ISCAP Proceedings: Abstract Presentation
Using generative AI to partially automate certain aspects of course design and development
Michael Smith
Georgia Institute of Technology
Abstract
This research in progress addresses the need for rapid development of new course material at the college level, enabling educators to more easily adapt to the evolving business and technology landscape. The primary objective is to establish a systematic approach by which educators can use the capabilities of generative AI to speed up course development. This work will be particularly beneficial for veteran instructors with deep domain expertise who are best qualified to evaluate the quality of generated outputs.
Building upon a model first introduced at the Decision Sciences Institute (DSI) 2023 conference, this research focuses on creating effective prompts and workflows to partially automate the development of comprehensive course frameworks and content. These frameworks include high-level objectives and detailed subobjectives, ensuring alignment with desired learning outcomes. The content must be adaptable for presentations, manuscripts, and assessments.
By offering a structured methodology for AI-assisted course creation, this work enables experienced educators to shift their focus from the labor-intensive process of initial course development to the more critical tasks of content refinement and delivery.
The presentation will feature live demonstrations of the prompting techniques and workflows developed in this research. These demonstrations will show how educators can use generative AI tools to produce high-quality course objectives and content with increased efficiency. Attendees will gain practical insights into how to incorporate these techniques into their course design processes.