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Luping Wang; Yun Hao; Shanshan Wang – Discover Education, 2025
In the traditional teaching mode, it is difficult for teachers to have a comprehensive understanding of each student's study, and it is also hard for them to provide targeted guidance and assistance. With the development of data collection and analysis technology, schools and educational institutions can make better use of big data technology to…
Descriptors: College Students, Predictor Variables, Scores, Academic Achievement
Ghasem Salimi; Azadeh Roodsaz; Mehdi Mohammadi; Fahimeh Keshavarzi; Amin Mousavi; Zamzami Zainuddin – International Journal of Information and Learning Technology, 2025
Purpose: The purpose of this paper is to examine how digital literacy influences knowledge sharing and academic performance among graduate students in online learning environments. Design/methodology/approach: Structural equation modeling via AMOS was utilized to test the research hypotheses in this cross-sectional study. Students' digital…
Descriptors: Foreign Countries, Graduate Students, Digital Literacy, Information Dissemination
Michael L. Chrzan; Francis A. Pearman; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2025
The increasing rate of permanent school closures in U.S. public school districts presents unprecedented challenges for administrators and communities alike. This study develops an early-warning indicator model to predict mass closure events -- defined as a district closing at least 10% of its schools -- five years in advance. Leveraging…
Descriptors: Artificial Intelligence, Electronic Learning, School Districts, School Closing
Alvin M. Ramos; Hyunkyung Lee; Romualdo A. Mabuan – International Review of Research in Open and Distributed Learning, 2025
This study investigated the relationship among e-learning readiness, learning engagement, and learning performance of preservice teachers in HyFlex learning environments. To identify the causal relationship, data collected from 776 preservice teachers at four universities in the Philippines were analyzed using structural equation modeling (SEM).…
Descriptors: Blended Learning, Preservice Teachers, Electronic Learning, Readiness
Junxian Shen; Hongfeng Zhang; Jiansong Zheng – Psychology in the Schools, 2024
Online learning is becoming more and more common, so how to maintain learners' online learning engagement is very important. This study aims to explore the impact of future self-continuity on college students' online learning engagement and its underlying mechanism of action. We utilized the Future Self-Continuity Questionnaire, the Learning…
Descriptors: College Students, Learner Engagement, Electronic Learning, Predictor Variables
Anggraini, Merliyani Putri; Cahyono, Bambang Yudi; Anugerahwati, Mirjam; Ivone, Francisca Maria – Education and Information Technologies, 2022
The current research aimed to discover the most frequently used reading strategies of EFL university students across their reading proficiency and personality types and examine the interaction between the predictive factors in using the strategies when reading English online texts. Data were collected using a questionnaire on reading strategies…
Descriptors: Reading Comprehension, Personality Traits, English (Second Language), Second Language Learning
Stacy Nobles – ProQuest LLC, 2022
Ebooks have been eagerly adopted by higher education institutions. Printed text versus ebook preference poses a complex situation for college students. Postsecondary students will continue using this medium in their courses. Research has been lacking to effectively understand what relationships influence the efficacious use of ebooks. There is a…
Descriptors: Electronic Books, Electronic Learning, Community College Students, Technology Uses in Education
Ghai, Akanksha; Tandon, Urvashi – Education and Information Technologies, 2023
The current study investigates the interaction of Gamification, and Instructional Design to enhance the Usability of e-Learning in higher education programs. The study also examines the mediating role of Instructional design. Data were collected from a self-structured questionnaire from the academicians and was analyzed through Structural Equation…
Descriptors: Gamification, Instructional Design, Usability, Electronic Learning
Tiana P. Johnson-Clements; Guy J. Curtis; Joseph Clare – Journal of Academic Ethics, 2025
Concerns over students engaging in various forms of academic misconduct persist, especially with the post-COVID-19 rise in online learning and assessment. Research has demonstrated a clear role of the personality trait psychopathy in cheating, yet little is known about why this relationship exists. Building on the research by Curtis et al.…
Descriptors: Pandemics, COVID-19, Cheating, Electronic Learning
Ayça Fidan; Yasemin Koçak Usluel – Education and Information Technologies, 2024
It is pointed out that one of the main problems of online learning environments is determining whether students engage or not. As engagement is a complex and multifaceted concept, researchers have stated that engagement is effected by many factors (environmental conditions and learner characteristics) and changes according to the context. Among…
Descriptors: Online Courses, Electronic Learning, Metacognition, Emotional Response
Miftah Arifin; Anas Ma'ruf Annizar; Moh. Khusnuridlo; Abd. Halim Soebahar; Agus Yudiawan – Journal of Education and e-Learning Research, 2025
This study examines a level and model for technology acceptability and use in online learning inside universities. The unified theory of UTAUT is used as an analysis tool. An associative quantitative method is used with a sample of 392 students. Data were collected by distributing questionnaires through a specially designed Google Form. The data…
Descriptors: Educational Technology, Electronic Learning, Technology Uses in Education, College Students
Shixin Fang; Yi Lu; Guijun Zhang – Online Learning, 2023
Building and testing a framework of interactive and indirect predictors of student satisfaction would help us understand how to improve student online learning experience. The current study proposed that external predictors such as poor technological, environmental, and pedagogical factors would be internalized as negative psychological traits and…
Descriptors: Student Satisfaction, Electronic Learning, Educational Technology, Predictor Variables
Stephanie Dionne Connolly – ProQuest LLC, 2023
Data scientists in educational research utilize learning analytics to investigate predictors of adult learner performance or final grades in closed online courses, blended or hybrid courses, and Massive Open Online Courses (MOOCs). The purpose of this quantitative correlational study was to investigate if and to what extent a predictive…
Descriptors: MOOCs, Adult Students, Private Colleges, Learner Controlled Instruction
Humida, Thasnim; Al Mamun, Md Habib; Keikhosrokiani, Pantea – Education and Information Technologies, 2022
Digital transformation and emerging technologies open a horizon to a new method of teaching and learning and revolutionizes the e-learning industry. The goal of this study is to scrutinize a proposed research model for predicting factors that influence student's behavioral intention to use e-learning system at Begum Rokeya University, Bangladesh.…
Descriptors: Student Behavior, Intention, Electronic Learning, College Students
Deeva, Galina; De Smedt, Johannes; De Weerdt, Jochen – IEEE Transactions on Learning Technologies, 2022
Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…
Descriptors: Electronic Learning, MOOCs, Dropouts, Prediction

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