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Guo, Lin – Journal of Computer Assisted Learning, 2022
Background: It has been assumed that prompting students to plan, monitor and evaluate their learning process could stimulate strategy use and thereby improve learning outcomes. Objectives: This study aimed to examine the effects of metacognitive prompts on students' self-regulated learning (SRL) and learning outcomes in the context of…
Descriptors: Metacognition, Independent Study, Learning Processes, Outcomes of Education
Carolien A. N. Knoop-van Campen; Joep van der Graaf; Anne Horvers; Rianne Kooi; Rick Dijkstra; Inge Molenaar – Journal of Computer Assisted Learning, 2024
Background: Even though monitoring and control enactment are key aspects of self-regulated learning (SRL), Adaptive learning technologies (ALTs) may reduce the need for learners to monitor and control their learning. Personalized dashboards are effective in supporting learners' monitoring and can potentially support control behaviour. Allowing…
Descriptors: Elementary School Students, Grade 5, Educational Technology, Technology Uses in Education
Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
Evi-Colombo, Alessia; Cattaneo, Alberto; Bétrancourt, Mireille – Journal of Computer Assisted Learning, 2023
Background: While the use of digital technologies in collaborative design tasks have gained acceptance amongst educational researchers and instructors, few studies have analysed the application of video-supported collaborative learning-by-design (VSC-LBD) in the authentic setting of professional education and training. Objectives: This study on…
Descriptors: Knowledge Level, College Students, Nursing Education, Instructional Effectiveness
Yadviga Radzitskaya; Artem Islamov – Journal of Computer Assisted Learning, 2024
Nanolearning represents an educational methodology rooted in personalisation and the individualisation of the educational process, leveraging contemporary information technologies. Nanolearning, closely intertwined with self-regulated learning, entails an individual's capacity to plan, monitor and regulate their learning process, objectives and…
Descriptors: Microcredentials, Teaching Methods, Information Technology, Learning Processes
Explaining Trace-Based Learner Profiles with Self-Reports: The Added Value of Psychological Networks
Jelena Jovanovic; Dragan Gaševic; Lixiang Yan; Graham Baker; Andrew Murray; Danijela Gasevic – Journal of Computer Assisted Learning, 2024
Background: Learner profiles detected from digital trace data are typically triangulated with survey data to explain those profiles based on learners' internal conditions (e.g., motivation). However, survey data are often analysed with limited consideration of the interconnected nature of learners' internal conditions. Objectives: Aiming to enable…
Descriptors: Psychological Patterns, Networks, Profiles, Learning Processes
Bender, Lisa; Renkl, Alexander; Eitel, Alexander – Journal of Computer Assisted Learning, 2021
Background: Past research has shown that seductive details (i.e., interesting, but irrelevant adjuncts in learning materials) hamper learning in short, instructor-paced learning sessions through impaired cognitive processing. Objectives: We integrate theory and research on multimedia learning and self-control to test whether detrimental effects of…
Descriptors: Instructional Materials, Lecture Method, Multimedia Instruction, Relevance (Education)
van Harsel, Milou; Hoogerheide, Vincent; Verkoeijen, Peter; van Gog, Tamara – Journal of Computer Assisted Learning, 2022
Nowadays, students often practice problem-solving skills in online learning environments with the help of examples and problems. This requires them to self-regulate their learning. It is questionable how novices self-regulate their learning from examples and problems and whether they need support. The present study investigated the open questions:…
Descriptors: Sequential Learning, Independent Study, Problem Solving, Electronic Learning
Geng, Xuewang; Yamada, Masanori – Journal of Computer Assisted Learning, 2023
Background: Augmented reality has been widely applied in various fields, and its benefits in language learning have been increasingly recognized. However, the investigation of effective learning behaviours and processes in augmented reality learning environments, taking into account temporality and analysis of differences in learning behaviours…
Descriptors: Learning Analytics, Second Language Learning, Second Language Instruction, Learning Processes
Lisa Stark; Andreas Korbach; Roland Brünken; Babette Park – Journal of Computer Assisted Learning, 2024
Background: Both learning and problem solving are major goals of complex problem solving in engineering education. The order of knowledge construction and problem solving in learning through problem solving, however, has not been explained in current literature. Objectives: To understand their relationships, this study compared the effects of…
Descriptors: Metacognition, Multimedia Instruction, Multimedia Materials, Eye Movements
Yueh-Min Huang; Wei-Sheng Wang; Hsin-Yu Lee; Chia-Ju Lin; Ting-Ting Wu – Journal of Computer Assisted Learning, 2024
Background: Virtual reality (VR) offers significant potential for hands-on learning environments by providing immersive and visually stimulating experiences. Interacting with such environments can bring numerous benefits to learning, including enhanced engagement, knowledge construction, and higher-order thinking. However, many current VR studies…
Descriptors: Computer Simulation, Feedback (Response), Reflection, Experiential Learning
Xie, Heping; Zhao, Tingting; Deng, Sue; Peng, Ji; Wang, Fuxing; Zhou, Zongkui – Journal of Computer Assisted Learning, 2021
Eye movement modelling examples (EMME) are computer-based videos displaying the visualized eye gaze behaviour of a domain expert person (model) while carefully executing the learning or problem-solving task. The role of EMME in promoting cognitive performance (i.e., final scores of learning outcome or problem solving) has been questioned due to…
Descriptors: Eye Movements, Attention, Cognitive Ability, Learning Processes
Jiarui Hou; James F. Lee; Stephen Doherty – Journal of Computer Assisted Learning, 2025
Background: Recent research has demonstrated the potential of mobile-assisted learning to enhance learners' learning outcomes. In contrast, the learning processes in this regard are much less explored using eye tracking technology. Objective: This systematic review study aims to synthesise the relevant work to reflect the current state of eye…
Descriptors: State of the Art Reviews, Eye Movements, Electronic Learning, Handheld Devices
Ziyi Kuang; Fuxing Wang; Frank Andrasik; Xiangen Hu – Journal of Computer Assisted Learning, 2024
Background: Little is known about the effectiveness of instructors when presenting content in videos alone. In recent years, researchers have increasingly begun to explore the effects of instructors' social cues (e.g., eye gaze, body orientation, etc.) on learning. However, previous studies exploring the effects of eye gaze have confounded the…
Descriptors: Teacher Behavior, Eye Movements, Human Body, Teacher Effectiveness
Yi-Fan Li; Jue-Qi Guan; Xiao-Feng Wang; Qu Chen; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: Self-regulated learning (SRL) is a predictive variable in students' academic performance, especially in virtual reality (VR) environments, which lack monitoring and control. However, current research on VR encounters challenges in effective interventions of cognitive and affective regulation, and visualising the SRL processes using…
Descriptors: Electronic Learning, Individualized Instruction, Learning Processes, Performance

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