Learning Experience

The Learning Lab experience is supported by both asynchronous and synchronous components. Each part includes a set of resources, an asynchronous discussion, and an interactive live session, all of which culminate in the development of a project to apply learning to local and specific contexts in support of the learning objectives.


Part 1: Exploring AI Prompting

January 22 | 1:00–2:30 p.m. ET

In part 1, we will build on our introduction to responsible prompting, potential benefits of AI in education, and ethical considerations. This live session will be hands-on, allowing participants to experiment with AI tools and platforms and explore integration into their workflows.

Part 2: Refining AI Prompts

January 25 | 1:00–2:30 p.m. ET

In part 2, we'll refine our understanding of prompt engineering through interactive exercises and peer review, giving participants the opportunity to practice writing and refining prompts to provide adequate context for the AI tool to generate useful text for specific work and contexts at their institutions.

Part 3: AI-Generated Prompts and Pedagogical and Design Best Practices

January 29 | 1:00–2:30 p.m. ET

In part 3, participants will continue to experiment with prompting techniques and receive feedback on AI-generated prompts while aligning with best practices in pedagogy and instructional design.

Part 4: Review and Reflect: Applying AI to Your Work

February 5 | 1:00–2:30 p.m. ET

In part 4, participants will cohere their techniques and outcomes into a final project. We will frame some categories for a final project, such as organizational change plans, career maps, or learning objects for instruction. Participants will design alongside classmates and take initial steps to apply their new knowledge into a project.

Lab Project

Participants will apply their learning to develop a final project that incorporates generative AI capabilities to support work in their specific domains.

Participants will have the opportunity to choose a project that aligns with their professional interests and responsibilities. Examples of projects could include creating a video for online teaching they can use in their class right now, developing a sample organizational change plan from the perspective of their position, creating a crucial conversation plan to discuss with their supervisor, developing a career trajectory map with needed learnings and information, or creating an operating budget for their group.

Throughout the project development process, participants will be encouraged to incorporate generative AI capabilities in a responsible and ethical manner, aligning with best practices in pedagogy and instructional design. They will also have the opportunity to collaborate with peers and receive feedback on their projects for continuous learning and improvement.