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Guidance for Students

Students are permitted to make appropriate use of GenAI tools to support their personal study, research and formative work, however, due to differences between disciplines across the University, you should always consult local guidance (e.g., from your department, faculty, college etc.) 
More specific guidance around the use of GenAI in assessments is available.
When using GenAI tools and websites, please consider the following in addition to the general guiding principles:

  • The use of GenAI tools is not an effective replacement for developing skills or understanding in your subject area.
  • GenAI tools can commonly produce incorrect or unsubstantiated information and as such should always be verified from trusted and reliable sources.
  • Consider thoughtful use of GenAI and associated software where possible, making appropriate use to support your own development, using the most effective tool for the task at hand, and using efficient prompt-engineering to reduce the amount of iteration necessary.   
  • Remain aware of the limitations, inconsistencies, and biases that can exist within GenAI tools and data sets, and exercise caution when deciding to use information provided software  
  • Be accountable and take responsibility for how, when, and why you decide to use generated materials or information from Gen AI software. 

If you are unsure about how to effectively use GenAI for your own needs please discuss with your Supervisor or Personal Tutor and, if in doubt, seek clarification of permissible use of AI from your Director of Studies or Director of Teaching.

Guidance for Staff

As GenAI and Large Language Models are likely to continue developing at a rapid pace and become further integrated into our personal and professional lives, all staff are encouraged to explore the possibilities for integrating appropriate AI use into their teaching, learning and assessment. 
When doing so, remember to maintain clear and transparent expectations for students, and above all continue to provide a supportive environment for students to discuss, consider, and make the most of these technologies whilst feeling comfortable to approach staff where questions and concerns arise. 
We understand that there are sound concerns over the potential implications the use of AI may have on academic integrity, the authenticity of submitted work, and the overall quality of a degree classification with these considered risks. Assessments should be designed, and where necessary redesigned, to mitigate inappropriate use, emphasise key learning outcomes and competencies, and support an integrated approach to these new technologies  .
More specific guidance around the use of GenAI in assessments is available.
As staff, we suggest the following guidelines when considering how to respond to wider use of GenAI in teaching and learning in addition to the general guiding principles:

  • Reflect on how GenAI tools can support students in broadening their understanding, exploring wider topics, and understanding differing approaches to their subject.
  • Review learning outcomes or competencies and provide clarification for students on how GenAI may or may not be used in relation to these.
  • Engage with other staff and students to understand how GenAI tools may be used effectively within a controlled teaching and learning context. 
  • Maintain clear and transparent guidance for students

For further information and support in developing local approaches to the use of GenAI in teaching and learning, please contact the Blended Learning Service.

Generative AI Use Cases

The following table presents a variety of ways in which GenAI tools are commonly used as well as some example use cases. This list is not exhaustive and does not account for discipline specific uses. This table can be used to support local decision making and communication to staff and students. An expanded version of this list is in development and will be released as part of an upcoming AI Policy Framework to better support the decision making process.

LLM Tool Use

Description

Topic Selection

The software can suggest essay topics based on a general theme or subject area.

Research Assistance

The software can collate and present information and data on a given topic.

Summarising Literature

The software can summarise literature, analyse information and provide insights

Outline Creation

The software can help create a structured outline for the essay, or part of an essay.

Generating Text

The software can assist in writing the essay including writing introductions, body paragraphs, and conclusions.

Data Analysis

The software can analyse, summarise, and visualise qualitative data, providing insights for further evaluation.

Editing and Proofreading

The software can suggest improvements in grammar, punctuation, sentence structure, and word choice.

Citation and Referencing Guidance

The software can provide guidance on how to cite sources and create a bibliography in a specified style.

Paraphrasing

The software can be used to paraphrase existing content to make it appear as original work.

Translation

The software can translate content from one language to another.

Code Generation

The software can write feasible code in a variety of languages to meet the prompted brief.

Interpret Images

The software can “read”, interpret, and communicate the contents of an image including text.

Image Generation

The software can generate images and diagrams to varying degrees of accuracy.

Mathematical Problems

The software can be used to explain solutions to mathematical problems and, in some cases, provide solutions.

Informed Feedback

The software can provide feedback on a piece of work, this can reference criteria and rubrics if provided.

Inspiration & Direction Setting

The software can suggest sentences or paragraphs which are used to inspire a student’s own line of thought.

Discussion & Development

The software can provide a critical “partner” for students to discuss ideas and ask questions to further their own understanding.