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Giora Alexandron; Aviram Berg; Jose A. Ruiperez-Valiente – IEEE Transactions on Learning Technologies, 2024
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…
Descriptors: Cheating, Identification, Online Courses, Artificial Intelligence
Yuan Liu; Yongquan Dong; Chan Yin; Cheng Chen; Rui Jia – Education and Information Technologies, 2024
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…
Descriptors: MOOCs, Online Courses, Models, Course Selection (Students)
Oleksandra Poquet; Sven Trenholm; Marc Santolini – Educational Technology Research and Development, 2024
Interpersonal online interactions are key to digital learning pedagogies and student experiences. Researchers use learner log and text data collected by technologies that mediate learner interactions online to provide indicators about interpersonal interactions. However, analytical approaches used to derive these indicators face conceptual,…
Descriptors: Computer Mediated Communication, Interpersonal Communication, Online Courses, Discussion
Ozan Rasit Yürüm; Tugba Taskaya-Temizel; Soner Yildirim – Technology, Knowledge and Learning, 2024
The purpose of this study was to investigate the use of predictive video analytics in online courses in the literature. A systematic literature review was performed based on a hybrid search strategy that included both database searching and backward snowballing. In total, 77 related publications published between 2011 and April 2023 were…
Descriptors: Literature Reviews, Distance Education, Online Courses, Video Technology
Nuo Cheng; Wei Zhao; Xiaoqing Xu; Hongxia Liu; Jinhong Tao – Education and Information Technologies, 2024
Learning analytics dashboards are becoming increasingly common tools for providing feedback to learners. However, there is limited empirical evidence regarding the effects of learning analytics dashboard design features on learners' cognitive load, particularly in digital learning environments. To address this gap, we developed goal-based,…
Descriptors: Learning Analytics, Learning Management Systems, Cognitive Ability, Online Courses
Juan Antonio Martinez-Carrascal; Jorge Munoz-Gama; Teresa Sancho-Vinuesa – IEEE Transactions on Learning Technologies, 2024
Academic institutions dedicate a substantial effort to ensure the academic success of their students. At the course level, teachers recommend learning paths (RLPs) for students to guarantee the achievement of their learning outcomes. In terms of performance, these kinds of approaches are deemed more effective than others based uniquely on…
Descriptors: Online Courses, Mathematics Instruction, Undergraduate Students, Mathematics Achievement
Hui Han; Silvana Trimi – Education and Information Technologies, 2024
Cloud computing-based online education has played a vital role in enabling uninterrupted learning during crises such as the COVID-19 pandemic. This study explored the key variables associated with cloud computing that can effectively support the operation of online education platforms. By analyzing real data from 63 online learning platforms, the…
Descriptors: Computer Software, Learning Management Systems, Online Courses, Correlation
Using Analytics to Predict Students' Interactions with Learning Management Systems in Online Courses
Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
Sonja Kleter; Uwe Matzat; Rianne Conijn – IEEE Transactions on Learning Technologies, 2024
Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…
Descriptors: Prediction, Models, Academic Achievement, Learning Analytics
Mohammad Khalil; Paraskevi Topali; Alejandro Ortega-Arranz; Erkan Er; Gökhan Akçapinar; Gleb Belokrys – Technology, Knowledge and Learning, 2024
The use of videos in teaching has gained impetus in recent years, especially after the increased attention towards remote learning. Understanding students' video-related behaviour through learning (and video) analytics can offer instructors significant potential to intervene and enhance course designs. Previous studies explored students' video…
Descriptors: Foreign Countries, MOOCs, Distance Education, Online Courses
Mustafa Tepgec; Joana Heil; Dirk Ifenthaler – Assessment & Evaluation in Higher Education, 2025
Despite the widespread implementation of learning analytics (LA)-based feedback systems, there exists a gap in empirical investigations regarding their influence on learning outcomes. Moreover, existing research primarily focuses on individual differences, such as self-regulation and motivation, overlooking the potential of feedback literacy (FL).…
Descriptors: Feedback (Response), Learning Analytics, Outcomes of Education, Transfer of Training
Amy L. Jones – ProQuest LLC, 2024
In this study, I identified, implemented, and evaluated an appropriate solution set to improve the quality of asynchronous online training (i.e., eLearning) project intake at a research site in a government agency. The current project intake mechanism left eLearning production teams without sufficient information to move forward with educational…
Descriptors: Electronic Learning, Public Agencies, Online Courses, Asynchronous Communication
Yawen Yu; Yang Tao; Gaowei Chen; Can Sun – Journal of Computer Assisted Learning, 2024
Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning…
Descriptors: Learning Analytics, College Students, Epistemology, Computer Mediated Communication
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