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Tanya Chichekian; Joel Trudeau; Tawfiq Jawhar; Dylan Corliss – Journal of Computer Assisted Learning, 2024
Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K-12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to…
Descriptors: College Students, Computation, Thinking Skills, Transfer of Training
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Ting-Ting Wu; Edi Sarwono; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Virtual laboratories are used to supplement or even replace physical laboratories in engineering education. Although these virtual laboratories allow students to learn foundational experimental skills, they do not provide the learners with the chance to develop higher-order thinking skills (HOTS). Computational thinking (CT) is an…
Descriptors: Computation, Thinking Skills, Computer Simulation, Laboratories
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Lai, Xiaoyan; Ye, Jiachu; Wong, Gary Ka Wai – Journal of Computer Assisted Learning, 2023
Background: Collaboration has commonly been integrated in computational thinking education to foster novice learning. While the majority of existing studies on developing students' CT skills have been based on competency or personality factors, social factors have been largely ignored. Objectives: This systematic review, framed by social cognitive…
Descriptors: Cooperative Learning, Instructional Effectiveness, Computation, Thinking Skills
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Shuhan Zhang; Gary K. W. Wong – Journal of Computer Assisted Learning, 2024
Background: Computational thinking (CT) has been broadly considered one of the 21st-century competencies, and an emerging trend has been seen in integrating CT into primary education. Cumulative research was conducted to investigate the influencing factors of CT learning performance, and an ample range of factors has been identified, involving…
Descriptors: Logical Thinking, Personality Traits, Elementary School Students, Negative Attitudes
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Jiahong Su; Weipeng Yang; Iris Heung Yue Yim; Hui Li; Xiao Hu – Journal of Computer Assisted Learning, 2024
Background: While the integration of robot-based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning. Objectives: The study explored the effectiveness of two AI education approaches in advancing kindergarteners'…
Descriptors: Early Childhood Education, Artificial Intelligence, Kindergarten, Program Effectiveness
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Seyedahmad Rahimi; Russell Almond; Andrea Ramírez-Salgado; Christine Wusylko; Lauren Weisberg; Yukyeong Song; Jie Lu; Ted Myers; Bowen Wang; Xiaomaon Wang; Marc Francois; Jennifer Moses; Eric Wright – Journal of Computer Assisted Learning, 2024
Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the…
Descriptors: Competence, Models, Research Methodology, Research Design
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Pellas, Nikolaos – Journal of Computer Assisted Learning, 2023
Background: Owing to the exponential growth of three-dimensional (3D) environments amongst researchers and educators to create simulation games (SGs) in primary education, there is a growing interest to examine their potential support in computer science courses instead of visual programming environments. Objectives: This study explores the…
Descriptors: Computation, Thinking Skills, Programming, Skill Development