The modern world is awash in data, greatly amplifying the necessity of statistics education. Introductory statistics courses are often both large and populated by students from a diverse array of backgrounds. Tailoring what is said to these students with an awareness of their interests and goals and an understanding of their background and progress can substantially improve their learning experience. This is true for all students - from those likely to struggle to those who most easily master the material.
For this project, learning analytics techniques are being used to drive personalized instruction for each of the 1400 students who take Stats 250 each term at the University of Michigan. A detailed portrait of the student's background, interests and goals is being created as well as a real-time state of each student's academic progress by collating the rich array of data captured from student work in the LectureTools active learning environment. Given these portraits, the E2Coach system is using computer tailored communication technology to individually address each student and enabling interaction with the student as if they sat down with the instructional team for the course for an expert coaching session.
