Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…

Predicting and improving the academic achievement of university students is a multifactorial problem. Considering the low success rates and high dropout rates, particularly in open education programs characterized by mass enrollment, academic success is an important research area with its causes and consequences. This study aimed to solve a…

Educational disparities between traditional and non-traditional student groups in higher distance education can potentially be reduced by alleviating social identity threat and strengthening students' sense of belonging in the academic context. We present a use case of how Learning Analytics and Machine Learning can be applied to develop and…

In open and higher education, digital technologies are increasingly used to enable flexible learning pathways and unbundle programs into separate courses. Whereas technologies have been praised for enhancing the flexibility of curricula, the implications of going digital have yet to be fully explored in curriculum studies. This article aims to…

The authors are conducting a study of instructors teaching data structure and algorithm topics, with a focus on the use of diagrams and tracing. The results of this study are being used to inform the design of the Support Kit for Animation (SKA). This article describes a preliminary version of SKA, and possible usage scenarios. (Author/AEF)