Building Metacognitive Skills Using AI Tools to Help Higher Education Students Reflect on Their Learning Process
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Abstract
This study examines how AI can be used to improve higher education students’ ability to learn effectively. The research focuses on using AI to enhance metacognition, which is the students’ ability to understand and control their learning processes. Specifically, the study explores the potential of AI-powered prompts to encourage individuals to reflect on their learning and explain their understanding of the materials provided by teachers. Additionally, it highlights the benefits of implementing AI-powered learning companions to provide personalized support and guidance throughout the learning process. Recommendations for future research include investigating how AI can further improve students’ self-regulation skills and enhance peer-review processes through AI-generated feedback.
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References
Anderson, J. R. (2000). Learning and problem solving with multimedia learners: Cognitive foundations of instructional design. Educational Psychologist(1), pp. 161-173.
Baker, R. S. (2014). Learning analytics and educational data mining: A review of learning analytics in higher education. Educational Researcher(8), pp. 307-314.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. California Law Review(3), pp. 671-737.
Clark, R. E. (2016). E-learning and the science of instruction (Vol. 4). Wiley.
Cristina, D. Z., & Timothy, J. N.-M. (2023, January 15). Assessing Metacognitive Regulation during Problem Solving: A Comparison of Three Measures. journal of jintelligence, pp. 2-5. https://doi.org/10.3390/jintelligence11010016
Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A theoretical framework. Cognitive Psychology(3), pp. 290-332.
Lin, S., & Zhang, D. (2021). ACM Conference on Intelligent User Interfaces. The Impact of AI-powered Self-Explanation Prompts on Metacognition and Learning Outcomes (pp. 720-729). Association for Computing Machinery.
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record(6), pp. 1017-1064.
OECD. (2018). PISA 2018 Results: Collaborative Problem Solving. OECD Publishing(1). https://doi.org/10.1787/pisa-2018-results-collab-prob-solving-9789264091580-en) [Marginalization: OECD, 2019
Pintrich, P. R., Roehr, W. C., & DeWiest, F. J. (1995). The development of a model of self-regulated learning. Educational Psychologist(40), pp. 231-259.
Rosalyn, S. (2021, March 17, 2021 1). Metacognition in the Classroom: Benefits & Strategies. Retrieved 4 22, 2024, from Metacognition in the Classroom: Benefits & Strategies: https://www.Metacognition in the Classroom: Benefits & Strategies.co.uk/hub/metacognition-in-the-classroom/
Schunk, D. H., & Zimmerman, B. J. (2008). Self-regulated learning: From theory to practice. Educational Psychologist(4), pp. 141-166.
Warschauer, M. (2004). Technology and social inclusion: Basing educational decisions on evidence. Comparative Education(1), pp. 17-38.
Winograd, P. (2006). Educational Psychology: A Modular Approach (Vol. 4). Pearson Education.