Separate AI Literacy and Assessment Integrity
Source: Mike Kentz Substack
Author: Mike Kentz
Original source: https://mikekentz.substack.com/p/separate-ai-literacy-and-assessment
Published: 2026-05-24
Source type: essay
Private backup: the full article text is archived in the private repository at archives/articles/mikekentz-substack-com-separate-ai-literacy-and-assessment.source.md. It is not published on the public Quartz site.
Summary
Mike Kentz argues that educators keep stalling because they treat AI literacy and assessment integrity as one problem. AI literacy asks how students can use AI critically, metacognitively, and in ways that build their own thinking. Assessment integrity asks how schools can know what students understand when polished digital artifacts are easy to outsource. Kentz says the two concerns overlap, but they need separate working groups, experiments, and success metrics: AI literacy work should focus on mature AI use, metacognition, and societal context, while assessment-integrity work should focus on portfolios, project-based learning, process evidence, and other ways to evaluate student thinking that may not require AI at all.
Pull quotes
Integrity is a separate problem
“Assessment integrity has deteriorated because of AI. Students can more easily cut corners on assignments, which destroys an educator’s ability to evaluate student thinking in any digital space.”
Literacy builds cognition
“AI Literacy is a different project. It focuses not on preserving assessment integrity but on teaching students to be critical thinkers in the chat — to reflect, push back, and use AI in a way that builds their own cognition rather than replacing it.”
Separate tracks
“The answer isn’t to bolt AI literacy onto the integrity crisis or vice versa. The answer is to give each problem the focused attention it deserves — separate working groups, separate experiments, separate success metrics.”
Big ideas
- District AI work is a long-term redesign project
- Learning still needs some struggle, even when AI can make things easier
- AI literacy needs different kinds of practice, not one generic skill
Claims
- Schools should separate AI literacy work from assessment integrity work
- AI literacy takes system capacity, not just tool access
- In an AI world, assessment should focus on watching students think
- AI-assisted homework requires redesign, not just policing
- AI literacy should teach students what to do with AI, not just what to think about it
Key evidence and examples
- Kentz cites faculty surveys showing widespread concern about AI-written work, over-reliance, and increased cheating.
- He distinguishes assessment integrity from AI literacy: one is about whether student work remains reliable evidence of thinking, while the other is about helping students use AI critically and metacognitively.
- He says combined approaches, such as comparative transcript analysis, can work but place a heavy cognitive burden on students and educators when scaled.
- He recommends separate AI Literacy and Assessment Integrity working groups, with separate experiments and success metrics.
- The AI literacy track should focus on mature AI use, metacognition, skills in the chat, and social context.
- The assessment-integrity track should focus on portfolios, project-based learning, process-based evaluation, and conversation-as-artifact approaches.
Education relevance
Very high relevance for school AI strategy, faculty and teacher professional learning, assessment redesign, academic integrity, K-12 and higher education AI governance, and Clay’s likely conversations with educators who may conflate AI literacy with cheating prevention.
Durability note
The survey figures and named institutional reports will age, but the distinction between AI-literacy capacity building and assessment-integrity redesign is likely to remain useful as schools organize their AI work.
My notes
- Clay noted that this distinction will matter because conversations with teachers about AI literacy and conversations about assessment will constantly get in each other’s way unless the two tracks are named separately.