Leveraging Artificial Intelligence to Enhance Personalised Learning and Academic Performance in Higher Education: A Mixed-Methods Study

However, despite the increasing adoption of AI technologies in education, empirical evidence remains limited regarding their effectiveness in improving learning outcomes, ethical implications, and impact on the student–teacher dynamic. Concerns persist about data privacy, algorithmic bias, and overreliance on technology.

This research aims to critically examine how AI-based educational tools can be optimised to foster personalised learning, improve academic outcomes, and ensure ethical and equitable use in higher education. The study aligns with global educational priorities, emphasising digital transformation and inclusivity in learning environments.

Academic qualifications

Have, or expect to achieve by the time of start of the studentship a first-class honours degree, or a distinction at master level, ideally in Information management, Education, Educational technology with a good fundamental knowledge of Knowledge of research design, qualitative and quantitative methods.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

• Technology impact
• Educational theory
• Only a first-class honours degree, or a distinction at master level in a subject relevant to the PhD project will be considered, or equivalent achievements.

Desirable attributes:

• Blend of Technical and Educational Knowledge
• Digital pedagogy
• Practical experience in research or industry will be considered an advantage.

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about:
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.
• The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.
• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use

• the advertised title as project title

For informal enquiries about this PhD project, please contact Dr Wegene Demeke email W.Demeke@napier.ac.uk