Publication Date
| In 2026 | 0 |
| Since 2025 | 18 |
| Since 2022 (last 5 years) | 42 |
| Since 2017 (last 10 years) | 42 |
| Since 2007 (last 20 years) | 42 |
Descriptor
Source
Author
| Dragan Gaševic | 2 |
| Roberto Martinez-Maldonado | 2 |
| Abdelali Zakrani | 1 |
| Abdellah Bennane | 1 |
| Abdullah Saykili | 1 |
| Ahmad Faza | 1 |
| Akwasi Adomako Boakye | 1 |
| Alejandro Ortega-Arranz | 1 |
| Aleksandr Malkin | 1 |
| Ali Alshammari | 1 |
| Alina Hase | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 38 |
| Reports - Research | 34 |
| Information Analyses | 4 |
| Reports - Descriptive | 2 |
| Speeches/Meeting Papers | 2 |
| Books | 1 |
| Collected Works - Proceedings | 1 |
| Dissertations/Theses -… | 1 |
| Reports - Evaluative | 1 |
Education Level
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Abdullah Saykili; Sinan Aydin; Yusuf Zafer Can Ugurhan; Aylin Öztürk; Mustafa Kemal Birgin – Technology, Knowledge and Learning, 2025
Learning analytics offer unprecedented opportunities for tracking and storing learning behaviors, thereby providing chances for optimizing learner engagement and success. The limited adoption of learning analytics by educational institutions hinders efforts to optimize learning processes through organizational and educational interventions,…
Descriptors: Undergraduate Students, Online Courses, Learning Analytics, Student Characteristics
Kyle M.L. Jones; Lisa Janicke Hinchliffe – College & Research Libraries, 2025
As institutions of higher education further develop their learning analytics efforts, academic library practitioners are called upon to participate in these efforts and have opportunities to shape their campus strategies. Nonetheless, library practitioners may not be prepared with the knowledge, skills, and strategies to engage with campus…
Descriptors: Academic Libraries, Librarians, Privacy, Learning Analytics
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
Peer reviewedEduardo Davalos; Namrata Srivastava; Yike Zhang; Amanda Goodwin; Gautam Biswas – Grantee Submission, 2024
As online learning tools become more widespread, understanding student behaviors through learning analytics is increasingly important. Traditional methods relying on system log data fall short of capturing the full range of cognitive strategies students use. To address this, we developed an in-depth post-assignment reflection dashboard that…
Descriptors: Visualization, Eye Movements, Electronic Learning, 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
Jeongwon Lee; Dongho Kim – Journal of Computing in Higher Education, 2025
Although learning analytics dashboards (LADs) are being recognized as tools that can enhance engagement--a crucial factor for the success of asynchronous online higher education--their impact may be limited without a solid theoretical basis for motivation. Furthermore, the processes through which students make decisions using dashboards and engage…
Descriptors: Self Determination, Learning Analytics, Educational Technology, Learner Engagement
Aylin Ozturk; Robin Schmucker; Tom Mitchell; Alper Tolga Kumtepe – International Educational Data Mining Society, 2025
This study investigates the heterogeneity in the effects of a Learning Analytics Dashboard (LAD) intervention, which provides personalized feedback messages, across a diverse population of learners. Specifically, it evaluates the impact of the LAD on learners' total material usage and final grades, considering variables such as age, sex, prior…
Descriptors: Learning Analytics, Learning Management Systems, Feedback (Response), Grades (Scholastic)
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
Chin-Yuan Lai; Li-Ju Chen – Educational Technology & Society, 2025
Web-based multimedia annotation is a valuable tool for engaging learners with diverse materials. This study aimed to assess the effects of multimedia annotation on student performance, self-regulation, and cognitive load in an online learning environment. We developed and implemented a multimedia annotation system in an online biology class using…
Descriptors: Multimedia Materials, Instructional Effectiveness, Metacognition, Cognitive Ability
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

Direct link
