EFFICIENCY, ENGAGEMENT, AND COGNITIVE OFFLOADING: A REVIEW OF GENERATIVE AI IN EDUCATION
DOI:
https://doi.org/10.35631/IJEPC.1162072Keywords:
Cognitive Engagement, Cognitive Offloading, Efficiency, Generative Artificial Intelligence, Student LearningAbstract
This narrative review examines how generative artificial intelligence (GenAI) influences student learning through three interrelated dimensions: efficiency, engagement, and cognitive offloading. A structured search of Scopus identified 56 studies published between 2022 and 2025 that examined GenAI use in educational contexts and its implications for cognitive or learning processes. The review reveals consistent evidence that GenAI enhances task efficiency by accelerating drafting, feedback cycles, and information processing. However, efficiency gains do not uniformly translate into deeper learning, as several studies report tendencies toward surface-level completion strategies. Findings related to engagement are mixed, with perception-based studies emphasizing reduced anxiety and increased confidence, while experimental studies report variable effects on cognitive involvement. Cognitive offloading emerges as a central tension: although GenAI use is associated with reduced cognitive load and support for higher-order reasoning, concerns persist regarding over-reliance and diminished independent thinking. To interpret these patterns, this review advances a three-lens framework positioning GenAI as a mediator of cognitive effort rather than a uniformly beneficial or detrimental tool. The framework highlights the interdependence of efficiency gains, engagement dynamics, and cognitive delegation. The findings underscore the critical role of learner regulation and instructional design in shaping GenAI’s educational impact. Future research should prioritize longitudinal designs, objective learning measures, and process-oriented methodologies to clarify long-term cognitive implications.
Downloads
References
Ahmed Kofahi, M., & Husain, A. (2025). ChatGPT for Operating Systems: Higher-Order Thinking in Focus. Journal of Information Technology Education: Research, 24, 001. https://doi.org/10.28945/5382
Al-Obaydi, L. H., & Pikhart, M. (2025). AI partner versus human partner: Comparing AI-based peer assessment with human-generated peer assessment in examining writing skills. Language Testing in Asia, 15(1), 38. https://doi.org/10.1186/s40468-025-00375-8
Asamoah, P., Zokpe, D., Boateng, R., Marfo, J. S., Boateng, S. L., Asamoah, D., Muntaka, A. S., & Manso, J. F. (2024). Domain knowledge, ethical acumen, and query capabilities (DEQ): A framework for generative AI use in education and knowledge work. Cogent Education, 11(1), 2439651. https://doi.org/10.1080/2331186X.2024.2439651
Baumeister, R. F., & Leary, M. R. (1997). Writing Narrative Literature Reviews. Review of General Psychology, 1(30), 311–320.
Chauncey, S. A., & McKenna, H. P. (2023). A framework and exemplars for ethical and responsible use of AI Chatbot technology to support teaching and learning. Computers and Education: Artificial Intelligence, 5, 100182. https://doi.org/10.1016/j.caeai.2023.100182
Costa, A. R., Lima, N., Viegas, C., & Caldeira, A. (2024). Critical minds: Enhancing education with ChatGPT. Cogent Education, 11(1), 2415286. https://doi.org/10.1080/2331186X.2024.2415286
Dahlkemper, M. N., Lahme, S. Z., & Klein, P. (2023). How do physics students evaluate artificial intelligence responses on comprehension questions? A study on the perceived scientific accuracy and linguistic quality of ChatGPT. Physical Review Physics Education Research, 19(1), 010142. https://doi.org/10.1103/PhysRevPhysEducRes.19.010142
Dai, Y., Lai, S., Lim, C. P., & Liu, A. (2023). ChatGPT and its impact on research supervision: Insights from Australian postgraduate research students. Australasian Journal of Educational Technology, 39(4), 74–88. https://doi.org/10.14742/ajet.8843
De La Puente, M., Torres, J., Troncoso, A. L. B., Meza, Y. Y. H., & Carrascal, J. X. M. (2024). Investigating the use of chatGPT as a tool for enhancing critical thinking and argumentation skills in international relations debates among undergraduate students. Smart Learning Environments, 11(1), 55. https://doi.org/10.1186/s40561-024-00347-0
