Development of an AI-Transparency Rubric for K-12 Education

• In Event: AERA Poster Session Thursday 7:45am
  In Poster Session: AI, Learning, and Innovation: Emerging Research in Education

Abstract

AI transparency is an attribute of AI systems that determines how well AI tools are able to explain their internal functioning to their users. This paper presents an AI transparency rubric that allows AI stakeholders to evaluate the transparency of an educational AI tool in order to make an informed ethical decision about the appropriateness of the tool for the K-12 context. The rubric includes four key criteria for transparency and each criterion has been defined by five key indicators of the criterion. Educational stakeholders may use the rubric to rate each criterion of the AI tool to calculate the final explainability score. The rubric will be validated and tested for reliability by experts and in-service teachers.

Authors

• Deepti Tagare, University of Texas - San Antonio

• Hyejeong Lee, University of Texas - San Antonio