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Showing 31 to 45 of 211 results Save | Export
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Arslan, Okan; Xing, Wanli; Inan, Fethi A.; Du, Hanxiang – Journal of Computer Assisted Learning, 2022
Background: There has been increasing interest in online professional learning networks in a variety of social media platforms, especially in Twitter. Twitter offers immediacy, personalization, and support of networks to increase professional knowledge and the sense of membership. Knowing the topics discussed in Twitter and the factors that affect…
Descriptors: Electronic Learning, Social Media, Networks, Communities of Practice
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Zhihao Cui; Oi-Lam Ng; Morris Siu-yung Jong; Xiaojing Weng – Journal of Computer Assisted Learning, 2025
Background: Amidst the increasing application of online education in the post-COVID era, new challenges in student engagement have emerged. However, most studies on online engagement have adopted macro-level approaches and relied on self-report measures of retrospective engagement. Few have examined micro-level engagement in terms of real-time and…
Descriptors: Middle School Students, Learner Engagement, Attention, Synchronous Communication
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Tanya Chichekian; Joel Trudeau; Tawfiq Jawhar; Dylan Corliss – Journal of Computer Assisted Learning, 2024
Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K-12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to…
Descriptors: College Students, Computation, Thinking Skills, Transfer of Training
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Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
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Shuang Li; Jingxi Chen; Sizhuo Liu – Journal of Computer Assisted Learning, 2024
Background: Enhancing the effectiveness of online learning has become a key challenge with regard to the ability of blended learning to reach its full potential. However, mechanisms by which students' self-regulated learning (SRL) skills influence their online learning engagement in blended learning and subsequent learning achievement have yet to…
Descriptors: Blended Learning, Elementary Secondary Education, Self Management, Self Evaluation (Individuals)
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Zixuan Cheng; Peijian Paul Sun – Journal of Computer Assisted Learning, 2025
Background: While a substantial number of studies have investigated English-as-a-foreign-language (EFL/L2 English) anxiety, they predominantly examined it from a unidimensional perspective, overlooking the potential insights offered by examining language-skill-specific L2 anxiety from a multidimensional lens. Moreover, prior research has…
Descriptors: Second Language Learning, Speech Communication, Anxiety, In Person Learning
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Marquès Puig, Joan Manuel; Daradoumis, Thanasis; Arguedas, Marta; Calvet Liñan, Laura – Journal of Computer Assisted Learning, 2022
Background: Recent research in online settings reports that supporting self-regulated learning (SRL) strategy use could lead to greater online academic success. A growing number of studies have started to investigate SRL supports in online environments recently, which indicates a great interest in this matter. Though several systems for automatic…
Descriptors: Cognitive Processes, Metacognition, Critical Thinking, Electronic Learning
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Sun, Chunmei; Hwang, Gwo-Jen; Yin, Zhaoyi; Wang, Zhonghou; Wang, Zhuo – Journal of Computer Assisted Learning, 2023
Background: Social annotation (SA) allows users to collaboratively highlight important texts, make comments and discuss with each other on the same online document. This would not only accelerate and deepen learners' cognitive understanding of information, but also help build a sense of rapport, which is critical especially because of the…
Descriptors: Trend Analysis, Computer Mediated Communication, Cooperative Learning, Documentation
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Hoi, Vo Ngoc; Le Hang, Ho – Journal of Computer Assisted Learning, 2021
Enhancing student engagement plays a critical role in reducing student drop-out rate in online learning as students usually feel isolated and disconnected in this learning environment. This requires a clear conceptualization of the student engagement construct and its underlying structure. However, the conceptual understanding of the student…
Descriptors: Learner Engagement, Electronic Learning, Structural Equation Models, Factor Analysis
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Sule Biyik Bayram; Gamze Özener; Nilay Çakici; Handan Eren; Sinan Aydogan; Deniz Öztürk; Emel Gülnar; Nurcan Çaliskan – Journal of Computer Assisted Learning, 2024
Background: There are deficiencies in ensuring the permanence of some theoretical information taught in nursing education and transferring it to practice environment. Mobile-assisted teaching can be useful to eliminate deficiencies. The aim of this study was to determine the effect of mobile-assisted teaching on nursing students' learning…
Descriptors: Foreign Countries, Nursing Students, Human Body, Electronic Learning
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Anna Flavia Di Natale; Claudia Repetto; Daniela Villani – Journal of Computer Assisted Learning, 2024
Background: Online synchronous learning in higher education frequently struggles to overcome the social presence gap, resulting in dissatisfaction and poor learning outcomes. Objectives: This study examined the effectiveness of desktop-based virtual reality (VR) social platforms compared to video conferencing (VC) platforms in enhancing students'…
Descriptors: Computer Simulation, Social Media, Computers, Teleconferencing
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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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Jingrong Liu; Shujun Li; Wanfang Zhang – Journal of Computer Assisted Learning, 2024
Background: Limited research on the effectiveness of additional online and face-to-face practise opportunities for promoting active learning among Chinese EFL learners in higher education. Current understanding of self-regulated and collaborative learning theories in educational contexts. Objectives: To establish the efficacy of interactive online…
Descriptors: Foreign Countries, English (Second Language), English Language Learners, Electronic Learning
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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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Bacca-Acosta, Jorge; Fabregat, Ramon; Baldiris, Silvia; Kinshuk; Guevara, Juan – Journal of Computer Assisted Learning, 2022
Background: Mobile-based assessment has been an active area of research in the field of mobile learning. Prior research has demonstrated that mobile-based assessment systems positively affect student performance. However, it is still unclear why and how these systems positively affect student performance. Objectives: This study aims to identify…
Descriptors: Academic Achievement, Electronic Learning, Handheld Devices, Computer Assisted Testing
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