Working memory and generative AI tools in higher education: A systematic review
Main Article Content
Abstract
Generative artificial intelligence (GenAI) tools have rapidly permeated higher education, yet their cognitive consequences for working memory, cognitive offloading, and higher-order thinking remain insufficiently synthesized. This systematic review, conducted in accordance with PRISMA 2020 guidelines, aimed to consolidate and critically evaluate empirical and theoretical evidence examining GenAI's effects on university students' cognitive functioning. A comprehensive search across six bibliographic databases covering 2023 to 2025 yielded 27 eligible peer-reviewed studies, appraised using design-matched quality instruments including RoB 2, AMSTAR-2, and MMAT. Findings reveal that unrestricted GenAI use measurably impairs long-term knowledge retention and critical thinking by substituting for the generative cognitive effort essential to durable memory encoding. However, structured, metacognitively scaffolded AI integration demonstrably preserves cognitive engagement and may enhance learning outcomes. Humanities students demonstrated disproportionate vulnerability to cognitive decline relative to STEM peers. Institutional policy frameworks, discipline-specific pedagogical redesign, and deliberate scaffolding strategies are identified as essential mitigating responses. The review concludes that cognitively informed, policy-guided GenAI integration represents the most defensible institutional approach, while urgent calls are made for longitudinal experimental research to establish stronger causal evidence.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
You are free to: Share — copy and redistribute the material in any medium or format. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
How to Cite
Share
References
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(1), 10. https://doi.org/10.1186/s41239-024-00444-7
Almarzouki, A. F. (2024). Stress, working memory, and academic performance: a neuroscience perspective. Stress, 27(1), 2364333. https://doi.org/10.1080/10253890.2024.2364333
Alshamy, A., Al-Harthi, A. S. A., & Abdullah, S. (2025). Perceptions of Generative AI Tools in Higher Education: Insights from Students and Academics at Sultan Qaboos University. Education Sciences, 15(4), 501. https://doi.org/10.3390/educsci15040501
Amzil, A. (2022). Working memory capacity, cognitive regulation, and their relationship to academic achievement in university students. Journal of Education and Learning, 11(6), 133. https://doi.org/10.5539/jel.v11n6p133
Atchley, P., Pannell, H., Wofford, K., Hopkins, M., & Atchley, R. A. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive Research Principles and Implications, 9(1), 20. https://doi.org/10.1186/s41235-024-00547-9
Barcaui, A. (2025). ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention. Social Sciences & Humanities Open, 12, 102287. https://doi.org/10.1016/j.ssaho.2025.102287
Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025). Looking beyond the hype: Understanding the effects of AI on learning. Educational Psychology Review, 37(2). https://doi.org/10.1007/s10648-025-10020-8
Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1), 4. https://doi.org/10.1186/s41239-023-00436-z
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00408-3
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. https://doi.org/10.1186/s41239-023-00411-8
Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments, 10(1), 60. https://doi.org/10.1186/s40561-023-00269-3
Chen, Y., Wang, Y., Wüstenberg, T., Kizilcec, R. F., Fan, Y., Li, Y., Lu, B., Yuan, M., Zhang, J., Zhang, Z., Geldsetzer, P., Chen, S., & Bärnighausen, T. (2025). Effects of generative artificial intelligence on cognitive effort and task performance: study protocol for a randomized controlled experiment among college students. Trials, 26(1), 244. https://doi.org/10.1186/s13063-025-08950-3
Dabis, A., & Csáki, C. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanities and Social Sciences Communications, 11(1), 1006. https://doi.org/10.1057/s41599-024-03526-z
