The Learning Lab experience is supported by both asynchronous and synchronous components. Each Learning Lab sequence includes a set of resources, an asynchronous discussion, and an interactive live session, all of which culminate in the development of a project or application to apply learning to local and specific contexts in support of the learning objectives.
Schedule
Part 1: The Foundations and Challenges of the HyFlex Model
January 27, 2025, 12:00–1:30 p.m. ET
In Part 1, participants will receive an orientation to the Learning Lab and get to know their fellow participants and facilitators. We’ll review the HyFlex pillars and discuss universal design principles that address time and cost challenges. Participants will have the opportunity to discuss the current status of HyFlex in the literature and their specific context.
Learning Goals:
- Discuss and review HyFlex foundational concepts, including delivery modalities, and implementation challenges.
- Discuss and apply a universal course design approach to create a flexible course structure that is based on Bloom’s taxonomy-based flipped learning principles.
Part 2: Designing and Redesigning Your HyFlex Course Using AI Support
January 30, 2025, 12:00–1:30 p.m. ET
In part 2, participants will identify key evidence-based design elements and strategies to take their courses to the next-level of HyFlex teaching and learning–they’ll go beyond offering basic flexibility options and utilize AI tools to streamline and enhance the course design and building process. Participants will also critique and refine each other’s course designs to maximize quality and flexibility.
Learning Goals:
- Identify key design elements that support next-level (advanced) HyFlex course delivery.
- Apply evidence-based design strategies to develop or improve specific HyFlex course content and delivery
- Utilize AI tools to streamline and enhance the course design process.
- Collaborate with peers to critique and refine course designs.
Part 3: Evaluating Impact of your HyFlex Design/Redesign
February 4, 2025, 12:00–1:30 p.m. ET
In part 3, participants will focus on assessing the effectiveness of their HyFlex course designs using a variety of evaluation instruments. Emphasis will be placed on leveraging AI tools to streamline the feedback gathering and interpretation process so educators can efficiently analyze course data, gaining deeper insights into student engagement, learning outcomes, and overall course effectiveness. Collaborative activities will allow participants to share their findings and strategies, fostering a community of practice focused on innovative and effective HyFlex teaching.
Learning Goals:
- Assess the effectiveness of your HyFlex course design using provided instruments or those you develop.
- Utilize AI to gather and interpret course feedback.
- Create actionable plans based on evaluation results to improve course quality.
Part 4: Finalizing Your HyFlex Course Design/Redesign Plans
February 11, 2025, 12:00–1:30 p.m. ET
In part 4, participants will finalize the HyFlex course design/redesign and evaluation plans and share their completed plans with peers for constructive critique and collaborative refinement. Additionally, participants will share the AI approaches they used to develop and evaluate their plans and comment on the effectiveness and efficiency of these tools.
Learning Goals:
- Finalize the detailed design plan for your HyFlex course.
- Create a timeline and implementation plan for your course design (post-course plan). (Optional) use AI to help you develop the plan.
- Develop a framework for ongoing course iteration and improvement using the feedback you anticipate receiving from the tools you identified in Session 3.
- Present your completed design plan to peers for feedback.
Design/Redesign Plan with Generative AI Assist
To synthesize the concepts learned throughout the lab, participants will select and complete the following design/redesign project plan that includes:
- A proposed implementation timeline (for a fully built course).
- A plan to address HyFlex best practices including methods to engage students across delivery modes and strategies to foster a sense of instructor presence and peer connection.
- A way to use AI tools to enhance course delivery and assessment (optional).
- Tools and strategies for assessing course effectiveness and making iterative improvements.
Participants will present their completed projects to peers for feedback and discussion and reflect on the process and anticipated impact on their teaching and student learning.
NOTE: While it is possible to develop a course during the Learning Lab, it is recommended that participants come with a course in mind to maximize their time.