Beyond Scores: Explainable Intelligent Assessment Strengthens Pre-service Teachers' Assessment Literacy

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Authors: Yuang Wei, Fei Wang, Yifan Zhang, Brian Y. Lim, Bo Jiang
Cited by: 1
References: 125

Abstract

Assessment literacy (AL) is essential for personalized education, yet difficult to cultivate in pre-service teachers. Conventional teacher preparation programs focus on theoretical knowledge, while digital assessment tools commonly provide opaque scores or parameters. These limitations hinder reflection and transfer, leaving AL underdeveloped. We propose XIA, an eXplainable Intelligent Assessment platform that extends statistics-informed support with visualized cognitive diagnostic reasoning, including contrastive and counterfactual explanations. In a pre-post controlled study with 21 pre-service teachers, we combined quantitative tasks and questionnaires with qualitative interviews. The findings offer preliminary evidence that XIA supported reflection, self-regulation, and assessment awareness, and helped reduce assessment errors. Interviews further showed a shift from score-based judgments toward evidence-based reasoning. This work contributes insights into the design of intelligent assessment tools, showing how explanatory scaffolding can bridge assessment theory and classroom practice and support the cultivation of AL in teacher education.

Fields of Study & Subjects

Student Assessment and Feedback Intelligent Tutoring Systems and Adaptive Learning Innovative Teaching and Learning Methods

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–26
Publication date
13 April 2026