I led an AI workgroup to explore the practical applications of GenAI for UCLA Extension instructors and course developers.
Recognizing the transformative potential of AI in education, the initiative focused on responsible AI integration and effective prompting techniques to maximize outcomes in three key areas: course design, course development, and teaching.
My role encompassed project leadership and content creation.
As workgroup lead, I oversaw the strategy and development of the AI initiative, ensuring alignment with institutional goals and instructor needs.
I led research and upskilling team workshops and cross-campus partnerships to develop practical AI use cases and resources. I also contributed to AI policy discussions.
Focusing on low-cost, high-impact AI projects, I developed a variety of resources, including:
The primary goal was to develop actionable AI resources that instructors could implement right away. Here’s a quick snapshot of some key resources that were developed:
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Centralized access to AI resources, training, groups, publications, article guides, and more.
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Developed 300+ useful prompts in the areas of course design, course development, and teaching.
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Developed 10+ article guides on AI literacy, responsible use, and prompting techniques.
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Developed a framework of AI webinars and workshops to provide ongoing training to instructors.
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Mapped out a structured workflow that integrates AI into the course design and development process to enhance efficiency.
The approach was to be students of GenAI as much as trainers. Building on this foundation, our focus was to research, learn, and build scalable training solutions by:
Conducting extensive research on existing trainings, academic resources, institutional policies, intellectual property guidelines, ethical considerations, and compliance standards.
Forming cross-campus partnerships with instructional design teams, IT, and EDI offices on UCLA’s main campus to align AI resources and strategies institution-wide.
Collaborative upskilling through internal workshops, enabling the team to explore AI capabilities, test applications, and collaboratively develop use cases.
Developing scalable AI resources like prompt libraries, Knowledge Base articles, and webinars/workshops that can be continuously updated as AI tools and best practices evolve.
Here are a few samples from the ongoing initiative.