Empowering Education

A Paradigm Shift in Content Delivery Through Automated Personalization

Abstract

E-learning platforms have evolved to become essential instruments for educational content delivery. However, a significant challenge lies in the development of high-quality educational content, a process often constrained by resource-intensive requirements and the expertise necessary for content creation.
This study introduces an innovative system designed to revolutionize content creation and delivery in an educational setting by leveraging the capabilities of Natural Language Processing (NLP) and Large Language Models (LLMs), specifically Generative Pre-Trained Transformers (GPT). Our approach utilizes prompt engineering, a method of tailoring input text to guide the output of these models, thus generating content that is aligned with the specific needs of educators and learners.
Empirical evaluation of our system indicates promising results. User feedback reveals a high acceptance rate, with approximately 84% of participants expressing satisfaction. Moreover, 82% of users verified the accuracy of the generated content, and 83% indicated their willingness to integrate this content into their teaching practices.
This research also aims to explore further the potential of automated content creation in enhancing networked learning environments. Our focus will be on expanding the applicability of this technology and investigating its impact on the broader educational ecosystem.