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Safa Ridha Albo Abdullah; Ahmed Al-Azawei – International Review of Research in Open and Distributed Learning, 2025
This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…
Descriptors: Electronic Learning, Academic Achievement, Grade Prediction, Data Analysis
Hwang, Gwo-Jen; Tu, Yun-Fang; Tang, Kai-Yu – International Review of Research in Open and Distributed Learning, 2022
This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI)…
Descriptors: Artificial Intelligence, Electronic Learning, Educational Research, Data Analysis
Araka, Eric; Oboko, Robert; Maina, Elizaphan; Gitonga, Rhoda – International Review of Research in Open and Distributed Learning, 2022
With the increased emphasis on the benefits of self-regulated learning (SRL), it is important to make use of the huge amounts of educational data generated from online learning environments to identify the appropriate educational data mining (EDM) techniques that can help explore and understand online learners' behavioral patterns. Understanding…
Descriptors: Data Analysis, Metacognition, Comparative Analysis, Behavior Patterns
van den Beemt, Antoine; Buys, Joos; van der Aalst, Wil – International Review of Research in Open and Distributed Learning, 2018
The increasing use of digital systems to support learning leads to a growth in data regarding both learning processes and related contexts. Learning Analytics offers critical insights from these data, through an innovative combination of tools and techniques. In this paper, we explore students' activities in a MOOC from the perspective of personal…
Descriptors: Online Courses, Student Behavior, Behavior Patterns, Academic Achievement
Yildiz, Gizem; Yildirim, Abdurrahman; Akça, Bedreddin Ali; Kök, Ayse; Özer, Açelya; Karatas, Serçin – International Review of Research in Open and Distributed Learning, 2020
A total of 1023 selected articles published in 2016-2019 related to mobile learning were examined and classified according to the categories in this research: 40% of these articles used quantitative approaches, 18% of them used mixed, and 13% of them were literature reviews. The published studies were analyzed according to research model, sample…
Descriptors: Educational Trends, Educational Research, Electronic Learning, Handheld Devices
Lundqvist, Karsten Ø.; Liyanagunawardena, Tharindu; Starkey, Louise – International Review of Research in Open and Distributed Learning, 2020
Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the use of automated sentiment analysis in assessing…
Descriptors: Feedback (Response), Online Courses, Student Experience, Peer Relationship
Sun, Jerry Chih-Yuan; Lin, Che-Tsun; Chou, Chien – International Review of Research in Open and Distributed Learning, 2018
This study aims to apply a sequential analysis to explore the effect of learning motivation on online reading behavioral patterns. The study's participants consisted of 160 graduate students who were classified into three group types: low reading duration with low motivation, low reading duration with high motivation, and high reading duration…
Descriptors: Student Motivation, Student Behavior, Reading, Behavior Patterns
Chatti, Mohamed Amine; Muslim, Arham – International Review of Research in Open and Distributed Learning, 2019
Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…
Descriptors: Guidelines, Data Analysis, Learning Experience, Metacognition
Shea, Peter; Bidjerano, Temi – International Review of Research in Open and Distributed Learning, 2018
Recent research indicates that certain students are at risk of lower levels of academic performance in online settings when compared to peers who study only in the classroom. Community college students have been a population of particular concern. In this paper, we hypothesize that online course load and institutional quality may impact outcomes…
Descriptors: Online Courses, Enrollment, Community Colleges, Graduation
Hew, Khe Foon; Qiao, Chen; Tang, Ying – International Review of Research in Open and Distributed Learning, 2018
Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884…
Descriptors: Learner Engagement, Large Group Instruction, Online Courses, Man Machine Systems
Bodily, Robert; Nyland, Rob; Wiley, David – International Review of Research in Open and Distributed Learning, 2017
The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the…
Descriptors: Open Source Technology, Educational Resources, Educational Improvement, Data Analysis
Prasad, Deepak; Totaram, Rajneel; Usagawa, Tsuyoshi – International Review of Research in Open and Distributed Learning, 2016
Textbook costs have skyrocketed in recent years, putting them beyond the reach of many students, but there are options which can mitigate this problem. Open textbooks, an open educational resource, have proven capable of making textbooks affordable to students. There have been few educational development as promising as the development of open…
Descriptors: Textbooks, Shared Resources and Services, Data Collection, Data Analysis
Rienties, Bart; Herodotou, Christothea; Olney, Tom; Schencks, Mat; Boroowa, Avi – International Review of Research in Open and Distributed Learning, 2018
The importance of teachers in online learning is widely acknowledged to effectively support and stimulate learners. With the increasing availability of learning analytics data, online teachers might be able to use learning analytics dashboards to facilitate learners with different learning needs. However, deployment of learning analytics…
Descriptors: Teacher Attitudes, Technology Integration, Online Courses, Data Analysis
Amigud, Alexander; Arnedo-Moreno, Joan; Daradoumis, Thanasis; Guerrero-Roldan, Ana-Elena – International Review of Research in Open and Distributed Learning, 2017
This paper presents the results of integrating learning analytics into the assessment process to enhance academic integrity in the e-learning environment. The goal of this research is to evaluate the computational-based approach to academic integrity. The machine-learning based framework learns students' patterns of language use from data,…
Descriptors: Data Collection, Data Analysis, Integrity, Electronic Learning
Fynn, Angelo – International Review of Research in Open and Distributed Learning, 2016
The prediction and classification of student performance has always been a central concern within higher education institutions. It is therefore natural for higher education institutions to harvest and analyse student data to inform decisions on education provision in resource constrained South African environments. One of the drivers for the use…
Descriptors: Academic Achievement, Higher Education, Foreign Countries, Data Collection
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