NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 11 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Febe 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 reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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)
Peer reviewed Peer reviewed
Direct linkDirect link
Yanqing Wang; Shaoying Gong; Ning Jia; Ying Liu – Journal of Computer Assisted Learning, 2025
Background: Online learning is becoming increasingly popular among learners. To enhance the effectiveness of online learning, researchers have embedded an affective pedagogical agent (PA) on the computer screen to help regulate learners' emotions and support their learning. However, previous research has paid little attention to the effects of…
Descriptors: Metacognition, Prompting, Electronic Learning, Computer Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Chih-Chung Lin; Tzu-Hsuan Lin; Chi-Kay Tang – Journal of Computer Assisted Learning, 2025
Background: The integration of generative artificial intelligence (Gen-AI) into second language (L2) education has opened new possibilities for personalized and adaptive instruction. While Gen-AI has shown promise in supporting language production skills, its application in reading, particularly in pre-reading scaffolding, remains underexplored.…
Descriptors: Reading Comprehension, English (Second Language), Second Language Learning, College Freshmen
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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