Fall 2026 Offerings
GenAI Faculty Resources Canvas Site
Critical Thinking with AI: A Few Ideas
Facilitated by Leslie Bruce
This asynchronous WAC LIAISONS workshop will introduce recent research on critical thinking and AI use, then explore a few generalizable ideas for using student-LLM interactions to strengthen students' critical thinking skills as they increase their subject mastery. (1-hour certificate credit)
From Syllabus to Canvas: Building Your Course Shell with an AI Agent
Facilitated by David Adams
This hands-on workshop shows faculty how to use an AI agent to turn a plain-text syllabus into a scaffolded Canvas course — weekly modules, assignment stubs, due dates, and a course landing page — in a single session. No programming experience is required; every step from file conversion to agent prompting is demonstrated live, with time built in for participants to try it in their own sandbox course. The workshop emphasizes a faculty-first workflow: the agent drafts, you verify, and nothing goes live until you've audited dates, policy language, and grading weights against your original syllabus. Participants leave with a reusable set of prompt cards and a pre-publish checklist they can adapt for any course they teach.
Adapting Major Assignments to Reduce AI Overreliance
Facilitated by Leslie Bruce
Attempts to evade and detect generative AI use in coursework are never foolproof. To ensure student learning, we can adapt our assignments to better engage students. Focusing on longer assignments and projects, this asynchronous workshop introduces several strategies for reducing AI use in your favorite major assignments. (1-hour certificate credit)
SIFTing Through AI: Teaching Students to Question, Verify, and Think Critically
Facilitated by Leslie Bruce
Generative AI can provide quick answers, but students still need to know how to question, verify, and build upon the information it produces. In this session, participants will engage in an active learning activity based on the SIFT framework: Stop, Investigate, Find, and Trace. Using a shared AI-generated response to the question, "Does pineapple belong on pizza?", attendees will examine prompt bias, evaluate AI-cited sources, compare claims against stronger evidence, and trace information back to its original context. The activity models how AI-generated answers can serve as a starting point for inquiry rather than the end of the research process. Participants will leave with practical strategies and adaptable resources for incorporating source evaluation, AI literacy, and critical thinking into their own courses and classroom activities.
Using NotebookLM to Support Teaching & Learning
Facilitated by Rachel Riter, Pollak Library
This one-hour, asynchronous workshop will show faculty how to reduce their workloads using Google's NotebookLM. This free LLM research tool is easily accessible and does not train AI using users' data. The workshop shows faculty multiple faculty- and student-facing ways to use NotebookLM to lighten their teaching and service workflows. (1-hour certificate credit)
Analysts and Correspondents: Keeping Human Thinking at the Center of Classroom Learning
Facilitated by Katherine Heaton, Department of Sociology
This session explores two rotating student roles designed to keep the central intellectual work of a course in students’ hands. The Contemporary Connections Analyst brings a current issue, event, cultural artifact, or emerging research example into class and uses course readings and concepts to explain its broader significance. Rather than simply summarizing information, students connect ideas, apply disciplinary concepts, and guide discussion. The Correspondent listens for major concepts, arguments, evidence, connections, and unresolved questions, then concludes class with a brief recap and contributes to a collective course archive. AI use is intentionally constrained so that reflection, discussion, analysis, listening, synthesis, and communication remain human-centered. Participants will leave with adaptable role descriptions that can be used across disciplines to encourage participation, critical thinking, and student ownership of learning.
Think First, AI Second: Using AI Summaries as Objects of Critical Analysis
Facilitated by Sangeetha Carmona, Department of MSIDT
In this activity, participants watch a short recording and first create their own notes about the main ideas, important moments, questions, or takeaways before seeing any AI-generated content. They then compare their notes with a summary generated by Zoom AI Companion and work together to examine what the AI captured well, what was oversimplified, what may have been misrepresented, and what important context, perspective, or nuance may be missing. The central question is simple: What did the AI capture, and what did it flatten? AI is used intentionally and in a limited way. Participants do their own thinking first, then treat the AI summary as something to analyze rather than something to rely on. Faculty will leave with a ready-to-use activity, reflection prompts, annotation guide, and rubric that can be adapted across disciplines to help students make their thinking visible and critically evaluate AI-generated summaries.
