Neutral comparison · QLM category creation

AI Detection vs Process-Based Assessment

Detection asks whether output might be AI-generated. Process-based assessment asks what the learner can demonstrate.

Fair comparison

Detection is a suspicion workflow; process-based assessment is an evidence workflow.

AI detection tools estimate whether a submitted artifact may have been generated or assisted by AI.

QLM shifts the assessment design toward process evidence, AI-use transparency, oral defense, simulations, and reviewable reasoning.

Comparison table

QuestionAI detectionQLM
Primary questionDid AI generate this output?What reasoning and performance evidence did the learner produce?
RiskFalse positives, false negatives, adversarial behavior.Requires thoughtful task design and review workflow.
Best usePolicy support in limited contexts.AI-transparent assignments and defensible evidence.

Related QLM paths

Keep building the category map.

Higher educationProcess-Based AssessmentQLM helps faculty assess planning, reasoning, revision, and AI use rather than relying only on final submissions.Enterprise authority hubAI Assessment GovernanceQLM helps institutions govern AI-era assessment with evidence standards, transparency, review workflows, and defensible performance signals.GlossaryAI-Use TransparencyAI-use transparency asks learners to disclose, explain, and defend how AI supported their work.

Next step

Turn the category into a pilot.

Use this path when you want a pilot, research partnership, or product walkthrough.

Explore process-based assessment →