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…

Massive online Open Courses (MOOCs) make extensive use of videos. Students interact with them by pausing, seeking forward or backward, replaying segments, etc. We can reasonably assume that students have different patterns of video interactions, but it remains hard to compare student video interactions. Some methods were developed, such as Markov…

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…

Recommender systems in educational contexts have proven to be effective in identifying learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In this article, we present the design of a hybrid…

In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…

Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…

For decades, self-report instruments -- which rely heavily on students' perceptions and beliefs -- have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to…

Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…

Since MOOC is suffering high dropout rate, researchers try to explore the reasons and mitigate it. Focusing on this task, we employ a composite model to infer behaviors of learners in the coming weeks based on his/her history log of learning activities, including interaction with video lectures, participation in discussion forum, and performance…

This paper reports on the evaluation of an ambitious attempt to embed academic literacy support within a core content course for first-year students at the University of the South Pacific. The course is offered in both blended and online modes, catering for on-campus and off-campus students, respectively, using Moodle as the virtual learning…

The focus of this study was to answer the following overarching question: How does a Twitter discussion format compare to a Facebook discussion format in terms of promoting collaborative argumentative discourse? Data analysis focused on the difference in amount of arguments, counter-arguments, reasons, and elaborations generated by participants…

This study compared the characteristics of students who excel (those in the top quarter of their class) and students who merely survive (bottom quarter of class) when attending a course either in-class or online. Student characteristics such as personal attributes (learning styles and gender), individual competence (grade point average), and major…