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Xiaomeng Huang; Xavier Ochoa – Journal of Learning Analytics, 2025
Collaboration skills are fundamental to effective collaborative learning, career success, and responsible citizenship. Collaborative learning analytics (CLA) systems hold significant potential in helping students develop these skills by automatically collecting group interaction data, analyzing skill levels, and providing actionable feedback so…
Descriptors: Learning Analytics, Cooperative Learning, Cooperation, Skill Development
Caitlin Snyder; Clayton Cohn; Joyce Horn Fonteles; Gautam Biswas – Grantee Submission, 2025
Recently, there has been a surge in developing curricula and tools that integrate computing (C) into Science, Technology, Engineering, and Math (STEM) programs. These environments foster authentic problem-solving while facilitating students' concurrent learning of STEM+C content. In our study, we analyzed students' behaviors as they worked in…
Descriptors: Learning Analytics, Problem Solving, STEM Education, Computation
Zhennan Sun; Mingyong Pang; Yi Zhang – Education and Information Technologies, 2025
The evolution of individual and global learning preferences is influenced by correlation factors. This study introduces a novel evolutionary modeling approach to observe and analyze factors that affect the evolution of learning preferences. The influencing factors considered in this study are closely interwoven with the underlying personality of…
Descriptors: Learning Analytics, Learning Processes, Preferences, Student Characteristics
Joni Lämsä; Justin Edwards; Eetu Haataja; Marta Sobocinski; Paola R. Peña; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2024
The theory of socially shared regulation of learning (SSRL) suggests that successful collaborative groups can identify and respond to trigger events stemming from cognitive or emotional obstacles in learning. Thus, to develop real-time support for SSRL, novel metrics are needed to identify different types of trigger events that invite SSRL. Our…
Descriptors: Cooperative Learning, Learning Analytics, Linguistics, Physiology
Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
Rachelle Esterhazy; Rogers Kaliisa; Daniel Sanchez; Malcolm Langford; Crina Damsa – Journal of Learning Analytics, 2025
The advent of advanced technology has opened new horizons for studying collaborative learning, although ambiguity remains in the classification and rationale for combining modalities in multimodal collaboration analytics (MMCA). Addressing this gap is crucial for the progression of collaborative learning practices and research. This review…
Descriptors: Learning Analytics, Cooperative Learning, Learning Processes, Learning Modalities
Charlott Sellberg; Amit Sharma – International Journal of Computer-Supported Collaborative Learning, 2025
Collaborative learning in high-fidelity simulators is an important part of how master mariner students are preparing for their future career at sea by becoming part of a ship's bridge team. This study aims to inform the design of multimodal learning analytics to be used for providing automated feedback to master mariner students engaged in…
Descriptors: Cooperative Learning, Learning Analytics, Simulation, Ethnography
Xavier Ochoa; Xiaomeng Huang; Adam Charlton – Journal of Learning Analytics, 2024
Even before the inception of the term "learning analytics," researchers globally had been investigating the use of various feedback systems to support the self-regulation of participation and promote equitable contributions during collaborative learning activities. While some studies indicate positive effects for distinct subgroups of…
Descriptors: Learning Analytics, Feedback (Response), Independent Study, Cooperative Learning
Ouyang, Fan; Xu, Weiqi; Cukurova, Mutlu – International Journal of Computer-Supported Collaborative Learning, 2023
Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance of examining the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical…
Descriptors: Artificial Intelligence, Learning Analytics, Cooperative Learning, Problem Solving
Reet Kasepalu; Pankaj Chejara; Luis P. Prieto; Tobias Ley – International Journal of Computer-Supported Collaborative Learning, 2023
Teachers in a collaborative learning (CL) environment have the demanding task of monitoring several groups of students at the same time and intervening when needed. This withitness (both the situational awareness and interventions taken in class) of the teacher might be increased with the help of a guiding dashboard alerting the teacher of…
Descriptors: Cooperative Learning, Teacher Behavior, Observation, Educational Technology
Yingbo Ma – ProQuest LLC, 2023
Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…
Descriptors: Cooperative Learning, Models, Interaction, Behavior
Halim Acosta; Seung Lee; Daeun Hong; Wookhee Min; Bradford Mott; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2025
Understanding the relationship between student behaviors and learning outcomes is crucial for designing effective collaborative learning environments. However, collaborative learning analytics poses significant challenges, not only due to the complex interplay between collaborative problem-solving and collaborative dialogue but also due to the…
Descriptors: Learning Analytics, Cooperative Learning, Student Behavior, Prediction
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
Belle Dang; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2024
Socially shared regulation in learning (SSRL) contributes to successful collaborative learning (CL). Empirical research into SSRL has received considerable attention recently, with increasingly available multimodal data, advanced learning analytics (LA), and artificial intelligence (AI) providing promising research avenues. Yet, integrating these…
Descriptors: Learning Analytics, Cooperative Learning, Artificial Intelligence, Epistemology
Xing, Wanli; Zhu, Gaoxia; Arslan, Okan; Shim, Jaesub; Popov, Vitaliy – Journal of Computing in Higher Education, 2023
Engagement is critical in learning, including computer-supported collaborative learning (CSCL). Previous studies have mainly measured engagement using students' self-reports which usually do not capture the learning process or the interactions between group members. Therefore, researchers advocated developing new and innovative engagement…
Descriptors: Learning Analytics, Cooperative Learning, Learner Engagement, Learning Motivation

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