Featured Application The herein survey is among the first research efforts to synthesize the
intelligent models and paradigms applied in education to predict the attainment of student …

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 …

Student retention is an essential measurement metric in education, indicated by retention
rates, which are accumulated as students re-enroll from one academic year to the next. High …

Predicting students' performance in advance could help assist the learning process; if “at-
risk” students can be identified early on, educators can provide them with the necessary …

Prediction models that underlie “early warning systems” need improvement. Some predict
outcomes using entrenched, unchangeable characteristics (eg, socioeconomic status) and …

Educational institutions need to formulate a well-established data-driven plan to get long-
term value from their learning analytics (LA) strategy. By tracking learners' digital traces and …

The educational research is increasingly emphasizing the potential of student engagement
and its impact on performance, retention and persistence. This construct has emerged as an …

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 …

Artificial intelligence (AI) has been develo**, and its application is spreading at a good
pace in recent years, so much so that AI has become part of everyday life in various sectors …

School closures during the COVID-19 pandemic presented a threat to student learning and
motivation. Suspension of achievement testing created a barrier to understanding the extent …