Enhanced Personalized Learning Experiences by Leveraging Knowledge Graphs and Prompt Engineering

Naik, Malav Hiteshbhai (2025) Enhanced Personalized Learning Experiences by Leveraging Knowledge Graphs and Prompt Engineering. Masters thesis, Dublin, National College of Ireland.

Preview	PDF (Master of Science) Download (1MB) | Preview
Preview	PDF (Configuration Manual) Download (237kB) | Preview

Abstract

Billions of opportunities in personalized learning have now been opened up since the emergence of personalized learning. artificial intelligence to transform learning (Chen, Hwang & Wang 2021). In In our research we are proposing SkillBot that is a novel AI driven web app. to help users develop capabilities in such domains as programming, Language acquisition, problem analysis and discovery of general knowledge. Deep down the core of it all, the most inner part of it.combines the power of Large Language Models (LLMs) (Brown et al. 2020) with special utilization of the interactive skills assessment through knowledge graphs (Hogan et al. 2021). Individualised learning suggestions, immediate feedback. The version of the CRISP-DM methodology that it uses, therefore, takes advantage of the diversity (Wirth & Hipp 2000), version of the CRISP-DM methodology, it utilizes different aspects of diverse and unique methodologies. data–such as student engagement scores and the present job market dynamics to improve the quality of learning. Some of its most important innovation entails a new LLM and knowledge graph fusion framework and a chatbot system that won an accuracy of 87 percent in recommendations. We have reviewed Excel-Incredible performance, and easy to use on lending usability SUS score of 86/100 (Brooke 1996), robust performance marked by an F1-score of 84% (Chinchor 1993), and competent real-time performance. ultimately, SkillBot would be a flexible and scalable platform of AI-based learning that seems right and efficient to ordinary customers.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Basilio, Jorge UNSPECIFIED
Subjects:	L Education > L Education (General) Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	01 Jul 2026 11:49
Last Modified:	01 Jul 2026 11:49
URI:	https://norma.ncirl.ie/id/eprint/9439

Actions (login required)

View Item