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Jelena Jovanovic; Dragan Gaševic; Lixiang Yan; Graham Baker; Andrew Murray; Danijela Gasevic – Journal of Computer Assisted Learning, 2024
Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable…
Descriptors: Psychological Patterns, Networks, Profiles, Learning Processes
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Linghong Li; Martin Valcke; Linda Badan; Christoph Anderl – Journal of Computer Assisted Learning, 2024
Background study: Chinese tone pronunciation instruction gains increasingly attention and various instructional strategies have been studied to develop effective tones in students. Students usually listen to successful pronunciation stimuli provided by the teacher or peers, to be copied by themselves. However, individuals seem more sensitive to…
Descriptors: Second Language Instruction, Second Language Learning, Chinese, Intonation
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Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
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Davy Tsz Kit Ng; Chen Xinyu; Jac Ka Lok Leung; Samuel Kai Wah Chu – Journal of Computer Assisted Learning, 2024
Background: As the significance of artificial intelligence (AI) continues to increase, there is a need for effective scaffolding and support for novice learners. Educators have encountered challenges in effectively scaffolding novice learners AI concepts, and providing appropriate motivational support. Research evidence has shown the potential of…
Descriptors: Artificial Intelligence, Novices, Scaffolding (Teaching Technique), Game Based Learning
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Fu, En; Gao, Qiufeng; Wei, Chuqian; Chen, Qianyi; Liu, Yijun – Journal of Computer Assisted Learning, 2021
Smartphone use in learning settings is a common behaviour amongst college students. Building on the theory of consumerism, self-efficacy and addictive behaviours, the current study developed a three-component conceptual framework to understand college students' smartphone use in organizational as well as self-directed learning settings. One…
Descriptors: Foreign Countries, College Students, Handheld Devices, Telecommunications
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Yeh, Y. -c.; Lin, C. S. – Journal of Computer Assisted Learning, 2018
Although cultivating creativity is greatly emphasized in elementary school education and that digital games can be a promising tool for improving creativity, little research has been conducted to identify and explore how player-related factors might influence the learning outcomes of digital creativity games. This study identifies 3 individual…
Descriptors: Goal Orientation, Academic Achievement, Structural Equation Models, Self Efficacy
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Thai, Ngoc Thuy Thi; De Wever, Bram; Valcke, Martin – Journal of Computer Assisted Learning, 2020
This study compares four learning environments: face-to-face learning (F2F), fully e-learning (EL), blended learning (BL), and flipped classroom (FC) with respect to students' learning performance. Moreover, this present research studies changes in perceived flexibility, intrinsic motivation, self-efficacy beliefs of students, and the interaction…
Descriptors: Blended Learning, Teaching Methods, Comparative Analysis, Self Efficacy
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Makransky, Guido; Borre-Gude, Stefan; Mayer, Richard E. – Journal of Computer Assisted Learning, 2019
The main objective of this study was to examine the effectiveness of immersive virtual reality (VR) as a medium for delivering laboratory safety training. We specifically compare an immersive VR simulation, a desktop VR simulation, and a conventional safety manual. The sample included 105 first year undergraduate engineering students (56 females).…
Descriptors: Computer Simulation, Self Efficacy, Learning Motivation, Comparative Analysis