Eager, B., & Brunton, R. (2023). Prompting higher education towards AI-Augmented Teaching and Learning practice. Journal of University Teaching and Learning Practice, 20(5), 2. https://doi.org/10.53761/1.20.5.02
Farrelly, T., & Baker, N. (2023). Generative Artificial Intelligence: Implications and considerations for higher education practice. Education Sciences, 13(11), 1109. https://doi.org/10.3390/educsci13111109
Francis, N. J., Jones, S., & Smith, D. P. (2025). Generative AI in Higher Education: Balancing innovation and integrity. British Journal of Biomedical Science, 81, 14048. https://doi.org/10.3389/bjbs.2024.14048
Gerlich, M. (2025). AI Tools in Society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
Gkintoni, E., Antonopoulou, H., Sortwell, A., & Halkiopoulos, C. (2025). Challenging Cognitive Load Theory: The role of educational neuroscience and artificial intelligence in redefining learning efficacy. Brain Sciences, 15(2), 203. https://doi.org/10.3390/brainsci15020203
Gligorea, I., Cioca, M., Oancea, R., Gorski, A., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216
Grinschgl, S., & Neubauer, A. C. (2022). Supporting cognition with modern technology: Distributed cognition today and in an AI-Enhanced future. Frontiers in Artificial Intelligence, 5, 908261. https://doi.org/10.3389/frai.2022.908261
Hong, H., Vate-U-Lan, P., & Viriyavejakul, C. (2025). Cognitive Offload Instruction with Generative AI: A Quasi Experimental Study on Critical Thinking Gains in English Writing. Forum for Linguistic Studies, 7(7), 325–334. https://doi.org/10.30564/fls.v7i7.10072
Hughes, L., Malik, T., Dettmer, S., Al-Busaidi, A. S., & Dwivedi, Y. K. (2025). Reimagining Higher Education: Navigating the challenges of Generative AI adoption. Information Systems Frontiers. https://doi.org/10.1007/s10796-025-10582-6
Iqbal, J., Hashmi, Z. F., Asghar, M. Z., & Abid, M. N. (2025). Generative AI tool use enhances academic achievement in sustainable education through shared metacognition and cognitive offloading among preservice teachers. Scientific Reports, 15(1), 16610. https://doi.org/10.1038/s41598-025-01676-x
Ivanov, S., Soliman, M., Tuomi, A., Alkathiri, N. A., & Al-Alawi, A. N. (2024). Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour. Technology in Society, 77, 102521. https://doi.org/10.1016/j.techsoc.2024.102521
Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 2. https://doi.org/10.1007/s40979-024-00149-4
Khlaif, Z. N., Ayyoub, A., Hamamra, B., Bensalem, E., Mitwally, M. a. A., Ayyoub, A., Hattab, M. K., & Shadid, F. (2024). University teachers’ views on the adoption and integration of generative AI tools for student assessment in higher education. Education Sciences, 14(10), 1090. https://doi.org/10.3390/educsci14101090
Kim, J., Klopfer, M., Grohs, J. R., Eldardiry, H., Weichert, J., Cox, L. A., & Pike, D. (2025). Examining faculty and student perceptions of generative AI in university courses. Innovative Higher Education, 50(4), 1281–1313. https://doi.org/10.1007/s10755-024-09774-w
Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen-Vacs, D., Gal, E., Zailer, G., & Barak-Medina, E. (2024). Strategies for Integrating Generative AI into Higher Education: Navigating Challenges and Leveraging Opportunities. Education Sciences, 14(5), 503. https://doi.org/10.3390/educsci14050503
Lee, S. S., & Moore, R. L. (2024). Harnessing Generative AI (GeNAI) for Automated feedback in Higher Education: A systematic review. Online Learning, 28(3), 82–106. https://doi.org/10.24059/olj.v28i3.4593
Mariyono, D., & Hidayatullah, A. N. A. (2025). Navigating the moral maze: Ethical challenges and opportunities of generative chatbots in global higher education. Applied Computational Intelligence and Soft Computing, 2025(1), 8584141. https://doi.org/10.1155/acis/8584141
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of Generative AI for higher Education as explained by ChatGPT. Education Sciences, 13(9), 856. https://doi.org/10.3390/educsci13090856
Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 49(5), 847–864. https://doi.org/10.1080/03075079.2024.2323593
Omarsaib, M., Mitha, S. B., Vahed, A., & Mohamed, G. M. (2025). Mapping the AI surge in Higher Education: a bibliometric study spanning a decade (2015–2025). Informatics, 12(4), 137. https://doi.org/10.3390/informatics12040137
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., . . . Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Peng, P., & Kievit, R. A. (2020). The Development of Academic Achievement and Cognitive Abilities: a Bidirectional perspective. Child Development Perspectives, 14(1), 15–20. https://doi.org/10.1111/cdep.12352
Qian, Y. (2025). Pedagogical Applications of Generative AI in Higher Education: A Systematic Review of the field. TechTrends, 69(5), 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Rohilla, D. (2025). Impact of excessive AI tool usage on the cognitive abilities of undergraduate students: a mixed method study. Advance Social Science Archive Journal, 4(1), 2131–2143. https://doi.org/10.55966/assaj.2025.4.1.0115
Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524
Ruiz-Rojas, L. I., Salvador-Ullauri, L., & Acosta-Vargas, P. (2024). Collaborative working and critical Thinking: adoption of generative artificial intelligence tools in higher education. Sustainability, 16(13), 5367. https://doi.org/10.3390/su16135367
Sana, F., & Fenesi, B. (2025). Working Memory and Instructional fit: Reintroducing Aptitude–Treatment Interaction in Education Research. Behavioral Sciences, 15(6), 765. https://doi.org/10.3390/bs15060765
Skulmowski, A. (2023). The cognitive architecture of digital externalization. Educational Psychology Review, 35(4), 101. https://doi.org/10.1007/s10648-023-09818-1
Skulmowski, A. (2024). Placebo or Assistant? Generative AI between externalization and anthropomorphization. Educational Psychology Review, 36(2), 58. https://doi.org/10.1007/s10648-024-09894-x
Skulmowski, A., & Xu, K. M. (2021). Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load. Educational Psychology Review, 34(1), 171–196. https://doi.org/10.1007/s10648-021-09624-7
Sousa, A. E., & Cardoso, P. (2025). Use of generative AI by higher education students. Electronics, 14(7), 1258. https://doi.org/10.3390/electronics14071258
Symeou, L., Louca, L., Kavadella, A., Mackay, J., Danidou, Y., & Raffay, V. (2025). Development of Evidence‐Based Guidelines for the integration of Generative AI in university education through a multidisciplinary, Consensus‐Based approach. European Journal of Dental Education, 29(2), 285–303. https://doi.org/10.1111/eje.13069
Tzirides, A. O., Zapata, G., Kastania, N. P., Saini, A. K., Castro, V., Ismael, S. A., You, Y., Santos, T. a. D., Searsmith, D., O’Brien, C., Cope, B., & Kalantzis, M. (2024). Combining human and artificial intelligence for enhanced AI literacy in higher education. Computers and Education Open, 6, 100184. https://doi.org/10.1016/j.caeo.2024.100184
Wang, X., Xu, X., Zhang, Y., Hao, S., & Jie, W. (2024). Exploring the impact of artificial intelligence application in personalized learning environments: thematic analysis of undergraduates’ perceptions in China. Humanities and Social Sciences Communications, 11(1), 1644. https://doi.org/10.1057/s41599-024-04168-x
Wong, W., Aristidou, A., & Scheuermann, K. (2025). The future of learning or the future of dividing? Exploring the impact of generative artificial intelligence on higher education. Data & Policy, 7, e44. https://doi.org/10.1017/dap.2025.10011
Wu, F., Dang, Y., & Li, M. (2025). A systematic review of responses, attitudes, and utilization behaviors on generative AI for teaching and learning in higher education. Behavioral Sciences, 15(4), 467. https://doi.org/10.3390/bs15040467
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839–1850. https://doi.org/10.1038/s41562-024-02004-5
Yavich, R. (2025). Will the use of AI undermine students independent thinking? Education Sciences, 15(6), 669. https://doi.org/10.3390/educsci15060669
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7