Designing assignments for AI Fluency
Designing assignments for AI Fluency
This video focuses on designing assignments that help students both develop and demonstrate AI Fluency. It emphasizes three key principles: authenticity (creating assignments that mirror real-world AI collaboration), iteration (building in opportunities for refinement that showcase growth), and pedagogical transparency (being clear about assessing the collaboration process, not just outputs). The video presents various assignment types including outcome-based assignments (like improving AI outputs or comparing different AI systems), process-based assignments (such as annotated chat logs or recorded narrations), and reflection-based assignments (including learning journals and personal policy statements). It also addresses practical strategies for managing the increased volume of content that AI-enhanced assignments generate, such as using detailed rubrics, emphasizing peer review, conducting lightning round conferences, and selective sampling of student work.
Key takeaways
- Effective AI Fluency assignments emphasize authenticity, iteration, and pedagogical transparency
- Outcome-based assignments focus on products but reveal collaboration skills
- Process-based assignments make invisible decision-making visible through documentation
- Reflection-based assignments develop metacognitive awareness but need variety to avoid fatigue
- Managing increased volume requires strategic approaches like rubrics, peer review, and selective sampling
Exercises
This exercise helps you create a comprehensive assignment that develops and assesses AI Fluency.
Assignment Architecture
Estimated time: 10 minutes.
Continue your conversation from Exercise 1 about assessment design:
Connecting to your rubric:
- Reference the rubric you just created and the competencies it emphasizes
- Discuss with the AI what type of assignment/component would best allow students to demonstrate these competencies
- Consider whether you want to focus on outcome, process, reflection, or a combination
- Explore how this assignment fits within your broader course structure
Selecting assignment components:
- Review the different assignment components discussed in the videos with the AI
- Choose 2-3 components that work together coherently for your purposes
- Adapt these components to feel natural within your course context
- Ensure the workload is manageable for both students and yourself
- Work with the AI to ensure the assignment mirrors real-world AI collaboration in your field and build in genuine problems where AI partnership adds value
Lesson reflection
- What challenges do you anticipate in implementing these assessments?
- How will you communicate the value of process and reflection to students?
What's next
In the next lesson, we'll examine AI's specific impact on curriculum, pedagogy, and assessment in your field.