Exploration of AI

Think about the data or prompts you are using with AI systems as this could potentially become data that is shared with wider groups. The more suitable prompts will be based around designing ideas, asking questions, and generating new content. However, it is not recommended that you:

• put any form of personal data (your own, or the data of others) into AI systems as this would be considered a GDPR breach.
• copy and paste students’ work into the tool to check if the work has been produced by AI. AI is not able to reliably check for this information and it can produce false feedback.

As mentioned in the AAAA framework (web), think about using free, accessible AI tools so that all students will be able to have fair and equitable access to support their learning. If the tools you are recommending have a better paid-for version, this could lead to unfair advantages when creating content.

One of the limitations of AI (web) is that it can produce false information (hallucinations). When experimenting, especially if asking it to collate research or answer a question, it should be examined closely before use to ensure the data is accurate. Identifying the source of the data it has used can be a useful way of determining if the information is from a trusted resource. AI sometimes produces false references or sources that appear correct, so be sure to verify each one. For more help with this see the AI Study Skills Guide (web).

Think about the content that you want to produce: is this accessible (Accessibility Toolkit | web) and how will students view the information? AI itself can be a useful tool to help support accessibility issues with content, but the way this information is presented to students needs to be considered.

As mentioned previously, different AI tools respond differently to prompts; it can be useful when experimenting to think carefully about the prompts given to the system. Simple variations in length, tone, and approach can have differing outputs. Sometimes it may take several attempts at reworking prompts before you receive an output that is appropriate.

When designing a prompt, be really clear with the output that you are looking for, especially if you would like it in a certain format or type. This clarity will help the AI to support you when it’s gathering information.

As a university, we work collaboratively as ‘One Community’ and encourage collaboration and the sharing of practice with other colleagues. Gaining an understanding of the tools and approaches used can be a useful way of developing our own understanding of what AI can achieve and how we can embed it inside of learning and teaching. If you have an interesting approach that you would like to share, please contact digitaleducation@lincoln.ac.uk and we can add this to our shared practices page.

Quick navigation

• Data
• Access requirements
• Critical analysis
• Accessibility
• Experiment
• Outputs
• Sharing