AI as Co-Designer: Reimagining Open Pedagogy Through Transparent, Ethical AI Integration
Program Type
Event
Start Date and Time
11-5-2026 8:00 AM
Program Description
This session responds directly to the theme Reimagining Learning: The Future of Open Education by demonstrating how generative AI can be intentionally integrated into OER-based courses to strengthen access, rigor, and learner agency. Rather than treating AI as a threat or relegating it to policy statements, I present a design-centered approach that positions generative AI as a co-designer of open pedagogy, one that amplifies critical thinking and makes learning more adaptive and participatory. Using my Sneaker Hustle project, a consumer behavior and marketing simulation built on openly licensed materials, I illustrate how I redesigned a traditional OER assignment into a dynamic, AI-supported learning system. In my courses, students use generative AI as a structured ideation and analysis partner to generate alternative market scenarios, draft consumer personas, and test positioning strategies. However, they must critique, revise, and document their intellectual contributions, making their thinking visible. Through this example, I demonstrate how AI-integrated course design aligns with the CARE Framework for sustainable OER stewardship by enabling iterative student contributions, requiring transparent attribution of human and AI input, structuring materials for open and platform-neutral reuse, and leveraging AI as a cognitive scaffold that lowers barriers while preserving accountability. Participants will examine concrete artifacts, including AI-use language, collaboration statements, and assignment templates, and leave with a replicable framework for integrating AI into their own open courses. This session positions AI as a design opportunity that advances the sustainability and future of open education. Learning outcomes: Analyze how generative AI can function as a co-designer within an OER-based assignment. Develop transparent AI-use language and collaboration statements that make student thinking and AI contributions visible. Apply the CARE Framework to redesign an existing open assignment to enhance contribution, attribution, release, and learner empowerment.
AI as Co-Designer: Reimagining Open Pedagogy Through Transparent, Ethical AI Integration
This session responds directly to the theme Reimagining Learning: The Future of Open Education by demonstrating how generative AI can be intentionally integrated into OER-based courses to strengthen access, rigor, and learner agency. Rather than treating AI as a threat or relegating it to policy statements, I present a design-centered approach that positions generative AI as a co-designer of open pedagogy, one that amplifies critical thinking and makes learning more adaptive and participatory. Using my Sneaker Hustle project, a consumer behavior and marketing simulation built on openly licensed materials, I illustrate how I redesigned a traditional OER assignment into a dynamic, AI-supported learning system. In my courses, students use generative AI as a structured ideation and analysis partner to generate alternative market scenarios, draft consumer personas, and test positioning strategies. However, they must critique, revise, and document their intellectual contributions, making their thinking visible. Through this example, I demonstrate how AI-integrated course design aligns with the CARE Framework for sustainable OER stewardship by enabling iterative student contributions, requiring transparent attribution of human and AI input, structuring materials for open and platform-neutral reuse, and leveraging AI as a cognitive scaffold that lowers barriers while preserving accountability. Participants will examine concrete artifacts, including AI-use language, collaboration statements, and assignment templates, and leave with a replicable framework for integrating AI into their own open courses. This session positions AI as a design opportunity that advances the sustainability and future of open education. Learning outcomes: Analyze how generative AI can function as a co-designer within an OER-based assignment. Develop transparent AI-use language and collaboration statements that make student thinking and AI contributions visible. Apply the CARE Framework to redesign an existing open assignment to enhance contribution, attribution, release, and learner empowerment.
