Overdependence on AI Supported Learning and Critical Thinking: Investigating Opportunities and Risks in Modern Education at Higher Educational Level

Abstract

This research examines how AI-based learning resources can help learners develop a critical thinking skill in the context of higher education, both as an opportunity and a potential danger of overreliance. This research is aimed at evaluating the role of AI based learning on critical thinking skills in students concerning the proportions of potential disadvantages and the positive effects of AI tools. The participants were separated into two groups, including those who used AI-supported learning tools and those who did not. The sample of the study was extracted using multistage sampling approach in which 150 students were randomly selected at first stage. At second stage these participants were divided in to two groups (75 in each group) using convenient sampling technique to identify students using AI too and student who did not use. The data were collected using a specially developed critical thinking test in multiple choice as well as performance-based formats, based on Watson-Glaser Critical Thinking Appraisal (WGCTA).

Descriptive statistics, paired t-tests, and independent t-tests were applied in order to compare the critical thinking scores of the two groups and determine the relationship between exploring AI tools and cognitive performance. These results showed that AI-tool users have improved critical thinking scores by a significant margin, 51.5 (SD = 6.3) to 68.0 (SD = 5.0) (t = 8.72, p < 0.05), and the control group did not significantly improve in critical thinking scores.

Nevertheless, risks of being over dependent on AI tools were also noted in the study as it was observed that students had to engage into frequent use of AI tools which led to cognitive offloading where students had to rely less on free-thinking to solve their independent problems. The correlation test (r = 0.56, p < 0.05) indicated that the excessive use of AI tools could result in a lack of critical thinking and the use of superficial method of learning. This explains why it is necessary to combine the introduction of AI tools with the classic teaching method to encourage critical thinking and metacognition. Other ethical concerns like fair access to AI devices and possible bias within the AI algorithms were also addressed, and a reasonable and conscious approach towards the use of AI in learning was highlighted.

References

Azevedo, R., et al. (2020). Does training on self-regulated learning help college students learn more effectively? Educational Psychology Review, 32(3), 245–260. https://doi.org/10.1007/s10648-020-09506-1

Baker, R. S., & Siemens, G. (2020). The role of artificial intelligence in improving learning outcomes. Educational Psychologist, 55(4), 181–195. https://doi.org/10.1080/00461520.2020.1796638

Bennett, R. E. (2021). The changing nature of educational assessment. Educational Assessment, 26(1), 11–23. https://doi.org/10.1080/10627197.2021.1876744

Evans, C., & Lee, S. (2026). Predictive analytics and student profiling systems: A new frontier in education equity. Journal of Educational Data Mining, 34(2), 139–157.

Eynon, R., & Helsper, E. J. (2021). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83.

Flavell, J. H. (2021). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906

Garcia, M., Kumar, S., & Zhang, Y. (2024). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83.

Gonzalez, P., & Harper, R. (2025). Generative AI and reflective thinking: New insights into student learning. Journal of Educational Psychology, 118(2), 220–230.

Hassan, B., Rafiq-uz-Zaman, M., & Khan, Z. A. (2025). Beyond memorization: Cultivating critical thinking skills through classic literature in secondary education for the 21st century learner. Review of Education, Administration & Law, 8(1), 115–124. https://doi.org/10.47067/real.v8i1.410

Hattie, J., & Timperley, H. (2020). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487

Hsin, W., & Cigas, J. (2021). AI and inquiry-based learning: Enhancing problem-solving and critical thinking. International Journal of Learning Technology, 16(1), 38–52.

Johnson, M., et al. (2025). AI in education: Enhancing learning or enabling cheating? Journal of Educational Integrity, 17(2), 100–115.

Jones, H., Rogers, R., & Pappas, E. (2023). AI-assisted learning and critical thinking: A balanced approach. Journal of Educational Technology, 32(2), 47–58.

Kim, S., & Morrison, M. (2026). The oversimplification of problem-solving in generative AI: Effects on cognitive engagement. AI & Education Journal, 12(3), 189–201.

Liu, X., & Martinez, A. (2025). Multistage assessments in AI-integrated classrooms: Enhancing critical thinking. Journal of Educational Research & Development, 52(1), 23–45.