Elshall, A. S., & Badir, A. (2025). Balancing AI-assisted learning and traditional assessment: The FACT assessment in environmental data science education. Frontiers in Education, 10, 1596462. https://doi.org/10.3389/feduc.2025.1596462
Essien, A., Bukoye, O. T., O’Dea, X., & Kremantzis, M. (2024). The influence of AI text generators on critical thinking skills in UK business schools. Studies in Higher Education, 49(5), 865–882. https://doi.org/10.1080/03075079.2024.2316881
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). https://doi.org/10.30564/fls.v7i7.10072
Jošt, G., Taneski, V., & Karakatič, S. (2024). The Impact of Large Language Models on Programming Education and Student Learning Outcomes. Applied Sciences, 14(10), 4115. https://doi.org/10.3390/app14104115
Juntarciego, M. J. C., Gaboy, R., Delos Santos, Ma. R. H., & Collantes, L. (2025). Chat, copy, change: Prospects and risks of ChatGPT in the teaching and learning process. Acta Scientiarum. Education, 47, e71533. https://doi.org/10.4025/actascieduc.v47i1.71533
Khampusaen, D. (2025). The Impact of ChatGPT on Academic Writing Skills and Knowledge: An Investigation of Its Use in Argumentative Essays. LEARN Journal: Language Education and Acquisition Research Network, 18(1), 963–988. https://doi.org/10.70730/PGCQ9242
Klar, M. (2025). Using ChatGPT is easy, using it effectively is tough? A mixed methods study on K-12 students’ perceptions, interaction patterns, and support for learning with generative AI chatbots. Smart Learning Environments, 12(1), 32. https://doi.org/10.1186/s40561-025-00385-2
Klimova, B., & De Campos, V. P. L. (2024). University undergraduates’ perceptions on the use of ChatGPT for academic purposes: Evidence from a university in Czech Republic. Cogent Education, 11(1), 2373512. https://doi.org/10.1080/2331186X.2024.2373512
Kong, S.-C., Lee, J. C.-K., & Tsang, O. (2024). A pedagogical design for self-regulated learning in academic writing using text-based generative artificial intelligence tools: 6-P pedagogy of plan, prompt, preview, produce, peer-review, portfolio-tracking. Research and Practice in Technology Enhanced Learning, 19, 030. https://doi.org/10.58459/rptel.2024.19030
Leahy, K., Ozer, E., & Cummins, E. (2025). AI-ENGAGE: A Multicentre Intervention to Support Teaching and Learning Engagement with Generative Artificial Intelligence Tools. Education Sciences, 15(7), 807. https://doi.org/10.3390/educsci15070807
Lee, H.-Y., Chen, P.-H., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2024). Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction. International Journal of Educational Technology in Higher Education, 21(1), 16. https://doi.org/10.1186/s41239-024-00447-4
Lee, S., & Eronen, J. (2025). Transforming English education in Japan by utilizing large language models for tailored learning and diverse skill development. Discover Education, 4(1), 403. https://doi.org/10.1007/s44217-025-00856-1
Li, H. (2023). Effects of a ChatGPT-based flipped learning guiding approach on learners’ courseware project performances and perceptions. Australasian Journal of Educational Technology, 39(5), 40–58. https://doi.org/10.14742/ajet.8923
Li, L., & Kim, M. (2024). It is like a friend to me: Critical usage of automated feedback systems by self-regulating English learners in higher education. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.8821
Magalhães Araujo, S., & Cruz-Correia, R. (2024). Incorporating ChatGPT in Medical Informatics Education: Mixed Methods Study on Student Perceptions and Experiential Integration Proposals. JMIR Medical Education, 10, e51151. https://doi.org/10.2196/51151
Mekheimer, M. (2025). Generative AI-assisted feedback and EFL writing: A study on proficiency, revision frequency and writing quality. Discover Education, 4(1), 170. https://doi.org/10.1007/s44217-025-00602-7
Moon Hidayati Otoluwa, Arhanuddin Salim, Kadir, Gina Nurvina Darise, Indah Wardaty Saud, & Andi Asma. (2025). Students’ perceptions and effect of ChatGPT on research proposal quality across gender in Indonesia. IAES International Journal of Artificial Intelligence (IJ-AI), 14(5), 3613–1623. https://doi.org/DOI:%252010.11591/ijai.v14.i5
Naatonis, R. N., Rusijono, R., Jannah, M., & Malahina, E. A. U. (2024). Evaluation of Problem Based Gamification Learning (PBGL) Model on Critical Thinking Ability with Artificial Intelligence Approach Integrated with ChatGPT API: An Experimental Study. Qubahan Academic Journal, 4(3), 485–520. https://doi.org/10.48161/qaj.v4n3a919
