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Tamisha Thompson; Jennifer St. John; Siddhartha Pradhan; Erin Ottmar – Journal of Computer Assisted Learning, 2025
Background: Educational technologies typically provide teachers with analytics regarding student proficiency, but few digital tools provide teachers with process-based information about students' variable problem-solving strategies as they solve problems. Utilising design thinking and co-designing with teachers can provide insight to researchers…
Descriptors: Mathematics Instruction, Educational Technology, Problem Solving, Instructional Design
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Qian Tian; Xudong Zheng – Journal of Computer Assisted Learning, 2024
Background: During the COVID-19 pandemic, online collaborative problem solving (online CPS) has become one of the most crucial learning methods to develop students' learning performance. However, it remains unclear of the effectiveness of the online CPS method on students' learning performance. Objectives: To explore the overall effect of online…
Descriptors: Electronic Learning, COVID-19, Pandemics, Teaching Methods
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Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
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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
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Hui-Tzu Chang; Chia-Yu Lin – Journal of Computer Assisted Learning, 2024
Background: Numerous higher education institutions worldwide have adopted English-language-medium computer science courses and integrated online problem-solving competitions to bridge gaps in theory and practice (Alhamami "Education and Information Technologies," 2021; 26: 6549-6562). Objectives: This study aimed to investigate the…
Descriptors: Artificial Intelligence, Instructional Improvement, Problem Solving, Competition
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Flor, Michael; Andrews-Todd, Jessica – Journal of Computer Assisted Learning, 2022
Background: Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology-enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory-driven measurements that are usually carried out…
Descriptors: Automation, Documentation, Cooperative Learning, Teamwork
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Hwang, Gwo-Jen; Chang, Shao-Chen; Song, Yanjie; Hsieh, Min-Chuan – Journal of Computer Assisted Learning, 2021
Scholars have suggested that flipped learning can be enhanced by designing effective in-class learning activities to improve students' higher order thinking skills. Problem posing has been recognized as such a learning strategy that has great potential for improving students' higher order thinking skills. However, it has been reported as a…
Descriptors: Flipped Classroom, Educational Environment, Electronic Learning, Concept Mapping
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Gyllen, J.; Stahovich, T.; Mayer, R. – Journal of Computer Assisted Learning, 2018
Time on task has been recognized as an important variable in academic learning, but self-report measures of study time are problematic. Therefore, this study employs an automated system for recording time spent reading a course textbook. College students in an introductory engineering course accessed their textbook online. The book contained pages…
Descriptors: Undergraduate Students, Engineering Education, Electronic Learning, Electronic Publishing
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Chang, Wen-Hui; Liu, Yuan-Chen; Huang, Tzu-Hua – Journal of Computer Assisted Learning, 2017
The purpose of this study is to develop a multi-dimensional scale to measure students' awareness of key competencies for M-learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical…
Descriptors: Test Construction, Multidimensional Scaling, Electronic Learning, Test Reliability
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van Schaik, P.; Martin, S.; Vallance, M. – Journal of Computer Assisted Learning, 2012
In contexts other than immersive virtual environments, theoretical and empirical work has identified flow experience as a major factor in learning and human-computer interaction. Flow is defined as a "holistic sensation that people feel when they act with total involvement". We applied the concept of flow to modeling the experience of…
Descriptors: Structural Equation Models, Interaction, Problem Solving, Psychometrics