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Showing 1 to 15 of 43 results Save | Export
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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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Isaac Dunmoye; Olanrewaju Olaogun; Nathaniel Hunsu; Dominik May; Robert Baffour – IEEE Transactions on Education, 2024
Contribution: The study examines the predictive and mediating significance of social and teaching presences on cognitive presence in a Community of Inquiry (CoI) mediated by a desktop virtual reality (VR). The findings of this study have implications for how to leverage VR learning environments to support meaningful collaborative engagement.…
Descriptors: Computer Simulation, Engineering Education, Interpersonal Relationship, Cooperative 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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Rico Amoussohoui; Aminou Arouna; Miroslava Bavorova; Vladimir Verner; Wilfried Yergo; Jan Banout – Journal of Agricultural Education and Extension, 2024
Purpose: The study evaluates new approach of digital extension services for the long-term adoption of digital extension technologies. We propose an indirect adoption approach to address following research questions. What socioeconomic factors influence rice farmers' decision to prefer one business profile over another? Which business profile is…
Descriptors: Foreign Countries, Socioeconomic Influences, Agricultural Occupations, Predictor Variables
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Caleb Or – OTESSA Journal, 2024
This study uses one-step meta-analytic structural equation modelling to delve into the technology acceptance model's (TAM) application within education, assessing perceived usefulness, ease of use, intentions to use, and actual technology use. It synthesises previous findings to validate the TAM's effectiveness and uncover the model's predictive…
Descriptors: Literature Reviews, Meta Analysis, Technology Integration, Educational Technology
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Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
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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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Sanghoon Park; Heoncheol Yun – Educational Technology Research and Development, 2024
Although numerous studies have demonstrated the potential benefits of augmented reality (AR) in education, the influence of education students' learning experiences on their AR technology acceptance in the classroom has yet to be examined thoroughly. In this empirical study, we explored the affective experiences (i.e., positive emotions, negative…
Descriptors: Computer Simulation, Educational Technology, Student Experience, Emotional Response
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Xindi Kong; Hongyu Liang; Chunsheng Wu; Zheyan Li; Yuxin Xie – European Journal of Psychology of Education, 2025
Learning engagement is considered a reliable predictor for evaluating the effectiveness of online learning and has become a focal point in online education in recent years. This study investigated the roles and mechanisms of social presence and online learning self-efficacy in mediating the relationship between perceived teacher emotional support…
Descriptors: Online Courses, Self Efficacy, Teacher Student Relationship, Teacher Role
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Kheira Ouassif; Benameur Ziani – Education and Information Technologies, 2025
The integration of educational data mining and deep neural networks, along with the adoption of the Apriori algorithm for generating association rules, focuses to resolve the problem of misdirection of students in the university, leading to their failure and dropout. This is reached through the development of an intelligent model that predicts the…
Descriptors: Predictor Variables, College Students, Majors (Students), Decision Making
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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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Qiong Wang; Guoqing Zhao; Jinglan Zeng – Australasian Journal of Educational Technology, 2024
Although studies have highlighted the importance of facilitating conditions in enhancing students' digital informal learning (DIL), the effect mechanism is still unclear. This study examined the mediating role of digital competence and the moderating role of technostress between facilitating conditions and DIL. Data were collected from 385…
Descriptors: Educational Technology, Technology Uses in Education, Technological Literacy, Stress Variables
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Yaqian Zhao; Keyun Zhao; Shiqi Wei – Psychology in the Schools, 2025
Digital training has significantly transformed the landscape of teacher professional development, introducing various uncertainties. In this context, adaptability can play a crucial role in helping teachers cope with stress and effectively navigate new and changing scenarios. However, existing research on adaptability has not adequately addressed…
Descriptors: Faculty Development, Value Judgment, Teacher Attitudes, Technological Literacy
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Silvia Di Battista – British Journal of Educational Psychology, 2025
Background: According to gender-differentiated attributions of failure in the STEM field, errors tend to be attributed to internal factors more to girls than to boys. Aims: This experimental study explored factors influencing gender-differentiated teachers' internal attributions of girls' and boys' errors and the consequent likelihood of teachers'…
Descriptors: Gender Differences, Failure, Attribution Theory, STEM Education
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Sha Tian; Wenjiao Yang – Education and Information Technologies, 2024
The growing popularity of interpreting technology in the industry has raised awareness of incorporating it into interpreter education. However, it is unclear what factors may contribute to students' behavioral use and the consequent effects of using it. With the addition of three external factors (motivation, task-technology fit, and technology…
Descriptors: Translation, Educational Technology, Technology Integration, Technology Uses in Education
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