Digital learning fatigue and its psychological consequences among tertiary students: a systematic review

Authors

DOI:

https://doi.org/10.55056/etq.1056

Keywords:

digital learning fatigue, online education, tertiary students, psychological wellbeing, cognitive load, resilience, systematic review

Abstract

This systematic review synthesises empirical evidence on digital learning fatigue (DLF) and its psychological consequences among tertiary students in the post-pandemic era. It addresses prevalence patterns, contributing factors, mental health impacts, and moderating variables shaping fatigue experiences across global higher education contexts. Following PRISMA-2020 guidelines, a multi-database search (Scopus, Web of Science, PubMed, ERIC, and Google Scholar) identified 2,315 records (January 2020-May 2025). Twenty-two studies met the inclusion criteria after rigourous screening and quality appraisal using the Newcastle-Ottawa Scale. Data were narratively and thematically synthesised to integrate quantitative prevalence evidence and qualitative psychosocial insights. Across studies, DLF affected 45-75 % of tertiary students and manifested through intertwined cognitive, emotional, and behavioural symptoms. The most common psychological outcomes were anxiety (68 %), stress (64 %), and depressive symptoms (55 %). Fatigue consistently reduced motivation, concentration, and academic engagement while elevating burnout risk. Gender (higher in females), academic discipline (arts/humanities > STEM), and screen exposure (6-8 h+ per day) amplified fatigue, whereas resilience and adaptive coping moderated adverse effects. Cross-regional variations reflected technological infrastructure and institutional preparedness. The review identifies an urgent need for evidence-based interventions such as balanced asynchronous-synchronous workloads, resilience-building programs, ergonomic design standards, and institutional mental-health support. This is among the first post-pandemic systematic syntheses to conceptualise DLF as a multidimensional psychosocial syndrome rather than a transient technological stressor. By integrating cognitive load, self-determination, and conservation-of-resources perspectives, the review offers an ecological framework for reducing fatigue and promoting sustainable digital learning wellbeing.

Downloads

Download data is not yet available.
Abstract views: 78 / PDF views: 52

References

Alarabiat, A., 2024. The impact of online learning fatigue on students’ continuous use of online learning. Journal of Theoretical and Applied Information Technology, 102(20), pp.7423–7432. Available from: https://jatit.org/volumes/Vol102No20/13Vol102No20.pdf.

Alyoubi, A., Halstead, E.J., Zambelli, Z. and Dimitriou, D., 2021. The Impact of the COVID-19 Pandemic on Students’ Mental Health and Sleep in Saudi Arabia. International Journal of Environmental Research and Public Health, 18(17), p.9344. Available from: https://doi.org/10.3390/ijerph18179344. DOI: https://doi.org/10.3390/ijerph18179344

An, R., Qian, G., Mumtaz, A., Alotaibi, K.A. and Wang, X., 2025. Digital fatigue and academic resilience among university students with grit and flexibility as mediators. Scientific Reports, 15, p.45407. Available from: https://doi.org/10.1038/s41598-025-29313-7. DOI: https://doi.org/10.1038/s41598-025-29313-7

Anderson, M. and Perrin, A., 2018. Nearly one-in-five teens can’t always finish their homework because of the digital divide. Pew Research Center. Available from: https://www.pewresearch.org/short-reads/2018/10/26/nearly-one-in-five-teens-cant-always-finish-their-homework-because-of-the-digital-divide/.

