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Using artificial intelligence tools responsibly in your studies and assessments
It's important that you understand how to responsibly use AI tools during your studies and when doing your assessments.
The University is updating its assessment policies to address the opportunities and challenges presented by new technologies including generative artificial intelligence (AI).
Our goal is to make assessment and feedback more meaningful, supportive and fair, while maintaining academic integrity and the value of your University of Sydney degree, and helping you build essential academic skills, including critical thinking.
What's Changing?
From Semester 2, 2025, the University has implemented a ‘two-lane’ approach to assessments.
Secure assessments (lane 1)
These in-person, supervised assessments are used to ensure students have acquired the skills and knowledge required in their unit.
Students are not permitted to use AI in secure tasks unless the Unit of Study coordinator has given express permission in the Unit Outline. Using AI when not allowed could amount to a breach of academic integrity for which you could be investigated.
Open assessments (lane 2)
These unsupervised assessments support the development of disciplinary knowledge and skills. They allow students to engage productively and responsibly with AI tools as part of their learning experience.
For open tasks, students will be able to use AI, and need to appropriately acknowledge its use – provided they do so, this would not be a breach of academic integrity.
Unit Outlines
In the Unit of Study outline, there will be an assessment table with a column titled “Use of AI”. Every assessment in your unit will have an AI stipulation in this column.
The options within this column are:
- AI prohibited
- AI allowed
- AI limited (for certain in-person tasks, unit coordinators might stipulate that a particular AI tool can be used in a particular way)
- Not applicable.
New assessment categories and types
The tables below show the full range of assessment types under the new framework, grouped by secure and open assessments.
Secure assessments - where AI is generally not allowed
- These are supervised assessments. The use of AI in secure assessments is generally prohibited.
- Completed in person (such as exams, in-semester tests, interactive oral assessments, practical tasks, and so on) and are used to verify that you've met specific learning outcomes.
- Your unit outline will have information about using AI for these assessments.
Final exams
| Type | Description | Assessment percentage |
|---|---|---|
| Written exam | Live written exam, written exam with non-written elements, or non-written exam, however administered. | 30–60% |
| Practical exam | Practical exam, or practical exam with non-practical elements, however administered. Includes assessment of laboratory, clinical and performance skills. | 10–60% |
| Oral exam | Live oral exam. | 10–60% |
| In person, practical, skills, or performance task or test | Observation and assessment of live demonstrated practical, skills or performance tasks. Includes tests of clinical, laboratory, field or other skills in supervised environment. | N/A |
| In person written or creative task | Observation and assessment of live written or creative tasks. | N/A |
| Q&A following presentation, submission or placement | Live question and answer session following a live performance, presentation, placement or submission of an artefact. | N/A |
In-semester tests
| Type | Description | Assessment percentage |
|---|---|---|
| Written test | Live written test, written test with non-written elements, or non-written test, however administered. | 20–60% |
| Practical test | Practical test, practical test with non-practical elements, however administered. Includes assessment of laboratory, clinical and performance skills. | 10–60% |
| Oral test | Live oral test. | 10–60% |
In class
| Type | Description |
|---|---|
| Interactive oral | Scenario-based conversations to demonstrate, synthesise, and extend knowledge and skills. Unlike an oral exam, oral test or viva voce, this is a practical application of what has been learned often with a real-world scenario. Examples include Objective Structured Clinical Examination (OSCE). |
Placement, internship or supervision
| Type | Description |
|---|---|
| Peer or expert observation or supervision | Live observation by a peer or expert or supervisor on a placement, internship or in another supervised environment. |
| In person practical or creative task | Live observation and assessment of practical or creative tasks on a placement, internship or in another supervised environment. |
| Clinical exams | Live clinical exam on a placement, internship or in another supervised environment. |
Open assessments - where AI is allowed
- These are unsupervised assessments where you are encouraged to use AI in a supported and scaffolded way.
- AI use in open assessments is allowed. Your educators will guide you on the most appropriate types of AI use.
- Open assessments help build both disciplinary knowledge and AI literacy.
- When you submit your assessment, you must acknowledge how you have used AI.
