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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
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
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
Jyun-Chen Chen; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Based on the embodied cognition perspective, interdisciplinary hands-on learning combines several disciplines, such as science, technology, engineering and mathematics (STEM), to improve students' capacity to solve real-world problems. Despite the popularity of interdisciplinary hands-on learning, particularly the six-phase 6E model,…
Descriptors: Interdisciplinary Approach, Experiential Learning, STEM Education, Problem Solving
Richter, Juliane; Lachner, Andreas; Jacob, Leonie; Bilgenroth, Friederike; Scheiter, Katharina – Journal of Computer Assisted Learning, 2022
Background: Engaging students in computer-assisted guided inquiry learning has great potential to scaffold their scientific understanding: Students are expected to improve their scientific problem-solving skills, and at the same time gain a deep conceptual understanding of the subject-matter. Additional generative activities such as creating video…
Descriptors: Self Concept, Problem Solving, Video Technology, Computer Assisted Instruction
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
Julius Moritz Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…
Descriptors: Video Technology, Models, Cues, Problem Solving
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
Liru Hu; Gaowei Chen; Jiajun Wu – Journal of Computer Assisted Learning, 2024
Background: The existing research on dialogue-based learning and teaching predominantly highlights its capacity to yield productive educational outcomes, yet it often overlooks the pivotal factor of participation equity, which is fundamental to ensuring the efficacy of dialogic teaching and learning. Objectives: In this study, participation equity…
Descriptors: Problem Solving, Participation, Equal Education, Student Participation
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
Pramila-Savukoski, Sari; Kärnä, Raila; Kuivila, Heli-Maria; Oikarainen, Ashlee; Törmänen, Tiina; Juntunen, Jonna; Järvelä, Sanna; Mikkonen, Kristina – Journal of Computer Assisted Learning, 2023
Background: Health sciences education prepares students for social- and healthcare by developing evidence-based nursing, leadership and working life skills, including collaboration. Due to the changes caused by the global pandemic, health sciences education has shifted more to online and hybrid contexts, which can challenge students' competence…
Descriptors: Competence, Health Sciences, Student Development, Blended Learning
Mohammad Nayef Ayasrah; Mohamad Ahmad Saleem Khasawneh; Mazen Omar Almulla; Amoura Hassan Aboutaleb – Journal of Computer Assisted Learning, 2025
Background: One area that has been dramatically changed by artificial intelligence (AI) is educational environments. Chatbots, Recommender Systems, Adaptive Learning Systems and Large Language Models have been emerging as practical tools for facilitating learning. However, using such tools appropriately is challenging. In this regard, the…
Descriptors: Test Construction, Test Validity, Test Reliability, Rating Scales
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
Zhihui Cai; Xin Zhang; Caiyan Liu; Jieni Zhan – Journal of Computer Assisted Learning, 2025
Background: Problem-solving ability is an important skill for students to develop in the 21st century. Many previous studies have focused on the impact of diverse digital educational games on problem-solving ability. However, there is inconsistency in the findings, with some studies reporting positive effects of digital game-based learning (DGBL)…
Descriptors: Game Based Learning, Video Games, Problem Solving, 21st Century Skills
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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