Evaluating an AI-Powered Moodle Plugin for Enhancing Conceptual Understanding in Secondary Physics
Kahaleh, Rabih (University of Balamand (Líban))
López Simó, Víctor (Universitat Autònoma de Barcelona)
Imad, Rodrigue (University of Balamand (Líban))
Maneva, Elitza Nikolaeva (Universitat Autònoma de Barcelona)

Data:	2025
Resum:	This pilot study explores the feasibility of integrating large language model (LLM) assistants into physics education through a Moodle plugin designed to address conceptual understanding in Newtonian mechanics. Using OpenAI's GPT for real-time Socratic dialogue, the plugin guides students through misconception-targeted questions adapted from the Force Concept Inventory (FCI). Aligned with principles of inquiry-based learning, the intervention compares AI-guided feedback with instructor-guided materials over a one-week, three-session classroom study. Results suggest that students receiving AI-guided Socratic dialogue showed greater conceptual gains on certain targeted items (e. g. , Newton's Third Law), whereas instructor guidance proved more effective for other concepts (e. g. , mass and free-fall independence). Survey feedback highlights the immediacy and interactive nature of the AI while also noting a preference for the clarity provided by instructors. Qualitative analysis of open-ended question responses suggests that AI-driven dialogue promotes deeper reasoning when restating student ideas and scaffolding reflection. These preliminary findings underscore the potential of LLMs to support conceptual change in physics education when thoughtfully embedded within learning management systems, highlighting the complexity and value of personalized, interactive feedback for addressing student misconceptions.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Large Language Models ; Force Concept Inventory ; Learning Management System ; Conceptual change ; Physics misconceptions ; Socratic dialogue ; AI Moodle Plugin ; Artificial Intelligence in STEM education ; Constructivist learning
Publicat a:	International Journal of Emerging Technologies in Learning (iJET), Vol. 20, Num. 4 (2025) , p. 81-97

DOI: 10.3991/ijet.v20i04.57879

17 p, 1.1 MB

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