Volume 3,Issue 9
Artificial Intelligence as a Catalyst for Transforming Problem-Based Learning in Higher Education
This study aims to systematically explore the theoretical underpinnings of Artificial intelligence (AI)-enabled Problem-based learning (PBL), clarify its transformative mechanisms in higher education practice, and provide theoretical and practical references for optimizing AI-integrated PBL models. To achieve this goal, the research adopts two core methodological approaches: conceptual analysis and literature synthesis.
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[3] Siemens G, 2019, Learning Analytics: The Emergence of a Discipline. American Behavioral Scientist, 64(3): 213–230.
[4] Avello D, Zurita S, 2025, Exploring the Nexus of Academic Integrity and Artificial Intelligence in Higher Education: A Bibliometric Analysis. International Journal for Educational Integrity, 21(1): 24.
[5] Zamir S, Mehmood M, Abbasi B, et al., 2025, Examining the Role of Higher Education Learning, Research Excellence, and Innovation Capacity in Driving AI-Technological Advancements in Nordic Countries. Humanities and Social Sciences Communications, 12(1): 1325.
[6] Wang Z, Li Y, 2025, Research on the Reform of English Teaching Models in Higher Education Based on Artificial Intelligence Capabilities. Education Reform and Development, 7(7): 102–107.
[7] Sebihi A, Schoelen L, Uwamwezi B, 2025, Unveiling AI’s Impact in Rwandan Higher Education: Navigating Trends, Challenges, and Imperatives at the University of Rwanda. Discover Education, 4(1): 166.
[8] Quan J, Xu M, 2025, The Enabling Mechanisms and Practical Pathways of Artificial Intelligence in Driving High-Quality Development of Higher Education: An Analysis Based on Connotation Interpretation, Dilemma Diagnosis, and Path Construction. Journal of International Education and Science Studies, 2(6): 69–76.