Teaching & Learning
- Students must follow the AI guidance given for the specific assessment, and using AI beyond what is permitted can be treated as academic misconduct
- The university also states that students remain responsible for the accuracy, integrity, and originality of submitted work even where AI use is allowed
- Coursework use of generative AI is governed through a university-wide traffic-light model and may be allowed, limited, or prohibited depending on the assignment
In all your assessments and exams, use of GenAI is categorised according to a traffic light system.
Green indicates that there are no restrictions on the use of GenAI.
Amber indicates that there are some restrictions and students should follow the specific guidance in place for their assignment.
Red indicates that GenAI should not be used.
- The university applies the same traffic-light model to exams and assessments
- Unauthorized AI use in an examination is treated as cheating and academic misconduct
- In-person exams are expected to prevent access to AI tools, while for other assessments students must follow the published AI status and instructions
In all your assessments and exams, use of GenAI is categorised according to a traffic light system.
Green indicates that there are no restrictions on the use of GenAI.
Amber indicates that there are some restrictions and students should follow the specific guidance in place for their assignment.
Red indicates that GenAI should not be used.
In-person exams and tests are already a secure environment where access to GenAI tools would not be possible.
Cheating in an examination includes any attempt by a candidate to gain an unfair advantage in an examination by taking unauthorised material into the examination room, disrupting the conduct of the examination, copying from another candidate or by any other means.
- The guidance frames AI as useful for study support, but not as a substitute for academic judgment
- Students are warned to evaluate outputs carefully and not rely on AI-generated information without checking it
- The university encourages students to develop AI literacy and recognises AI tools as resources that can support learning, provided students use them critically and responsibly
At Oxford Brookes, we are committed to helping our students become AI-literate and capable of using AI tools safely and ethically.
This means understanding the opportunities and risks associated with AI technologies and knowing how to use them in ways that support learning, creativity, and future employability.
Like all online material, information generated by AI tools should be used critically and with caution.
Remember that AI generated content can contain fabricated information, errors and bias.
Research
- Research-related AI use must align with broader research integrity expectations, including honesty and accountability in scholarly work
- However, the sources provided do not set a detailed university-wide rule specifically authorizing or prohibiting AI drafting of manuscripts
- The university states that AI tools cannot be listed as authors and that researchers are responsible for the accuracy, integrity, and originality of outputs produced with AI assistance
As non-legal entities AI cannot be named as an author on publications, as they cannot take responsibility for the outputs.
Researchers are responsible for the originality, validity and integrity of the content of publications.
The University expects all staff and students involved in research to observe the highest standards of integrity in the conduct of their research.
- The policy is therefore restrictive where protected data are involved and requires human oversight of AI-supported research processes
- It also cautions that AI outputs may be inaccurate or biased, so researchers remain responsible for checking and validating analytical results
- The university warns researchers not to upload personal, confidential, or sensitive data into public AI tools and requires compliance with data protection, confidentiality, and contractual obligations
Do not upload personal data, confidential information, or commercially sensitive material into public AI tools.
Researchers must ensure that use of AI tools complies with data protection law, confidentiality obligations, intellectual property rights, and any contractual terms attached to research data.
AI outputs can be inaccurate, misleading or biased and must be checked carefully.
- Research use of AI is subject to the university’s general research integrity and ethics framework
- The university also emphasizes that responsibility for research outputs remains with the human researcher, not the AI system
- Researchers are expected to act with honesty and integrity and to ensure AI use complies with ethical, legal, and governance requirements, including research ethics review where appropriate
The University expects all staff and students involved in research to observe the highest standards of integrity in the conduct of their research.
Research should be conducted according to appropriate ethical, legal and professional frameworks, obligations and standards.
As non-legal entities AI cannot be named as an author on publications, as they cannot take responsibility for the outputs.
