We introduce a unified metric set for evaluating LLM tutors by inductively coding 177 recent literature-based metrics and scoring tutoring dialogues with three LLM judges. Exploratory factor analysis identified five constructs and a strong general factor. We present the resulting 10-category, 41-item framework for confirmatory analysis and human validation.

19 K-12 teachers participated in a co-design pilot study of an AI education platform, testing assessment grading. Teachers valued AI’s rapid narrative feedback for formative assessment but distrusted automated scoring, preferring human oversight. Students appreciated immediate feedback but remained skeptical of AI-only grading, highlighting needs for trustworthy, teacher-centered AI tools.