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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
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
Koç, Ebru Melek – International Review of Research in Open and Distributed Learning, 2016
The aim of the present study was to explore what types of difficulties student teachers enrolled in a Bachelor of Arts (B.A.) in English Language Teacher Education program offered in a blended format and their cooperating teachers encountered during the student teacher practicum. The participants were 21 fourth grade student teachers and 12…
Descriptors: Blended Learning, English Instruction, Language Teachers, Preservice Teacher Education
Veletsianos, George; Shepherdson, Peter – International Review of Research in Open and Distributed Learning, 2016
A deluge of empirical research became available on MOOCs in 2013-2015 and this research is available in disparate sources. This paper addresses a number of gaps in the scholarly understanding of MOOCs and presents a comprehensive picture of the literature by examining the geographic distribution, publication outlets, citations, data collection and…
Descriptors: Literature Reviews, Educational Technology, Online Courses, Large Group Instruction
Sarrab, Mohamed; Al Shibli, Ibtisam; Badursha, Nabeela – International Review of Research in Open and Distributed Learning, 2016
Mobile learning (M-learning) provides a new learning channel in which learners can access content and just in time information as required irrespective of the time and location. Even though M-learning is fast evolving in many regions of the world, research addressing the driving factors of M-learning adoption is in short supply. This article…
Descriptors: Foreign Countries, Electronic Learning, Adoption (Ideas), Higher Education
Luo, Tian; Murray, Alexander; Crompton, Helen – International Review of Research in Open and Distributed Learning, 2017
Online learning is increasingly being used in K-12 learning environments. A concomitant trend is found towards learning becoming "authentic" as students learn with tasks that are connected to real world occupations. In this study, 48 pre-service teachers use an online environment to engage in authentic practice as they developed online…
Descriptors: Instructional Design, Learning Activities, Preservice Teachers, Preservice Teacher Education
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