Guiding Principles for Teaching and Learning with AI
- Struggle Before Querying AI
Students must engage meaningfully with a writing or thinking challenge before turning to AI. The struggle should include free-writing, brainstorming, clustering, or any such activity that aids in thinking.- This practice promotes cognitive investment, helps clarify what students need help with, and keeps AI in a subordinate—not supervisory—role.
- Model AI Use as Part of the Process
AI should be integrated explicitly into the writing process through instructor modeling and discussion.- This practice normalizes AI as a tool for brainstorming, revising, or rephrasing—not a shortcut for entire assignments.
- Modeling can help students see how experienced writers critically engage with AI, rather than outsourcing thinking.
- Link AI Use to Skill Development
AI should reinforce core writing and thinking skills. It should be used as an ideation partner or workflow manager but not for mere convenience.- For example: query AI to practice transitions, generate counterarguments, or explore tone—rather than summarize sources or write introductions.
- This practice encourages intentionality and metacognition.
- Prioritize Authentic Voice Over Academic Perfection
A student’s exploratory prose—even if it contains flaws in grammar, logic, or rhetoric—is more valuable than AI-generated fluency.- This principle challenges the idea that correctness is the goal and emphasizes originality, identity, and risk-taking in writing.
- This priority helps students build confidence in their own voice, even if it is unpolished by academic standards.