Learning by Making with Generative AI: A Faculty Development Design Case
Article Sidebar
Main Article Content
Abstract
This design case presents a series of exploratory faculty development workshops created in response to institutional uncertainty about how to meaningfully engage with generative AI. Developed at a teaching-focused university in the United States, the workshops were grounded in constructionist pedagogy and emphasized playful prompting, peer interaction, and the creation of contextually relevant artifacts. Rather than offering training or technical guidance, the design aimed to cultivate GenAI literacy through hands-on experimentation and reflection. Participants surfaced misconceptions, tested tool limitations, and adapted outputs to their pedagogical needs. Some found the open format empowering; others desired more conceptual grounding. This tension underscores broader challenges in applying constructionist methods to faculty learning. The case traces the pedagogical commitments and design logic behind the workshop series, while reflecting on key facilitation choices and unexpected outcomes.
Downloads
Article Details
Matthew R Fischer, Norwich University
Matthew R Fischer is an assistant professor of criminology and criminal justice at a teaching-focused university in the northeastern United States. His work explores trust, governance, experiential learning, and the role of generative AI in faculty development.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright © 2026 by the International Journal of Designs for Learning, a publication of the Association of Educational Communications and Technology (AECT), published by Indiana University Libraries Journals. Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee, provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Except as otherwise noted, the content published by IJDL is licensed under CC BY-NC-ND 4.0. A simpler version of this statement is available here.