Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective

Learning analytics is receiving increased attention, in part because it offers to assist educational institutions in increasing student retention, improving student success, and easing the burden of accountability. Although these large-scale issues are worthy of consideration, faculty might also be interested in how they can use learning analytics in their own courses to help their students succeed. In this paper, we define learning analytics, how it has been used in educational institutions, what learning analytics tools are available, and how faculty can make use of data in their courses to monitor and predict student performance. Finally, we discuss several issues and concerns with the use of learning analytics in higher education. Have you ever had the sense at the start of a new course or even weeks into the semester that you could predict which students will drop the course or which students will succeed? Of course, the danger of this realization is that it may create a self-fulfilling prophecy or possibly be considered “profiling”. But it could also be that you have valuable data in your head, collected from semesters of experience, that can help you predict who will succeed and who will not based on certain variables. In short, you likely have hunches based on an accumulation of experience