AI Design Challenge: Make Your Own Instructional Design Tool!

 Please Note: While attending the webinar live is free for OLC members and non-members, on-demand recordings will be available post-webinar for Professional and Institutional Members only. Consider becoming an OLC member for access to these and many other great benefits!

**This webinar is part of the OLC Accelerate 2024 Best-in-Track webinar series!**

In 2023, a large university’s learning and teaching center within the engineering department began experimenting with large language models (LLMs) for various instructional design tasks. By early 2024, the department embarked on a university-wide challenge, securing support to collaboratively develop AI tools for instructional design. Led by members of that AI development team, this webinar will show participants how to use their process to develop their own AI tools. Participants will learn a structured approach to designing AI tools, from defining use cases to storyboarding human-AI interactions. The session emphasizes collaboration, inclusivity, and empowering instructional designers to build solutions that align with their unique needs. 

Participants will be provided with an AI Development Starter Kit containing resources that will guide them through the design process. Attendees will have access to a repository which includes tools like Learning Objective Creators, Project Based Learning Assessment Suggestion Engine, Alignment Checkers, Lesson Planners, Learning Scenario Generators, Inclusive Design Assistants, among many more. It will include a set of prompts annotated to explain the prompting strategy used in these tools and attendees will leave the session with access to those prompts.

Key Takeaways:

  • Gain practical experience in developing AI tools for instructional design. 
  • Learn how to integrate AI tools into your instructional design workflows. 
  • Foster a collaborative and innovative environment for AI development. 
  • Leave with actionable insights and a structured approach to AI tool development.

Intended Audience: 

Instructional designers, design thinkers, and faculty

Speaker Bio
Jonathan McMichael
Learning Experience Designer – Arizona State University-Tempe

Jonathan McMichael is a Learning Experience Designer at the Fulton School of Engineering’s Learning and Teaching Hub at Arizona State University. He holds a BA in Education from the University of Kentucky and a Master’s in Library Science from the University of Illinois at Urbana-Champaign. In his current role, Jonathan collaborates with faculty and course instructors to create engaging environments and experiences that support the success and well-being of all FSE students. Since 2022, Jonathan has focused on the intersection of Generative AI and higher education, leading initiatives in instructional design, classroom pedagogy, and community-centered design thinking. His work emphasizes principled exploration and innovation, empowering educators to navigate and leverage AI tools for impactful teaching and learning. Before joining ASU, Jonathan served as an academic librarian, specializing in early undergraduate success and information literacy instruction. In these roles, he designed research assignments, developed institution-wide curricula, implemented student success initiatives that improved retention and graduation rates, and facilitated training for instructors and colleagues in evidence-based, high-impact teaching practices.

Sue Huffman
Learning Experience Designer – Arizona State University-Tempe

Sue Huffman is a Learning Experience Designer in the Learning and Teaching Hub at Arizona State University, where she collaborates with faculty in the College of Engineering to create engaging online learning environments. Sue has a Master of Science in Science Education and before joining the hub has worked as a science teacher, curriculum writer, and project coordinator- developing and presenting informal K12 STEM programs and teacher professional development. Her current work at ASU spans diverse areas, including biomedical engineering, construction programs, and virtual reality development. Sue is passionate about creating communities of practice around AI that are reflective, inclusive, and support exploration and honest feedback.