AI in higher education
Faculty need evidence of how a student reasons after using AI. An assignment can ask students to commit to a decision, examine a challenge and explain the revision, giving the teacher work that can be assessed.
What does a polished AI-assisted case memo establish?
AI in higher education requires decisions about permitted student use, disclosure and evidence of learning. Faculty should specify how students will explain source choices, assumptions, rejected alternatives, revisions and final decisions. Assignments and feedback activities can then be designed around those requirements. Faculty programmes develop usable teaching materials such as revised assignments, rubrics, simulations or case companions. Institutional review examines which materials entered courses, how students practised and what evidence was available for feedback. The same approach can be applied to selected administrative or student-support workflows by defining the work, responsible owner and measures of the result.
Faculty programmes ask what a teacher will be able to assess after a student uses AI. Participants develop an assignment, rubric or learning activity that records the student’s reasoning and revision, with repeated practice and feedback where appropriate.
Work on a decision you recognise.
A student submits a well-written case memo, but the assignment records no initial decision, rejected alternative or response to feedback. What evidence does the teacher need to assess the student's judgement?
Specify the evidence for assessment
The final memo shows what was submitted. To assess the student's reasoning, ask for the initial decision, the evidence checked and an explanation of what changed after a challenge or feedback.
Use a short oral question to examine the student's choice and an alternative. Apply a rubric tied to the learning objective, so the teacher can assess the reasoning demonstrated through the task.
- Starting material
- The case material, learning objective, permitted-use rules and criteria for the student's decision and explanation.
- The task
- Provide a challenge or comparison for the student to inspect after recording an initial answer.
- Review the result
- Examine source use, alternatives, revision and the student's explanation of the final decision against the course rubric.
What participants work on.
- Course-level AI-use rules: permitted use, disclosure, evidence and student responsibility
- Redesigned assessments examining process, sources, revision and judgement
- Faculty-built material such as a simulation, rubric, case companion or feedback activity
- Repeated student practice in communication, research, analysis or placement preparation
- Assessment criteria for student reasoning and source use
- 30-day review of assignments, student work, faculty materials and further trials
Specify AI-use and assessment requirements
For each course, define what AI use is permitted, what must be disclosed and what evidence must accompany the submission. Identify which decisions students must explain and defend.
Use those requirements when designing the assignment and feedback.
Develop usable course material
Each participating faculty member develops material for a course, such as a revised assignment, case companion, source-checking exercise, viva questions or feedback activity.
Review how that material will be used and what it allows the teacher to assess.
Examine student reasoning and revision
Ask students to explain the task they gave AI, the sources they checked and the choices they made after reading the output.
The submission can include rejected alternatives, feedback, revisions and the final decision. Assess that evidence against the course’s learning objectives.
Provide repeated practice and feedback
Students need opportunities to make a decision, receive feedback and revise their work. An interview response, case memo, research note or presentation can provide a practice task.
Record the changes across attempts so the teacher can review how the student applied the feedback.
Review the changes after 30 days
Review which assignments were redesigned, which materials faculty used and what student reasoning was available for assessment. Examine the practice attempted and the revisions made.
Use that evidence to decide which activities to retain or change.
Connect the problem to an action.
| Area | Question to examine | Programme response |
|---|---|---|
| Course assessment requirements | The campus has AI rules, but students and faculty still do not know what must be visible in an AI-assisted submission. | Define course-level contracts: permitted use, required disclosure, process evidence, review criteria, and where human judgment remains non-negotiable. |
| Teaching materials produced | Faculty leave with tool awareness, but nothing reusable enters a course, case discussion, assignment, or feedback routine. | Make every participating faculty member build one usable artifact: a rubric, simulation, case prompt, feedback loop, or revised assignment. |
| Evidence from student practice | Students may practise, submit, and revise with AI, but the institution sees only final work or attendance data. | Review judgment traces, practice frequency, feedback loops, and assignment changes after 30 days so adoption becomes visible. |
Questions about the programme.
What should AI in higher education focus on first?
Start with the assessment contract: what AI use is allowed, what must be disclosed, what process evidence students must show, and what judgment remains theirs. Then redesign a small number of assignments around that contract.
How should faculty be trained for GenAI?
Faculty training should develop usable course material, such as a revised assignment, rubric, simulation, case companion or source-checking exercise. Review what the material allows students to practise and teachers to assess.
How can institutions handle student AI use?
Ask students to explain their sources, assumptions, rejected alternatives, revisions and final decisions. Assess this evidence against the learning objectives and the course’s permitted-use and disclosure requirements.