Practice Assignments with Structured AI Support
Faculty Reflection
In designing these Practice Assignments, I wanted to solve a fundamental challenge: how can students use generative AI to genuinely enhance their learning without it becoming a crutch that prevents actual understanding? The three-step structure emerged from recognizing that the key to learning is repetition with feedback. By forcing students to first attempt problems independently, then explicitly seek help (whether from AI, peers, or instructors), and finally reflect on what changed in their understanding, students develop both physics knowledge and metacognitive awareness. The [FLAG] system ensures I can provide targeted feedback on the most meaningful learning moments while keeping grading sustainable. Students consistently report that this structure helps them distinguish between problems they truly understand versus ones where they're just following steps.
What Students Create
Weekly practice assignments demonstrating conceptual physics understanding through a three-step process: independent attempt, getting help (including strategic AI use), and reflective revision with flagged responses for instructor feedback.
Why This Assignment Matters
Students learn to use AI as a learning tool rather than an answer generator, developing both physics reasoning skills and metacognitive awareness of their own learning process. The structured approach ensures repetition with feedback—the foundation of genuine learning.
Materials
How It’s Graded
The points you earn on Practice Assignments come from having done the three-step process. For the questions that you specifically [FLAG], I will read about your process and offer some feedback.
My honest expectation is that you will get nearly full credit on Practice Assignments, unless you skip some of the steps, or leave some questions with wrong answers. If you submit the assignment without engaging in all three steps, you will lose at least 5 out of 10.
Practice Assignments count for 10% of your total grade.
Learning Prompts
Use prompts like these with generative AI (LLMs) to enhance your learning, rather than losing out on the chance to improve.
Prompt: Semi-Socratic Tutor
This will really push you to be the one driving the learning. It won't give you answers and will always be asking you to think and explain. The downside is that this can be frustrating if you are really stuck.
Adapted from openNCCC, I worked with Google Gemini to draft this and then edited it to add context.
Prompt: Misconception Hunting Tutor
This comes from years of research on the idea that confronting misconceptions is key to learning new ideas, especially in physics.
I worked with Google Gemini to draft this prompt and then edited it.