Online mathematics programs and the figured world of primary school mathematics in the digital era
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Horvath, K., & Steinberg, M. (2023) · Learning Media and Technology · doi:10.1080/17439884.2023.2219900 · Cited by 14 · see citing works
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Sobre la gobernanza digital, política digital y educación
Valenzuela-Fernández, L. A., Inga, Z. M. C., & Hipólito, E. E. D. (2020) · Eleuthera · doi:10.17151/eleu.2020.22.2.6 · Cited by 12 · see citing works
Digital Technologies as a Means of Improving the Efficiency of Higher Education
Sharlovych, Z., Vilchynska, L., Danylyuk, S. S., Huba, B., & Задільська, Г. (2023) · International Journal of Information and Education Technology · doi:10.18178/ijiet.2023.13.8.1923 · Cited by 12 · see citing works
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Whitman, M. (2021) · Science and Engineering Ethics · doi:10.1007/s11948-021-00346-1 · Cited by 14 · see citing works
Labraña, J., & Ponce, E. R. (2026) · Journal of Organizational Change Management · doi:10.1108/jocm-02-2025-0157 · Cited by 13 · see citing works
Gidiotis, I. (2026) · Futures · doi:10.1016/j.futures.2026.103762 · Cited by 12 · see citing works
Exploring student and family concerns and confidence in BigTech digital platforms in public schools
Rivera-Vargas, P., Calderón-Garrido, D., Jacovkis, J., & Parcerisa, L. (2024) · Journal of New Approaches in Educational Research · doi:10.1007/s44322-023-00003-4 · Cited by 15 · see citing works
Joecks, L. (2024) · Research in Education · doi:10.1177/00345237241242993 · Cited by 11 · see citing works
Maneuvering constellations of valuation: a critical investigation of the edtech startup sector
Decuypere, M., Hartong, S., Brandau, N., Joecks, L., Loft-Akhoondi, A., Ortegón, C., Tierens, T., & Vanermen, L. (2024) · Critical Studies in Education · doi:10.1080/17508487.2024.2362196 · Cited by 11 · see citing works
Moll, I., Agherdien, N., Hoosen, N., Na-Allah, D. M., Nkambule, T., Martin, C. D., Pillay, P., Martin, M., Nkomo, S. A., Phakathi, N., et al. (2022) · doi:10.4102/aosis.2022.bk376 · Cited by 11 · see citing works
Higher Education in a Post-Pandemic World
Τsantopoulos, G., Karasmanaki, E., Ιωάννου, Κ., & Kapnia, M. (2022) · Education Sciences · doi:10.3390/educsci12120856 · Cited by 11 · see citing works
Breaking the Magic of Automation and Augmentation in Swedish Classrooms
Stenliden, L., & Sperling, K. (2024) · Nordisk tidsskrift for pedagogikk og kritikk · doi:10.23865/ntpk.v10.6174 · Cited by 10 · see citing works
Kucirkova, N., Toda, Y., & Flewitt, R. (2020) · Technology, Knowledge and Learning · doi:10.1007/s10758-020-09465-3 · Cited by 7 · see citing works
Ramiel, H., & Dishon, G. (2021) · Discourse Studies in the Cultural Politics of Education · doi:10.1080/01596306.2021.1953444 · Cited by 10 · see citing works
Helgetun, J. B., & Decuypere, M. (2023) · Learning Media and Technology · doi:10.1080/17439884.2023.2226876 · Cited by 9 · see citing works
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Friesen, N., Forsman, M., & Forsler, I. (2025) · Postdigital Science and Education · doi:10.1007/s42438-025-00559-8 · Cited by 9 · see citing works
Manzanares, M. C. S., Sánchez, R. M., & González, Á. A. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17093315 · Cited by 9 · see citing works
Haugsbakk, G. (2021) · Seminar net · doi:10.7577/seminar.4303 · Cited by 9 · see citing works
Horvath, K., Steinberg, M., & Frei, A. I. (2023) · Learning Media and Technology · doi:10.1080/17439884.2023.2193412 · Cited by 9 · see citing works
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Schiefner-Rohs, M., Hofhues, S., & Breiter, A. (2021) · MedienPädagogik Zeitschrift für Theorie und Praxis der Medienbildung · doi:10.21240/mpaed/44/2021.10.25.x · Cited by 9 · see citing works
Delahunty, T. (2024) · Educational Philosophy and Theory · doi:10.1080/00131857.2024.2435333 · Cited by 9 · see citing works
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Forsler, I., Bardone, E., Forsman, M., & Mõttus, P. (2025) · Postdigital science and education · doi:10.1007/978-3-032-01539-6_11 · Cited by 8 · see citing works
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Mertala, P. (2021) · Kasvatus & Aika · doi:10.33350/ka.100161 · Cited by 9 · see citing works
Darragh, L. (2021) · Research in Mathematics Education · doi:10.1080/14794802.2021.1993977 · Cited by 8 · see citing works
Hacia la enseñanza en línea. Estudio mixto de una reestructuración metodológica en pandemia
González-Villa, Á., Regueira, U., & Barujel, A. G. (2022) · Campus Virtuales · doi:10.54988/cv.2022.2.973 · Cited by 8 · see citing works
- Authors
- Knox, J., Williamson, B., & Bayne, S.
- Affiliations
- University of Edinburgh (GB)
- Centre for Research in Digital Education, University of Edinburgh, Edinburgh, UK
- Corresponding author
- Knox, Jeremy
- Venue
- Learning Media and Technology
- Publisher
- Informa UK Limited
- Published
- 2019-06-10
- Volume
- 45
- Issue
- 1
- Pages
- 31-45
- ISSN
- 1743-9884 (ISSN-L)
- 1743-9892
- OpenAlex
- W2951066188
- Cited by
- 261
- References
- 47
- Citations by year
- 2026: 46 · 2025: 46 · 2024: 34 · 2023: 46 · 2022: 39 · 2021: 34 · 2020: 15 · 2019: 1
- FWCI
- 27.69
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- Locations
- Learning Media and Technology (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Political Science and International Relations › Global Educational Policies and Reforms
- Keywords
- learnification, datafication, machine learning in education, nudging, choice architecture, behavioral economics, behaviorism, educational software design, educational data science, student independence, learner behavior, big data in education
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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