AI In Education: What Trust Leaders Should Be Thinking About

• Published date: 18 January 2024
• Subject Matter: Consumer Protection, Privacy, Technology, Data Protection, Education, New Technology
• Law Firm: Wrigleys Solicitors
• Author: Ms Alacoque Marvin and Michael Crowther

This article looks at the opportunities, challenges and risks of generative AI for schools and trust leaders.

As a starting point, school and trust leaders should consider the Department for Education's 'Generative artificial intelligence (AI) in education' which sets out the position of the DfE on the use of generative AI.

The opportunities

Whilst there are undoubtedly complex legal and moral issues to navigate with AI (some of which we will consider below), there are also significant potential opportunities to exploit. These include:

Personalised learning

This is thought to be one of the most promising applications of AI in education. AI can be used to analyse a student's learning style, strengths and weaknesses to tailor educational content to the pupil's specific needs. This means that students could learn at their own pace, focusing on areas where they need improvement and skipping over material they've already mastered. This could lead to improved learning outcomes and a more engaging educational experience.

The potential for AI to operate as an artificial teaching assistant also has significant potential to help teachers personalise and differentiate learning when working with pupils and students.

Automating administrative tasks

AI could help to automate many of the administrative tasks that take up a significant amount of time for teachers and administrators. This includes tasks like marking, scheduling classes, and tracking student attendance. By automating these tasks, teachers might spend more time on instruction and less time on paperwork. Likewise, many administrative tasks could in theory be given to AI systems to monitor and action, or AI could be used to make those tasks quicker - for example writing letters, compiling and updating data, and so on.

Enhancing accessibility

For example, speech recognition technology could help students with disabilities to interact with digital learning materials. Similarly, AI-powered translation tools can make educational content accessible to students whose first language is not English or who speak very little English. It may also be possible to use AI to create tools that make learning more accessible for students with SEND.

Predictive analytics

Whilst acknowledging the need for scrutiny, AI can analyse data to predict trends and outcomes, which can be particularly useful in education. For example, it might help to identify students who are, or who are at risk of, falling behind, allowing more effective...