EE-Eval is an automated evaluation framework that represents interactivity in AI-generated explorable explanations as finite state machines, compares extracted FSMs to ideal pedagogical FSMs using graph and embedding metrics, and shows stronger alignment with human judgments than baselines across 12
Practical and ethical challenges of large language models in education: A systematic scoping review.British Journal of Educational Technology, 55(1):90–112, August 2023
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.HC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Evaluating Interactivity: Toward Automated Assessment of AI-Generated Explorable Explanations
EE-Eval is an automated evaluation framework that represents interactivity in AI-generated explorable explanations as finite state machines, compares extracted FSMs to ideal pedagogical FSMs using graph and embedding metrics, and shows stronger alignment with human judgments than baselines across 12