Arnett, J.J., 2000. Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), pp.469–480. Available from: https://doi.org/10.1037/0003-066X.55.5.469. DOI: https://doi.org/10.1037/0003-066X.55.5.469

Auerbach, R.P., Mortier, P., Bruffaerts, R., Alonso, J., Benjet, C., Cuijpers, P., Demyttenaere, K., Ebert, D.D., Green, J.G., Hasking, P., Murray, E., Nock, M.K., Pinder-Amaker, S., Sampson, N.A., Stein, D.J., Vilagut, G., Zaslavsky, A.M. and Kessler, R.C., 2018. WHO World Mental Health Surveys International College Student Project: Prevalence and distribution of mental disorders. Journal of Abnormal Psychology, 127(7), pp.623–638. Available from: https://doi.org/10.1037/abn0000362. DOI: https://doi.org/10.1037/abn0000362

Bailenson, J.N., 2021. Nonverbal overload: A theoretical argument for the causes of Zoom fatigue. Technology, Mind, and Behavior, 2(1), pp.1–6. Available from: https://doi.org/10.1037/tmb0000030. DOI: https://doi.org/10.1037/tmb0000030

Baltà-Salvador, R., Olmedo-Torre, N., Peña, M. and Renta-Davids, A.I., 2021. Academic and emotional effects of online learning during the COVID-19 pandemic on engineering students. Education and Information Technologies, 26(6), pp.7407–7434. Available from: https://doi.org/10.1007/s10639-021-10593-1. DOI: https://doi.org/10.1007/s10639-021-10593-1

Bandura, A., 1997. Self-Efficacy: The Exercise of Control. New York: W. H. Freeman and Company.

Barkley, R.A., ed., 2018. Attention-Deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment. 4th ed. Guilford Press.

Bernard, R.M., Abrami, P.C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P.A., Fiset, M. and Huang, B., 2004. How Does Distance Education Compare With Classroom Instruction? A Meta-Analysis of the Empirical Literature. Review of Educational Research, 74(3), pp.379–439. Available from: https://doi.org/10.3102/00346543074003379. DOI: https://doi.org/10.3102/00346543074003379

Besser, A., Flett, G.L. and Zeigler-Hill, V., 2022. Adaptability to a sudden transition to online learning during the COVID-19 pandemic: Understanding the challenges for students. Scholarship of Teaching and Learning in Psychology, 8(2), pp.85–105. Available from: https://doi.org/10.1037/stl0000198. DOI: https://doi.org/10.1037/stl0000198

Boursier, V., Gioia, F. and Griffiths, M.D., 2020. Objectified Body Consciousness, Body Image Control in Photos, and Problematic Social Networking: The Role of Appearance Control Beliefs. Frontiers in Psychology, 11, p.147. Available from: https://doi.org/10.3389/fpsyg.2020.00147. DOI: https://doi.org/10.3389/fpsyg.2020.00147

Broadbent, J. and Poon, W.L., 2015. Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, pp.1–13. Available from: https://doi.org/10.1016/j.iheduc.2015.04.007. DOI: https://doi.org/10.1016/j.iheduc.2015.04.007

Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J. and Zheng, J., 2020. The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, p.112934. Available from: https://doi.org/10.1016/j.psychres.2020.112934. DOI: https://doi.org/10.1016/j.psychres.2020.112934

Carello, J. and Butler, L.D., 2015. Practicing What We Teach: Trauma-Informed Educational Practice. Journal of Teaching in Social Work, 35(3), pp.262–278. Available from: https://doi.org/10.1080/08841233.2015.1030059. DOI: https://doi.org/10.1080/08841233.2015.1030059

Castro-Alonso, J.C., Ayres, P. and Paas, F., 2016. Comparing apples and oranges? A critical look at research on learning from statics versus animations. Computers & Education, 102, pp.234–243. Available from: https://doi.org/10.1016/j.compedu.2016.09.004. DOI: https://doi.org/10.1016/j.compedu.2016.09.004

Charoenporn, V., Hanvivattanakul, S., Jongmekwamsuk, K., Lenavat, R., Hanvivattanakul, K. and Charernboon, T., 2024. Zoom fatigue related to online learning among medical students in Thailand: Prevalence, predictors, and association with depression. F1000Research, 13, p.617. Available from: https://doi.org/10.12688/f1000research.146084.2. DOI: https://doi.org/10.12688/f1000research.146084.1