Engaging AI Critically with Your Students
Facilitated by Leslie Bruce
Take this asynchronous workshop at your own pace. Learn some of the promises and perils of AI chatbots, explore ways to support critical thinking about AI in class, and draft your own in-class AI-infused activity for feedback. (2-hour certificate credit)
Annotation Matching: Designing Reading Activities That Keep Students Doing the Interpretive Work
Facilitated by Volker Janssen, Department of History
In this session, participants will explore a low-stakes primary document annotation activity used in an asynchronous online U.S. History survey course. Students are presented with a historical primary source and asked to match numbered passages to explanatory annotations or commentary. Rather than simply locating information, students must make judgments, evaluations, and comparisons as they determine which annotation best fits each passage. The activity is intentionally designed so that the intellectual work of interpretation remains with the student, while the screen format makes it cumbersome to outsource the task to an AI chatbot. Although developed for history courses, the approach can be adapted wherever students engage with readings, commentary, explanatory notes, or connections to course concepts. Faculty will receive a Canvas quiz template, sample materials, and guidance on creating auto-graded activities that promote close reading, interpretation, and sustained engagement with course content.
The Five-Minute Defense: Making Student Thinking Visible
Facilitated by
Mohammad Abdel-Haq, Department of Sociology
The Five-Minute Defense is a brief follow-up conversation in which students are asked to explain, defend, and extend the reasoning represented in their submitted work. Rather than focusing on who or what produced the final product, this approach focuses on whether students can demonstrate ownership of the thinking behind it. The conversation is built around three types of questions: Explain (Can students explain an idea or conclusion in their own words?), Defend (Can they justify an analytical choice, use of evidence, or conclusion?), and Transfer (Can they apply the same reasoning to a new situation?). The approach can support assignments where AI is restricted, permitted, or intentionally incorporated. The goal is not simply to detect AI use, but to make student cognition visible and assess whether students can explain, justify, and transfer the intellectual work their assignments are intended to develop. Participants will create a ready-to-use Five-Minute Defense for one of their own assignments and leave with adaptable questions, implementation guidance, and sample syllabus language.
“So What?” Hot Potato: Practicing Analysis Without AI
Facilitated by Michelle Greer, Department of English, Comparative Literature, and Linguistics
Students often assume they have reached the end of an idea when, in reality, there is much more to say. This session demonstrates a flexible, low-preparation activity that helps students practice analysis by continually asking, “So what?”, “Who cares?”, and “Why does this matter?” After a brief discussion about what effective analysis looks like, participants engage in a fast-paced “hot potato” game where each person builds on a simple statement by identifying additional significance, implications, or consequences. The class evaluates each response, helping students recognize that analysis requires specificity, curiosity, and sustained inquiry rather than repetition. AI is intentionally absent from the activity, reinforcing that students can generate insightful ideas through conversation and critical thinking. Faculty will leave with an adaptable strategy that can be used across disciplines to strengthen analytical reasoning, discussion skills, and confidence in students’ own thinking.
Prepares you to apply generative AI (gAI) technology efficiently, effectively, and ethically to level up learning in the classes you teach. Online and asynchronous.
After completing this course, you will be able to:
- Articulate and differentiate how language-based and image-based generative AI tools actually work.
- Describe an action plan for ensuring student awareness of bias, privacy, and other ethical concerns inherent in using generative AI tools.
- Construct a syllabus statement on using generative AI tools appropriate to at least one of your courses.
- Understand the variety of popular generative AI options and selectively build a tailored toolkit appropriate to your academic work.
- Iteratively refine prompt results leading to effective querying of generative AI.
Once you have completed the SDSU microcredential, upload the course completion certificate to this
form
to count toward the AI Learning Trailblazer certificate program.
AI LinkedIn Learning Pathways (Online and Asynchronous)
New to LinkedIn? Read this
article on how to access LinkedIn Learning
with your CSUF username.
Explore the fundamentals of generative AI, its applications, and the ethical considerations surrounding bias in this 2.5-hour LinkedIn video series designed for staff and faculty. (2.5-hour certificate credit)
Advance your skills in generative AI with this intermediate 3-hour LinkedIn video series, designed for staff and faculty to enhance aptitude, communication, and critical thinking with AI. (3-hour certificate credit)
