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%0 Conference Proceedings
%T Towards evaluating teacher discourse without task-specific fine-tuning data
%A Beigman Klebanov, Beata
%A Suhan, Michael
%A Mikeska, Jamie N.
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2025
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-218-84228-4
%F beigman-klebanov-etal-2025-towards
%X Teaching simulations with feedback are one way to provide teachers with practice opportunities to help improve their skill. We investigated methods to build evaluation models of teacher performance in leading a discussion in a simulated classroom, particularly for tasks with little performance data.
%U https://aclanthology.org/2025.aimecon-main.21/
%P 192-200

Markdown (Informal)

[Towards evaluating teacher discourse without task-specific fine-tuning data](https://aclanthology.org/2025.aimecon-main.21/) (Beigman Klebanov et al., AIME-Con 2025)

• Towards evaluating teacher discourse without task-specific fine-tuning data (Beigman Klebanov et al., AIME-Con 2025)

ACL

• Beata Beigman Klebanov, Michael Suhan, and Jamie N. Mikeska. 2025. Towards evaluating teacher discourse without task-specific fine-tuning data. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 192–200, Wyndham Grand Pittsburgh, Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).