TeachingCoach synthetic dialogue dataset (406,183 training examples)¶
Product or Programme · All products and programmes
Evidence · 3 claims (1 for, 2 mixed) · 1 study (1 design),q2· 0 of 1 report an effect size · 3 claims rest on one study
Description¶
Isabel Molnar et al.'s dataset of GPT-4o-generated, expert-filtered multi-turn instructor–consultant dialogues conditioned on teaching rules, instructor profiles, and teaching challenges.
Components¶
Claims¶
- Expert raters rate TeachingCoach higher than a GPT-4o baseline on clarity, tone, reflection, and acknowledgment of user input [+W]
- In a user study, the GPT-4o-mini baseline was preferred overall, but participants more often attributed learning to the fine-tuned TeachingCoach model [~W]
- Users experienced a trade-off between conversational depth and interaction efficiency between the fine-tuned and baseline chatbots [~W]
Related Products and Programmes¶
Key Sources¶
- Isabel Molnar, Peiyu Li, Si Chen, Sugana Chawla, James Lang, Ronald Metoyer, Ting Hua, Nitesh V. Chawla. (2026). TeachingCoach: A Fine-Tuned Scaffolding Chatbot for Instructional Guidance to Instructors. https://arxiv.org/abs/2603.18189
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
teachingcoach-synthetic-dialogue-dataset-406183-training-examples |
title |
TeachingCoach synthetic dialogue dataset (406,183 training examples) |
description |
Isabel Molnar et al.'s dataset of GPT-4o-generated, expert-filtered multi-turn instructor–consultant dialogues conditioned on teaching rules, instructor profiles, and teaching challenges. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
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