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Showing 1 to 15 of 27 results Save | Export
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Miao Chao; Weiyi Sun; Jie Liu; Jiahui Ding; Ye Zhu – Journal of Computer Assisted Learning, 2025
Background: The use of social media among students has become debatable concern due to both positive and negative effects on academic performance. Yet, understanding of the diverse patterns of social media use and their influence on actual and perceived academic performance remains limited. Objectives: This study distinguishes between academic and…
Descriptors: Social Media, Performance, Influence of Technology, Predictor Variables
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Ding, Yan; Zhao, Ting – Journal of Computer Assisted Learning, 2020
Emotions are critical to learning. However, the function of emotions in the emerging context of massive open online courses (MOOCs) has been under-researched. The present study complemented this line of research by modelling the relation between learner emotions, engagement with videos, engagement with assignments, and self-perceived achievement…
Descriptors: Psychological Patterns, Online Courses, Learner Engagement, 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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Soffer, Tal; Cohen, Anat – Journal of Computer Assisted Learning, 2019
This study examined students' engagement characteristics in online courses and their impact on academic achievements, trying to distinguish between course completers and noncompleters. Moreover, this research is intended to differentiate between those who pass the final exam and those who do not. Four online courses were examined with a similar…
Descriptors: Learner Engagement, Student Participation, Online Courses, Educational Technology
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Heckel, Christian; Ringeisen, Tobias – Journal of Computer Assisted Learning, 2019
The current study validated the proposed structure of relationships among outcome-related achievement emotions (pride and anxiety), their cognitive predictors (appraisals und online-learning-related self-efficacy), and learning outcomes (competence gain and satisfaction) in the context of online learning in higher education. On the basis of a…
Descriptors: Emotional Response, Anxiety, Predictor Variables, Student Satisfaction
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Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
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Niu, Liwei; Wang, Xinghua; Wallace, Matthew P.; Pang, Hui; Xu, Yanping – Journal of Computer Assisted Learning, 2022
Background: In view of the widespread use of digital technologies in English as a foreign language (EFL) learning and the importance of students' approaches to learning (SAL) and digital competence, as well as the threats of technostress in digital settings, digital EFL learning requires a critical examination. Objectives: This study sought to…
Descriptors: English (Second Language), Educational Technology, Electronic Learning, Second Language Learning
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Menabò, Laura; Sansavini, Alessandra; Brighi, Antonella; Skrzypiec, Grace; Guarini, Annalisa – Journal of Computer Assisted Learning, 2021
Background: The rapid spread of COVID-19 forced many countries to adopt severe containment measures, transferring all didactic activities into virtual environments. However, the integration of technology in teaching may present difficulties, especially in some countries, such as Italy. Objectives: The present study analyzed how the two main…
Descriptors: Technology Integration, Intention, Adoption (Ideas), Electronic Learning
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Blau, Ina; Shamir-Inbal, Tamar; Hadad, Shlomit – Journal of Computer Assisted Learning, 2020
The purpose of this study was to examine the influence of online collaborative learning experiences on students' digital collaboration skills and on the sustainability of e-collaboration in schools' culture--comparing individualistic versus collectivistic cultures. In addition, we explored how the leadership experience of schools' ICT coordinators…
Descriptors: Electronic Learning, Cooperative Learning, Individualism, Collectivism
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Zhu, Jinxin; Mok, Magdalena M. C. – Journal of Computer Assisted Learning, 2020
In recent years, it has become common to use the internet or computer tutoring with a programme or application for additional instruction (ICTPAAI), in addition to the mandatory school schedule. This study aimed to understand students' participation in ICTPAAI and its relation to academic achievement. Multilevel structural equation modelling was…
Descriptors: Predictor Variables, Student Participation, Internet, Computer Assisted Instruction
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Alario-Hoyos, C.; Muñoz-Merino, P. J.; Pérez-Sanagustín, M.; Delgado Kloos, C.; Parada Gelvez, H. A. – Journal of Computer Assisted Learning, 2016
The role of social tools in massive open online courses (MOOCs) is essential as they connect participants. Of all the participants in an MOOC, top contributors are the ones who more actively contribute via social tools. This article analyses and reports empirical data from five different social tools pertaining to an actual MOOC to characterize…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Technology Uses in Education
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Almusharraf, Norah Mansour; Bailey, Daniel – Journal of Computer Assisted Learning, 2021
During the COVID-19 outbreak, students had to cope with succeeding in video-conferencing classes susceptible to technical problems like choppy audio, frozen screens and poor Internet connection, leading to interrupted delivery of facial expressions and eye-contact. For these reasons, agentic engagement during video-conferencing became critical for…
Descriptors: COVID-19, Pandemics, Cooperative Learning, English (Second Language)
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de Barba, P. G.; Kennedy, G. E.; Ainley, M. D. – Journal of Computer Assisted Learning, 2016
Over the last 5 years, massive open online courses (MOOCs) have increasingly provided learning opportunities across the world in a variety of domains. As with many emerging educational technologies, why and how people come to MOOCs needs to be better understood and importantly what factors contribute to learners' MOOC performance. It is known that…
Descriptors: Online Courses, Large Group Instruction, Educational Technology, Electronic Learning
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Dindar, Muhterem; Suorsa, Anna; Hermes, Jan; Karppinen, Pasi; Näykki, Piia – Journal of Computer Assisted Learning, 2021
COVID-19 pandemic has caused a massive transformation in K-12 settings towards online education. It is important to explore the factors that facilitate online teaching technology adoption of teachers during the pandemic. The aim of this study was to compare Learning Management System (LMS) acceptance of Finnish K-12 teachers who have been using a…
Descriptors: Technology Integration, Elementary School Teachers, Secondary School Teachers, Expectation
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