AI in AI: Adjudicating Academic Integrity Cases Alleging Use of Artificial Intelligence

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 (2025 : Orlando, Fla.)

Location

Seminole E

Start Date

29-5-2025 2:45 PM

End Date

29-5-2025 3:10 PM

Publisher

University of Central Florida Libraries

Keywords:

Academic integrity; Artificial intelligence; Student conduct; Misconduct assessment; Ethical strategies

Subjects

Artificial intelligence--Study and teaching (Higher); Artificial intelligence--Moral and ethical aspects; Artificial intelligence--Educational applications; Student ethics; Community and college--Moral and ethical aspects

Description

This session provides an overview of AI's impact on academic integrity at Valencia College. Beginning with introductions, we will explore the AI landscape through a combination of lecture and large group activities. The session will then cover Valencia College's approach to academic integrity, including a detailed review of the student conduct process for academic dishonesty cases. Participants will engage in an "Egregiousness Spectrum" activity to assess varying levels of misconduct, followed by a reflection session. The event will conclude with a collaborative discussion on strategies for maintaining academic integrity in an AI-driven world.

Language

eng

Type

Presentation

Rights Statement

All Rights Reserved

Audience

Faculty; Administrators

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May 29th, 2:45 PM May 29th, 3:10 PM

AI in AI: Adjudicating Academic Integrity Cases Alleging Use of Artificial Intelligence

Seminole E

This session provides an overview of AI's impact on academic integrity at Valencia College. Beginning with introductions, we will explore the AI landscape through a combination of lecture and large group activities. The session will then cover Valencia College's approach to academic integrity, including a detailed review of the student conduct process for academic dishonesty cases. Participants will engage in an "Egregiousness Spectrum" activity to assess varying levels of misconduct, followed by a reflection session. The event will conclude with a collaborative discussion on strategies for maintaining academic integrity in an AI-driven world.