Chen, C.M., Wang, J.Y. and Yu, C.M., 2017. Assessing the attention levels of students by using a novel attention aware system based on brainwave signals. British Journal of Educational Technology, 48(2), pp.348–369. Available from: https://doi.org/10.1111/bjet.12359. DOI: https://doi.org/10.1111/bjet.12359

Clark, L.A. and Watson, D., 2019. Constructing validity: New developments in creating objective measuring instruments. Psychological Assessment, 31(12), pp.1412–1427. Available from: https://doi.org/10.1037/pas0000626. DOI: https://doi.org/10.1037/pas0000626

Clark, S.C., 2000. Work/Family Border Theory: A New Theory of Work/Family Balance. Human Relations, 53(6), pp.747–770. Available from: https://doi.org/10.1177/0018726700536001. DOI: https://doi.org/10.1177/0018726700536001

Craig, L. and Churchill, B., 2021. Dual-earner parent couples’ work and care during COVID-19. Gender, Work & Organization, 28(S1), pp.66–79. Available from: https://doi.org/10.1111/gwao.12497. DOI: https://doi.org/10.1111/gwao.12497

Daumiller, M., Rinas, R., Hein, J., Janke, S., Dickhäuser, O. and Dresel, M., 2021. Shifting from face-to-face to online teaching during COVID-19: The role of university faculty achievement goals for attitudes towards this sudden change, and their relevance for burnout/engagement and student evaluations of teaching quality. Computers in Human Behavior, 118, p.106677. Available from: https://doi.org/10.1016/j.chb.2020.106677. DOI: https://doi.org/10.1016/j.chb.2020.106677

de Oliveira Kubrusly Sobral, J.B., Lima, D.L.F., Lima Rocha, H.A., de Brito, E.S., Duarte, L.H.G., Bento, L.B.B.B. and Kubrusly, M., 2022. Active methodologies association with online learning fatigue among medical students. BMC Medical Education, 22(1), p.74. Available from: https://doi.org/10.1186/s12909-022-03143-x. DOI: https://doi.org/10.1186/s12909-022-03143-x

DeLeeuw, K.E. and Mayer, R.E., 2008. A comparison of three measures of cognitive load: Evidence for separable measures of intrinsic, extraneous, and germane load. Journal of Educational Psychology, 100(1), pp.223–234. Available from: https://doi.org/10.1037/0022-0663.100.1.223. DOI: https://doi.org/10.1037/0022-0663.100.1.223

Deniz, M.E., Satici, S.A., Doenyas, C. and Griffiths, M.D., 2022. Zoom Fatigue, Psychological Distress, Life Satisfaction, and Academic Well-Being. Cyberpsychology, Behavior, and Social Networking, 25(5), pp.270–277. Available from: https://doi.org/10.1089/cyber.2021.0249. DOI: https://doi.org/10.1089/cyber.2021.0249

Fardouly, J. and Vartanian, L.R., 2016. Social Media and Body Image Concerns: Current Research and Future Directions. Current Opinion in Psychology, 9, pp.1–5. Social media and applications to health behavior. Available from: https://doi.org/10.1016/j.copsyc.2015.09.005. DOI: https://doi.org/10.1016/j.copsyc.2015.09.005

Fauville, G., Luo, M., Queiroz, A.C.M., Bailenson, J.N. and Hancock, J., 2021. Nonverbal Mechanisms Predict Zoom Fatigue and Explain Why Women Experience Higher Levels than Men. SSRN Electronic Journal. Available from: https://doi.org/10.2139/ssrn.3820035. DOI: https://doi.org/10.2139/ssrn.3820035

Fridkin, L., Bover Fonts, N., Quy, K. and Zwiener-Collins, N., 2023. Understanding effects of COVID-19 on undergraduate academic stress, motivation and coping over time. Higher Education Quarterly, 77(4), pp.623–637. Available from: https://doi.org/10.1111/hequ.12425. DOI: https://doi.org/10.1111/hequ.12425

