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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
Ridwan Whitehead; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2025
Incorporating non-verbal data streams is essential to understanding the dynamics of interaction within collaborative learning environments in which a variety of verbal and non-verbal modes of communication intersect. However, the complexity of non-verbal data -- especially gathered in the wild from collaborative learning contexts -- demands…
Descriptors: Case Studies, Nonverbal Communication, Video Technology, Data Analysis
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
Hadyaoui, Asma; Cheniti-Belcadhi, Lilia – Smart Learning Environments, 2023
This article introduces an ontology-based framework for group assessment analytics that investigates the impact of intra-group interactions on group performance within the context of project-based collaborative learning (PBCL). Additionally, it aims to predict learners' performance based on these interactions. The study involved 312 first-degree…
Descriptors: Learning Analytics, Academic Achievement, Prediction, Student Projects
Zheng, Lanqin; Niu, Jiayu; Zhong, Lu – British Journal of Educational Technology, 2022
Learning analytics (LA) has been widely adopted in research on education. However, most studies in the area have conducted LA after computer-supported collaborative learning (CSCL) activities rather than during CSCL. To address this problem, this study proposed a LA-based real-time feedback approach based on a deep neural network model to improve…
Descriptors: Learning Analytics, Feedback (Response), Outcomes of Education, Cooperative Learning
Zheng, Lanqin; Kinshuk; Fan, Yunchao; Long, Miaolang – Education and Information Technologies, 2023
Online collaborative learning has been an effective pedagogy in the field of education. However, productive collaborative learning cannot occur spontaneously. Learners often have difficulties in collaborative knowledge building, group performance, coregulated behaviors, learning engagement, and social interaction. To promote productive…
Descriptors: Learning Analytics, Performance, Electronic Learning, Cooperative Learning
Li, Xu; Ouyang, Fan; Chen, WenZhi – Journal of Computing in Higher Education, 2022
Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Group Dynamics, Grouping (Instructional Purposes)
Changhao Liang; Rwitajit Majumdar; Yuta Nakamizo; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…
Descriptors: Algorithms, Group Dynamics, Group Activities, Learning Analytics
Worsley, Marcelo; Anderson, Khalil; Melo, Natalie; Jang, JooYoung – Journal of Learning Analytics, 2021
Collaboration has garnered global attention as an important skill for the 21st century. While researchers have been doing work on collaboration for nearly a century, many of the questions that the field is investigating overlook the need for students to learn how to read and respond to different collaborative settings. Existing research focuses on…
Descriptors: Learning Analytics, Cooperative Learning, 21st Century Skills, College Students
Kam Hong Shum; Samuel Kai Wah Chu; Cheuk Yu Yeung – Interactive Learning Environments, 2023
This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…
Descriptors: Student Behavior, Online Courses, Cooperative Learning, Computer Software
Bao, Haogang; Li, Yanyan; Su, You; Xing, Shuang; Chen, Nian-Shing; Rosé, Carolyn Penstein – Technology, Pedagogy and Education, 2021
The learning analytics dashboard (LAD) has been recognised as a useful tool to facilitate teachers' diagnosis and intervention in collaborative learning. However, little empirical evidence has been reported concerning the effects of LAD on teachers in computer-supported collaborative learning (CSCL). The purpose of this study was to evaluate the…
Descriptors: Learning Analytics, Visual Aids, Computer Interfaces, Educational Diagnosis
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
Hui, Bowen – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of this work is to illustrate the processes involved in managing teams in order to assist designers and developers to build software that support teamwork. A deeper investigation into the role of team analytics is discussed in this article. Design/methodology/approach: Many researchers over the past several decades studied the…
Descriptors: Design, Guidelines, Research Needs, Teamwork
Martinez-Maldonado, Roberto – International Journal of Computer-Supported Collaborative Learning, 2019
In Computer-Supported Collaborative Learning (CSCL) classrooms it may be challenging for teachers to keep awareness of certain aspects of the learning process of each small group or assess whether the enactment of the class script deviates from the original plan. Orchestration tools, aimed at supporting the management of the increasing uncertainty…
Descriptors: Computer Assisted Instruction, Handheld Devices, Teacher Attitudes, Cooperative Learning
Hur, Paul; Bosch, Nigel; Paquette, Luc; Mercier, Emma – International Educational Data Mining Society, 2020
Collaborative problem solving behaviors are difficult to identify and foster due to their amorphous and dynamic nature. In this paper, we investigate the value of considering early class period behaviors, based on small group development theory, for building predictive machine learning models of collaborative behaviors during problem solving. Over…
Descriptors: Cooperative Learning, Interaction, Peer Relationship, Handheld Devices