Data mining has become an important method to explore and track patterns of behavior in various fields of life. E-learning designers always want to match their content to as many learning styles as possible and are eager to explore the learners' choices and behaviors. Unfortunately, up to now, we had to be satisfied with representative samples. But now, data-mining applications and methods can provide us with solid facts about learning patterns of mass numbers of participants, completely monitored by every click of the learner. How is this done and what insights can it provide us? In this session, the speaker will use one case study of an online course attended by 10,000 students a year. The focus will be on methods and techniques to data mine such a course and the information, knowledge, and lessons to be taken from this data in order to understand the learners better and improve the next product.

Learning Objectives - Use the methods and techniques to data mine e-learning patterns and behaviors. Analyze and process the data into instructional insights. Apply data mining as an innovative method to evaluate e-learning courses.