Exploring the Utilization of Multimodal LLMs on Personalized Learning in Higher Education

Abstract

Use of Large Language Models (LLM) is rising in popularity amongst students in higher education. It has transformed the way students tackle their academic work, offering stu- dents powerful new tools for explanation, idea generation, writing support, and independent study. While their adoption has been widely discussed in theory, there remains limited empirical evidence on how students are using these technologies, how they per- ceive their benefits and risks, and how such practices may reshape learning. This dissertation explores the perceptions and practices of 55 UK university students re- garding the use of LLMs in academic work. Using a survey-based methodology, the study examines five key objectives: to identify patterns of LLM use, analyze the purposes for which they are employed, evaluate student attitudes toward their advantages and limita- tions, assess their influence on study habits and independent learning, and provide insights for ethical and effective integration into higher education. The results reveals that students use LLMs as tools for understanding and organizing knowledge such as summarization or concept explanations and clarifications. Secondly, they employ them for supporting their academic writing and production like proofreading, editing, or as a writing assistant. Likert-scale analyses indicate that students generally per- ceive LLMs as both useful and easy to use, consistent with the Technology Acceptance Model (TAM). However, concerns around trust and over-reliance temper this enthusiasm, highlighting a critical awareness of the risks involved. The findings suggest that while LLMs are integrated into study habits and promote efficiency, their long-term value will depend on guidance, ethical frameworks, and digital literacy training. The study contributes to the growing body of research on AI in education by offering evi- dence from the UK universities context. It demonstrates how perceptions of usefulness, ease of use, and reliability shape adoption, and it paves the way for future research, includ- ing cross-cultural comparisons, to better understand the evolving role of LLMs in higher education.