Ghanem, E.A., Elhussiney, D.M. and Elbadawy, D.A.G.E.D., 2022. Prevalence, Risk Factors of Videoconference Fatigue, and Its Relation to Psychological Morbidities Among Ain Shams Medical Students, Egypt. The Egyptian Journal of Community Medicine, 41(2), pp.111–117. https://web.archive.org/web/20251115183041/https://ejcm.journals.ekb.eg/article_271157_39511244dcbc43705486f3f9bd18365e.pdf, Available from: https://doi.org/10.21608/ejcm.2022.159150.1234. DOI: https://doi.org/10.21608/ejcm.2022.159150.1234

Gin, L.E., Guerrero, F.A., Brownell, S.E., Cooper, K.M. and Momsen, J., 2021. COVID-19 and Undergraduates with Disabilities: Challenges Resulting from the Rapid Transition to Online Course Delivery for Students with Disabilities in Undergraduate STEM at Large-Enrollment Institutions. CBE—Life Sciences Education, 20(3), p.ar36. Available from: https://doi.org/10.1187/cbe.21-02-0028. DOI: https://doi.org/10.1187/cbe.21-02-0028

Göldağ, B., 2022. An Investigation of the Relationship between University Students’ Digital Burnout Levels and Perceived Stress Levels. Available from: https://doi.org/10.53850/joltida.958039. DOI: https://doi.org/10.53850/joltida.958039

Gonzalez, T., de la Rubia, M.A., Hincz, K.P., Comas-Lopez, M., Subirats, L., Fort, S. and Sacha, G.M., 2020. Influence of COVID-19 confinement on students’ performance in higher education. PLoS ONE, 15(10), p.e0239490. Available from: https://doi.org/10.1371/journal.pone.0239490. DOI: https://doi.org/10.1371/journal.pone.0239490

Graham, C.R., 2006. Blended Learning Systems: Definition, Current Trends, and Future DirectionsDirections. In: C.J. Bonk and C.R. Graham, eds. The Handbook of Blended Learning: Global Perspectives, Local Designs. San Francisco, CA: Pfeiffer Publishing, pp.3–21. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=9100&context=facpub.

Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S. and Ziegler, A., 2022. Digital readiness and its effects on higher education students’ socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 54(2), pp.267–280. Available from: https://doi.org/10.1080/15391523.2020.1846147. DOI: https://doi.org/10.1080/15391523.2020.1846147

Hobfoll, S.E., 1989. Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), pp.513–524. Available from: https://doi.org/10.1037/0003-066x.44.3.513. DOI: https://doi.org/10.1037/0003-066X.44.3.513

Hodges, C., Moore, S., Lockee, B., Trust, T. and Bond, A., 2020. The Difference Between Emergency Remote Teaching and Online Learning. EDUCAUSE Review. Available from: https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning.

Hofstede, G., 2011. Dimensionalizing Cultures: The Hofstede Model in Context. Online Readings in Psychology and Culture, 2(1). Available from: https://doi.org/10.9707/2307-0919.1014. DOI: https://doi.org/10.9707/2307-0919.1014

Honicke, T. and Broadbent, J., 2016. The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, pp.63–84. Available from: https://doi.org/10.1016/j.edurev.2015.11.002. DOI: https://doi.org/10.1016/j.edurev.2015.11.002

Inan, F.A., Sosi, E.T., Unal, D., Marzban, F. and Bayne, G.A., 2025. The Impact of Coursework Demand and Learning Engagement on Mental Fatigue in Online College Students. International Journal of Environmental Research and Public Health, 22(12), p.1860. Available from: https://doi.org/10.3390/ijerph22121860. DOI: https://doi.org/10.3390/ijerph22121860

Kalyuga, S. and Singh, A.M., 2016. Rethinking the Boundaries of Cognitive Load Theory in Complex Learning. Educational Psychology Review, 28(4), pp.831–852. Available from: https://doi.org/10.1007/s10648-015-9352-0. DOI: https://doi.org/10.1007/s10648-015-9352-0

