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September 16, 2025Journal of Educational Computing Research20 citationsOpen Access

RAISE the Standard: A Framework for Transparent Reporting of Artificial Intelligence Studies in Education

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JAJordan Allison

Key Points

  • RAISE enhances the interpretability of AI educational studies, boosting their scholarly impact and replicability.
  • The framework includes a checklist of 30 items over ten domains, promoting clear and comprehensive reporting.
  • Illustrative examples outline 'Good' and 'Bad' reporting, guiding authors in effective communication of their findings.
  • The framework addresses emerging expectations for transparency in AI-focused educational research, fostering better practices.

Abstract

The rapid integration of artificial intelligence (AI) into educational research and practice has highlighted the need for clear and consistent reporting standards. The RAISE (Reporting AI Studies in Education) framework offers a structured checklist of 30 items across ten thematic domains, designed to guide authors in transparently documenting AI interventions, study design, learner context, data collection, outcomes, and findings. This editorial introduces RAISE, explains its rationale, and provides practical guidance for its application, including illustrative “Bad” and “Good” reporting examples. By promoting comprehensive and replicable reporting, RAISE aims to enhance the interpretability, reproducibility, and scholarly impact of AI-focused educational research, while supporting authors in meeting emerging expectations for transparency in the field.

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Cite This Study

Jordan Allison (2025) studied this question.

synapsesocial.com/papers/68d454bb31b076d99fa59c6chttps://doi.org/10.1177/07356331251377430
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