A framework for integrating large language models in secondary physics education: practical design, opportunities, risks, and pedagogical principles

Abstract

The rapid advancement of large language models (LLMs) offers transformative potential for secondary physics education. However, theoretical and practical frameworks for responsible, pedagogically sound LLM integration remain underdeveloped. This paper proposes a structured, theory-grounded framework for embedding LLMs into secondary physics instruction, informed by constructivism, cognitive load theory, and the TPACK model. We identify three core application modalities: teacher-facing instructional design tools, guarded student-facing inquiry tools, and assessment-augmentation tools. We analyze domain-specific opportunities (targeting misconceptions in mechanics and electromagnetism) and risks (cognitive offloading, epistemic opacity, algorithmic bias). Drawing on empirical evidence from a small-scale single-class pilot feasibility study rather than systematic full empirical verification , we formalize six pedagogical principles: progressive autonomy, epistemic transparency, cognitive load optimization, disciplinary fidelity, ethical scaffolding, and human–AI complementarity. A one-group pretest–posttest pilot exploration was implemented with 36 secondary school students (ages 14–16) learning Newton’s Third Law solely to examine the preliminary practicability of the proposed framework instead of validating its universal effectiveness. Data analyses included paired-samples t-tests, effect size calculation, compliance coding, and descriptive survey statistics. Results showed significantly improved conceptual understanding within this limited pilot sample ( p  < 0.001, d = 1.32, large effect), high in-class observed adherence to AI use guardrails (91.7%), and generally positive learner perceptions among the participating cohort. This pilot-tested operable framework clarifies the evolving role of physics teachers as orchestrators of human–AI collaboration and offers actionable preliminary guidance for educators, instructional designers, and policymakers.