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Mubarak, Ahmed Ali; Ahmed, Salah A. M.; Cao, Han – Interactive Learning Environments, 2023
In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…
Descriptors: MOOCs, Learner Engagement, Performance, Student Behavior
Cohen, Anat – Educational Technology Research and Development, 2017
Persistence in learning processes is perceived as a central value; therefore, dropouts from studies are a prime concern for educators. This study focuses on the quantitative analysis of data accumulated on 362 students in three academic course website log files in the disciplines of mathematics and statistics, in order to examine whether student…
Descriptors: Academic Persistence, Predictor Variables, Dropouts, At Risk Students
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
Epp, Carrie Demmans; Phirangee, Krystle; Hewitt, Jim – Journal of Learning Analytics, 2017
Identifying which online behaviours and interactions are associated with student perceptions of being supported will enable a deeper understanding of how those activities contribute to learning experiences. Student language is one aspect of their interaction in need of greater exploration within discourse-based online learning environments. As a…
Descriptors: Student Behavior, Computer Mediated Communication, Form Classes (Languages), Language Usage
Douglas, Kerrie A.; Bermel, Peter; Alam, Md Monzurul; Madhavan, Krishna – Journal of Learning Analytics, 2016
MOOCs attract a large number of learners with largely unknown diversity in terms of motivation, ability, and goals. To understand more about learners in highly technical engineering MOOCs, this study investigates patterns of learners' (n = 337) behaviour and performance in the Nanophotonic Modelling MOOC, offered through nanoHUB-U. The authors…
Descriptors: Online Courses, Large Group Instruction, Distance Education, Technology Uses in Education
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
Lowes, Susan; Lin, Peiyi; Kinghorn, Brian – Journal of Learning Analytics, 2015
As enrolment in online courses has grown and LMS data has become accessible for analysis, researchers have begun to examine the link between in-course behaviours and course outcomes. This paper explores the use of readily available LMS data generated by approximately 700 students enrolled in the 12 online courses offered by Pamoja Education, the…
Descriptors: Integrated Learning Systems, Student Behavior, Online Courses, Asynchronous Communication
Dunn, Caroline; Shannon, David; McCullough, Brittany; Jenda, Overtoun; Qazi, Mohammed – Journal of Postsecondary Education and Disability, 2018
Careers in the science, technology, engineering, and mathematics (STEM) fields have many benefits, including decent salaries, a strong employment outlook, and high job satisfaction. Unfortunately, workers with disabilities are underrepresented in the STEM fields. This practice brief describes a program designed to support college students with…
Descriptors: STEM Education, Postsecondary Education, Disabilities, College Students
Dart, Evan H.; Radley, Keith C.; Briesch, Amy M.; Furlow, Christopher M.; Cavell, Hannah J.; Briesch, Amy M. – Behavioral Disorders, 2016
Two studies investigated the accuracy of eight different interval-based group observation methods that are commonly used to assess the effects of classwide interventions. In Study 1, a Microsoft Visual Basic program was created to simulate a large set of observational data. Binary data were randomly generated at the student level to represent…
Descriptors: Observation, Intervention, Simulation, Statistical Analysis
Youngs, Bonnie L.; Prakash, Akhil; Nugent, Rebecca – Computer Assisted Language Learning, 2018
Logged tracking data for online courses are generally not available to instructors, students, and course designers and developers, and even if these data were available, most content-oriented instructors do not have the skill set to analyze them. Learning analytics, mined from logged course data and usually presented in the form of learning…
Descriptors: Online Courses, French, Second Language Learning, Second Language Instruction
Kahan, Tali; Soffer, Tal; Nachmias, Rafi – International Review of Research in Open and Distributed Learning, 2017
In recent years there has been a proliferation of massive open online courses (MOOCs), which provide unprecedented opportunities for lifelong learning. Registrants approach these courses with a variety of motivations for participation. Characterizing the different types of participation in MOOCs is fundamental in order to be able to better…
Descriptors: College Students, Student Behavior, Online Courses, Large Group Instruction
Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie – Technology, Knowledge and Learning, 2017
There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…
Descriptors: College Freshmen, Pharmaceutical Education, Individualized Instruction, Data
Lessne, Deborah; Cidade, Melissa; Gerke, Amy; Roland, Karlesha; Sinclair, Michael – National Center for Education Statistics, 2016
Crime and violence in schools continue to be major concerns for educators, policymakers, administrators, parents, and students. This Statistics in Brief presents estimates of student criminal victimization at school by selected student characteristics and school conditions, experiences with being bullied, school security measures, and student…
Descriptors: Crime, Victims, Student Characteristics, Bullying
Wang, Shu-Ming; Hou, Huei-Tse; Wu, Sheng-Yi – Educational Technology Research and Development, 2017
Instructional strategies can be helpful in facilitating students' knowledge construction and developing advanced cognitive skills. In the context of collaborative learning, instructional strategies as scripts can guide learners to engage in more meaningful interaction. Previous studies have been investigated the benefits of different instructional…
Descriptors: Cognitive Processes, Electronic Journals, Student Journals, Web Based Instruction
D'Amico, Mark M.; Morgan, Grant B.; Robertson, Shun; Houchins, Carlie – Journal of Continuing Higher Education, 2014
Nearly 40% of all public community college enrollment is in noncredit courses. While there have been several recent reports on the noncredit function at community colleges, little has been done in terms of large-scale studies and/or statewide analyses on this population. The purpose of this study was to explore one state's community college…
Descriptors: Noncredit Courses, Community Colleges, Enrollment Trends, State Surveys