Knowledge Discovery in Virtual Education: A Learning Analytics Approach
TL;DR
The research findings show that learning analytics is useful to enhance the quality of education, learner engagement, and informed decision-making in modern online education.
Abstract
This paper explores the application of learning analytics in online educational environments to derive actionable insights from student-teacher interactions and digital learning activities. The proposed approach systematically utilizes techniques of data warehousing and data mining to collect, organize, process and analyze educational data generated by virtual learning systems. The approach proposed captures meaningful behavior patterns, interaction trends and learning outcomes that can support evidence-based pedagogical decisions. Through analysing student engagement, participation, assessment performance and tutoring, the approach reveals hidden relationships and predicts performance. This information helps teachers recognize students who require more help, adjust their law instruction, and boost online teaching. The case study of a virtual learning environment and the application of learning analytics is used to demonstrate the method and to understand the complexities of learning in a virtual context. The research findings show that learning analytics is useful to enhance the quality of education, learner engagement, and informed decision-making in modern online education.