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Cited by 13Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningEthics and Social Impacts of AI

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

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Hwang, Gwo-Jen, Xie, Haoran, Wah, Benjamin W., Gašević, Dragan·2026·Computers and Education: Artificial Intelligence
DOI 10.1016/j.caeai.2026.100598
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Abstract

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.

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Authors
Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D.
Affiliations
  • National Taiwan University of Science and Technology (TW)
  • Lingnan University (HK)
  • Chinese University of Hong Kong (HK)
  • Monash University (AU)
Corresponding author
Hwang, Gwo-Jen
ORCID
Venue
Computers and Education: Artificial Intelligence
Publisher
Elsevier BV
Published
2026-06
Volume
10
Pages
100598
ISSN
2666-920X (ISSN-L)
DOI
10.1016/j.caeai.2026.100598
OpenAlex
W7155542654
Cited by
9
References
17
Citations by year
2026: 9
FWCI
76.56
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers and Education Artificial Intelligence (publishedVersion, cc-by)
  • HAL (submittedVersion)
Funders
  • National Taiwan University of Science and Technology
  • Ministry of Education
  • National Science and Technology Council (NSTC 112-2410-H-011-012-MY3, NSTC 113-2410-H-142-004-MY3)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
artificial intelligence in education, generative AI, transparency, research ethics, learner-AI interaction, reproducibility, ethical governance, learner agency, AI equity, research rigor

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