Kaplan, A.M. and Haenlein, M., 2016. Higher education and the digital revolution: About MOOCs, SPOCs, social media, and the Cookie Monster. Business Horizons, 59(4), pp.441–450. Available from: https://doi.org/10.1016/j.bushor.2016.03.008. DOI: https://doi.org/10.1016/j.bushor.2016.03.008

Karr-Wisniewski, P. and Lu, Y., 2010. When more is too much: Operationalizing technology overload and exploring its impact on knowledge worker productivity. Computers in Human Behavior, 26(5), pp.1061–1072. Available from: https://doi.org/10.1016/j.chb.2010.03.008. DOI: https://doi.org/10.1016/j.chb.2010.03.008

Kim, H., Kim, S.J. and Hwang, S., 2024. Visual display terminal syndrome and its associated factors among university students during the COVID-19 pandemic. Work, 77(1), pp.23–36. Available from: https://doi.org/10.3233/WOR-220265. DOI: https://doi.org/10.3233/WOR-220265

Klimova, B. and Pikhart, M., 2025. Exploring the effects of artificial intelligence on student and academic well-being in higher education: a mini-review. Frontiers in Psychology, 16, p.1498132. Available from: https://doi.org/10.3389/fpsyg.2025.1498132. DOI: https://doi.org/10.3389/fpsyg.2025.1498132

Langner, R., Steinborn, M.B., Chatterjee, A., Sturm, W. and Willmes, K., 2010. Mental fatigue and temporal preparation in simple reaction-time performance. Acta Psychologica, 133(1), pp.64–72. Available from: https://doi.org/10.1016/j.actpsy.2009.10.001. DOI: https://doi.org/10.1016/j.actpsy.2009.10.001

Lee, J., 2020. Mental health effects of school closures during COVID-19. The Lancet Child & Adolescent Health, 4(6), p.421. Available from: https://doi.org/10.1016/S2352-4642(20)30109-7. DOI: https://doi.org/10.1016/S2352-4642(20)30109-7

Li, H. and Yang, J., 2025. Managing online learning burnout via investigating the role of loneliness during COVID-19. BMC Psychology, 13(1), p.151. Available from: https://doi.org/10.1186/s40359-025-02419-3. DOI: https://doi.org/10.1186/s40359-025-02419-3

Lipson, S.K., Lattie, E.G. and Eisenberg, D., 2019. Increased Rates of Mental Health Service Utilization by U.S. College Students: 10-Year Population-Level Trends (2007–2017). Psychiatric Services, 70(1), pp.60–63. Available from: https://doi.org/10.1176/appi.ps.201800332. DOI: https://doi.org/10.1176/appi.ps.201800332

Llanes-Castillo, A., Pérez-Rodríguez, P., Reyes-Valdéz, M.L. and Cervantes-López, M.J., 2022. Burnout: Efectos del confinamiento en estudiantes universitarios en México. Revista de Ciencias Sociales, 28(3), pp.69–81. Available from: https://doi.org/10.31876/rcs.v28i3.38451. DOI: https://doi.org/10.31876/rcs.v28i3.38451

Madigan, D.J. and Curran, T., 2021. Does Burnout Affect Academic Achievement? A Meta-Analysis of over 100,000 Students. Educational Psychology Review, 33(2), pp.387–405. Available from: https://doi.org/10.1007/s10648-020-09533-1. DOI: https://doi.org/10.1007/s10648-020-09533-1

Maslach, C. and Leiter, M.P., 2016. Understanding the burnout experience: recent research and its implications for psychiatry. World Psychiatry, 15(2), pp.103–111. Available from: https://doi.org/10.1002/wps.20311. DOI: https://doi.org/10.1002/wps.20311

Mayer, R.E., 2014. Cognitive Theory of Multimedia Learning. In: R.E. Mayer, ed. The Cambridge Handbook of Multimedia Learning. 2nd ed. Cambridge University Press, Cambridge Handbooks in Psychology, pp.43–71. Available from: https://doi.org/10.1017/cbo9781139547369.005. DOI: https://doi.org/10.1017/CBO9781139547369.005

