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Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
Sun Kyung Kim; Youngho Lee; Hye Ri Hwang; Oe Nam Kim – Journal of Computer Assisted Learning, 2025
Background: Comprehensive assessment of skills and performance are necessary to improve the quality of care in nursing education. Various factors pose challenges to accurate assessments, including high student-teacher ratio and observer bias. Objectives: To establish an assessment system based on first-person video of smart glasses and validate…
Descriptors: Handheld Devices, Technology, Video Technology, Evaluation Methods
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
Yuqin Yang; Xueqi Feng; Gaoxia Zhu; Kui Xie – Journal of Computer Assisted Learning, 2024
Background: Undergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer-supported collaborative inquiry approaches, such as KB--the focus of this…
Descriptors: Undergraduate Students, Cooperative Learning, Epistemology, Inquiry
Changqin Huang; Jianhui Yu; Fei Wu; Yi Wang; Nian-Shing Chen – Journal of Computer Assisted Learning, 2024
Background: Investigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on…
Descriptors: MOOCs, Discussion Groups, Computer Mediated Communication, Learning Processes
Saleh Alhazbi; Afnan Al-ali; Aliya Tabassum; Abdulla Al-Ali; Ahmed Al-Emadi; Tamer Khattab; Mahmood A. Hasan – Journal of Computer Assisted Learning, 2024
Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…
Descriptors: Learning Analytics, Independent Study, Higher Education, College Students
Tiphaine Colliot; Abraham E. Flanigan – Journal of Computer Assisted Learning, 2024
Background: Many instructors transitioned their courses from face-to-face environments to computer-mediated learning environments (CMLEs) following the onset of the coronavirus disease 2019 (COVID-19) pandemic. However, little was known about how teleconferencing platforms and their corresponding functions affect student learning when the COVID-19…
Descriptors: Reading Processes, Notetaking, Video Technology, Lecture Method
Fan, Yizhou; Tan, Yuanru; Rakovic, Mladen; Wang, Yeyu; Cai, Zhiqiang; Shaffer, David Williamson; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Select and enact appropriate learning tactics that advance learning has been considered a critical set of skills to successfully complete highly flexible online courses, such as Massive open online courses (MOOCs). However, limited by analytic methods that have been used in the past, such as frequency distribution, sequence mining and…
Descriptors: MOOCs, Students, Learning Processes, Learning Strategies
Wang, Wei-Sheng; Cheng, Yu-Ping; Lee, Hsin-Yu; Lin, Chia-Ju; Huang, Yueh-Min – Journal of Computer Assisted Learning, 2023
Background: Benefited from advances in technology, virtual reality (VR) has been widely applied to learning content in operational training as well as hands-on courses. However, most current studies tend to evaluate learning effectiveness in this application, and few were focused on how learners can be benefited from transferring the knowledge…
Descriptors: Computer Simulation, Learning, Experiential Learning, Anxiety
Daniela Decker; Martin Merkt – Journal of Computer Assisted Learning, 2024
Background: Virtual reality (VR) offers much potential for learning, but it challenges learners' orientation. Objectives: This paper investigates whether it is possible to use light or movement cues to facilitate orientation in a search task in a desktop-VR environment so that participants can better attend to the learning content presented…
Descriptors: Cues, Educational Technology, Computer Simulation, Light
Jun Oshima; Ritsuko Oshima; Anthony J. Taiki Kawakubo – Journal of Computer Assisted Learning, 2025
Background: This study aimed to develop and test new analytics for knowledge-building practices from the transactive perspective. Based on a literature review, network analysis was identified as a promising analytical tool for these practices. We observed two aspects of network analysis that could be further developed: the multilayers of networks…
Descriptors: Network Analysis, Concept Formation, Learning Processes, Performance
Jansen, Renée S.; Leeuwen, Anouschka; Janssen, Jeroen; Kester, Liesbeth – Journal of Computer Assisted Learning, 2022
Background: Learners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self-regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching…
Descriptors: Student Behavior, Learning Processes, Online Courses, Personal Autonomy
Tan, Sophia Huey Shan; Thibault, Guillaume; Chew, Anna Chia Yin; Rajalingam, Preman – Journal of Computer Assisted Learning, 2022
Background: Different types of assessments influence learning and learning behaviour. Multiple-choice questions (MCQs) reward partial knowledge and encourage surface learning, while open-ended questions (OEQs) promote deeper learning. Currently, MCQs is part of team-based learning (TBL) curriculum, and it is challenging to implement OEQs as…
Descriptors: Questioning Techniques, Academic Achievement, Learner Engagement, Learning Processes
Tristan H. S. de Jonge; Timo Kegelaar; Fabiola Figueroa Esquivel – Journal of Computer Assisted Learning, 2025
Background: Learner-generated digital media has gained significant attention as a supplementary learning tool. However, a need exists for empirical research to discern among various learner-generated digital media formats. One potential area of divergence lies in the arousal levels evoked during media creation due to varying emphasis on the…
Descriptors: Student Projects, Multimedia Materials, Nonverbal Communication, Comparative Analysis
Zhiwei Liu; Haode Zuo; Yongjing Lu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, a generative artificial intelligence (GenAI) chatbot, has gained significant traction as a tool for supporting students learning. Despite its growing popularity, there is still no academic consensus on its effectiveness in enhancing students' academic achievement. Objectives: This study aims to explore the effect of ChatGPT on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Meta Analysis

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