This workshop is based on "Instructors as Innovators: A Future-Focused Approach to New AI Learning Opportunities, with Prompts" by Dr. Ethan Mollick and Dr. Lilach Mollick. Attendees will learn how to create personalized learning experiences by building pedagogical tools through hands-on activities and collaborative exercises that utilize innovative prompting methodologies.

This workshop will explore the transformative potential of customized learning tools such as GPTs for enriching teaching and learning, drawing from the insights presented in "Instructors as Innovators: A Future-Focused Approach to New AI Learning Opportunities, with Prompts" by Dr. Ethan Mollick and Dr. Lilach Mollick. Participants will learn how to build learning tools for students that enable novel forms of practice and application, such as simulations, mentoring, coaching, and co-creation. The workshop will cover various prompt types, including negotiation simulation, goal setting, critique, teaching, case creation, concept integration, and tutoring, all designed to create personalized learning experiences. Attendees will learn how customize prompts based on their subject matter expertise and their course learning goals. Attendees will gain hands-on experience in customizing and using these prompts to suit their educational contexts. The session will start with a presentation on the methodologies behind these prompts, followed by a live demonstration of how to interact with and customize prompts using large language models like ChatGPT or Claude. Participants will then engage in a 45-minute "Prompting Playground" session, where they can create, and test custom prompts tailored to their teaching goals. The workshop will conclude with small group discussions to share experiences and a large group debrief to consolidate learning and discuss future applications. Participant Learning Outcomes: 1. Develop proficiency in using prompting methodologies to enhance educational experiences. 2. Gain hands-on experience in designing and interacting with custom AI learning tools. 3. Cultivate a mindset of innovation and playfulness in educational AI applications. 4. Apply learned AI strategies to create personalized learning experiences in their teaching contexts. Structure and Time Allotments: 1. Introduction and Presentation (10 mins): Overview of prompting methodologies, including Chain-of-Thought (CoT), Tree of Thought (ToT) and the common elements (e.g., goals, personae, narrative, steps) of the prompts used in the workshop. 2. Demonstration (10 mins): Facilitator demonstrates how to use sophisticated pedagogical prompts, custom GPTs and explains customization options. 3. Hands-On Activity - Prompting Playground (45 mins): Participants create and test custom prompts, receiving real-time feedback. 4. Small Group Discussion (15 mins): Participants discuss experiences and applications of prompts. 5. Large Group Discussion and Wrap-Up (10 mins): Sharing insights, troubleshooting, and future applications. Engagement Strategies: • Demonstrations of generative AI tools to foster excitement around personalizing learning experiences. • Collaborative prompting playground for active development of custom prompts. • Iterative feedback loops for refining prompting skills. • Hands-on tinkering to encourage playful experimentation. Materials Required for Participants: Laptops or mobile devices with internet access, access to LLMs like ChatGPT, Claude, or Gemini. Primary Audience: Educators, instructional designers, and academic technologists interested in integrating AI into teaching and learning to create personalized and interactive educational experiences. Unique Takeaways: • Practical skills in intermediate AI prompting techniques. • Customized AI learning tools tailored to individual teaching contexts. • Strategies for troubleshooting and testing AI prompts before classroom use. • Innovative and playful approach to AI integration in education. Presenter's Note: This hands-on workshop model using the prompts outlined in the Mollick & Mollick research article was well received at a recent faculty workshop. The OLC workshop will be slightly refined based on faculty feedback.