Intelligent Recommendation of Content for Enhancing User Experience in E-learning Systems for Sri Lanka

Abstract

E-learning systems are used to increase the educational back- ground of students. E-learning systems are very popular nowa days which is important to monitor and evaluate student per- formance by delivering interactive content and personalized learning targeting student learning. This research highlights various data mining algorithms that can be used to identify user interactions, trends, and patterns to recommend per- sonalized content for E-learning systems. The content can be changed through translations and summarizations across different media to maintain high student interest. Personal- ized learning increases the student’s satisfaction by increas- ing the student’s behavior toward learning. Then, this re- search aims to provide personalized learning content using a weightage (value-based) mechanism. Finally, this research proposes a model that could help to create an intelligent E- learning system using the mechanism. Then, it can be used to generate personalized content recommendations accord- ing to user performance ratings that help to recommend the content output. This is aimed at improving student engage- ment and user experience towards the content. As a result of developing this system, a 73.99% accuracy value was gen- Abbreviations: E-learning, Electronic learning. *Equally contributing authors. erated in initial training and a 63.16% accuracy value was generated in initial testing. Then, an 85.58% accuracy value was given after retraining the model, and a 78.90% accu- racy value was given after retesting the model. Further, the content of the E-learning will be arranged according to the SCORM standard.