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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
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
Andy Nguyen; Yeyu Wang; Ridwan Whitehead; Muhammad Ashiq; Sanna Järvelä; David Williamson Shaffer – Journal of Learning Analytics, 2025
This paper presents a transmodal analysis (TMA) study that investigates the interplay between gaze and verbal interactions through regulation-triggering events within the context of socially shared regulation of learning (SSRL) in face-to-face collaborative settings with shared computer-mediated materials. In face-to-face collaborative learning…
Descriptors: Attention, Eye Movements, Verbal Communication, Interaction
Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
Malmberg, Jonna; Saqr, Mohammed; Järvenoja, Hanna; Järvelä, Sanna – Journal of Learning Analytics, 2022
The current study uses a within-person temporal and sequential analysis to understand individual learning processes as part of collaborative learning. Contemporary perspectives of self-regulated learning acknowledge monitoring as a crucial mechanism for each phase of the regulated learning cycle, but little is known about the function of the…
Descriptors: High School Students, Group Activities, Learning Processes, Student Motivation
Halpin, Peter – Journal of Learning Analytics, 2021
This paper addresses dynamical interdependence among the actions of group members. I assume that the actions of each member can be represented as nodes of a dynamical network and then collect the nodes into disjoint subsets (components) representing the individual group members. Interdependence among group members' actions can then be defined with…
Descriptors: Learning Analytics, Group Dynamics, Group Membership, Interpersonal Relationship
Emara, Mona; Hutchins, Nicole M.; Grover, Shuchi; Snyder, Caitlin; Biswas, Gautam – Journal of Learning Analytics, 2021
The integration of computational modelling in science classrooms provides a unique opportunity to promote key 21st century skills including computational thinking (CT) and collaboration. The open-ended, problem-solving nature of the task requires groups to grapple with the combination of two domains (science and computing) as they collaboratively…
Descriptors: Cooperative Learning, Self Management, Metacognition, Computer Science Education
Saucerman, Jenny; Ruis, A. R.; Shaffer, David Williamson – Journal of Learning Analytics, 2017
Learning to solve "complex problems"--problems whose solutions require the application of more than basic facts and skills--is critical to meaningful participation in the economic, social, and cultural life of the digital age. In this paper, we use a theoretical understanding of how professionals use reflection-in-action to solve complex…
Descriptors: Reflection, Problem Solving, Automation, Skill Development
Rau, Martina A. – Journal of Learning Analytics, 2017
STEM instruction often uses visual representations. To benefit from these, students need to understand how representations show domain-relevant concepts. Yet, this is difficult for students. Prior research shows that physical representations (objects that students manipulate by hand) and virtual representations (objects on a computer screen that…
Descriptors: High School Students, Charter Schools, STEM Education, Knowledge Representation
Sutherland, Scot M.; White, Tobin F. – Journal of Learning Analytics, 2016
The development of the constraint-referenced analytics tool for monitoring algebra learning activities presented here came from the desire to firstly, take a more quantitative look at student responses in collaborative algebra activities, and secondly, to situate those activities in a more traditional introductory algebra setting focusing on…
Descriptors: Algebra, Learning Activities, Data Analysis, Cooperative Learning
Pei-Ling Tan, Jennifer; Koh, Elizabeth; Jonathan, Christin; Yang, Simon – Journal of Learning Analytics, 2017
The affordances of learning analytics (LA) tools and solutions are being increasingly harnessed for enhancing 21st century pedagogical and learning strategies and outcomes. However, use cases and empirical understandings of students' experiences with LA tools and environments aimed at fostering 21st century literacies, especially in the K-12…
Descriptors: Critical Reading, Literacy, Student Attitudes, Learning Strategies