More than Model Documentation: Uncovering Teachers' Bespoke Information Needs for Informed Classroom Integration of ChatGPT

要旨

ChatGPT has entered classrooms, circumventing typical training and vetting procedures. Unlike other educational technologies, it placed teachers in direct contact with the versatility of generative AI. Consequently, teachers are urgently tasked to assess its capabilities to inform their use of ChatGPT. However, it is unclear what support teachers have and need and whether existing documentation, such as model cards, provides adequate direction for educators in this new paradigm. By interviewing 22 middle- and high-school ELA and Social Studies teachers, we connect the discourse on AI transparency and documentation with educational technology integration, highlighting the information needs of teachers. Our findings reveal that teachers confront significant information gaps, lacking clarity on exploring ChatGPT's capabilities for bespoke learning tasks and ensuring its fit with the needs of diverse learners. As a solution, we propose a framework for interactive model documentation that empowers teachers to navigate the interplay between pedagogical and technical knowledge.

著者
Mei Tan
Stanford University, Stanford, California, United States
Hariharan Subramonyam
Stanford University, Stanford, California, United States
論文URL

https://doi.org/10.1145/3613904.3642592

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Education and AI A

316B
5 件の発表
2024-05-13 23:00:00
2024-05-14 00:20:00