Learning Management Systems (LMS) are software applications that facilitate the management and monitoring of online teaching courses and/or training programs, workshops, webinars, forums, and other similar learning activities. The LMS provides learning and teaching benefits and possibilities for synchronous, asynchronous, and hybrid training. For…

Predicting academic performance using trace data from learning management systems is a primary research topic in educational data mining. An important application is the identification of students at risk of failing the course or dropping out. However, most approaches utilise past grades, which are not always available and capture little of the…

With the increased emphasis on the benefits of self-regulated learning (SRL), it is important to make use of the huge amounts of educational data generated from online learning environments to identify the appropriate educational data mining (EDM) techniques that can help explore and understand online learners' behavioral patterns. Understanding…

Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…

Big Data Technology (BDT) and Analytics have gained immense recognition in recent years. BDT plays an essential role in various sectors. This study intends to provide a review of BDT in the education sector which includes analyzing, predicting learner's results based on behavior patterns, assessing their performance regularly. Education…

Nowadays many companies and institutions are interested in learning what do people think and want. Many studies are conducted to answer these questions. That's why, emotions of people are significant in terms of instructional design. However, processing and analysis of many people's ideas and emotions is a challenging task. That is where the…

Process mining methodologies are designed to uncover underlying business processes, deviations from them, and in general, usage patterns. One of the key limitations of these methodologies is that they struggle in cases in which there is no structured process, or when a process can be performed in many ways. Learning Management Systems are a…

Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…

Educators in higher education institutes often use statistical results obtained from their online Learning Management System (LMS) dataset, which has limitations, to evaluate student academic performance. This study differs from the current body of literature by including an additional dataset that advances the knowledge about factors affecting…

Content assessment has broadly improved in e-learning scenarios in recent decades. However, the e-Learning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only content, but also students' acquisition of core skills such as self-regulated learning. Our objective was to discover students'…

The premise for this study was that learner interaction in an online web-based course could be assessed in relation to academic performance, or in other words, e-learning. Although some studies reveal that learner interaction with online content is related to student academic performance, it remains unproven whether this is casual, or even if…

With the development of online learning, LMSs accumulated huge amounts of students' interaction data. Unfortunately, with the support of LMSs data, few researchers put a sight on interaction research in MPOCs. Particularly, comparing interaction activity patterns of different achievement student groups and in different course processes in MPOCs…

Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…

This research connects several data-driven educational data mining approaches to a framework for interaction developed in educational research. In particular, 10 million usage data points collected by a Learning Management System used by students and teachers in 450 online undergraduate courses were analyzed with this framework. A range of…

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather…