For a start, universities can use the data to generate predictions of students’ performance, which are then fed into early alert systems with other information such as the students’ current semester study load and their previous semesters’ cumulative grade point average. These can, in turn, provide information for faculty members to formulate intervention strategies to support individual students in their learning. For example, students who are expected to perform well in the semester can be further encouraged to not only achieve their potential but to surpass it. On the other hand, students who are expected not to perform as well can be advised to adopt good study habits and strategies and seek help early when they experience difficulties in their learning. These can contribute towards a positive learning experience and supportive learning environment.