Different sources of data about students, ranging from static demographics to dynamic
behavior logs, can be harnessed from a variety sources at Higher Education Institutions …

This paper presents a data mining methodology to analyze the careers of University
graduated students. We present different approaches based on clustering and sequential …

Education often involves categorizing students into broad groups based on perceived
attributes like academic abilities, learning pace, and unique challenges. However, the …

Online learning systems allow learners to freely access learning contents and record their
interactions throughout their engagement with the content. By using data mining techniques …

Individual differences have been recognized as an important factor in the learning process.
However, there are few successes in using known dimensions of individual differences in …

The beyond-relevance objectives of recommender systems have been drawing more and
more attention. For example, a diversity-enhanced interface has been shown to associate …

The learning style of a learner is an important parameter in his learning process. Therefore,
learning styles should be considered in the design, development, and implementation of e …

Online programming discussion forums have grown increasingly and formed sizable
repositories of problem-solving solutions. In this paper, we investigate programming …

Educational software data promises unique insights into students' study behaviors and
drivers of success. While much work has been dedicated to performance prediction in …

Students' interactions with online tools can provide us with insights into their study and work
habits. Prior research has shown that these habits, even as simple as the number of actions …