Malik, N., Bano, S., & Rafiq-uz-Zaman, M. (2025). Navigating the future of learning: A review of teacher professional development and implementation challenges in K–12 STEAM education (2015–2025). Physical Education, Health and Social Sciences, 3(3), 615–628. https://doi.org/10.63163/jpehss.v3i3.681

Martins, G., Patel, R., & Ramachandran, R. (2025). Designing AI assessments for critical thinking: Challenges and opportunities. Journal of Learning & Technology, 10(2), 77–91.

Mohiuddin, D. (2026). Adaptive Marketing Systems and Consumer Feedback Loops: Implications for Market Development in Emerging Economies. Journal of Business Insight and Innovation, 5(1), 37–48.

Mohiuddin, D. (2025). HR Tech Adoption in Digital Banking: Implications for Workforce Development and Financial Sector Growth in Emerging Economies. Journal of Business Insight and Innovation, 4(2), 77–90.

O’Neil, C. (2020). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.

Park, Y., et al. (2024). Cognitive offloading in the age of artificial intelligence: Implications for learning. Educational Psychologist, 60(1), 19–35.

Patel, R., & Singh, K. (2025). Designing AI systems to foster metacognitive awareness in students. Journal of Educational Technology Research, 15(4), 78–91.

Pillai, R., et al. (2024). Long-term effects of AI interaction on cognitive growth: A longitudinal study. British Journal of Educational Psychology, 56(3), 146–158.

Rafiq-uz-Zaman, M. (2023). The impact of digital literacy on students’ learning outcomes: A comprehensive review. Inverge Journal of Social Sciences, 2(2), 194–205. https://doi.org/10.63544/ijss.v2i2.210

Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. https://doi.org/10.71317/RJSA.003.06.0523

Rafiq-uz-Zaman, M. (2025b). Beyond STEM: A narrative review of STEAM education’s impact on creativity and innovation (2020–2025). Inverge Journal of Social Sciences, 4(4), 1–16. https://doi.org/10.63544/ijss.v4i4.175

Rafiq-uz-Zaman, M. (2025c). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56

Rafiq-uz-Zaman, M. (2026). AI-driven competency-based education: Shaping lifelong learning and skill acquisition in dynamic educational environments. Artificial Intelligence in Lifelong and Life-Course Education, 1(1), 61–77. https://doi.org/10.66053/aillce.v1i1.29

Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025). Effectiveness of STEAM education in enhancing 21st century skills: A systematic review. Journal of Asian Development Studies, 14(3), 590–598. https://doi.org/10.62345/jads.2025.14.3.49

Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026a). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300

Rafiq-uz-Zaman, M., Shih, Y.-H., & Muthmainnah. (2026b). Effectiveness of online and blended learning on students’ academic achievement in Pakistan: A systematic review and meta-analysis. ProScholar Insights, 5(1), 116–125. https://doi.org/10.55737/psi.2026a-51164

Rao, S., & Stein, D. (2026). Embedding metacognitive scaffolds in AI learning systems: Enhancing critical thinking. Journal of Educational Technology Research, 12(4), 34–47.

Selwyn, N. (2020). AI and education: The implications of artificial intelligence for education policy and practice. Routledge.

Shute, V. J., & Hansen, E. (2021). Adaptive learning: A review of AI-supported learning systems. Educational Psychologist, 46(3), 148–160.

Singh, A., & Zhao, D. (2026). Metacognitive design in AI tools: Impact on student cognitive development. Educational Technology & Society, 29(2), 78–91.

Sweller, J., Ayres, P., & Kalyuga, S. (2021). Cognitive load theory: Implications for learning and instruction. Springer.

Torrance, H., et al. (2025). Long-term effects of AI on critical thinking: A longitudinal study in higher education. British Educational Research Journal, 51(2), 153–169.

Woolf, B. P. (2020). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann.

Zhang, Y., & Wang, H. (2023). Impact of AI tools on cognitive engagement and critical thinking in education. Journal of Cognitive Enhancement, 7(4), 222–235. https://doi.org/10.1007/s41465-023-00277-7