AITutor-EvalKit: Exploring the Capabilities of AI Tutors
Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, Ekaterina Kochmar
TL;DR
AITutor-EvalKit is a comprehensive tool that assesses AI tutors' pedagogical quality, offers demonstration and evaluation capabilities, and facilitates model inspection and data visualization for education stakeholders and researchers.
Contribution
This paper introduces AITutor-EvalKit, a novel application combining evaluation, visualization, and feedback collection for AI tutors in educational settings.
Findings
Supports pedagogical quality assessment of AI tutors
Enables model inspection and data visualization
Facilitates user feedback collection
Abstract
We present AITutor-EvalKit, an application that uses language technology to evaluate the pedagogical quality of AI tutors, provides software for demonstration and evaluation, as well as model inspection and data visualization. This tool is aimed at education stakeholders as well as *ACL community at large, as it supports learning and can also be used to collect user feedback and annotation.
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Taxonomy
TopicsIntelligent Tutoring Systems and Adaptive Learning · Teaching and Learning Programming · Explainable Artificial Intelligence (XAI)