Generative AI for Personalised Feedback in Digital Learning

Are you ready to be at the forefront of AI innovation and transform how digital learning is designed, delivered, and experienced? Join us on a cutting-edge project investigating how generative AI can provide automated assessment and personalised feedback in digital learning environments, with a particular focus on health and social care education.

This PhD studentship is 42-month fully funded through the EPSRC Research Excellence Awards (REA) within the John Anderson Research Studentship Scheme (JARSS). You will be based in the Department of Computer and Information Sciences at the University of Strathclyde, working in close collaboration with NHS Scotland Academy.

About the Project

Digital learning has become a central mechanism for delivering education and training across sectors, particularly in large, distributed workforces such as health and social care. While it offers flexibility and accessibility, current digital learning systems remain fundamentally limited in their ability to assess complex, free-text responses and provide timely, high-quality feedback at scale.

As a result, many platforms rely on multiple-choice assessments and passive content delivery, limiting learner engagement, reflection, and the development of deeper understanding. This is a significant challenge in healthcare contexts, where effective learning directly impacts professional practice and outcomes.

Recent advances in generative AI and large language models (LLMs) present a promising opportunity to address these limitations. These technologies can interpret and generate natural language, enabling the possibility of automated assessment and tailored feedback that mirrors key aspects of human tutoring.

This project will systematically investigate how generative AI can be used to enhance digital learning by developing, evaluating, and validating AI-driven feedback systems. Working with NHS Scotland Academy, the project will be grounded in real-world educational settings, generating evidence on the effectiveness, reliability, and acceptability of AI-enhanced learning in professional contexts.

Why This PhD Is Your Opportunity to Innovate

Generative AI is rapidly reshaping how we interact with information and learn. In education, it has the potential to move beyond static content toward interactive, adaptive, and personalised learning experiences.

However, key challenges remain around accuracy, consistency, trust, and pedagogical alignment, particularly in high-stakes domains such as healthcare.

Imagine a system that can read a learner’s written response, understand their reasoning, and provide feedback that supports reflection and improvement. This is where your research will make a difference, helping to develop AI systems that enhance learning outcomes while remaining robust, transparent, and trustworthy.

What You Will Do

You will design and develop innovative approaches for automated assessment and personalised feedback using generative AI, contributing to the next generation of digital learning systems.

Key Objectives:

• Develop methods for assessing free-text learner responses using generative AI
• Design feedback generation techniques that are constructive, context-aware, and aligned with learning objectives
• Create tools that allow educators to define and control assessment criteria and feedback behaviour
• Benchmark and evaluate different generative AI models in terms of accuracy, reliability, and consistency
• Conduct experimental studies to assess the impact of AI-driven feedback on learning outcomes and engagement
• Investigate the use of AI-enhanced learning in real-world settings through collaboration with NHS Scotland Academy
• Ensure alignment with responsible AI principles, including transparency, fairness, and trust

What We are Looking For

We are seeking ambitious and curious researchers who want to push the boundaries of AI and create meaningful impact.

Essential Skills:

• A 2:1 Honours degree or Master’s degree in Computer Science, AI, Data Science, or a related field
• A strong background in machine learning, natural language processing, or data analysis
• Proficiency in programming and model development (e.g. Python)
• Excellent written and oral communication skills
• An understanding of experimental design and evaluation

Desirable Skills:

• Experience with generative AI or large language models
• Interest in educational technology, HCI, or human-centred AI
• Familiarity with evaluation in real-world or applied settings
• Experience working with interdisciplinary teams or external partners
• Interest in responsible and ethical AI

How to Apply:

Applications will be processed on a 'first come, first served' basis, and the hiring process will conclude as soon as a suitable candidate is identified. Interested candidates should email Dr Yashar Moshfeghi (yashar.moshfeghi@strath.ac.uk) and include detailing contact information, and motivation, or background and attach an up-to-date CV.

Funding Notes

All home and international students are eligible to apply which will cover the full stipend and tuition fees at the home rate (not the international rate). It includes:

• A fee waiver equivalent to the Home rate; and
• A tax-free stipend of approx. £22,442 p.a. for a maximum of four years and does not need to be paid back. This amount will increase every year, typically with inflation.

International students are permitted to self-fund the difference between the home and international fee rates.

We also welcome self-funded or externally funded applications.