Mayer, R.E., 2017. Using multimedia for e-learning. Journal of Computer Assisted Learning, 33(5), pp.403–423. Available from: https://doi.org/10.1111/jcal.12197. DOI: https://doi.org/10.1111/jcal.12197

Mayer, R.E. and Moreno, R., 2003. Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educational Psychologist, 38(1), pp.43–52. Available from: https://doi.org/10.1207/s15326985ep3801_6. DOI: https://doi.org/10.1207/S15326985EP3801_6

Means, B. and Neisler, J., 2021. Teaching and Learning in the Time of COVID: The Student Perspective. Online Learning, 25(1), pp.8–27. Available from: https://doi.org/10.24059/olj.v25i1.2496. DOI: https://doi.org/10.24059/olj.v25i1.2496

Means, B., Neisler, J. and Langer Research Associates, 2020. Suddenly Online: A National Survey of Undergraduates During the COVID-19 Pandemic. San Mateo, CA: Digital Promise. Available from: https://doi.org/10.51388/20.500.12265/98. DOI: https://doi.org/10.51388/20.500.12265/98

Menard, S., 2002. Longitudinal Research. 2nd ed. Sage Publications. DOI: https://doi.org/10.4135/9781412984867

Nesher Shoshan, H. and Wehrt, W., 2022. Understanding “Zoom fatigue”: A mixed-method approach. Applied Psychology, 71(3), pp.827–852. Available from: https://doi.org/10.1111/apps.12360. DOI: https://doi.org/10.1111/apps.12360

Nilsen, P., 2015. Making sense of implementation theories, models and frameworks. Implementation Science, 10(1), p.53. Available from: https://doi.org/10.1186/s13012-015-0242-0. DOI: https://doi.org/10.1186/s13012-015-0242-0

Oleksiyenko, A., Blanco, G., Hayhoe, R., Jackson, L., Lee, J., Metcalfe, A., Sivasubramaniam, M. and Zha, Q., 2021. Comparative and international higher education in a new key? Thoughts on the post-pandemic prospects of scholarship. Compare: A Journal of Comparative and International Education, 51(4), pp.612–628. Available from: https://doi.org/10.1080/03057925.2020.1838121. DOI: https://doi.org/10.1080/03057925.2020.1838121

Page, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D. and Moher, D., 2021. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, p.n71. Available from: https://doi.org/10.1136/bmj.n71. DOI: https://doi.org/10.1136/bmj.n71

Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P., 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), pp.879–903. Available from: https://doi.org/10.1037/0021-9010.88.5.879. DOI: https://doi.org/10.1037/0021-9010.88.5.879

Ra, Y.A. and Shin, K., 2025. An Investigation into Academic Stress and Coping Strategies of South Korean Third Culture Kid (TCK) College Students. Behavioral Sciences, 15(3), p.316. Available from: https://doi.org/10.3390/bs15030316. DOI: https://doi.org/10.3390/bs15030316

Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L. and Koole, M., 2021. Balancing Technology, Pedagogy and the New Normal: Post-pandemic Challenges for Higher Education. Postdigital Science and Education, 3(3), pp.715–742. Available from: https://doi.org/10.1007/s42438-021-00249-1. DOI: https://doi.org/10.1007/s42438-021-00249-1

Reed, H.C., 2022. E-Learning Fatigue and the Cognitive, Educational, and Emotional Impacts on Communication Sciences and Disorders Students During COVID-19. Perspectives of the ASHA Special Interest Groups, 7(6), pp.1885–1902. Available from: https://doi.org/10.1044/2022_persp-22-00049. DOI: https://doi.org/10.1044/2022_PERSP-22-00049

Richardson, M., Abraham, C. and Bond, R., 2012. Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), pp.353–387. Available from: https://doi.org/10.1037/a0026838. DOI: https://doi.org/10.1037/a0026838

