Purpose
This is the second of the two small group sessions covering the AI content. Week 6 established the technical foundation: agents, search, the learning taxonomy, decision trees, and neural networks. Week 7 builds outward from that foundation into the broader AI landscape: reinforcement learning techniques, unsupervised learning, and large language models — the systems your students are already using and asking about.
There is no Competency Demo this week. This session is not assessment preparation — it is synthesis. The goal is to connect both weeks into a coherent picture and think through what it means for your practice as a teacher.
By the end of your hour together, you should:
- Be able to explain hill climbing, genetic algorithms, unsupervised learning, and LLMs in plain language, connecting each to the learning taxonomy from Topic 6c.
- Have stepped back to see the full arc of both AI weeks as a connected story, from simple reflex agents to large language models.
- Have formed a position on at least one of the Week 7 SEC scenarios.
- Have thought concretely about what you will say to students about AI — and what you will do when they ask questions you cannot yet answer.
Before You Meet
Complete the Week 7 topics (7a–7c) and the SEC page, or get as far as you reasonably can. Then spend about 5 minutes on your 3-2-1 reflection. Write 1–2 sentences for each item.
- 3 things from Week 7 that surprised you, confused you, or stuck with you
- 2 ways you can imagine connecting Week 7 material to your students
- 1 question about AI in education that you are still sitting with after both weeks
Then do this one additional task: before you arrive, write two or three sentences answering this question as if a student asked you: "How does ChatGPT actually work?" Be as accurate and specific as you can. You will share your answer in the opening and revise it with the group.
During Your Discussion
Opening: Explaining ChatGPT (10 minutes)
Go around and share the answer you wrote to "How does ChatGPT actually work?" Listen for what each person emphasizes and what they leave out. As a group, assemble the most accurate, most student-accessible version you can. What concepts from Weeks 6 and 7 are essential to include? What is safe to simplify?
The Full Arc (10 minutes)
Together, reconstruct the conceptual arc of both AI weeks from memory — without looking at notes. Start with "What is an AI agent?" and work forward through search, decision trees, the three learning types, neural networks, hill climbing, unsupervised learning, and LLMs. This is not a quiz. It is a collaborative exercise that reveals where the connections are clear and where they still feel loose.
Week 7 Concepts (10–15 minutes)
Work through one or two of these together:
- Hill climbing vs. genetic algorithms: A school is trying to optimize its master schedule. Explain why hill climbing might get stuck. Explain how a genetic algorithm would approach the same problem differently.
- Unsupervised learning: A counselor runs K-means on three years of student data and finds four clusters. What did the algorithm contribute? What did the human contribute? Could the algorithm have named the clusters on its own?
- LLM limitations: A student submits an essay with a confident citation to a paper that does not exist. Explain to the class why this happened. Is it a bug or a feature of how LLMs work?
The SEC Scenarios (10 minutes)
Choose one of the scenarios from the Week 7 SEC page. Work through these specifically:
- What technical concept from Week 7 is at the root of the problem?
- If you were advising the institution involved, what one change would you recommend, and why?
- As a teacher in a real school right now, what is the most immediately relevant thing this scenario tells you?
Classroom Connections and the Post-Reflection (10 minutes)
Share the "2 ways I can connect Week 7 to my students" items from your 3-2-1. Let the group react. Then each person names one specific thing they plan to do differently in their classroom or in their thinking about AI based on anything from these two weeks.
Close by discussing the question from your 3-2-1 about AI in education. You will be writing your AI post-reflection this week — the companion to the pre-reflection you completed at the start of Week 6. What has shifted most in your thinking? What questions are still open?
After You Meet
- Write down one thing from the conversation that shifted or sharpened your thinking.
- Complete the AI post-reflection on Blackboard. This is the second half of the activity that started at the beginning of Week 6.
- Note any questions the group could not resolve and bring them to the course Q&A or faculty before the end of the week.
Your small group time is not graded. It is here because talking through ideas with peers is one of the most effective ways to consolidate what you have learned — and to discover that the questions you have are the same ones everyone else has too.