Generative AI guidance

Learn how you can use generative artificial intelligence (GenAI) at CCCU and what conditions the University has put on its use.

Our approach to GenAI is educative, rather than punitive. 'Educative' means 'learning with and about'. Therefore, you can use GenAI tools to complement your learning but not to replace it. You may not use GenAI to produce work for assessment, unless explicitly told to do so by your module lead. Here, we explain how to use GenAI tools effectively, ethically and responsibly.

If you are unfamiliar with the language of GenAI, you can to refer to the glossary in the FAQs. There you will find definitions of key terms such as 'generative artificial intelligence', 'ethics,' and 'prompts'.

Using genAI at CCCU by Education and Student Success

What is GenAI?

GenAI refers to a wide range of technologies that use artificial intelligence algorithms to create new content, such as text, images, audio, or code from written instructions called ‘prompts’. GenAI is built into applications we use every day for our study, work, and leisure, from ordering a cab, getting a parcel delivered, or tagging a person in a photo on social media.

For a short introduction to what GenAI is and how it works, watch this video.

Do I need to use GenAI?

Before we look at how GenAI can be used, consider whether you really need to use a GenAI tool for your task. GenAI has a large carbon footprint and consumes large amounts of energy and water, which have consequences for our environment. Being aware of these impacts helps us to make informed choices when it comes to our personal responsibility towards sustainable education and living.

Look at the slides below to learn about the environmental impact of using GenAI to write an email:

We all have a responsibility to make environmentally conscious decisions. Having an awareness and understanding of the environmental issues in using GenAI allows us to make informed choices when it comes to our study.

Here are some examples of alternative uses of GenAI in your study:

What can I use GenAI for?

GenAI has a broad range of uses. However, not all of these are appropriate for your study. This section explains appropriate and inappropriate uses.

Case studies of acceptable use of GenAI

It can be difficult to know what is acceptable use of GenAI. These slides show fictional case studies to give examples of acceptable and unacceptable uses of GenAI at University. Click through the slide show to learn where the students' actions sit on the scale of acceptability.

Research and GenAI

GenAI can be a powerful tool for enhancing your research capabilities. However, these benefits should be balanced against the risks and it is important not to become dependent on GenAI for thinking. GenAI can be useful as a research assistant or learning partner; it can supplement your own research and critical thinking skills, not replace them.

If you are a final-year Undergraduate, Postgraduate research student, or researcher, please also refer to our additional research guidance: Using generative AI in research: A checklist

Conducting research using GenAI

GenAI tools, when used appropriately and thoughtfully, can be very useful for research. They can retrieve data, summarise it, present it in a variety of formats, allow you to manipulate and tweak the data, and they can do all of this very quickly. The instructions or questions that you put into a GenAI chatbot or image generator are called 'prompts'.

Here are some steps you can take to use search prompts effectively and ethically.

Triangulation of research

AI-generated information and data should be cross-verified with other sources, methods, or theories to ensure accuracy and reliability. To verify sources and references generated using AI tools, it’s important to carry out further research using reading lists/recommended sources, and traditional, retrieval-based search tools such as Google Scholar, LibrarySearch, relevant online resources, and databases.

Triangulation is a research technique that involves cross-verifying information from multiple sources. It enhances the validity and credibility of research findings. The poster below shows how GenAI tools relate to literature searching practices.

Evaluating information

Whilst helpful, GenAI does not know anything. GenAI tools often produce content with a confident, authoritative style. However, this content is produced by algorithms based on probability, not a person with the ability to think, understand, or critically evaluate. You are always the best judge of what is appropriate or relevant, so view any information given or content generated with caution and a critical eye.

Your work should always strike a balance between your ideas and research, and ideas of others. An over-reliance on GenAI may hinder your own critical skills development. You might use GenAI to help you to develop ideas or identify relevant sources during the research process, but you should analyse outputs and integrate them with your work in a thoughtful way, acknowledging the work of others with accurate in-text citations and referencing.

For guidance on thinking critically about the information you use, watch this video that explains using the BREAD tool developed by one of CCCU's Learning and Research Librarians, David Bedford. The BREAD tool can also be applied to GenAI, as you can see in the graphic below.

Producing work with GenAI

GenAI tools can produce images, text, code, sound, video, and many other outputs. But they do not have an imagination of their own; they create content based on probability from your prompts. Although their output can provide initial ideas or inspiration, you should use your own creativity to build upon these ideas, whatever the medium. Your tutors value originality and creativity.

Your module leads may use the Artificial Intelligence Assessment Scale (AIAS) to 'rate' your module assessments according to how much GenAI interaction they will allow for your assessments. This will be communicated to you through your module handbook and assessment guidance.

Always check and follow the guidance provided by your lecturers if you are considering using GenAI for your academic work.

Written work (essays, reports, and dissertations)

GenAI can make language learning more effective and more accessible; it can be engaging and fun. Using GenAI tools can enhance the development of academic writing skills by offering a more sophisticated self-directed practice. However, they should not be used to replace your written work, by copying content or to prevent you developing your writing by uncritically accepting corrections or edits to your work.

GenAI chatbots are trained to be generalist. Whilst they can mimic particular writing styles, the text they produce is rarely nuanced and specific enough to provide academic writing of the level required at University.

Remember that to use GenAI tools with integrity, use must be declared and fully referenced.

