Make learning-objective evidence visible.
Complement clear AI-use rules with direct evidence of what each student can explain, justify and defend.
Integrevise for Northeastern University London
Keep AI-enabled assessment experiential—and make learning visible.
Integrevise adds a short adaptive oral discussion after submission. Questions use the existing brief, rubric and student work, giving faculty reviewable evidence of what each learner can explain and students personalised feedback—without timetabling a live viva for every submission.
One practical evidence layer
Support experiential assessment without adding a live viva to every submission.
Integrevise works from materials teaching teams already use. It creates a structured opportunity for explanation while academic judgement remains with the university.
Keep the brief, rubric and judgement.
Review structured evidence from a work-grounded discussion instead of scheduling every conversation manually.
Explain choices and receive useful feedback.
Give learners a transparent moment to demonstrate ownership, clarify their thinking and act on personalised feedback.
Peer-reviewed pilot2026One university setting
Early evidence, clearly bounded
A practical approach with preliminary university evidence.
A repeated, multi-cycle pilot at one private US liberal-arts college offers preliminary qualitative evidence that post-submission oral verification can surface comprehension gaps and implementation issues. It does not establish broad efficacy or scalability.
Read the peer-reviewed studyNU London policy → practical evidence
The essential question is already defined: can students demonstrate the learning objectives?
NU London’s Academic Misconduct Policy says permitted AI use must be declared and identifies excessive or unmediated use as a problem where it prevents a student from demonstrating the learning objectives. Integrevise complements that standard with a short, work-grounded discussion. It is not an AI detector or an automated misconduct decision.
NU London sets the expectation
Declared AI use and demonstrable learning objectives
Integrevise adds
Reviewable evidence through explanation
A focused first conversation
Compare priorities before designing anything.
Twenty minutes is enough to compare NU London’s priorities for authentic assessment, individual evidence and faculty workload—and decide whether the approach deserves a closer look.
Book a 20-minute conversation No module selection, pilot design or assessment redesign required.