Academic Integrity
- Disclosure requirements may therefore vary by assessment, but transparency is expected when AI contributes to submitted work
- The university provides explicit advice that AI-generated material should be cited and that students should be transparent about use
- Where AI use is permitted or partly permitted, students are expected to acknowledge and reference that use in line with assessment guidance
If you use AI tools in your work, you should acknowledge this clearly.
Where AI use is permitted in an assessment, your module guidance should explain how to declare and reference that use.
Always be transparent about your use of AI tools.
- Undisclosed or unauthorized AI use can be pursued under the university’s academic misconduct procedures
- The provided sources do not establish a specific university policy endorsing reliance on any one AI-detection tool
- The university describes cheating broadly as gaining unfair advantage by unauthorized means, and its AI guidance links misuse of AI to academic integrity processes
Using AI tools in ways that are not permitted for an assessment may be treated as academic misconduct.
Cheating in an examination includes any attempt by a candidate to gain an unfair advantage in an examination by taking unauthorised material into the examination room, disrupting the conduct of the examination, copying from another candidate or by any other means.
Academic misconduct is any action or attempted action that may result in creating an unfair academic advantage for oneself or an unfair academic advantage or disadvantage for any other member or members of the academic community.
Institutional & Administrative
- The university has institution-level guidance for teaching staff on how to design and classify assessments for AI use
- Staff are expected to decide and communicate whether assessments are green, amber, or red, and to provide clear instructions to students about permitted use
- The sources therefore define a staff role in assessment design and communication, but do not provide detailed rules in the provided text about grading, recommendation letters, or administrative communications
Schools/programmes/modules should determine the appropriate GenAI status of assessments using the traffic light framework.
Students should be given clear guidance on whether and how GenAI may be used in each assessment.
The principles are intended to support staff in making decisions about assessment design in relation to generative AI.
- The provided sources therefore establish data protection limits on AI use, but they do not identify a university-approved list of AI platforms in the text available here
- The university instructs users not to enter personal, confidential, or commercially sensitive information into public AI tools and requires compliance with data protection and confidentiality obligations
Do not upload personal data, confidential information, or commercially sensitive material into public AI tools.
Researchers must ensure that use of AI tools complies with data protection law, confidentiality obligations, intellectual property rights, and any contractual terms attached to research data.
- The framework is institution-wide rather than limited to individual departments
- Oxford Brookes has a university-wide generative AI policy and practice framework built around shared principles and a traffic-light assessment model
- Its strategy emphasizes safe, ethical, and literate use of AI by students and staff, while allowing local implementation through schools, programmes, and modules
Oxford Brookes has developed a university-wide policy and practice framework for generative AI.
At Oxford Brookes, we are committed to helping our students become AI-literate and capable of using AI tools safely and ethically.
The principles are intended to support staff in making decisions about assessment design in relation to generative AI.
DocuMark: Responsible AI Use for Academic Integrity
Knowing your institution's AI policy is step one. DocuMark helps enforce it fairly by empowering universities to manage AI-generated content, prevent cheating, and support student writing through responsible AI use.
Common Questions About Oxford Brookes University's AI Policies
Oxford Brookes University has defined AI policies in 11 of 12 categories, with an overall coverage score of 92%.
Where AI use is permitted or partly permitted, students are expected to acknowledge and reference that use in line with assessment guidance. The university provides explicit advice that AI-generated material should be cited and that students should be transparent about use. Disclosure requirements may therefore vary by assessment, but transparency is expected when AI contributes to submitted work.
Undisclosed or unauthorized AI use can be pursued under the university’s academic misconduct procedures. The university describes cheating broadly as gaining unfair advantage by unauthorized means, and its AI guidance links misuse of AI to academic integrity processes. The provided sources do not establish a specific university policy endorsing reliance on any one AI-detection tool.
The university instructs users not to enter personal, confidential, or commercially sensitive information into public AI tools and requires compliance with data protection and confidentiality obligations. The provided sources therefore establish data protection limits on AI use, but they do not identify a university-approved list of AI platforms in the text available here.