Investigation of Learning Analytics and Data Visualization Techniques (306581)Urvashi Desai, Miami University
*Vijayalakshmi Ramasamy, Miami University
Keywords: Educational data mining, learning analytics, LMS, visualization
Learning Analytics(LA) analyzes multi-faceted digital data to understand, optimize and augment learning in educational environments using intelligent algorithms. Educational Data Mining(EDM) relates to developing and applying algorithms to detect patterns in large collections of educational data. Combining LA and EDM enable developing efficient statistical models, data mining techniques to bridge the gap between descriptive and predictive analyses. Many Learning Management Systems (LMS) support eLearning upon which online courses and training modules are built. Efficient tools are needed to analyze student data across different platforms and usage statistics. This study helps unravel hidden and interesting patterns of students' behaviors, address challenges in data collection from diverse sources, represent data using schema-based architecture, analyze and visualize LMSs. Other implications include using tools to study ways women learn, obtain insights into LMSs usage worldwide, analyze popularity and reasons for trending LMSs in specific regions. The empirical analysis yields many benefits of improved course quality, retention, performance, student engagement, and belongingness.