Led by members of an AI development team, this session participants will collaboratively develop their own AI tools. Participants will engage in a rapid AI design challenge where they will explore and remix previously developed tools. This session will walk attendees through a design process that prioritizes instructional designer expertise.

Extended Abstract Description: 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 session will show participants how to use their process to develop their own AI tools. Participants will engage in a rapid AI design session, exploring and remixing previously developed instructional design AI tools and prompts. This session will guide attendees through a design process that prioritizes human expertise and learning when working with AI, and offer practical insights and practices that can be adapted by other educational institutions. Session Plan: We will start with a brief activation segment where participants share their experiences and ideas on using AI prompts in instructional design, setting the stage for collaborative learning (5 minutes). Following this, we will provide a demonstration explaining the context of our work with Generative AI, detailing our development process, and deconstructing an example prompt to illustrate how its components influence outputs (15 minutes). The core of the session involves an extended collaborative design challenge (45 minutes). Groups of participants will be provided with an AI Development Starter Kit containing resources that will guide them through the design process. In this design process, groups will work together to describe their use case for AI tools and identify the criteria for quality outputs. They will then storyboard the interaction they would like users to have with the AI tool. After describing their vision for the tool, groups will move on to crafting customized prompts that could utilize the prompting structure the team used or remix one of the existing prompts contained within a repository they will have access to. This repository 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 to access to those prompts. Finally, participants will test their tools, imagine next steps, and share their results in a way that shows the promise of what they are envisioning. Facilitators will provide guidance and support throughout this activity. Following the collaborative design activity, selected groups will present their AI tools and discuss their design vision (15 minutes). This will be followed by peer feedback and a constructive discussion. The session will conclude with reflections on the collaborative process, potential future applications of AI in instructional design (10 minutes). Session Goals: Attendees will: Gain practical experience in developing AI tools for instructional design. Learn how to integrate AI tools into their instructional design workflows. Foster a collaborative and innovative environment for AI development. Leave with actionable insights and a structured approach to AI tool development. Interactivity: Participants will engage in a design challenge where small groups will redesign or create new AI tool prompts and explain how their AI tool prioritizes human expertise and authentic learning experiences. At the end of the session, will reflect on the collaborative process and potential future applications of AI in instructional design at their institutions. Summary of Participant Activity In these session, participants will: Describe their specific use cases for AI tools in instructional design. Identify criteria for quality outputs when using AI tools. Storyboard user interactions with AI tools. Customize and remix AI prompts to meet instructional design needs. Test and refine AI tools based on immediate feedback. Share and present AI tool designs, demonstrating their potential impact on student learning. Collaborate effectively in small groups, leveraging collective expertise. Reflect on the design process and explore future applications of AI in instructional design.