Cross-Disciplinary Strategies for Supporting Student Learning with Text-Based GenAI
Alternative Title
Cross-Disciplinary Strategies for Supporting Student Learning with Text-Based Generative Artificial Intelligence (GenAI)
Contributor
University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2024 : Orlando, Fla.)
Location
Seminole B
Start Date
24-7-2024 10:15 AM
End Date
24-7-2024 10:45 AM
Publisher
University of Central Florida Libraries
Keywords:
Text-based AI; Student engagement; Reflective analysis; Cross-disciplinary learning; Interactive study tools
Subjects
Artificial intelligence--Educational applications; Artificial intelligence--Study and teaching; Learning--Research; Teaching teams--Research; Creative teaching--Research
Description
During fall 2023, a research team at the UK's teaching center conducted a 14-week exploration of the capacities of four text-based GenAI tools to support student learning across six disciplines. The study emphasized repeated prompting, pushing back, and re-prompting of the bots, as well as student reflection on the process. This session presents findings on GenAI's effectiveness as a dynamic, interactive study tool. Qualitative and reflective analysis of the data reveals strategies for effectively engaging students with these tools and highlights the importance of coaching students to be curious and critical in leveraging AI for their own learning.
Language
eng
Type
Presentation
Rights Statement
All Rights Reserved
Audience
Faculty, Students, Instructional designers
Recommended Citation
Abney, Jill and Conatser, Trey, "Cross-Disciplinary Strategies for Supporting Student Learning with Text-Based GenAI" (2024). Teaching and Learning with AI Conference Presentations. 18.
https://stars.library.ucf.edu/teachwithai/2024/wednesday/18
Cross-Disciplinary Strategies for Supporting Student Learning with Text-Based GenAI
Seminole B
During fall 2023, a research team at the UK's teaching center conducted a 14-week exploration of the capacities of four text-based GenAI tools to support student learning across six disciplines. The study emphasized repeated prompting, pushing back, and re-prompting of the bots, as well as student reflection on the process. This session presents findings on GenAI's effectiveness as a dynamic, interactive study tool. Qualitative and reflective analysis of the data reveals strategies for effectively engaging students with these tools and highlights the importance of coaching students to be curious and critical in leveraging AI for their own learning.