AITutor-EvalKit: Exploring the Capabilities of AI Tutors

Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, Ekaterina Kochmar


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.
Anthology ID:
2026.eacl-demo.32
Volume:
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
Month:
March
Year:
2026
Address:
Rabat, Marocco
Editors:
Danilo Croce, Jochen Leidner, Nafise Sadat Moosavi
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
457–479
Language:
URL:
https://preview.aclanthology.org/ingest-eacl/2026.eacl-demo.32/
DOI:
Bibkey:
Cite (ACL):
Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, and Ekaterina Kochmar. 2026. AITutor-EvalKit: Exploring the Capabilities of AI Tutors. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 457–479, Rabat, Marocco. Association for Computational Linguistics.
Cite (Informal):
AITutor-EvalKit: Exploring the Capabilities of AI Tutors (Naeem et al., EACL 2026)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-eacl/2026.eacl-demo.32.pdf