Learning Outcomes

After working through this resource, instructors will be able to:

• Speak generally about the history of generative AI and LLMs
• Define keywords and general terms used in the industry
• Apply their understanding of the training and development of LLM tools to the implications for layperson use
• Speak generally about currently available LLM-based tools (both free and paid)
• Discuss the technical limitations of current LLM-based tools
• Describe the types of bias inherent in LLM-based tools
• Provide mitigation efforts for bias in these tools
• Describe potential uses for LLM-based tools in teaching and learning science at the post-secondary level
• Discuss considerations when using LLM-based tools in teaching (e.g., reliability, bias, privacy and security, accessibility, equity, etc.)
• Integrate GenAI use into low-stakes activities and assessments
• Improve the “AI-immunity” of assessments
• Participate in inter- and intra-institutional committees and collegial governance on the role of generative AI in post-secondary teaching