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AITutor-EvalKit: Exploring the Capabilities of AI Tutors

Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, Ekaterina Kochmar · Dec 3, 2025 · Citations: 0

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.

Human Data Lens

  • Uses human feedback: Yes
  • Feedback types: Demonstrations
  • Rater population: Unknown
  • Unit of annotation: Unknown
  • Expertise required: General

Evaluation Lens

  • Evaluation modes: Automatic Metrics
  • Agentic eval: None
  • Quality controls: Not reported
  • Confidence: 0.65
  • Flags: None

Research Summary

Contribution Summary

  • 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.

Why It Matters For Eval

  • 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.

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