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Direct linkFebe Demedts; Sameh Said-Metwaly; Kristian Kiili; Manuel Ninaus; Antero Lindstedt; Bert Reynvoet; Delphine Sasanguie; Fien Depaepe – Journal of Computer Assisted Learning, 2025
Background: The potential of adaptive feedback in digital educational games remains largely unexplored. Fractions are a suitable topic for investigating the effectiveness of adaptive feedback, as the complexity of this domain highlights the need for adequate feedback. Objectives: This study examines the effectiveness of explanatory adaptive…
Descriptors: Grade 4, Educational Games, Video Games, Feedback (Response)
Peer Interactions during Computer-Supported Collaborative Learning: A Self-Determination Perspective
Anouschka van Leeuwen; Lisette Hornstra; Jeroen Janssen; En Ning Leow – Journal of Computer Assisted Learning, 2025
Background: Computer-supported collaborative learning (CSCL) environments are hypothesised to offer a learning environment that satisfies basic psychological needs for autonomy, relatedness and competence, subsequently improving learning and motivational outcomes. However, the underlying mechanism of how basic psychological needs are fulfilled…
Descriptors: Peer Relationship, Interaction, Computer Assisted Instruction, Cooperative Learning
Wenji Wang; Wenjuan Wang – Journal of Computer Assisted Learning, 2025
Background Study: The combination of artificial intelligence (AI) and foreign language learning is emerging as a significant trend in language education. Objectives: This study aimed to investigate the impact of technology acceptance, attitude and motivation on behavioural intentions regarding the use of AI in language learning. Methods:…
Descriptors: College Students, Student Behavior, Intention, Educational Technology
Marlene Steinbach; Johanna Fleckenstein; Livia Kuklick; Jennifer Meyer – Journal of Computer Assisted Learning, 2025
Background: Providing students with information on their current performance could help them improve by stimulating their reflection, but negative feedback that saliently mirrors task-related failure can harm motivation. In the context of automated scoring based on artificial intelligence, we explored how feedback on written texts might be…
Descriptors: Student Motivation, Academic Achievement, Low Achievement, Feedback (Response)
Venus Chan – Journal of Computer Assisted Learning, 2025
Background: Technology advancement changes not only interpreting practices but also its pedagogy, which has long been criticised for lacking authenticity in/out-of-classroom practices. Objective: This empirical research aims to develop a mobile-assisted language learning application powered by extended reality (XR). Shortened as 'XR MALL', this…
Descriptors: Computer Simulation, Computer Assisted Instruction, Second Language Learning, Translation
Yang Jiang; Beata Beigman Klebanov; Jiangang Hao; Paul Deane; Oren E. Livne – Journal of Computer Assisted Learning, 2025
Background: Writing is integral to educational success at all levels and to success in the workplace. However, low literacy is a global challenge, and many students lack sufficient skills to be good writers. With the rapid advance of technology, computer-based tools that provide automated feedback are being increasingly developed. However, mixed…
Descriptors: Feedback (Response), Writing Evaluation, Middle School Students, High School Students
Shunmeng Chen – Journal of Computer Assisted Learning, 2025
Background: Computer-mediated writing classes have experienced a significant increase in popularity in recent years, serving as an effective modality for enhancing writing skills within an online framework. Objectives: This study seeks to bridge the gap in the literature by investigating the effectiveness of cognitive, social, and group-awareness…
Descriptors: Cognitive Processes, Difficulty Level, Computer Assisted Instruction, Writing Instruction
Qianwen Tang; Wenbo Deng; Yidan Huang; Shuaijie Wang; Hao Zhang – Journal of Computer Assisted Learning, 2025
Background: Generative Artificial Intelligence (AI) shows promise in enhancing personalised learning and improving educational efficiency. However, its integration into education raises concerns about misinformation and over-reliance, particularly among adolescents. Teacher supervision plays a critical role in mitigating these risks and ensuring…
Descriptors: Artificial Intelligence, Teaching Methods, Educational Quality, Technology Integration
Juliana do Amaral; Ladislao Salmerón; Davi Alves Oliveira – Journal of Computer Assisted Learning, 2025
Background: Misconceptions are unjustified beliefs about a topic. Nonetheless, they are pervasive among educational practitioners. Although the internet can be a powerful tool to learn and debunk misconceptions, their use requires competencies like navigating through search engine results pages (SERPs), evaluating the reliability of content, and…
Descriptors: Eye Movements, Second Language Learning, Second Language Instruction, Computer Assisted Instruction
