AI is changing how students study, but the rules of academic integrity haven't changed. Understand where the line is, how to stay on the right side of it, and how tools like ISMGenius are designed to help — not replace — your own work.
Academic integrity means being honest about your work. It means that what you submit is genuinely yours — your own ideas, your own analysis, your own writing. It is the foundation of fair assessment and the reason your qualifications have value.
Everything you submit must reflect your own thinking, analysis, and effort. Getting feedback is fine. Having someone — or something — do the work for you is not.
If your school asks what tools you used, be honest. Using an AI feedback tool to check your draft is not the same as using AI to write your draft — but both deserve transparency.
Assignments exist to help you learn. Skipping the process with AI might save time now, but it costs you the skills, knowledge, and confidence you need for exams, real-life work, and your future.
If you use ideas, data, or wording from another source — including AI-generated content — reference it properly. Unattributed use of anyone else's work is plagiarism.
AI tools are not inherently good or bad for academic integrity. What matters is how you use them. Here is a clear breakdown.
ISMGenius is fundamentally different from generative AI tools like ChatGPT. Here is why.
ISMGenius analyses work you have already written. It tells you how your draft aligns with your rubric criteria — strengths, gaps, and areas for improvement. The thinking and writing remain entirely yours.
Getting rubric-aligned feedback on your draft is conceptually the same as asking a tutor, parent, or peer to review your work before you submit. ISMGenius automates that review — it does not automate the work itself.
Scanning your own draft for AI-generated patterns or unattributed sources before you submit is a legitimate integrity practice, not an attempt to evade one. If something is flagged, the honest response is to revise it in your own words and attribute what needs attributing.
The revision workflow is designed to help you submit multiple drafts and track your improvement over time. Each revision builds your skills rather than bypassing the learning process.
Schools and QCAA take academic integrity seriously. The consequences of submitting AI-generated work or plagiarised content are real.
You may receive zero for the entire assessment piece.
The incident may be recorded on your academic file, which can affect future references.
For senior assessments, serious cases can be escalated to QCAA for investigation.
Rebuilding trust with your teachers after academic misconduct takes time and consistent honest effort.
The Queensland Curriculum and Assessment Authority requires that all work submitted for assessment is authentically the student's own. That applies to internal assessment, external assessment, and anything contributing to your final result. Submitting AI-generated content as your own work breaches that requirement.
Two things follow from QCAA's own published policy. First, from 2026 every Year 12 graduate has to complete an academic integrity course as part of QCE eligibility. Second, the QCE and QCIA handbook requires schools to explicitly teach the critical and responsible use of AI and to communicate the consequences of academic misconduct with explicit reference to AI. So your school is obliged to tell you where its line sits.
Using AI for legitimate study support, such as feedback on a draft, grammar checking, or understanding rubric criteria, is generally acceptable where it supports your own thinking rather than replacing it. QCAA publishes guidance documents for students and parents on this. Your school's own policy sits on top of it, and it is the one that governs your assessment.
We have detailed guidance for teachers on AI detection, formative assessment strategies, and proactive approaches to reducing AI misuse in the classroom.
View Educator GuidanceUpload your draft and ISMG rubric. Get rubric-aligned feedback that helps you improve — without crossing any lines.
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This page covers the policy. If you are looking for the detection tooling itself, or worried about being wrongly flagged, start here.