Teaching students to use AI responsibly

Resources to use in your course:

• Introduction to AI, UQ Support and your assessment slides (PPTX, 24.2 MB)
• Example guidance for students acknowledging AI use adapted from Dr Peter Worthy (PPTX).

Students are looking for guidance about how to use AI effectively in their courses. Research at UQ, led by Kelly Matthews with Christine Slade, explored how students are using AI. Winter research students Claudia Maya and Alessandra Tran developed a guide for staff (PDF, 217.3 KB) based on this work highlighting students’:

• uncertainty about AI in their studies
• desire for further guidance
• trust through transparency when using AI
• connection and compassion. 

UQ has also developed the AI student hub with information to support students in their coursework studies.

As academics, we play a crucial role in preparing our students to navigate a future shaped by AI. This involves not only thinking about how AI is used in our disciplines but also ensuring that students are equipped to use it ethically and effectively in their studies and future careers. 

Dr Peter Worthy discusses: What does responsible use of AI tools mean?

Pratt and Zhang (2025) provide a case study of responsible AI us in a UQ first-year creative inquiry context. Taptamat et al. (2025) provides a case study of developing an online module for science students around responsible AI use in partnership with science students. Bidar (2025) reflects on developing students' AI capabilities in information systems courses.  

Dr Shahrzad Roohy Gohar: Integration of AI literacy into a first year core course

Addressing AI in your course assessment 

AI presents both opportunities and challenges for learning and assessment. To support students, it’s important to clearly articulate expectations about the use of AI in your course assessments and to foster open discussions about AI’s role in your course. Utilise the Introduction to AI, UQ Support and your assessment slides (PPTX, 24.5 MB) for informational and assessment examples that you can reference in your course and presentation materials. These slides were last updated 4 February 2025.

Clarify expectations

• Reinforce the guidance in course profiles about when and how AI can be used in assessments.
• Provide specific examples of acceptable uses, to clarify effective use versus uses that may impede learning. For example, prompts to support students following the steps for writing an assignment (as adapted by David Rowland)

Explain the rationale behind AI decisions

• Clearly communicate how assessment and learning activities are designed to help students achieve learning outcomes.
• Explain why decisions about AI were made in relation to assessment tasks. When students understand why an activity matters, they are more likely to engage actively, rather than rely on AI to do the work for them. 

Provide guidance on acknowledging or citing AI

• Be explicit about when and how AI should be acknowledged or cited in your course.
• Share examples and direct students to the relevant UQ Library’s guidance on referencing AI.
• Model these practices in your teaching to build trust and to set clear expectations. 
• Example guidance for students acknowledging AI use adapted from Dr Peter Worthy (PPTX).

Supporting students’ effective use of AI

Students are already integrating AI into their studies and lives — over 80% of UQ students report using AI in their academic work.

Learning requires time, effort, challenge and reflection. AI can provide feedback, encouragement and opportunities for practice, but it can also allow students to avoid the thinking and productive struggle through which learning develops.

Ask students to consider:

• What am I meant to learn through this activity?
• What thinking or practice do I need to undertake myself?
• How might AI support that learning?
• What might I fail to learn if AI performs this part of the task for me?
• How will I check the quality and accuracy of its output?
• Can I explain and take responsibility for the final work?

By proactively addressing these considerations, we can empower our students to use AI as a tool for learning, growth and professional success — while fostering a deeper understanding of its implications.

When using AI, you can let AI do all the thinking for you, which can suppress your ability to problem solve on your own.

- UQ student voice forum, July 2024 

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• understand, at an appropriate level, how generative AI produces outputs
• recognise bias, hallucinations, uncertainty and other limitations
• evaluate claims, evidence, sources and references
• check outputs for accuracy, quality and relevance
• understand privacy, copyright, ethical and disclosure responsibilities
• recognise when AI use may undermine learning
• decide when not to use AI.

Responsible AI use requires more than technical proficiency or skill in writing prompts. Students need opportunities to understand how AI systems produce outputs, evaluate those outputs critically, recognise risks and decide when AI use is inappropriate.

For example, we can design activities for students to:

• compare an AI-generated response with a peer-reviewed source and a disciplinary example
• identify factual errors, unsupported claims and missing context
• evaluate AI-generated references
• compare how different prompts or tools frame the same issue
• identify perspectives, evidence or affected groups omitted from an output
• revise an AI-generated response and justify their changes
• discuss when AI would be useful, unreliable or inappropriate.

Students will encounter AI in professional, workplace and community contexts where errors, bias, confidentiality breaches or poorly justified decisions may affect other people. Responsible AI education should therefore help students connect university learning with disciplinary standards, professional obligations and public trust.

