Paper Type

ERF

Abstract

This work-in-progress paper explores how students’ trust in generative AI evolves during the learning process within a STEM education context. As tools like ChatGPT are increasingly used in classrooms, trust plays a pivotal role in shaping adoption, use, and learning outcomes. The planned case study will take place at a public university in France, where STEM students will use ChatGPT across a series of lab assignments, followed by a web-based survey. Semi-structured interviews with the course instructor will complement the data, exploring the instructor’s perspective on student trust, their own trust in AI, and broader pedagogical implications. Using a folk theory framework, the study approaches trust as a dynamic, experience-driven process rather than a fixed prerequisite.

Paper Number

1034

Author Connect URL

https://authorconnect.aisnet.org/conferences/AMCIS2025/papers/1034

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Aug 15th, 12:00 AM

Evolving Trust in Generative AI: A Study of Student Learning Experiences

This work-in-progress paper explores how students’ trust in generative AI evolves during the learning process within a STEM education context. As tools like ChatGPT are increasingly used in classrooms, trust plays a pivotal role in shaping adoption, use, and learning outcomes. The planned case study will take place at a public university in France, where STEM students will use ChatGPT across a series of lab assignments, followed by a web-based survey. Semi-structured interviews with the course instructor will complement the data, exploring the instructor’s perspective on student trust, their own trust in AI, and broader pedagogical implications. Using a folk theory framework, the study approaches trust as a dynamic, experience-driven process rather than a fixed prerequisite.

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