Riedl, R., 2012. On the biology of technostress: literature review and research agenda. SIGMIS Database, 44(1), p.18–55. Available from: https://doi.org/10.1145/2436239.2436242. DOI: https://doi.org/10.1145/2436239.2436242

Riedl, R., 2022. On the stress potential of videoconferencing: Definition and root causes of Zoom fatigue. Electronic Markets, 32(1), pp.153–177. Available from: https://doi.org/10.1007/s12525-021-00501-3. DOI: https://doi.org/10.1007/s12525-021-00501-3

Romero-Rodríguez, J.M., Hinojo-Lucena, F.J., Kopecký, K. and García-González, A., 2023. Fatiga digital en estudiantes universitarios como consecuencia de la enseñanza online durante la pandemia Covid-19. Educación XX1, 26(2), pp.165–184. Available from: https://doi.org/10.5944/educxx1.34530. DOI: https://doi.org/10.5944/educxx1.34530

Rosenfield, M., 2016. Computer vision syndrome (a.k.a. digital eye strain). Optometry in Practice, 17(1), pp.1–10. Available from: https://www.researchgate.net/publication/295902618.

Rutkowska, A., Cieślik, B., Tomaszczyk, A. and Szczepańska-Gieracha, J., 2022. Mental Health Conditions Among E-Learning Students During the COVID-19 Pandemic. Frontiers in Public Health, 10, p.871934. Available from: https://doi.org/10.3389/fpubh.2022.871934. DOI: https://doi.org/10.3389/fpubh.2022.871934

Ryan, R.M. and Deci, E.L., 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), pp.68–78. Available from: https://doi.org/10.1037/0003-066x.55.1.68. DOI: https://doi.org/10.1037//0003-066X.55.1.68

Salim, J., Tandy, S., Arnindita, J.N., Wibisono, J.J., Haryanto, M.R. and Wibisono, M.G., 2022. Zoom fatigue and its risk factors in online learning during the COVID-19 pandemic. Medical Journal of Indonesia, 31(1), pp.13–19. Available from: https://doi.org/10.13181/mji.oa.225703. DOI: https://doi.org/10.13181/mji.oa.225703

Salmela-Aro, K., Kiuru, N., Leskinen, E. and Nurmi, J.E., 2009. School Burnout Inventory (SBI): Reliability and Validity. European Journal of Psychological Assessment, 25(1), pp.48–57. Available from: https://doi.org/10.1027/1015-5759.25.1.48. DOI: https://doi.org/10.1027/1015-5759.25.1.48

Salmela-Aro, K. and Read, S., 2017. Study engagement and burnout profiles among Finnish higher education students. Burnout Research, 7, pp.21–28. Available from: https://doi.org/10.1016/j.burn.2017.11.001. DOI: https://doi.org/10.1016/j.burn.2017.11.001

Sawant, N.S., Vinchurkar, P., Kolwankar, S., Patil, T., Rathi, K. and Urkude, J., 2023. Online teaching, learning, and health outcomes: Impact on medical undergraduate students. Industrial Psychiatry Journal, 32(1), pp.59–64. Available from: https://doi.org/10.4103/ipj.ipj_52_22. DOI: https://doi.org/10.4103/ipj.ipj_52_22

Selwyn, N., 2016. Is Technology Good for Education? Cambridge, UK: Polity Press.

Sheppard, A.L. and Wolffsohn, J.S., 2018. Digital eye strain: Prevalence, measurement and amelioration. BMJ Open Ophthalmology, 3(1), p.e000146. Available from: https://doi.org/10.1136/bmjophth-2018-000146. DOI: https://doi.org/10.1136/bmjophth-2018-000146

Shin, H., Puig, A., Lee, J., Lee, J.H. and Lee, S.M., 2011. Cultural validation of the Maslach Burnout Inventory for Korean students. Asia Pacific Education Review, 12(4), pp.633–639. Available from: https://doi.org/10.1007/s12564-011-9164-y. DOI: https://doi.org/10.1007/s12564-011-9164-y

