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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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Mohamad Iyad Al-Khiami; Martin Jaeger; Sayed Mohamad Soleimani; Abdulhadi Kazem – Journal of Computer Assisted Learning, 2024
Background Study: The research discusses the need for a paradigm shift in engineering education current practices to accommodate the digital native students. The paper emphasizes the importance of integrating disruptive technologies, namely Virtual Reality (VR) through Head Mounted Displays VR (HMD VR) and Desktop Based VR (DB VR) and comparing it…
Descriptors: Undergraduate Students, Engineering Education, Computer Simulation, Student Motivation
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Chunqi Li; Lishi Liang; Luke K. Fryer; Alex Shum – Journal of Computer Assisted Learning, 2024
Background: Leaderboards are among the most popular gamification elements in education. Some studies have implemented leaderboards and reported their individual effects on students' learning. Despite the emergence of relevant empirical studies, most of the existing reviews have only investigated the holistic impact of gamification. No previous…
Descriptors: Higher Education, Gamification, Evidence Based Practice, Learning Motivation
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Meiyan Huang; Tang Yongquan – Journal of Computer Assisted Learning, 2025
Aim: In recent years, the integration of cutting-edge technology into professional sports training (ST) has revolutionized the way athletes prepare for competition. The study aims to quantitatively analyse the impact of cutting-edge technology on enhancing performance, efficiency, and outcomes in professional ST programs. Purpose: The purpose of…
Descriptors: Athletics, Technology, Influence of Technology, Training
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Tiphaine Colliot; Jean-Michel Boucheix – Journal of Computer Assisted Learning, 2024
Background: Previous studies have shown that dynamic illustrations, as compared to their static counterparts, lead to higher achievement levels, especially for hand-based procedures. Other researchers have investigated how the presence of seductive details (i.e., appealing but irrelevant adjunct displays) influences students' interest positively…
Descriptors: Illustrations, Animation, Handicrafts, Elementary School Students
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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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Jiang Xiaxia; Li Yahong; Kuang Ziyi; Yu Jiajun – Journal of Computer Assisted Learning, 2025
Background: Video conferencing technology has moved online education into a new stage of real-time video interaction. However, shortcomings such as students' lack of concentration and substantive engagement during video conferencing greatly limit the improvement of online learning effectiveness. According to social presence theory and the…
Descriptors: College Faculty, College Students, Electronic Learning, Distance Education
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Muhammet Fidan; Mustafa Fidan – Journal of Computer Assisted Learning, 2024
Background: Flipped classroom (FC) model has become increasingly popular in dental education (DE) with its strengths for students. However, major concerns are lack of interaction, unwillingness to complete the assignments, low engagement during the pre-class activities because of an unwell-designed instructional setting of FC. Objectives: The…
Descriptors: Flipped Classroom, Dentistry, Graduate Students, Video Technology
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Ute Mertens; Marlit A. Lindner – Journal of Computer Assisted Learning, 2025
Background: Educational assessments increasingly shift towards computer-based formats. Many studies have explored how different types of automated feedback affect learning. However, few studies have investigated how digital performance feedback affects test takers' ratings of affective-motivational reactions during a testing session. Method: In…
Descriptors: Educational Assessment, Computer Assisted Testing, Automation, Feedback (Response)
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Xin Tang; Zhiqiang Yuan; Shaojun Qu – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (AI) represents a significant technological leap, with platforms like OpenAI's ChatGPT and Baidu's Ernie Bot at the forefront of innovation. This technology has seen widespread adoption across various sectors of society and is anticipated to revolutionise the educational landscape, especially in the…
Descriptors: Influences, College Students, Student Behavior, Intention
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Yi-Fan Li; Jue-Qi Guan; Xiao-Feng Wang; Qu Chen; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: Self-regulated learning (SRL) is a predictive variable in students' academic performance, especially in virtual reality (VR) environments, which lack monitoring and control. However, current research on VR encounters challenges in effective interventions of cognitive and affective regulation, and visualising the SRL processes using…
Descriptors: Electronic Learning, Individualized Instruction, Learning Processes, Performance
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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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Pieter Vanneste; Kim Dekeyser; Luis Alberto Pinos Ullauri; Dries Debeer; Frederik Cornillie; Fien Depaepe; Annelies Raes; Wim Van den Noortgate; Sameh Said-Metwaly – Journal of Computer Assisted Learning, 2024
Background: Augmented reality (AR) is receiving increasing interest as a tool to create an interactive and motivating learning environment. Yet, it is unclear how instructional support affects performance in AR. Objectives: This study sought to explore how varying the instructional support in AR can affect performance-related behaviours of…
Descriptors: Computer Simulation, Artificial Intelligence, Cognitive Ability, Student Behavior
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Dana Kube; Sebastian Gombert; Brigitte Suter; Joshua Weidlich; Karel Kreijns; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Gender stereotypes about women and men are prevalent in computer science (CS). The study's goal was to investigate the role of gender bias in computer-supported collaborative learning (CSCL) in a CS context by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon.…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Gender Issues, Learning Activities