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

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Sep 24th, 3:00 PM Sep 24th, 3:45 PM

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.