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Froehlich, Laura; Sassenberg, Kai; Jonkmann, Kathrin; Scheiter, Katharina; Stürmer, Stefan – Journal of Computer Assisted Learning, 2023
Background: The use of e-exams in higher education is increasing. However, the role of student diversity in the acceptance of e-exams is an under-researched topic. In the current study, we considered student diversity in terms of three sociodemographic characteristics (age, gender, and second language) and three dispositional student…
Descriptors: Student Diversity, Student Attitudes, Computer Assisted Testing, Student Characteristics
Xin Gong; Weiqi Xu; Ailing Qiao; Zhixia Li – Journal of Computer Assisted Learning, 2025
Background: Robot programming can simultaneously cultivate learners' computational thinking (CT) and spatial thinking (ST). However, there is a noticeable gap in research focusing on the micro-level development patterns of learners' CT and ST and their interconnections. Objectives: This study aims to uncover the intricate development patterns and…
Descriptors: Mental Computation, Thinking Skills, Skill Development, Robotics
Yanan Dai; Abdullah Al Mamun; Mohammad Enamul Hoque; Mengling Wu; Yanan Cai – Journal of Computer Assisted Learning, 2025
Background: Virtual reality (VR) provides a unique immersive teaching experience and brings significant changes to existing education models. However, barriers may influence the resistance to and non-adoption of VR. Objectives: Grounded in innovation resistance theory (IRT), this study thus examined the resistance attitudes and non-adoption…
Descriptors: Educational Technology, Technology Integration, Innovation, Resistance (Psychology)
Allan Mesa Canonigo – Journal of Computer Assisted Learning, 2024
Motivation: This research investigates the transformative impact of integrating AI into mathematics education, aiming to enhance students' conceptual understanding and self-efficacy. It addresses the crucial need for innovative teaching methods in response to contemporary challenges in education and aims to fill gaps in understanding the potential…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Mathematics Instruction, Problem Solving
Piia Näykki; Saara Pyykkönen; Jenni Latva-aho; Tuula Nousiainen; Emilia Ahlström; Tapio Toivanen – Journal of Computer Assisted Learning, 2024
Background: In recent years, the use of virtual reality (VR) environments for education has gained interest in research and education. However, little is known about the potential of social VR environments for collaborative learning. Objectives: This study explores pre-service teachers' (PSTs') collaborative learning and role-based drama activity,…
Descriptors: Computer Simulation, Cooperative Learning, Preservice Teachers, Drama
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
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
Li, Yuhao; Chang, Mengyi; Zhao, Hanxuan; Jiang, Caihong; Xu, Sihua – Journal of Computer Assisted Learning, 2023
Background: Mobile devices facilitate learning activities in a self-paced way. However, the current understanding of learning participation and its consequence are minimal when learners take advantage of opportunities provided by mobile technologies worldwide. Aims: The primary purpose of this study is to examine the effectiveness of environmental…
Descriptors: Anxiety, Computer Software, Computer Assisted Instruction, Learning Processes
Gao, Ming; Zhang, Jingjing; Lu, Yu; Kahn, Ken; Winters, Niall – Journal of Computer Assisted Learning, 2023
Background: As a non-cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning…
Descriptors: Resilience (Psychology), Academic Persistence, Personality Traits, Usability
Hong, Jon-Chao; Tai, Kai-Hsin; Luo, Wan-Lun; Sher, Yung-Ji; Kao, Yi-Wen – Journal of Computer Assisted Learning, 2022
Background: Many gamification applications (apps) have been designed to motivate students to learn particular content. Based on the brain activation approach, the present study adapted an app, named Shaking-On, which requires students to shake their mobile devices to send their answers to multiple-choice questions to the teacher. Students then…
Descriptors: Comparative Analysis, Computer Games, Computer Software, Telecommunications
Zhihui Cai; Caiyan Liu; Jieni Zhan; Zhikeng Wang; Xin Hao; Si Zhang; Xinjie Chen – Journal of Computer Assisted Learning, 2025
Background: Attention has been paid to collaboration in digital game-based learning, as it fosters interaction and student engagement, thereby enhancing learning outcomes. Previous findings about the effect of collaboration in digital game-based learning were inconsistent, and few studies have explored the underlying mechanisms, particularly…
Descriptors: Cooperative Learning, Computer Games, Game Based Learning, Learning Experience
Mengshi Xiao; Weizi Li; Lei Han; Shasha Zheng – Journal of Computer Assisted Learning, 2025
Background: In multimedia learning environments, pedagogical agents have emerged as an innovative tool to enhance digital instruction, yet optimising their design for maximal learning effectiveness remains underexplored. Objectives: This study aimed to investigate how specific design elements of pedagogical agents, namely appearance and voice…
Descriptors: Multimedia Instruction, Instructional Design, Computer Simulation, Student Attitudes
Weipeng Shen; Xiao-Fan Lin; Jiachun Liu; Xinxian Liang; Ruiqing Chen; Xiaoyun Lai; Xinwen Zheng – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (GenAI) chatbots extend transformative impact in higher education. Current research requires more comprehensive evaluations of the collaborative learning fostered by students and GenAI chatbots. However, existing articles have rarely explored the dynamic process of student--AI collaboration in higher…
Descriptors: Undergraduate Students, Artificial Intelligence, Technology Uses in Education, Computer Mediated Communication
Fan Xu; Ana-Paula Correia – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) is an essential skill for preparing the younger generation to succeed in an AI-driven world, with pair programming emerging as a widely used approach to foster these skills. However, the role of individual factors and mutual engagement in shaping CT skills within pair programming remains underexplored,…
Descriptors: Computation, Thinking Skills, Learner Engagement, Middle School Students
Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention

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