Designing Custom AI Assistants for Higher Education: July 2025

Part 1: July 7, 2025 | 12:00–1:30 p.m.ET
Part 2: July 10, 2025 | 12:00–1:30 p.m.ET
Part 3: July 14, 2025 | 12:00–1:30 p.m.ET
Part 4: July 17, 2025 | 12:00–1:30 p.m.ET

Overview

In this “design thinking”-style Learning Lab, you will explore the transformative potential of generative AI in higher education. Through hands-on activities and real-world case studies, learners will deconstruct AI tools such as chatbots, customizable agents, and virtual assistants, and then build their own. No prior coding experience or paid-for generative AI model is necessary.

You will critically analyze the capabilities and applications of generative AI, fostering a deeper understanding of its impact on teaching, research, and administrative processes. During live sessions, you will engage in interactive exercises, evaluating and synthesizing practical use cases tailored to your specific unit and/or institutional needs. You will identify and assess tasks within your professional domains that could be supported by AI assistants. You will then test these hypotheses to determine where and how the technology works for your case, or―just as importantly―if AI is not the solution to the tasks that you have in mind. Collaborative sessions will challenge you to critically examine and devise innovative solutions, integrating generative AI into your existing workflows and practices. You will design and integrate strategies for your use of AI tools, including prompt engineering, to address complex scenarios and optimize efficiency across various higher education functions.

Learning Outcomes:

NOTE: You will be asked to complete assignments in between the Learning Lab segments that support the learning outcomes stated below. You will receive feedback and constructive critique from course facilitators.

• Analyze the key characteristics, capabilities, and potential applications of generative AI toolsets and technologies within the context of higher education.
• Ideate various use cases where generative AI can be applied to meet specific unit or institutional needs.
• Develop a custom chatbot or AI solution that addresses specific unit or institutional needs.
• Evaluate the effectiveness of the custom chatbot or AI solution at meeting specific unit or institutional needs.
• Iterate on the custom chatbot or AI solution to improve performance.