1. Evaluation of mathematical questioning strategies using data collected through weak supervision
- Author
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Datta, Debajyoti, Phillips, Maria, Bywater, James P, Chiu, Jennifer, Watson, Ginger S., Barnes, Laura E., and Brown, Donald E
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Human-Computer Interaction ,Computer Science - Machine Learning - Abstract
A large body of research demonstrates how teachers' questioning strategies can improve student learning outcomes. However, developing new scenarios is challenging because of the lack of training data for a specific scenario and the costs associated with labeling. This paper presents a high-fidelity, AI-based classroom simulator to help teachers rehearse research-based mathematical questioning skills. Using a human-in-the-loop approach, we collected a high-quality training dataset for a mathematical questioning scenario. Using recent advances in uncertainty quantification, we evaluated our conversational agent for usability and analyzed the practicality of incorporating a human-in-the-loop approach for data collection and system evaluation for a mathematical questioning scenario., Comment: Accepted to appear at the NeurIPS 2021 Workshop on Math AI for Education (MATHAI4ED)
- Published
- 2021