AI-Mediated Personalised Text Adaptation Strategies for Self-Regulated Learning

About the Project

Project advert

Technological innovation fosters educational independence for those learners that embrace it. Recently, AI (artificial Intelligence) chatbots have had a disruptive effect on the education sector with two thirds of university students using AI in 2023.

AI chatbots can be used for a variety of tasks to support educational outcomes. A student may translate a slide or article into their native language. They may ask for a simplified explanation. They may interrogate source texts via the chatbot, asking questions to deepen their understanding of the topic background. These interventions can be considered through the lens of automated text-adaptation operations, which are well defined within the field of NLP (Natural Language Processing).

In this project, we will consider AI-mediated text adaptations through the lens of self-regulated learning. The successful candidate will investigate a variety of strategies of AI-mediated text adaptations for education, identifying successful strategies for educational benefits. The candidate will identify personalized strategies for AI-mediated intervention in learning, crossing cultural barriers and educational levels.

This project is further supported by two international research projects, where the successful candidate will have the opportunity to participate in international networks beyond the university, applying technological and educational innovations in a globalized setting.

Project aims and objectives

• Contribute to world leading research on the use of Large Language Models for Text Adaptation operations in the educational setting
• Explore personalisation of learning through the lens of Self-regulated learning theory, as mediated by frontier LLM technology
• Develop novel research methodologies for the application of personalised technological interventions in the educational journey
• Apply research in-context with learners at home and in an international setting
• Participate in related research projects, tying applied research into wider practice settings.

Funding

Both Home and International students can apply. Only home tuition fees will be covered for the duration of the 3-year award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 2 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

Qualifications:

Essential

• Ability to write research code in Python
• Interest in pedagogy

Desirable

• Excellent English Language skills
• Willingness to travel as part of research field work.

How to apply

Professor Rupert Ward (r.ward@mmu.ac.uk) will lead the project as Principal Supervisor and Dr Matthew Shardlow (m.shardlow@mmu.ac.uk) will act as your First Supervisor. Please get in touch with the proposed supervisors if you have any queries regarding the project.

To apply you will need to complete the online application form for a full time PhD in Computing & Digital Technology.

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest.

Please upload these documents in the supporting documents section of the University’s Admissions Portal. If you encounter any difficulty uploading them to the designated area, please get in touch with the PGR Admissions team (pgradmissions@mmu.ac.uk)

Applications closing date: 26/06/2026

Expected start date: January 2027

Please quote the reference: SciEng-MS-2026-27-Education AI NLP