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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
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
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
Ma, Ning; Gong, Kaixin; Zeng, Min – Journal of Computer Assisted Learning, 2023
Background: Collaborative learning has become a crucial approach to promoting online in-service teacher training. Appropriate peer recommendation for group composition is the basis to ensure productive learning outcomes of collaborative learning. However, there is a lack of understanding of the impact of peer recommendation on in-service teachers'…
Descriptors: Teachers, Cooperative Learning, Electronic Learning, Faculty Development
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
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
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
Buchner, Josef; Buntins, Katja; Kerres, Michael – Journal of Computer Assisted Learning, 2022
Background: Previous studies on augmented reality-enriched learning and training indicated conflicting results regarding the cognitive load involved: some authors report that AR can reduce cognitive load, others have shown that AR is perceived as cognitively demanding and can lead to poorer performance. Objectives: The aim of this study is to…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Difficulty Level
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
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)
Pi, Zhongling; Deng, Lixia; Wang, Xu; Guo, Peirong; Xu, Tao; Zhou, Yun – Journal of Computer Assisted Learning, 2022
Background: Video lectures which include the instructor's presence are becoming increasingly popular. Presenting a real human does, however, entail higher financial and time costs in making videos, and one innovative approach to reduce costs has been to generate a virtual speaking instructor. Objectives: The current study examined whether the use…
Descriptors: Video Technology, Lecture Method, Computer Simulation, Instructional Effectiveness
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
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
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
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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