Click through the slides below for examples on using GenAI to develop your written work and for some example prompts. For further guidance on academic writing skills, visit the Learning Skills Hub.

Presentations (slides and posters)

GenAI tools can be very helpful for preparing visual aids for presentations. They can be used to produce images, infographics, and visually appealing layouts for slides. Be aware that image generation is also subject to bias and inappropriacy. See the section on image generation below for more information.

Writing for speech is different to writing essays or reports. As you will be speaking the words out loud, you will need to adapt to shorter sentences that suit the cadence of your voice. GenAI tools can help to shorten and simplify sentences for speech, or transcribe your speech so you can refine it further. However, ensure you retain the academic detail necessary to meet your learning outcomes and do not over-simplify.

Only use GenAI to produce work for assessed presentations with the explicit permission of your module lead. Ensure the content is derived from your own research and you have thought about it critically.

Remember that to use GenAI tools with integrity, use must be declared and fully referenced.

Visit the Learning Skills Hub for further guidance on presentation skills and academic poster design.

Spelling, punctuation, and grammar (SPaG)

The most common use of GenAI tools is to correct spelling, grammar, and punctuation (SPaG). However, we have all experienced an incorrect auto-correct! It is important to recognise that GenAI tools for spelling, punctuation, and grammar cannot replace learning grammar and writing skills. It is a requirement of University education that you graduate with advanced writing skills.

The good news is that GenAI chatbots make excellent tutors in this area. Using the GenAI chatbot in this way will help you shift your focus from an emphasis on accuracy and correction to learning and development.

Ask a chatbot to identify the common SPaG errors in your work, rather than correct them. Then ask for an explanation of how to correct those errors and make the corrections yourself. You can return the text to the chatbot and see if it has further recommendations. Some tools provide reports, which you can use to improve your writing and avoid the same mistakes in the future.

Be sure to specify that you want the rules of British English, or your work will be Americanised. Do not accept suggestions for words for which you do not know the meaning. The vocabulary suggested by some GenAI tools can be invented or used entirely out of context.

Remember that to use GenAI tools with integrity, use must be declared and fully referenced.

For further guidance, see the Learning Skills Hub module on SPaG.

Image generation

GenAI tools can generate images and artwork from written text prompts. These images might provide inspiration or starting points for your own projects.

In the graphic below, you will find some examples of potential uses for AI generated imagery.

As with text generated by AI, outputs are dependent on the data the tool is trained with. This means that any biases, assumptions, stereotypes, or other problematic content present in the data will be reflected in the images produced.

• It can be difficult to create prompts which produce the exact image required.
• Image generators may also produce low quality images, 'strange' compositions, or images where details are wrong, for example errors in images of hands or eyes are common.
• The data used to train the algorithm will likely comprise images with registered copyrights or trademarks. It is prudent to look out for watermarks, copyright, and trademark symbols and not to re-use images drawn from this content. Ensure you do not perpetuate bias and stereotyping that is offensive and harmful, for instance, around gender, race, and disability.
• Also, be cautious of the potential for illegal, offensive, or exploitative images being generated.
• Some tools have strict content rules for image creation (e.g. relating to violence, drugs, or politics) and may prohibit content based on controversial topics, so some users complain of restricted creativity.

Computer code

GenAI tools such as GitHub Copilot can be useful for developing computer code. However, lecturers will be assessing your ability to create and modify code, problem solve and understand coding concepts, so use these tools for learning.

As with text and images, GenAI coding tools work on probability and may struggle with understanding nuances and subtleties in user queries or project requirements. They may not always provide effective solutions to complex problems. The quality of responses can vary significantly based on the query's complexity and specificity.

Other limitations may include:

• Generating incorrect or inefficient code suggestions. Ensure your prompts are clear to generate useful responses.
• Accuracy depends heavily on the context provided in the existing code.
• Suggestions may not always align with the latest coding best practices.
• May not be as effective with less popular programming languages or frameworks.
• The GenAI tool might suggest code snippets that closely resemble existing public code, raising potential licensing and copyright concerns. It may be picked up by similarity software either from other sources or other students’ work.

Always view AI generated or modified code critically and ask yourself if it is efficient and gives the desired output. Most importantly, you should be able to understand and explain how the code works, rewriting, or modifying the code as necessary.

GenAI tools should be used in the appropriate way to support your work and should not be relied upon too heavily. Always ensure you check the specific criteria for each assignment and give a reference for the code in your work.

Look at the poster below for some ideas on how you could use GenAI to help with coding work.

Referencing and declaring the use of GenAI

It is always important to differentiate between our own original work and what comes from elsewhere. In academic writing we do this via a system of citations and references. You can find out more about referencing in the Learning Skills Hub module Introduction to Referencing.

We firmly advocate that you use reliable, academic sources for research. Where you use GenAI, you must acknowledge its influence on your work by acknowledging and referencing appropriately. We recommend you follow the links GenAI tools provide to their sources and verify the information’s accuracy and reliability.

Always verify GenAI outputs' truthfulness and accuracy.

Always acknowledge the use of GenAI in your work using the relevant statement provided in your module handbook.

Always reference GenAI in your work. Do not submit work produced in whole or part by GenAI tools, either verbatim or after paraphrasing, without citation. You can learn more about citing and referencing GenAI on Cite Them Right.

There are several different referencing systems used across the University, depending on the subject you are studying. You can find out which referencing system is used by your academic department by checking your module handbook.