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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
Daniela Olea-Ibarra; Christian Hartmann; Maria Bannert – Journal of Computer Assisted Learning, 2025
Background: Enjoyment and epistemic emotions are essential in education as they drive learners to actively and persistently engage with learning material. Augmented Reality (hereinafter referred to as AR) is an emerging educational tool that offers unique opportunities for immersive learning experiences. By incorporating AR into the learning…
Descriptors: Psychological Patterns, Positive Attitudes, Computer Simulation, Active Learning
Gwo-Jen Hwang; Jalil Fathi; Masoud Rahimi – Journal of Computer Assisted Learning, 2025
Background: The utilisation of video-dubbing tasks, wherein learners record their voices over video clips to practise pronunciation, fluency, grammatical accuracy, and vocabulary use, is relatively novel in the English language learning context. Exploring the effectiveness of video-dubbing tasks can lead to more innovative and effective speaking…
Descriptors: English (Second Language), Second Language Learning, Speech Skills, Cognitive Processes
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)
Jiarui Hou; James F. Lee; Stephen Doherty – Journal of Computer Assisted Learning, 2025
Background: Recent research has demonstrated the potential of mobile-assisted learning to enhance learners' learning outcomes. In contrast, the learning processes in this regard are much less explored using eye tracking technology. Objective: This systematic review study aims to synthesise the relevant work to reflect the current state of eye…
Descriptors: State of the Art Reviews, Eye Movements, Electronic Learning, Handheld Devices