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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
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
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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
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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
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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
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Engin Demir; Huseyin Cevik – Turkish Online Journal of Distance Education, 2025
Students' attitudes towards distance education can be shaped by the compatibility of their learning styles with this new educational environment. The study aimed to investigate whether various variables and e-learning styles predict student's attitudes towards distance education. The present research was conducted on 387 students enrolled in the…
Descriptors: Student Attitudes, Electronic Learning, Educational Technology, Predictor Variables
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Anshita Chelawat; Richal Tuscano; Roshani Prasad; Seema Sant – International Journal of Learning Technology, 2025
This study aims to explore factors predicting the use of e-learning as a sustainable solution in Indian higher education institutions by employing a modified version of the technology acceptance model (TAM). An online questionnaire (n = 200), capturing post-graduate management students from the Mumbai Metropolitan Region, was analysed using…
Descriptors: Educational Technology, Electronic Learning, Graduate Students, Value Judgment
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Corina Milagro Mosqueira Taipe; Larissa Cristina Mazer; Nayara Paula Fernandes Martins Molina; Caíque Rossi Baldassarini; Gabriela Di Donato; Assis Do Carmo Pereira Júnior; Adriana Inocenti Miasso; Patricia Leila dos Santos – Journal of Latinos and Education, 2025
The COVID-19 pandemic has brought the challenge of online teaching to graduate courses, without prior preparation for students and teachers. In this context, the aim of the study was to identify sociodemographic predictors of difficulty in carrying out online academic activities by graduate students, by region of Brazil, during the COVID-19…
Descriptors: Social Class, Demography, Predictor Variables, Difficulty Level
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Qixuan Wu; Hyung Jae Chang; Long Ma – Journal of Advanced Academics, 2025
It is very important to identify talented students as soon as they are admitted to college so that appropriate resources are provided and allocated to them to optimize and excel in their education. Currently, this process is labor-intensive and time-consuming, as it involves manual reviews of each student's academic record. This raises the…
Descriptors: Electronic Learning, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Mary Ellen Dello Stritto; Dane Skinner; Naomi R. Aguiar; Greta R. Underhill – Journal of Student Financial Aid, 2025
A wealth of evidence indicates that financial aid is positively associated with retention and graduation rates among college students attending in-person courses. However, limited research exists on the relation between financial aid, retention, and graduation rates among undergraduate students earning online degrees. The purpose of this study was…
Descriptors: Student Financial Aid, School Holding Power, Academic Persistence, Graduation Rate
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Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
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Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
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Yavuz Akbulut; Onur Dönmez; Beril Ceylan; Tayfun Firat – Journal of Computing in Higher Education, 2025
Providing pre-training on new material can simplify complex content for learners who may need guidance to understand basic facts and organize their efforts. However, the effect of pre-training on learning outcomes is controversial because it tends to vary by context. Our aim was to investigate the effectiveness of pre-training in reducing…
Descriptors: Training, Cognitive Processes, Difficulty Level, Academic Achievement
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Irena M. Ilic; Milena D. Ilic – Scandinavian Journal of Educational Research, 2025
The goal of this narrative review was to summarize the literature findings regarding the occurrence and predictors of burnout syndrome in medical students in the online learning period during the COVID-19 pandemic. This review of identified relevant studies showed that their results were highly heterogeneous, primarily due to the important…
Descriptors: Electronic Learning, COVID-19, Pandemics, Medical Education
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Na-Ra Nam; Sue-Yeon Song – Innovations in Education and Teaching International, 2025
This empirical study uses a random forest algorithm to examine the factors that influence learners' persistence in online learning at a prominent Korean institution. The data were collected from students who began their studies in Spring 2021, and encompassed a range of variables including individual attributes, academic engagement, academic…
Descriptors: Adult Students, Academic Persistence, Foreign Countries, Influences
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