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…

The widespread adoption of digital e-learning environments and other learning technology has provided researchers with ready access to large quantities of data. Much of this data comes from discussion forums and has been studied with analytical methods drawn from social network analysis. However, within this large body of research there exists…

Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…

We introduce a novel approach to visualizing temporal clickstream behaviour in the context of a degree-satisfying online course, "Habitable Worlds," offered through Arizona State University. The current practice for visualizing behaviour within a digital learning environment is to generate plots based on hand-engineered or coded features…

This quantitative, correlational study used learning analytics to examine correlations between predictor variables (student-content, student-instructor, and student-system interactions) and criterion variable (student-student interactions) and to determine if the four predictor variables were significant predictors of grades in graduate students…

This study investigates a possible way to analyze chat data from collaborative learning environments using epistemic network analysis and topic modeling. A 300-topic general topic model built from TASA (Touchstone Applied Science Associates) corpus was used in this study. 300 topic scores for each of the 15,670 utterances in our chat data were…

With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…

Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…

Embedded librarians in online courses provide a wealth of service and information to students. Though students indicate that these services are valuable, the librarians providing embedded services frequently note that these projects are very time consuming. This study examines the provision of a less time-intensive model of embedded librarianship…

This study examined student success, failure, withdrawal, and satisfaction in online public relations courses based on instructor-student interaction, student-student interaction, and instructor presence. Student passing rates, D/F rates, withdrawal rates, and evaluations of instruction were compiled from fifty-one online PR courses run over the…

Purpose: This paper presents a part of our research work that places an emphasis on Tracking Data Analysis and Visualization (TrAVis) tools, a web-based system, designed to enhance online tutoring and learning activities, supported by computer-mediated communication (CMC) tools. TrAVis is particularly dedicated to assist both tutors and students…

Feedback is a crucial form of information for learners. With the availability of new educational technologies, the manner in which feedback is delivered has changed tremendously. Existing research on the learning outcomes of the content and nature of computer mediated feedback is limited and contradictory. "Signals" is an educational data-mining…

Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…

This article reports that several colleges and universities like Purdue University are mining data they have about students to try to improve retention. The institutions analyze years' worth of data on which students did well and which did poorly, and what variables--whether they be SAT scores, financial-aid status, or attendance at the dining…

These proceedings contain the papers of the International Conference e-Learning 2015, which was organised by the International Association for Development of the Information and Society and is part of the Multi Conference on Computer Science and Information Systems (Las Palmas de Gran Canaria, Spain, July 21-24, 2015). The e-Learning 2015…