This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…

Early alert systems (EAS) are an important technological tool to help manage and improve student retention. Data spanning 16,091 students over 156 weeks was collected from a regionally based university in Australia to explore various microeconometric approaches that establish links between EAS and student retention outcomes. Controlling for…

One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…

Learning management systems (LMSs) are ubiquitous components of the academic technology experience for learners across a wide variety of instructional contexts. Learners' interactions within an LMS are often contingent upon how instructors architect a module, course, or program of study. Patterns related to these learner interactions, often…

Predictive analytics in higher education has become increasingly popular in recent years with the growing availability of educational big data. Particularly, a wealth of student activity data is available from learning management systems (LMSs) in most academic institutions. However, previous investigations into predictive analytics in higher…

Extensive research in learning science has established the importance of time management in online learning. Recently, learning analytics (LA) has shed further lights on the temporal characteristics of learning by allowing researchers to capture authentic digital footprints of student learning behaviours. Nonetheless, students' timing of…

The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper…

The first requirement for an online mathematics homework engine is to encourage students to practice and reinforce their mathematics skills in ways that are as good or better than traditional paper homework. The use of the computer and the internet should not limit the kind or quality of the mathematics that we teach and, if possible, it should…

Educational data science (EDS) is an emerging, interdisciplinary research domain that seeks to improve educational assessment, teaching, and student learning through data analytics. Teachers have been portrayed in the EDS literature as users of pre-constructed data dashboards in educational technologies, with little consideration given to them as…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…

This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…

Online environments can cultivate what have been referred to as 21st century skills and capabilities, as youth contribute, pursue, share, and interact around work and ideas. Such environments also hold great potential for addressing digital divides related to the development of such skills by connecting youth in areas with fewer resources and…

As enrolment in online courses has grown and LMS data has become accessible for analysis, researchers have begun to examine the link between in-course behaviours and course outcomes. This paper explores the use of readily available LMS data generated by approximately 700 students enrolled in the 12 online courses offered by Pamoja Education, the…

With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data--commonly known as trace data--are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities--typically referred to as time-on-task. These measures…

This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…