Educational data mining (EDM) is the application of data mining in the educational field.
EDM is used to classify, analyze, and predict the students' academic performance, and …

As computing becomes a mainstream discipline embedded in the school curriculum and
acts as an enabler for an increasing range of academic disciplines in higher education, the …

The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …

Algorithms and programming are some of the most challenging topics faced by students
during undergraduate programs. Dropout and failure rates in courses involving such topics …

The number of students who decided to study information technology related study
programs is continually increasing. Introductory programming courses represent the most …

Educational researchers have long sought to increase student retention. One stream of
research focusing on this seeks to automatically identify students who are at risk of drop** …

The identification of student struggles has drawn increasing interests from computing
education and learning analytics communities in recent years, considering the high failure …

A number of recent studies in computer science education have explored the value of
various data sources for early prediction of students' overall course performance. These data …

Due to usage of self-reported data which may contain biasness, the existing studies may not
unveil the exact relation between academic grades and app categories such as Video …

A pesar de las ventajas del e-learning, esta modalidad de aprendizaje es proclive a la
deserción. Estudios anteriores mostraron que se pueden aplicar técnicas de aprendizaje …