As generative AI becomes increasingly integrated into higher education, its influence is reshaping what it means to learn, teach, and think. This paper questions whether education should continue prioritizing problem-solving in an era where machines excel at it. Drawing from constructivist theory, Bloom’s Taxonomy, and the Cattell-Horn-Carroll model of intelligence, the paper proposes a shift from utilitarian models of learning to a framework that emphasizes conceptual agility, dialectical reasoning, and meaning-making. We explore how AI may alter cognitive development, risk passive knowledge acquisition, and deepen achievement gaps—while also offering opportunities for enhanced scaffolded learning. Ultimately, this paper argues for a human-centered, inquiry-based model of education that redefines learning beyond the mastery of problems toward the cultivation of imagination, ethical reasoning, and epistemic curiosity.
References
[1]
American Psychological Association, APA Board of Educational Affairs Working Group to Revise the APA Principles for Quality Undergraduate Education in Psychology (2023). Principles for Quality Undergraduate Education in Psychology. https://www.apa.org/about/policy/principles-quality-undergraduate-education-psychology.pdf
[2]
Anderson, L. W., & Krathwohl, D. R. (2001). A Taxonomy for Learning, Teaching, and Assessment: A Revision ofBloom’s Taxonomy of Educational Objectives. Longman.
[3]
Arends, B. (2021). Bloom’s Taxonomy: Benefits and Limitations. Intentional College Teaching.
[4]
Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review. Information, 15, Article 676. https://doi.org/10.3390/info15110676
[5]
Bloom, B. (1956). Taxonomy of Educational Objectives: The Classification of Educational Goals. Vol. 1: CognitiveDomain. McKay.
[6]
Burns, L. R., Stephenson, P. L., & Bellamy, K. (2016). The Socratic Method: Empirical Assessment of a Psychology Capstone Course. Psychology Learning & Teaching, 15, 370-383. https://doi.org/10.1177/1475725716671824
[7]
Dong, L., Tang, X., & Wang, X. (2025). Examining the Effect of Artificial Intelligence in Relation to Students’ Academic Achievement: A Meta-Analysis. Computers and Education: Artificial Intelligence, 8, Article 100400. https://doi.org/10.1016/j.caeai.2025.100400
[8]
Flanagan, D. P., & Dixon, S. G. (2014). The Cattell-Horn-Carroll (CHC) Theory of Cognitive Abilities. In C. R. Reynolds, K. J. Vannest, & E. Fletcher-Janzen (Eds.), Encyclopedia of Special Education. Wiley. https://doi.org/10.1002/9781118660584.ese0431
[9]
Fortner, M., & Katzarska-Miller, I. (2024). Using Generative AI to Promote the APA’s Five Goals for Undergraduate Majors. Teaching of Psychology. https://doi.org/10.1177/00986283241264793
[10]
Fuller, R. B. (1969). Operating Manual for Spaceship Earth. Southern Illinois University Press.
[11]
Gammoh, L. A. (2024). ChatGPT in Academia: Exploring University Students’ Risks, Misuses, and Challenges in Jordan. Journal of Further and Higher Education, 48, 608-624. https://doi.org/10.1080/0309877x.2024.2378298
[12]
Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15, Article 6. https://doi.org/10.3390/soc15010006
[13]
Lee, H.-P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects from a Survey of Knowledge Workers. In Association for Computing Machinery (Ed.), CHI’25: Proceedings of the CHI Conference on Human Factors in Computing Systems (pp. 1-23). ACM.
[14]
Malkus, N. (2025). Testing Theories of Why: Four Keys to Interpreting US Student Achievement Trends. American Enterprise Institute. https://www.aei.org/research-products/report/testing-theories-of-why-four-keys-to-interpreting-us-student-achievement-trends/
[15]
Meadows, A. M., Rose, M., Burns, L. R., & Bellamy, K. (2021). Using Discussion to Teach Capstone Courses in Psychology. Creative Education, 12, 122-139. https://doi.org/10.4236/ce.2021.121009
[16]
Palmer, P. J. (2011). Healing the Heart of Democracy: The Courage to Create a Politics Worthy of the Human Spirit (p. 84). Wiley.
[17]
Pujawan, I. G. N., Rediani, N. N., Antara, I. G. W. S., Putri, N. N. C. A., & Bayu, G. W. (2022). Revised Bloom Taxonomy-Oriented Learning Activities to Develop Scientific Literacy and Creative Thinking Skills. Journal Pendidikan IPA Indonesia, 11, 47-60. https://doi.org/10.15294/jpii.v11i1.34628
[18]
Schipolowski, S., Wilhelm, O., & Schroeders, U. (2014). On the Nature of Crystallized Intelligence: The Relationship between Verbal Ability and Factual Knowledge. Intelligence, 46, 156-168. https://doi.org/10.1016/j.intell.2014.05.014
[19]
Thomas, D. R., Lin, J., Gatz, E., Gurung, A., Gupta, S., Norberg, K. et al. (2024). Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. In Association for Computing Machinery (Ed.), Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 404-415). ACM. https://doi.org/10.1145/3636555.3636896
[20]
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial Intelligence in Education: A Systematic Literature Review. Expert Systems with Applications, 252, Article 124167. https://doi.org/10.1016/j.eswa.2024.124167
