Concern 720 · Working draft · editorial review in progress
Challenges to assessment integrity
Assessment-integrity risk arises when a submitted answer no longer gives a reliable picture of what the learner understands or can do.
Understanding the concern
An essay or take-home task may once have shown a student's reasoning through the work they produced. If AI can generate the result, the same task may reveal less about independent ability. The problem is not that every use of AI is dishonest; it is that the evidence may no longer match the skill being assessed.
Education guidance recommends multiple ways to judge learning, including work that makes reasoning and process visible. Think of assessing swimming by reading a description of a stroke: a polished description is not enough to show performance. Clear rules, discussion, practice and suitable demonstrations can help distinguish allowed assistance from the abilities students need to develop themselves.
An example
A student submits an excellent answer but cannot explain its reasoning or apply the idea to a new problem.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
Evidence and its limits
TEQSA offers assessment principles and implementation examples. It does not claim that all essays are useless or that AI detection can reliably prove misconduct.
Australian Tertiary Education Quality and Standards Agency 2025 · Education guidance
Enacting assessment reform in a time of artificial intelligence ↗ (opens in a new tab)Multiple ways to assure learning alongside responsible AI use. Not a claim that all essays or take-home assessments are invalid.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
What combination of work and conversation would show what this learner actually understands?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Learning together
Learning together means treating experience as something a group can examine and improve. It values honest feedback over appearing successful.
Agree on a question, try something manageable, and compare what different people observed. Share failures as well as gains. Decide together what the evidence supports and what remains uncertain.
Ask together: What have we learned together that should guide the next step?
Humility
Humility means recognizing the limits of our knowledge and being willing to learn from others. Expertise can be valuable without answering every question.
State where evidence is weak, invite criticism, and listen to people with different experience. Leave room to revise a decision when new information appears.
Ask together: What might we be missing, and who could help us see it?
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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