Son, C., Hegde, S., Smith, A., Wang, X. and Sasangohar, F., 2020. Effects of COVID-19 on College Students’ Mental Health in the United States: Interview Survey Study. Journal of Medical Internet Research, 22(9), p.e21279. Available from: https://doi.org/10.2196/21279. DOI: https://doi.org/10.2196/21279

Sweller, J., 1988. Cognitive Load During Problem Solving: Effects on Learning. Cognitive Science, 12(2), pp.257–285. Available from: https://doi.org/10.1207/s15516709cog1202_4. DOI: https://doi.org/10.1207/s15516709cog1202_4

Sweller, J., van Merrienboer, J.J.G. and Paas, F.G.W.C., 1998. Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), pp.251–296. Available from: https://doi.org/10.1023/A:1022193728205. DOI: https://doi.org/10.1023/A:1022193728205

Tuğtekin, U., 2023. Factors influencing online learning fatigue among blended learners in higher education. Journal of Educational Technology and Online Learning, 6(1), pp.16–32. Available from: https://doi.org/10.31681/jetol.1161386. DOI: https://doi.org/10.31681/jetol.1161386

UNESCO, 2023. COVID-19 Educational Disruption and Response. United Nations Educational, Scientific and Cultural Organization. Available from: https://www.unesco.org/en/articles/covid-19-educational-disruption-and-response.

Upadhyaya, P. and Vrinda, 2021. Impact of technostress on academic productivity of university students. Education and Information Technologies, 26(2), pp.1647–1664. Available from: https://doi.org/10.1007/s10639-020-10319-9. DOI: https://doi.org/10.1007/s10639-020-10319-9

van Deursen, A.J.A.M. and Helsper, E.J., 2015. The Third-Level Digital Divide: Who Benefits Most from Being Online? In: L. Robinson, S.R. Cotten, J. Schultz, T.M. Hale and A. Williams, eds. Communication and Information Technologies Annual. Emerald Group Publishing Limited, Studies in Media and Communications, vol. 10, pp.29–52. Available from: https://doi.org/10.1108/s2050-206020150000010002. DOI: https://doi.org/10.1108/S2050-206020150000010002

Villarroel, V., Bloxham, S., Bruna, D., Bruna, C. and Herrera-Seda, C., 2018. Authentic assessment: Creating a blueprint for course design. Assessment & Evaluation in Higher Education, 43(5), pp.840–854. Available from: https://doi.org/10.1080/02602938.2017.1412396. DOI: https://doi.org/10.1080/02602938.2017.1412396

Wang, X., Hegde, S., Son, C., Keller, B., Smith, A. and Sasangohar, F., 2020. Investigating Mental Health of US College Students During the COVID-19 Pandemic: Cross-Sectional Survey Study. Journal of Medical Internet Research, 22(9), p.e22817. Available from: https://doi.org/10.2196/22817. DOI: https://doi.org/10.2196/22817

Watermeyer, R., Crick, T., Knight, C. and Goodall, J., 2021. COVID-19 and digital disruption in UK universities: afflictions and affordances of emergency online migration. Higher Education, 81(3), pp.623–641. Available from: https://doi.org/10.1007/s10734-020-00561-y. DOI: https://doi.org/10.1007/s10734-020-00561-y

Downloads

Published

2026-06-20

Data Availability Statement

The article and supplementary materials contain the original contributions to the study; for further information, contact the corresponding author.

Issue

Section

Articles

How to Cite

Okpako, E., Adewuyi, H., Fehintola, V., Ojuolape, M., Raji, N., Adegoke, A. and Umanhonlen, S., 2026. Digital learning fatigue and its psychological consequences among tertiary students: a systematic review. Educational Technology Quarterly [Online], 2026(2), pp.99–128. Available from: https://doi.org/10.55056/etq.1056 [Accessed 4 August 2026].
Received 2025-07-15
Accepted 2025-12-06
Published 2026-06-20