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Notes on evidence, integrity, and learning.

From the team building artifact-based oral assessment for higher education.

assessment-designacademic-integrity

Validity matters more than suspicion

Whether a student broke a rule is a narrower question than whether the assessment still supports a sound judgment about their learning. The second question is the one worth designing around.

faculty-workloadacademic-integrity

What faculty actually worry about when they worry about AI

National surveys say the worry is not mainly about catching students. It is overreliance, thinning critical thinking, and workload growing faster than the guidance meant to manage it.

ai-detectionacademic-integrity

AI detection cannot carry the weight faculty need it to carry

Detectors report a probability about how text was produced. Faculty have to make decisions that need evidence they can inspect and explain, and a score supplies none of the process that makes a decision defensible.

academic-integrityoral-assessmentai-detection

When the paper trail can be counterfeited

Version histories and process logs looked like a sturdier alternative to AI detection — until tools appeared that manufacture them. A process trace holds up better when it is tied to explanation than when it is treated as proof on its own.

academic-integrityoral-assessment

Submitted work is no longer self-authenticating

A finished artifact no longer proves who did the thinking behind it. The better move isn't to authenticate the document — it's to let the student authenticate the learning.