Education is increasingly occurring online or in educational software, resulting in an explosion of data that can be used to improve educational effectiveness and support basic research on learning. In this course, you will learn how and when to use key methods for educational data mining and learning analytics on this data.
If you're not famiar with data mining, I would recommend to take Machine Learning with A.Ng first. Prof. Baker speaks fast and in "bullet points", constantly adding that he will talk "about it later". RapidMiner is the data mining tool used for this class. Allocate an extra time for understanding the concept and exploring the tool. Forum posts are very helpful though, and I've learned interesting facts from the "Predicting College Enrollment from Student Interaction with an Intelligent Tutoring System in Middle School" case study example. Gaming the system may have negative effect on learning, and students' carelessness is not a good indicator of actual skills. http://www.columbia.edu/~rsb2162/EDM2013_SBBH.pdf