Artificial intelligence | Staff guide

This page provides an overview of how AI is impacting online education.

What is AI?

AI is a collective term for a set of technologies that use large data sets to attempt to replicate certain actions such as creating an image, writing text, or responding to questions. AI also has links to fields such as Machine Learning and data processing. An example currently prominent in education is ChatGPT, but there are many other similar technologies.  AI is originally ‘trained’ off a large data set and then uses input data to refine its approaches, so the more work that it conducts in a particular area the more refined its outputs become.

AI is a collective term for a set of technologies that use large data sets to carry out tasks such as generating images or text, analysing information, or responding to questions and instructions. Tools such as ChatGPT, Copilot, and Gemini are currently prominent, but there are many others, and the field continues to develop quickly. These tools are built ('trained') using large existing data sets, and their outputs reflect patterns in that training data rather than genuine understanding. So while they can appear highly capable, they can also be confidently wrong.

Using AI for learning

Below are some suggestions to promote the responsible use of this technology. Now is the time to try something innovative that may also prove to be more effective and motivating for students.

• Get inquisitive and share your understanding: Try out some of these emerging AI tools to understand how they are changing common tasks. Consider how the use of the technology might help students learn. Bear in mind, that this is a rapidly developing field, so the nature and capacity of tools will change. Try to keep up-to-date and share your understanding with colleagues. 
• Create clear expectations: Discuss with students the concept of academic authorship and its relevance to the use of AI, and the extent to which it can be used to support the development of academic writing skills. Use this as an opportunity to reinforce debate around academic honesty and integrity, intellectual property, and the best use of technology. Explain and show how these systems make serious mistakes and hold bias that requires critical thinking, subject knowledge and understanding to identify and correct. Repeat these messages, in lectures, tutorials. Don’t just rely on a one-off talk.
• Review assessment strategies: Assessment is one of the areas most affected by AI, and needs coordinated, programme-level thinking rather than one-off fixes at module level. Detailed guidance on reviewing assessment design considerations can be found in https://www.ljmu.ac.uk/staff/assessment-and-feedback-guidance/ai-considerations. 

We need your help

Everyone is on a steep learning curve in terms of how to manage assessment in the face of increasingly sophisticated artificial intelligence software. Please contact the Teaching and Learning Academy if you have ideas or techniques that you are happy to share. Alternatively, let us know what you think about this guidance, and whether the suggestions have been useful or not.