Concurrent Session #4: SchemaStudy: Harnessing AI to Enhance Study Skills and Learning in Biology
Alternative Title
SchemaStudy: Harnessing Artificial Intelligence (AI) to Enhance Study Skills and Learning in Biology
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 (2023 : Orlando, Fla.)
Location
Key West B
Start Date
24-9-2023 3:00 PM
End Date
24-9-2023 3:45 PM
Publisher
University of Central Florida Libraries
Keywords:
AI in education; Biology study skills; Personalized feedback; Concept mapping; STEM learning enhancement
Subjects
Artificial intelligence--Educational applications; Biology--Computer-assisted instruction; Study skills--Computer programs; Learning strategies--Study and teaching; Science--Study and teaching--Computer programs
Description
SchemaStudy is a user-friendly web application designed to enhance student study skills in undergraduate biology. Utilizing an OpenAI API, SchemaStudy provides personalized formative feedback as students actively engage with course topics, terms, themes, examples, or concepts at three progressively complex levels. From defining terms and making connections to constructing intricate concept networks, students receive immediate feedback from the API. This accessible tool, which requires no coding experience from faculty, exemplifies the transformative potential of AI in fostering conceptual understanding and improving study skills in STEM education.
Language
eng
Type
Presentation
Rights Statement
All Rights Reserved
Audience
Educators, Faculty, Students
Recommended Citation
Reuther, Keefe, "Concurrent Session #4: SchemaStudy: Harnessing AI to Enhance Study Skills and Learning in Biology" (2023). Teaching and Learning with AI Conference Presentations. 49.
https://stars.library.ucf.edu/teachwithai/2023/sunday/49
Concurrent Session #4: SchemaStudy: Harnessing AI to Enhance Study Skills and Learning in Biology
Key West B
SchemaStudy is a user-friendly web application designed to enhance student study skills in undergraduate biology. Utilizing an OpenAI API, SchemaStudy provides personalized formative feedback as students actively engage with course topics, terms, themes, examples, or concepts at three progressively complex levels. From defining terms and making connections to constructing intricate concept networks, students receive immediate feedback from the API. This accessible tool, which requires no coding experience from faculty, exemplifies the transformative potential of AI in fostering conceptual understanding and improving study skills in STEM education.