Teaching the Teachers: Building Generative AI Literacy in Higher Ed Instructors

2025-09-15

AI Summary

Current generative AI literacy among higher education faculty is generally inadequate, while existing research predominantly focuses on students, leaving critical gaps in faculty professional development support. Method: This study designed and implemented the “AI Academy,” a context-embedded professional development program positioning faculty as designers of AI-integrated pedagogy. Grounded in educational technology theory and participatory design, it integrated technical exploration, pedagogical reflection, and peer collaboration within policy, tool, and institutional contexts to foster responsible AI integration. A mixed-methods approach—including pre-/post-surveys, learning journals, and facilitator interviews—was employed. Results: Among 25 participating faculty, significant gains in generative AI literacy were observed, particularly in tool application, ethical reasoning, and institutional coordination. The study produced a scalable program model, co-developed assessment instruments, and a robust framework for designing adaptive, iteration-responsive faculty development—thereby addressing empirical and practical gaps in AI literacy cultivation for educators.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Philosophy and Ethics of AI: Artificial General Intelligence
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Generative AI is reshaping higher education, yet research has focused largely on students, while instructors remain understudied despite their central role in mediating adoption and modeling responsible use. We present the extit{AI Academy}, a faculty development program that combined AI exploration with pedagogical reflection and peer learning. Rather than a course evaluated for outcomes, the Academy provided a setting to study how instructors build AI literacies in relation to tools, policies, peer practices, and institutional supports. We studied 25 instructors through pre/post surveys, learning logs, and facilitator interviews. Findings show AI literacy gains alongside new insights. We position instructors as designers of responsible AI practices and contribute a replicable program model, a co-constructed survey instrument, and design insights for professional development that adapts to evolving tools and fosters ethical discussion.

Problem

• Addressing understudied AI literacy development in higher education instructors
• Exploring how instructors build AI literacy through tools and peer learning
• Designing professional development for ethical AI adoption in teaching practices

Innovation

• Faculty development program combining AI exploration with pedagogy
• Studied instructors through surveys logs and facilitator interviews
• Co-constructed survey instrument for professional development adaptation