This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

As students in online courses usually show differences in their cognitive levels and lack communication with teachers, it is difficult for teachers to grasp student perceptions of the importance of knowledgepoints and to develop personalized teaching. Though recent studies have paid attention to this topic, existing methods fail to calculate the…

This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…

Online education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as…

Online education helped resume learning that had come to a momentary and uncertain pause with the onset of COVID-19 pandemic across the globe. Since then, learning in many educational institutions continued through synchronous and asynchronous modes, with teaching being undertaken remotely on digital platforms. In this large-scale migration…

The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…

The use of learning management systems (LMSs) for learning and knowledge sharing has accelerated quickly both in education and corporate worlds. Despite the benefits brought by LMSs, the current systems still face significant challenges, including the lack of automation in generating quiz questions and managing courses. Over the past decade, more…

The purpose of this paper is to present a specific case of CALL task design adopting the patterns-based learning design approach. The approach provides a common framework/vocabulary for educational designers, particularly teachers, to systematically capture, articulate, make explicit, share and reuse expert knowledge of teaching and good design.…

In this article, Susan Haarman discusses the ways in which datafication technologies such as Big Data and algorithms have the potential to either challenge or exacerbate what Miranda Fricker calls epistemic injustice. She briefly defines epistemic injustice using Fricker's subsets of testimonial and hermeneutical injustice before moving to the…

During the COVID-19 pandemic, an adult noncredit program in the California Community College system partnered with Ease Learning to help convert face-to-face courses to an online modality. Subsequent data revealed a misalignment in the courses' Student Learning Outcomes and Instructional Objectives which became a barrier to student success. Wile's…

Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing…