Event FinderUn-Coding AI in the Classroom: 2-Day Workshop for Faculty and Instructors
- Starts
- Ends
- Format
- In person
- Location
- DataLab Classroom, Shields Library, 360, Davis, CA, United States
About This Event
Generative AI is reshaping the landscape of higher education, raising important questions for teaching, learning, and academic integrity. Designed for faculty and instructors across all disciplines and requiring no prior technical background, this two-day workshop unpacks genAI and offers practical strategies for the university classroom. Whether you are curious about how these models work, eager to integrate AI into your teaching, or cautious about its impact on student learning, this series offers a supportive, nuanced space to explore. Participants will gain a clear foundational understanding of large language models (LLMs), evaluate the opportunities and limitations of genAI, and engage in hands-on practice configuring customized and privacy-protected AI learning environments for their courses. The workshop runs Thursday-Friday December 10-11 from 9 AM - 4 PM daily with a break for lunch. Full participation in both days is recommended as topics build across sessions. Day 1: Un-coding AI Day 1 strips away the technical jargon to examine what genAI actually is — and what it isn't. Taking a no-code approach, we begin by exploring how LLMs process and generate language using intuitive, non-mathematical concepts. We examine how these models are developed and generate responses, explore the root causes of hallucinations, trace the influence of algorithmic bias, and discuss the impacts of genAI on the environment, society and self. Moving into practical engagement, we will discuss pedagogical and prompting strategies that keep human judgment and critical thinking firmly at the center of the learning process while safeguarding privacy. At the end of the day we will review institutional technology stack options (including the RockyAI implementation in Canvas, Google Gemini, and open-source models) to help you weigh the pros, cons, and privacy considerations as you build a practical roadmap for considering genAI integration into your courses. Day 2: AI in the Classroom Building on Day 1's foundational concepts, Day 2 transitions into an interactive, hands-on workshop focused on implementing privacy-protected AI tools directly into your curriculum. Participants will work step-by-step to configure course-ready environments on their own devices. We will explore an implementation of RockyAI embedded within Canvas for 24/7 student support grounded in instructor-approved course materials, set up local open-source models via Ollama to ensure complete data privacy and minimal environmental resource impact, and finally how to leverage the campus-licensed Google Gemini suite. By the end of this session, you will have functional AI tools set up for your courses along with the knowledge and confidence to guide your students in using them effectively to enhance their learning. By participating in both days of this workshop, faculty and instructors will be able to: Demystify Core Concepts: Explain the basic principles, capabilities, and limitations of large language models without relying on technical or mathematical jargon. Validate & Evaluate Outputs: Apply systematic validation strategies to detect and explore hallucinations, bias, and factual inaccuracies in AI-generated content. Articulate Impacts: Describe the environmental, social, cognitive and psychological impacts of genAI use and common teaching and learning pitfalls. Navigate Campus Tech Stacks: Evaluate the privacy protections, costs, and practical trade-offs of various AI environments (including Canvas integrations, enterprise suites, and local models). Deploy Privacy-Protected Tools: Configure and manage course-specific, privacy-focused AI assistants (such as Rocky AI, Google Gemini, and Ollama) to support student learning. Design Pedagogy: Develop practical course-based roadmaps and effective prompting strategy examples to promote your student’s cognition, critical thinking, and academic integrity while protecting personal and institutional data. Participants should bring their laptops* and charger. Bringing a reusable cup or water bottle is encouraged. Coffe, tea, and lunch is available for those who register in advance. *Full participation in Day 2's activities requires that participants have permissions to install and run software locally on their laptop. Questions? Contact us at datalab@ucdavis.edu.