NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 17 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Kitto, Kirsty; Hicks, Ben; Shum, Simon Buckingham – British Journal of Educational Technology, 2023
An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results…
Descriptors: Causal Models, Learning Analytics, Educational Theories, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Nguyen, Viet Anh; Nguyen, Hoa-Huy; Nguyen, Duc-Loc; Le, Minh-Duc – Education and Information Technologies, 2021
How to choose the most appropriate courses to study throughout the learning process remains a question interested in by many students. Students often choose suitable courses according to their interests, needs, and advice from supporting staff, etc. This paper presents the results in developing a course recommendation system that will select…
Descriptors: Course Selection (Students), Majors (Students), Learning Analytics, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Witzenberger, Kevin; Gulson, Kalervo N. – Learning, Media and Technology, 2021
Pre-emption describes a system of automated knowledge creation and intervention that steers the present towards a desirable future, by building on knowledge derived from the past. Folding together temporalities makes it impossible to disprove pre-emption. It is increasingly featured within EdTech, introducing new forms of automated governance into…
Descriptors: Educational Technology, Technology Uses in Education, Governance, Learning Analytics
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Khor, Ean Teng; Dave, Darshan – International Review of Research in Open and Distributed Learning, 2022
The COVID-19 pandemic induced a digital transformation of education and inspired both instructors and learners to adopt and leverage technology for learning. This led to online learning becoming an important component of the new normal, with home-based virtual learning an essential aspect for learners on various levels. This, in turn, has caused…
Descriptors: Learning Analytics, Social Networks, Network Analysis, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
Peer reviewed Peer reviewed
Direct linkDirect link
Mavroudi, Anna; Papadakis, Spyros; Ioannou, Ioannis – TechTrends: Linking Research and Practice to Improve Learning, 2021
The article is focusing on aspects related to technology acceptance of LA in the context of school education. A survey that was based on the Technology Acceptance Model was distributed to 98 participants who work as schoolteachers and/or local educational policymakers and are geographically dispersed across two different European countries. The…
Descriptors: Teacher Attitudes, Learning Analytics, Intention, Usability
Peer reviewed Peer reviewed
Direct linkDirect link
Gillani, Nabeel; Eynon, Rebecca; Chiabaut, Catherine; Finkel, Kelsey – Educational Technology & Society, 2023
Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations--many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Educational Benefits
Peer reviewed Peer reviewed
Direct linkDirect link
Cogliano, MeganClaire; Bernacki, Matthew L.; Hilpert, Jonathan C.; Strong, Christy L. – Journal of Educational Psychology, 2022
We investigated the effects of a learning analytics-driven prediction modeling platform and a brief digital self-regulated learning skill training program targeted to support undergraduate biology students identified as likely to perform poorly in the course. A prediction model comprising prior knowledge scores and learning management system log…
Descriptors: Learning Analytics, College Science, Undergraduate Students, Biology
Peer reviewed Peer reviewed
Direct linkDirect link
Korkmaz, Ceren; Correia, Ana-Paula – Educational Media International, 2019
The purpose of this review is to investigate the trends in the body of research on machine learning in educational technologies, published between 2007 and 2017. The criteria for article selection were as follows: (1) study on machine learning in educational/learning technologies, (2) published between 2007-2017, (3) published in a peer-reviewed…
Descriptors: Electronic Learning, Educational Technology, Educational Trends, Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Ding, Xinyi; Larson, Eric C.; Doyle, Amanda; Donahoo, Kevin; Rajgopal, Radhika; Bing, Eric – Interactive Learning Environments, 2021
In this paper, we develop a context-aware, tablet-based learning module for adult education. Specifically, we focus on adult education in healthcare-teaching learners to perform a medical screening procedure. Based upon how learners navigate through the learning module (e.g. swipe-speed and click duration, among others), we use machine learning to…
Descriptors: Handheld Devices, Educational Technology, Navigation (Information Systems), Learning Modules
Peer reviewed Peer reviewed
Direct linkDirect link
De Jesús Liriano, Rubén; Sevillano, María C. – Distance Learning, 2019
In recent years, the academic industry has seen a widespread development of digital technology and learning analytics. Certainly, the exchange of automatic processing has opened a broad set of new ways and opportunities, allowing additional emphasis on interaction and connectivity. This new learning approach provides improvement in the development…
Descriptors: Learning Processes, Higher Education, Learning Analytics, Educational Technology
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pigeau, Antoine; Aubert, Olivier; Prié, Yannick – International Educational Data Mining Society, 2019
Success prediction in Massive Open Online Courses (MOOCs) is now tackled in numerous works, but still needs new case studies to compare the solutions proposed. We study here a specific dataset from a French MOOC provided by the OpenClassrooms company, featuring 12 courses. We exploit various features present in the literature and test several…
Descriptors: Success, Large Group Instruction, Online Courses, Prediction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Sense, Florian; van der Velde, Maarten; van Rijn, Hedderik – Journal of Learning Analytics, 2021
Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are…
Descriptors: Predictor Variables, Undergraduate Students, Learning Analytics, Cognitive Psychology
Peer reviewed Peer reviewed
Direct linkDirect link
Er, Erkan; Gómez-Sánchez, Eduardo; Dimitriadis, Yannis; Bote-Lorenzo, Miguel L.; Asensio-Pérez, Juan I.; Álvarez-Álvarez, Susana – Interactive Learning Environments, 2019
This paper presents the findings of a mixed-methods research that explored the potentials emerging from aligning learning design (LD) and learning analytics (LA) during the design of a predictive analytics solution and from involving the instructors in the design process. The context was a past massive open online course, where the learner data…
Descriptors: Alignment (Education), Learning Analytics, Instructional Design, Teacher Participation
Previous Page | Next Page »
Pages: 1  |  2