AI-Adapted Final Examination | Teaching and Learning Centre, Lingnan University

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AI-Adapted Final Examination

Issues With Traditional Assessment
Vulnerability to AI‑assisted cheating in online formats

Vulnerability to AI‑assisted cheating in online formats

Validity drift in measuring intended learning outcomes

Validity drift in measuring intended learning outcomes

Surface learning and memorisation bias

Surface learning and memorisation bias

Misalignment with real‑world and graduate skills

Misalignment with real‑world and graduate skills

Limited feedback and learning value

Limited feedback and learning value

Grade inflation and misrepresentation of competence

Grade inflation and misrepresentation of competence

AI-Adapted Solutions
  • Incorporate written final exams with authenticated assessment components, e.g., in‑class problem‑solving.
  • Redesign exam questions and rubrics to assess reasoning, decision‑making, and disciplinary judgement.
  • Design exam tasks that require explanation of reasoning, critique, and application to evolving scenarios.
  • Redesign exams to assess problem‑solving in authentic contexts and ethical or professional judgement.
  • Make explicit links between exam criteria and graduate attributes. 
  • Reposition the final exam as part of a formative‑summative continuum by providing outcome‑aligned feedback.

*Disclaimer:

The AI tools listed here are provided for reference and supportive purposes only. The Teaching and Learning Centre (TLC) does not assume responsibility for the content generated using these tools. Our referencing of these tools is solely to promote ethical and proper use of tools, originality and academic conduct in course work, in strict alignment with the university’s assessment guidelines and should be used at your own discretion.
Please also refer to our university’s data privacy and security guidelines when using AI tools from an external platforms.