Using Generative AI

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.

Experiences of Remote Teaching & Learning during the COVID-19 Pandemic

Between March and July 2021, CCTL led a short, focused project to explore students' and staff experiences during the pandemic, in order to inform enhancement activities over the next three to five years. The project included three strands: 

1. a rapid evidence review, synthesising existing evidence and literature on digitally enabled teaching and learning in Cambridge 
2. interviews and focus groups to explore Cambridge practices and cultures around teaching and learning in person and online during the pandemic 
3. interviews and focus groups to explore patterns of institutional support and training put in place for teaching staff and students 

Project findings include: 

• in many subjects, digital submission and marking of supervision work enabled students to receive and reflect on feedback before the supervision, providing a foundation for more advanced activities in in-person supervisions 
• digital availability of lecture materials (whether recorded live and uploaded later, flipped learning models, or specific short pre-recorded lecture content) should be retained 
• there should be further exploration of pedagogically beneficial approaches to using online materials to enhance lecture and class learning 
• students and staff hoped for continued increases in the availability and accessibility of online library materials 
• students valued clear, single-access points for the curation of online course materials

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.