Artificial Intelligence and Conceptual Understanding in Physics Education: Opportunities, Risks, and Research Directions

Artificial intelligence is swiftly becoming a significant force in physics education, adept at producing explanations, formulating hypotheses, and facilitating in-depth discussions about physical phenomena. This advancement presents novel opportunities for enhancing conceptual comprehension, especially in a field where students' intuitive notions tend to be consistent, coherent, and resistant to alteration. Simultaneously, AI systems often generate assertive yet erroneous reasoning, prompting apprehensions over epistemic trust, excessive dependence, and the perpetuation of fallacies. This Study analyzes artificial intelligence as an epistemic intermediary in physics education, emphasizing its role in conceptual transformation, inquiry-based pedagogy, and educator autonomy. Utilizing developing empirical evidence and theoretical frameworks, the paper contends that AI can enhance conceptual development by stimulating comparison, critique, and evidence-based reasoning, yet can hinder learning when regarded as an authoritative source of answers. The investigation underscores the transformation of teacher professional judgment in AI-enhanced classrooms and explores ethical and pedagogical limits concerning autonomy, equity, assessment integrity, and privacy. The article finishes by delineating essential research trajectories and underscoring that the educational efficacy of artificial intelligence is essentially contingent upon pedagogical design and ethical governance. The function of AI in physics education ought to be to enhance human reasoning rather than supplant it, and to assist learners in cultivating lasting, transferable conceptual comprehension.