EFFECT OF ARTIFICIAL INTELLIGENCE ON STUDENTS’ COGNITIVE ABILITIES AT UNIVERSITY LEVEL
Keywords:
Application, Artificial Intelligence, Bloom's Taxonomy, Cognitive Abilities, Cognitive Development, Comprehension, Evaluation, Knowledge, SynthesisAbstract
The role of artificial intelligence (AI) in modifying college students' cognitive abilities is explored in this research. It is important to know how the students' cognitive domains which are categorized into six by Bloom's Taxonomy are influenced by AI in order to incorporate AI in teaching. They are knowledge, understanding, application, analysis, synthesis, and evaluation. The experimental study compares the cognitive capacities of students exposed to AI-based learning methods with those exposed to traditional teaching methods using a randomized pre-test post-test control group. The results validate notable variations in cognitive development, with AI improving cognitive function in specific areas. The study urges cautious implementation of AI technologies to promote students' cognitive growth and emphasizes the necessity of continued research into AI's potential in today's classroom.
Downloads
References
Bloom, B. S. (1956). Taxonomy of. Educational Objectives.
Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia computer science, 136, 16-24.
Collins, A., & Halverson, R. (2010). The second educational revolution: Rethinking education in the age of technology. Journal of computer assisted learning, 26(1), 18-27.
Creswell, J. W. (2012). Educational Research. Pearson.
Fraenkel, J., Wallen, N., & Hyun, H. (1993). How to Design and Evaluate Research in Education 10th ed. McGraw-Hill Education.
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. metabolism, 69, S36-S40.
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational psychologist, 41(2), 75-86.
NGSS Lead States. (2013). Next generation science standards: For states, by states. National Academies Press.
Pokrivčáková, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of language and cultural education.
Theofilatos, K., Pavlopoulou, N., Papasavvas, C., Likothanassis, S., Dimitrakopoulos, C., Georgopoulos, E., ... & Mavroudi, S. (2015). Predicting protein complexes from weighted protein–protein interaction graphs with a novel unsupervised methodology: evolutionary enhanced Markov clustering. Artificial intelligence in medicine, 63(3), 181-189.
Tobias, S., & Duffy, T. M. (2009). Constructivist instruction. Success or failure.
Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. John Wiley & Sons.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Anum Iqbal, Irsa Tayyab (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