Nasr, N. R., Tu, C.-H., Werner, J., Bauer, T., Yen, C.-J., & Sujo-Montes, L. (2025). Exploring the Impact of Generative AI ChatGPT on Critical Thinking in Higher Education: Passive AI-Directed Use or Human–AI Supported Collaboration? Education Sciences, 15(9), 1198. https://doi.org/10.3390/educsci15091198
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
Rana, V., Verhoeven, B., & Sharma, M. (2025). Generative AI in Design Thinking Pedagogy: Enhancing Creativity, Critical Thinking, and Ethical Reasoning in Higher Education. Journal of University Teaching and Learning Practice, 22(4). https://doi.org/10.53761/tjse2f36
Sánchez-Ruiz, L. M., Moll-López, S., Nuñez-Pérez, A., Moraño-Fernández, J. A., & Vega-Fleitas, E. (2023). ChatGPT Challenges Blended Learning Methodologies in Engineering Education: A Case Study in Mathematics. Applied Sciences, 13(10), 6039. https://doi.org/10.3390/app13106039
Šedlbauer, J., Činčera, J., Slavík, M., & Hartlová, A. (2024). Students’ reflections on their experience with ChatGPT. Journal of Computer Assisted Learning, 40(4), 1526–1534. https://doi.org/10.1111/jcal.12967
Stofiana, T., Sunendar, D., Mulyati, Y., & Sastromiharjo, A. (2025). Writing with AI, thinking with Toulmin: Metacognitive gaps and the rhetorical limits of argumentation. Ampersand, 15, 100242. https://doi.org/10.1016/j.amper.2025.100242
Štuikys, V., Burbaitė, R., Binkis, M., & Ziberkas, G. (2025). Developing Problem-Solving Skills to Support Sustainability in STEM Education Using Generative AI Tools. Sustainability, 17(15), 6935. https://doi.org/10.3390/su17156935
Sun, D., Xu, P., Zhang, J., Liu, R., & Zhang, J. (2025). How Self-Regulated Learning Is Affected by Feedback Based on Large Language Models: Data-Driven Sustainable Development in Computer Programming Learning. Electronics, 14(1), 194. https://doi.org/10.3390/electronics14010194
Sweller, J. (1988). Cognitive Load During Problem Solving: Effects on Learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Thi, X. H. N., Thien, H. V. H., Vuong, K. N., & Nguyen, T. T. (2025). Enhancing writing skills through AI-powered tools: Perceived benefits and challenges among Vietnamese EFL students. Discover Education, 4(1), 472. https://doi.org/10.1007/s44217-025-00905-9
Wu, X.-Y., & Chiu, T. K. F. (2025). Integrating learner characteristics and generative AI affordances to enhance self-regulated learning: A configurational analysis. Journal of New Approaches in Educational Research, 14(1), 10. https://doi.org/10.1007/s44322-025-00028-x
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning (arXiv:2408.12143). arXiv. https://doi.org/10.48550/arXiv.2408.12143
Yang, Y., Huang, L., Lin, W., Li, Y., Xu, Y., & Cheng, L. (2025). Enhancing Sustainable English Writing Instruction Through a Generative AI-Based Virtual Teacher Within a Co-Regulated Learning Framework. Sustainability, 17(19), 8770. https://doi.org/10.3390/su17198770
Yunianto, W., Lavicza, Z., Kastner-Hauler, O., & Houghton, T. (2024). Investigating the use of ChatGPT to solve a GeoGebra based mathematics+computational thinking task in a geometry topic. Journal on Mathematics Education, 15(3), 1027–1052. https://doi.org/10.22342/jme.v15i3.pp1027-1052
Zhang, H., & Wang, Q. (2025). How could GenAI work on in-service teachers’ knowledge building process? An empirical study based on epistemic network analysis. International Journal of Educational Technology in Higher Education, 22(1), 47. https://doi.org/10.1186/s41239-025-00544-y
Zhao, G., Sheng, H., Wang, Y., Cai, X., & Long, T. (2025). Generative Artificial Intelligence Amplifies the Role of Critical Thinking Skills and Reduces Reliance on Prior Knowledge While Promoting In-Depth Learning. Education Sciences, 15(5), 554. https://doi.org/10.3390/educsci15050554
Zhou, X., Teng, D., & Al-Samarraie, H. (2024). The Mediating Role of Generative AI Self-Regulation on Students’ Critical Thinking and Problem-Solving. Education Sciences, 14(12), 1302. https://doi.org/10.3390/educsci14121302
Zied Bahroun, Chiraz Anane, Vian Ahmed, & Andrew Zacca. (2023). Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis. Sustainability, 15(12983). https://doi.org/10.3390/%20%20su151712983
