Whether we approve of Generative AI or not, it is here to stay. Therefore, it’s important to identify the areas in which it will improve the student learning experience.

A subsequent area of research on using GenAI that stemmed from a 2023 FFYE grant was a capstone project from Sumaiya Sidiq Ali. Sumaiya is primarily a software engineer but also has an interest in cognitive psychology. Her research aims to use GenAI to meet individual learning needs by adapting teaching materials and programs to students preferred learning styles. This is predicted to improve student results as well as their engagement with the materials.

Adapting in real time (with a little help from AI)

In her project, Sumaiya has been working with student volunteers to investigate how individualised study plans could be developed to reflect student learning styles. The program she developed allows individual study plans to be created and redeveloped in real time. Therefore, if a student is having difficulty with a specific area, the plan will change to concentrate on the problem area.

Before developing the program, questions were developed to establish students perceived learning style and to adopt an appropriate support program. A study plan was then created through GenAI. Students engaged with this study plan to complete the subject tasks as a supplement to their timetabled tutorials.

The post-project review

After the program, the students involved were interviewed to determine how useful they found the personalised program.

The students were asked:

  • if they felt their results would have been different without the program
  • how easy the study plan was to follow
  • whether they felt it helped improved their understanding and ability to complete the assessments
  • for suggestions to improve on future iterations

Initial student feedback shows that this could be a significant support tool for students who are struggling with subject content.

The two students involved in the prototype program reported:

  • some academic improvement in their performance
  • more interest in the subject and the materials
  • the program and materials were easier to engage with and more motivating.

This, in turn, indicates they would feel less stress and a better state of well-being.

Scaling up?

If the results show the project is worth expanding, a larger trial will need to be developed. This would indicate whether the program has scalability in that it would be able to support large numbers of students. Moreover, it would be necessary to look at a range of different subjects to understand the limitations of the subject matter for which it could be useful.

Potentially, the program could be used as a supplement to HELPS or Language Development Tutorials to help support students identified as struggling. This would be particularly useful if it could provide a program with manageable steps for students facing difficulties. A further issue may be that the amount of work needed to investigate students’ individual learning styles and then match it to a program may be time-consuming.

There has been much work around ensuring students create original work and effective, ethical engagement with GenAI to help brainstorm and write up research projects. There is perhaps less work available on ways that tutors can engage with AI as a core component of program development – something that projects of this type can hopefully help progress.

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