Schedule
| Week | Date | Topic |
|---|---|---|
| 1 | 1/26 |
1. (Snow day).
Class canceled. |
| 2 | 2/2 |
2. Introductions.
We will meet each other, sketch out the course, and lay down some frameworks for thinking about the potential role of AI in education. Assigned: A. Initial conjectures |
| 3 | 2/9 |
3. Design frameworks.
A conceptual and hands-on overview of how large language models work. |
| 4 | 2/16 |
4. Designing AI tools.
Design frameworks and introduction to how AI works. Assigned: B. User research |
| 5 | 2/23 |
5. Designing for/in context.
Decontextualized designs are a major reason computer-based interventions have failed to substantially shift classroom practice. We use activity theory to scope our designs and to frame the context for which we are designing. |
| 6 | 3/2 |
6. How do LLMs work?.
Assigned: C. Prototype |
| 7 | 3/9 |
7. Prototyping.
Prototyping; methods of quickly iterating designs. Due: B. User research Assigned: D. Field study |
| 8 | 3/23 |
8. Planning a field study.
Design and logistics of a field study. Revising conjecture maps. Assigned: E. Demo , F. Conference paper |
| 9 | 3/30 |
9. Critiques.
External experts critique student projects. Due: C. Prototype |
| 10 | 4/6 |
10. Field study design.
Study design for design questions and theoretical questions |
| 11 | 4/13 |
11. Quantitative data analysis.
Workshop initial quantitative data analysis. |
| 12 | 4/20 |
12. Data analysis workshop.
Data analysis workshop (bring field study data) Due: D. Field study |
| 13 | 4/27 |
13. Writing workshop.
Workshop final papers. (Bring drafts.) |
| 14 | 5/4 |
14. LLMs in Education Expo.
Presentation of final projects, open to the public. Due: E. Demo , F. Conference paper |