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Showing 1 to 15 of 42 results Save | Export
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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
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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
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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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Gonzalo Martinez-Munoz; Miguel Angel Alvarez-Rodriguez; Estrella Pulido-Canabate – IEEE Transactions on Education, 2024
In this article, student video visualization profiles are analyzed with two objectives: 1) to identify difficult sections in videos and 2) to predict student performance based on their video visualization profiles. For identifying critical sections in videos two novel indicators are proposed. The first one is designed to measure the complexity of…
Descriptors: Video Technology, Visualization, Electronic Learning, Profiles
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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
Mark Littler – ProQuest LLC, 2024
The dynamics of higher education have changed as a result of online learning. However, it can be challenging for teachers to effectively engage students online. Furthermore, limited research about the relationship between presence and online student engagement is a social problem that impacts the quality of online nursing education. The purpose of…
Descriptors: Electronic Learning, Learner Engagement, Predictor Variables, Teacher Student Relationship
Michelle A. Burnside – ProQuest LLC, 2024
Persistence in distance learning has become problematic. This quantitative nonexperimental study examined whether perceived connectivity, perceived internal locus of control, and age predict persistence in online master's degree programs. Rotter's locus of control theory, Moore's transactional distance theory, and Rovai's composite persistence…
Descriptors: Locus of Control, Age, Predictor Variables, Academic Persistence
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Abdessamad Chanaa; Nour-eddine El Faddouli – Journal of Education and Learning (EduLearn), 2024
Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning…
Descriptors: Electronic Learning, Evaluation Methods, Artificial Intelligence, Taxonomy
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Zhengze Li; Hui Chen; Xin Gao – Education and Information Technologies, 2024
Online supplementary education has been prevalent in recent years due to the advent of technology (e.g., live streaming) and the COVID-19 pandemic. However, the performance of students in this mode of education varies greatly, and the underlying reasons are yet to be investigated. This study aims to understand the impact of various factors and…
Descriptors: Predictor Variables, Elementary School Students, Electronic Learning, Supplementary Education
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Lamees Abdulrahman Alaulamie – Journal of Education and e-Learning Research, 2024
The transition to online learning during the COVID-19 pandemic was a new experience for parents of young children who were obliged to deal with various factors that had an impact on their level of satisfaction. It was essential to address these issues if their children were to continue receiving an education. This research investigates the factors…
Descriptors: Parent Attitudes, Online Courses, Electronic Learning, COVID-19
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LiuJie Xu; Ling Chen; Yiran Chen – Education and Urban Society, 2024
The Expert-based Collective Advising Mechanism (ECAM) was embedded in the open online tutoring project to provide free tutoring for rural students and to help them improve their academic performance, and thus, to solve education inequity. Taking urban and rural students in Tongzhou District of Beijing as the objects, this study gathered data on…
Descriptors: Foreign Countries, Rural Education, Tutoring, Academic Advising
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Doris U. Bolliger; Florence Martin; Stella Kim – Educational Technology Research and Development, 2024
Learner satisfaction is an important element in online learning because it impacts achievement motivation, success, and retention. It was the purpose of this study to develop an instrument that measures the satisfaction of learners in online learning environments. Data were collected from 335 students at higher education institutions. The Online…
Descriptors: Likert Scales, Test Construction, Test Validity, Student Satisfaction
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Michal B. Paradowski; Magdalena Jelinska – Computer Assisted Language Learning, 2024
Learning a foreign language is a long-term process requiring persistence and a willingness to engage in activities that will help develop communicative competence. An important role on the way to achieving linguistic proficiency is played by L2 grit. However, foreign language learners differ in the intensity of this trait. We identify the most…
Descriptors: Second Language Learning, Electronic Learning, Online Courses, Predictor Variables
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Ahmet Murat Uzun; Erhan Üna; Selcan Kilis – Educational Process: International Journal, 2024
Background/purpose: Widespread adoption of e-learning was triggered worldwide during the COVID-19 pandemic and modern higher education institutions dedicated significant resources to the use of diverse e-learning systems. However, to maximize the benefits of these investments, it is crucial that the degree to which end-users accept and continue…
Descriptors: Electronic Learning, COVID-19, Pandemics, Learning Management Systems
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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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