Presenting your AI in education research with rigor: The TEP-AIED model

The rapid expansion of Artificial Intelligence in Education (AIED), particularly with the emergence of generative AI, has intensified the need for rigorous, transparent, and pedagogically grounded research reporting. Although existing frameworks offer valuable guidance on ethical responsibility or technical disclosure, they may be complex, fragmented, or difficult to operationalize in empirical and experimental contexts. This paper proposes the TEP (Transparency-Ethics-Pedagogy)-AIED model, a streamlined three-dimensional framework integrating transparency, ethics, and pedagogy to guide the design and reporting of AIED studies. The model highlights clear disclosure of AI system characteristics and learner/teacher-AI interaction processes to strengthen interpretability and reproducibility, and it encourages proactive ethical governance by addressing data handling, risk mitigation, equity, and learner agency. It also foregrounds pedagogical grounding by requiring explicit articulation of learning objectives, theoretical alignment, and learner preparation to develop appropriate conceptions of AI-supported learning and avoid uncritical reliance. By positioning these dimensions as interconnected rather than as isolated requirements, the TEP-AIED model supports methodological rigor while remaining accessible to researchers and practitioners. Intended as practical guidance for reporting AIED research, the framework encourages authors to embed transparency, ethics, and pedagogy throughout the research lifecycle, thereby strengthening validity, accountability, and educational relevance in AI-enhanced learning research.