Practice or application
| Type | Description |
|---|---|
| In-class quiz (single instance and multiple weeks) | Quiz held in a live class such as a tutorial. Used for students to practice, apply or gauge their learning. |
| Out-of-class quiz | Quiz held asynchronously including online. Used for students to practice, apply or gauge their learning. |
| Practical skill | Development and application of technical, laboratory, creative, professional or other disciplinary skill in or out of class. |
| Presentation | The production and delivery of live or recorded oral, visual, and or multimedia communications for specific audiences. |
| Creative work | The creation and production of original and creative work, including short creative writing tasks. |
| Written work | The development and production of structured and/or long form writing (e.g. essay, report). |
| Dissertation or thesis | A written manuscript presenting the findings of a substantial original research project. Includes projects completed as part of an honours program. |
Inquiry or investigation
| Type | Description |
|---|---|
| Experimental design | The process of planning and/or conducting investigations, including hypotheses and methods, in or out of class (e.g. scientific experiments, market research, creative testing, etc.). |
| Data analysis | The process of collecting, analysing, and or visualising data to generate and communicate meaningful insights (e.g. statistical analyses, qualitative coding, business intelligence, etc.). |
| Case studies | The process of analysing real-world scenarios to identify problems, propose solutions, and/or justify decisions (e.g. business cases, patient scenarios, engineering problems, etc.). |
| Research analysis | The critical examination and interpretation of research data, methodologies and findings. |
Production and creation
| Type | Description |
|---|---|
| Portfolio or journal | The production and curation of work samples, documentation, reflections, drafts, laboratory report and or other evidence and small writing tasks demonstrating development over time. |
| Performance | The creation and delivery of live or recorded performance (e.g. artistic, dramatic, musical, etc.) work. |
Discussion
| Type | Description |
|---|---|
| Debate | A structured, evidence-based discussion held live or asynchronously where students present and defend positions using research, data, and/or disciplinary knowledge and applying critical thinking and argumentation skills. |
| Contribution | Meaningful participation in live or asynchronous environments demonstrating knowledge application, peer engagement, and/or advancement of collective understanding. |
| Conversation | A structured or informal dialogue demonstrating disciplinary knowledge, critical thinking, and/or communication skills (e.g. seminar discussions, professional interviews, client consultations, etc.). |
| Evaluation | Assessment of the quality of one’s own and others’ work by applying criteria to make informed and objective judgements. |
Attendance
| Type | Description |
|---|---|
| Attendance - accreditation or faculty requirement | Attendance requirements consistent with professional accreditation conditions, or faculty or course resolutions. |
Acknowledging AI Use
If you use AI in your assessments, you are required to acknowledge it. Failing to do so can lead to a breach of the Academic Integrity Policy. This includes acknowledging any tools that use generative AI, such as translation tools, paraphrasing tools, or referencing tools. (Students are not required to acknowledge tools used for word processing, or which only correct basic spelling and grammar.)
Find more information about acknowledging AI use, and how it relates to academic integrity.
Your Unit of Study coordinator may stipulate in the Unit of Study outline or assessment instructions what is required for AI acknowledgement in their unit. For example, they may require you to submit a log of the AI inputs and outputs used during the preparation of your assessment.
If they make no stipulation, the Academic Integrity Policy from Semester 2, 2025, states that you must at a minimum include information such as the name and the version of the AI tool used, the publisher, the URL of the tool, and a brief description of how the tool was used.
Examples of acknowledgement
- I acknowledge the use of [AI tool + version, publisher and URL] to generate [summary of what was generated].
- I acknowledge the use of [AI tool + version, publisher and URL] to summarise [x source], which I then [describe the action taken].
- I input the prompt [write the prompt in quotation marks or italics] into [AI tool + version, publisher and URL] which produced the output provided in Appendix A [attach an Appendix at end of assessment]. I then [describe how you used any part of the output for your assessment].
Using AI to Learn
You’re welcome to use generative AI tools outside of formal assessments to support your learning. For example, you can explore complex topics, plan out your study or brainstorm ideas, practise explanations or summarise material or check your grammar and structure. We expect you to use AI responsibly to support, not replace, your learning.
- Avoid over relying on AI for translations, as this may reduce your language learning and produce inaccurate results.
- Never enter personal or sensitive information into AI tools. Public AI tools can store and reuse what you type. Don’t enter names, student IDs, assignment questions, personal details, health or patient info, or any University content.
- Only use University-endorsed tools like Copilot. The University provides free access to Microsoft Copilot for Web for all students. Make sure that you log in with your UniKey using Okta so that you are using Copilot in protected mode, which introduces necessary guardrails within the system.
- You should not rely on the accuracy of generative AI outputs - generative AI models do not ‘know’ anything. Rather, they predict answers based on patterns from the internet’s existing information. Generative AI outputs may include entirely false information (also known as ‘AI hallucinations’) so you should always be careful when using the outputs.
- You are responsible for the work that you submit. Alongside the accuracy of the outputs, these also reflect the biases of the material on which the models are trained. Always make sure that your work reflects your own values.
- Don’t let your use of generative AI prevent you from developing crucial writing and communication skills. Learning to communicate effectively in your own words, whether in written or spoken communication, is an indispensable skill in any profession. Use generative AI to improve your communication skills rather than letting it do the writing or talking for you.
- Relying too heavily on AI in Open Assessments can leave gaps in your learning, which may affect your ability to succeed in Secure Assessments that are essential for completing your degree.
- AI models don’t know facts. They generate text based on patterns from data and may provide incorrect or misleading information (known as 'AI hallucinations').
- Don’t let AI do the work for you. Writing, problem-solving and communication are essential academic and professional skills.
Misuse of AI
Misusing AI can breach the Academic Integrity Policy 2022 (pdf, 380KB). Examples of misuse include:
- submitting AI-generated work without appropriate acknowledgment
- using AI where it has been prohibited in a ‘secure’ assessment type, such as during a secure exam
- inputting University teaching or course materials, content generated by another student, Intellectual Property from external partners, or any person’s personal or health information .
More information about the misuse of generative AI can be found on the academic integrity artificial intelligence page.
Getting help
If you're unsure whether AI use is appropriate in your coursework unit:
- talk to your unit coordinator
- contact the Office of Educational Integrity (OEI) via educational.integrity@sydney.edu.au.
Last updated: 12 September 2025