Schools should separate AI literacy work from assessment integrity work
Claim
Schools should treat AI literacy and assessment integrity as related but distinct workstreams, with separate goals, experiments, and success measures.
Stance
Supported by the source article as an institutional-design claim for AI in education.
Evidence
- Separate AI Literacy and Assessment Integrity argues that AI literacy and assessment integrity keep getting conflated in faculty meetings and AI working groups.
- Kentz distinguishes AI literacy as teaching students to use AI critically and metacognitively from assessment integrity as rebuilding reliable ways to evaluate student thinking.
- The article recommends separate AI Literacy and Assessment Integrity working groups, separate experiments, and separate success metrics.
- Kentz argues that combined approaches can work but are difficult to scale because they add cognitive burden for both students and educators.
Practical implication
Schools should stop asking one AI committee to solve every AI-in-education problem at once. They should name which meetings, pilots, and policies are about AI literacy and which are about assessment integrity, then coordinate the tracks without collapsing them into the same goal.
Related big ideas
- District AI work is a long-term redesign project
- AI literacy needs different kinds of practice, not one generic skill
- Learning still needs some struggle, even when AI can make things easier