This systematic literature review aims to identify the recent research trend, most studied
factors, and methods used to predict student academic performance from 2015 to 2021. The …

This bibliometric study on data mining in education synonymous with big educational data
utilizes VOSviewer and Harzing's Publish and Perish to analyze the metadata of 1,439 …

The multi-modal and unstructured nature of observational data in Electronic Health Records
(EHR) is currently a significant obstacle for the application of machine learning towards risk …

Educational Design and Evaluation Models are important factors in e-learning as they
provide guidance information for proper strategy organization pursuing both specific …

In this full review paper, the recent emerging trends in Educational Data Science have been
reviewed and explored to address the recent topics and contributions in the era of Smart …

From the perspective of computer-supported learning, the temporal tracking and early
warning plays an important role, and it is also an effective means to improve learning …

A proposal is presented for the adaptation of activities that have an impact on the
performance of students in common programming courses in engineering careers at the …

Learning analytics research has highlighted that contexts matter for predictive models, but
little research has explicated how contexts matter for models' utility. Such insights are critical …

The current pandemic has significantly impacted educational practices, modifying many
aspects of how and when we learn. In particular, remote learning and the use of digital …

Problem-solving approaches are an essential part of learning. Knowing how students
approach solving problems can help instructors improve their instructional designs and …