Personalisation of learning through artificial intelligence in higher education in the United Kingdom

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Article

Personalisation of learning through artificial intelligence in higher education in the United Kingdom

Fatmire Vrapi, Asllan Vrapi

Received 11.06.2025, Revised 20.10.2025, Accepted 26.11.2025

https://doi.org/10.67524/verus2/2.2026.04

Retrieved from Vol. 1, No. 1, 2025

Pages 4-18

Abstract

Artificial intelligence in higher education allows adapting the content to the individual needs of students, but it is necessary to evaluate the effectiveness, consider the issue of algorithmic bias and provide the appropriate development of staff. The purpose of the study was to investigate the influence of artificial intelligence integration on the personalisation of learning in higher education in terms of academic achievement, motivation and engagement. By comparing the functional possibilities of adaptive platforms, it was found that personalisation through intelligent algorithms allows for an individual approach to learning, dynamic adjustment of tasks and timely feedback, while the traditional model is limited in flexibility and is aimed at a nominal average student with a typical level of prior knowledge, a standard rate of content assimilation and conventional educational needs without regard for individual peculiarities. An analysis of educational platforms showed that learning management systems with integrated artificial intelligence tools (Moodle, Blackboard, Canvas, Brightspace, FutureLearn) make it possible to construct individual learning pathways, predict the risk of academic underperformance, and adapt materials in line with student progress, thereby reducing dropout rates and increasing module completion and system activity. The case study method indicated that the use of generative artificial intelligence at the University of Glasgow, the Open University, and the University of Manchester is regarded as a promising tool for supporting the learning process, developing digital competences, and enhancing the flexibility of interaction between students and academic staff, without detailed specification of particular pedagogical interventions, quantitative effectiveness indicators, or structural changes to curricula. An analysis of the role of the lecturer demonstrated that the integration of artificial intelligence transforms professional functions from those of a traditional lecturer to those of a coordinator and mentor who employs analytics to adapt content, adjust learning pathways, and provide personalised support, thereby creating a hybrid model of pedagogical guidance and enhancing the effectiveness of the educational process. The results show that personalisation of learning through artificial intelligence has a holistic positive impact: academic resilience, student engagement and the general effectiveness of the educational process in higher education in the United Kingdom are enhanced. The results of the study can be of use for lecturers, university managers and developers of educational platforms in the implementation of effective artificial intelligence solutions within the teaching and learning process

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Suggested citation
Vrapi, F., & Vrapi, A. (2025). Personalisation of learning through artificial intelligence in higher education in the United Kingdom. Educational Innovation & Technology Journal, 1(1), 4-18. https://doi.org/10.67524/verus2/2.2026.04