Alternative Title

Beyond the Basics: A Structured Faculty Development Model for Evaluating Generative Artificial Intelligence (GenAI) Research Applications

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

Sun & Surf I/II

Start Date

29-5-2025 2:00 PM

End Date

29-5-2025 2:25 PM

Publisher

University of Central Florida Libraries

Keywords:

Generative AI; Faculty development; Disciplinary expertise; Workshop series; Evaluation methods

Subjects

Artificial intelligence--Educational applications; Artificial intelligence--Study and teaching (Higher); Workshops (Adult education)--Evaluation; Artificial intelligence--Research; Educational innovations--Evaluation

Description

As generative AI transforms academic work, faculty development initiatives often struggle to bridge the gap between generic AI overviews and discipline-specific needs. Rush University implemented an innovative three-part workshop series that paired disciplinary expertise with AI-focused educational guidance to help faculty critically evaluate GenAI tools for academic research. Moving beyond theoretical presentations, the series demonstrated AI's potential through mini-experiments in the following areas: AI-powered literature reviews, data analysis and visualization, and innovative uses as a peer reviewer and evaluator. This evidence-based approach to systematically testing AI systems advances faculty development beyond general awareness toward rigorous, discipline-specific evaluation.

Language

eng

Type

Presentation

Format

application/pdf

Rights Statement

All Rights Reserved

Audience

Faculty

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May 29th, 2:00 PM May 29th, 2:25 PM

Beyond the Basics: A Structured Faculty Development Model for Evaluating GenAI Research Applications

Sun & Surf I/II

As generative AI transforms academic work, faculty development initiatives often struggle to bridge the gap between generic AI overviews and discipline-specific needs. Rush University implemented an innovative three-part workshop series that paired disciplinary expertise with AI-focused educational guidance to help faculty critically evaluate GenAI tools for academic research. Moving beyond theoretical presentations, the series demonstrated AI's potential through mini-experiments in the following areas: AI-powered literature reviews, data analysis and visualization, and innovative uses as a peer reviewer and evaluator. This evidence-based approach to systematically testing AI systems advances faculty development beyond general awareness toward rigorous, discipline-specific evaluation.