We need to prepare students to:

• apply disciplinary expectations and professional standards
• protect privacy and confidential information
• check outputs for accuracy, quality and suitability
• recognise when the risks of using AI are too high
• maintain human judgement in decisions that affect others
• explain and justify their decisions about AI use
• accept responsibility for the resulting work or decision.

AI can be a practical, time-saving support in teaching when it’s used deliberately and responsibly. One helpful starting point is Jason Tangen’s Academic AI guide, which frames AI as an “enhancer” and encourages educators to explore what’s possible while making careful ethical choices about what (and what not) to automate.

UQ practice also shows how AI can strengthen inclusive learning design. In a dentistry case study, AI was used (with human oversight) to help restructure course sites, clarify success criteria, and create multimodal learning materials (for example, slides, podcasts, interactive modules, and recorded tutorials), alongside explicit expectations for responsible use and disclosure (Weerakoon, 2025). 

Across the business school Mitchell (2025) describes three approaches to integrating AI. Wright and Baruah (2025) explore using a range of AI tools to strengthen counselling and communication in dietetic education. 

When using AI in your teaching ensure you are protecting personal information and copyright materials, monitoring bias and checking the accuracy of your work. Modelling appropriate acknowledgement can build trust and support your students to engage in ethical and effective AI use. 

Fitzgerald (2025) provides an overview of insights for people teaching in higher education in the age of AI.

Dr Olivia Wright: The AI learning initiative via engagement

Copyright and AI can be complex, many AI systems require user to provide rights to the content used. This page sets out a few use cases for how an AI tool might be used in a variety of teaching scenarios. This information only applies to the use of works with closed AI tools that have been authorised by UQ (Copilot). It does not apply to the use of AI tools that are free to use or have been used with a licence paid for by an individual.

There are two general uses here, one (a) which involves the use of third-party content with an AI tool, and one (b) that involves the use of personal/university owned works or works licenced with a Creative Commons licence with an AI tool. 

The examples provided here consider our responsibilities with copyright, we also have many other responsibilities in teaching including: the quality of our teaching and resources, the way we make assessment judgments, and the software we use.  Depending on the specific situation, a specific use my meet our copyright responsibilities, but this does not remove our responsibility to ensure the output is current, accurate and appropriate and we meet all the responsibilities of our roles.

a. Where third-party content is used

The use of third-party copyright works with AI tools without a licence or permission from the copyright holder is prohibited. 

In most cases, content that comes from one of the subscriptions that the UQ Library has access to cannot be used with any AI tool.  

The only exception to this is works that are licenced with a Creative Commons (CC) licence, as these licences do not prohibit the use of these works with AI tools. 

The following is a list of acceptable uses of third-party content with an AI tool where UQ has  an appropriate licence or permission: 

Examples of uses: 

• Creating a summary of third-party content for use in class/distribution to students 
• Analysis of key themes, sentiment and findings in an article for use in class/distributing to students 
• Synthesis of themes and information between articles – resulting in the creation of a new work for use in class/distribution to students 
• Creation of revision questions for use in class/distribution to students 
• Creation of class presentations, tutorials, lecture slides etc.  
• Paraphrasing text from third-party content for use in class/distribution to students 
• Creating infographics, flyers, posters, etc. based off third party content for use in class/distribution to students 
• Transforming third-party written content into an audible format 
• Creating a translation of an article, book chapter etc into a student’s native language to assist with understanding 
• Lecturer organising group projects and tasks where third-party content is uploaded 
• Producing a reference list for content distributed to students 
• Checking a reference list for accuracy etc. before distributing to students 
• Generating scenarios, examples, or case studies for distribution to students (for assessment or teaching) 
• Creating teaching and learning activities based on theories, readings etc. 
• Analysing data for patterns and trends for class use of distribution to students 
• Creating data visualisations for use in class/distribution based on published data 
• Curriculum analysis 
• Converting third-party text content to video/podcast for use in class/distribution

b. Where third-party content is not used 

The list below outlines some acceptable uses of works owned by UQ or works licenced with a Creative Commons licence with an AI tool. 

Examples of uses 

• Quiz test and exam question creation for use in class/distribution to students 
• Checking the accuracy of and/or marking tests and exams 
• Lecturer transcribing their own lecture into written text for distribution to students 
• Creating a translation of a research/assessment task into a student’s native language/university content into native language to assist with understanding 
• Testing the efficiency of equations, calculations or proposed solutions 
• Producing a reference list for content distributed to students  
• Checking a reference list for accuracy etc before distributing content to students  
• Writing emails to students  
• Generating AI content to critique in class against individual work  
• Improving grammar and sentence structure  
• Translating assessment feedback into native language to assist with understanding 
• Translating individual written content into English 
• Organising raw data/facts into spreadsheets and tables for use in class/distribution 
• Creating data visualisations for use in class/distribution based on raw data 
• Resource transformation for accessibility purposes 
• Curriculum analysis