The goal of this paper is to report on a meta-analysis about the effects of Computer-Supported Collaborative Learning (CSCL) in STEM education. The analysis is based on 316 outcomes from 143 studies ...that examined the effects of CSCL published between 2005 and 2014. Our analysis showed that the overall effect size of STEM CSCL was 0.51, a moderate but notable effect size in educational research. The effect was greatest on process outcomes, followed by knowledge outcomes, and affective outcomes. The sizes of the effects were moderated by types of technology and pedagogy, educational levels of learners, and learning domains. Moderators further interacted so that effects of technology and pedagogy varied depending on the modes of collaboration, learners' educational levels, and domains of learning. The current study demonstrates the overall advantage of CSCL in STEM education and highlights a need to understand how these variables may interact to contribute to overall CSCL effectiveness.
•A comprehensive meta-analysis of the effects of Computer-Supported Collaborative Learning (CSCL) in STEM education.•The overall effect size of STEM CSCL was 0.51, a moderate effect size notable in educational research.•CSCL effectiveness was moderated by the educational levels of learners, domains of learning, technology and pedagogies.•The effect of CSCL technology and pedagogy was moderated by collaboration types, educational levels, and learning domains.•There is no one-size-fits-all solution in CSCL.
A prevailing trend in CSCL literature has been the study of students' participatory roles. The majority of existing studies examine a single collaborative task or, at most, a complete course. This ...study aims to investigate the presence —or the lack thereof— of a more enduring disposition that drives student participation patterns across courses. Based on data from a 4-year program where 329 students used CSCL to collaborate in 10 successive courses (amounting up to 84,597 interactions), we identify the emerging roles using centrality measures and latent profile analysis (LPA) and trace the unfolding of roles over the entire duration of the program. Thereafter, we use Mixture Hidden Markov Models (MHMM) —methods that are particularly useful in detecting “latent traits” in longitudinal data— to identify how students' roles, transition, persist or evolve over time. Relevant covariates were also examined to explain students’ membership of different trajectories. We identified three different roles (leader, mediator, isolate) at the course level. At the program level, we found three distinct trajectories: an intense trajectory with mostly leaders, a fluctuating trajectory with mostly mediators, and a wallowing-in-the-mire trajectory with mostly isolates. Our results show that roles re-emerge consistently regardless of the task or the course over extended periods of time and in a predictable manner. For instance, isolates “assumed” such a role in almost all of their courses over four years.
•Three longitudinal roles in CSCL settings were identified that were homogeneous and relatively stable.•The trajectories were dominated by a certain role: e.g., leaders dominated the intense trajectory.•Roles were likely to re-emerge consistently regardless of the course, e.g., leaders always assumed the role of leaders.•The consistency of longitudinal roles points to a disposition that drives students to assume the same role repeatedly.•A method for studying the longitudinal evolution of student's behavior is described.
This meta-analysis synthesizes research findings on the effects of computer-supported collaborative learning (CSCL) based on its three main elements: (1) the collaboration per se, (2) the use of ...computers, and (3) the use of extra learning environments or tools, or supporting strategies in CSCL. In this analysis, 425 empirical studies published between 2000 and 2016 were extracted and coded, and these generated the following findings. First, the collaboration had significant positive effects on knowledge gain (ES effect size = 0.42), skill acquisition (ES = 0.64), and student perceptions (ES = 0.38) in computer-based learning conditions. Second, computer use led to positive effects on knowledge gain (ES = 0.45), skill acquisition (ES = 0.53), student perceptions (ES = 0.51), group task performance (ES = 0.89), and social interaction (ES = 0.57) in collaborative learning contexts. Third, the use of extra learning environments or tools produced a medium effectfor knowledge gain (ES = 0.55), and supporting strategies resulted in an ES of 0.38 for knowledge gain. Several study features were analyzed as potential moderators.
Computer-supported collaborative concept mapping (CSCCM) leverages technology and concept mapping to support conceptual understanding, as well as collaborative learning to foster knowledge ...co-construction. This article investigated the effect of different instructional designs using CSCCM on students' conceptual understanding, and on the type of processes of knowledge co-construction that students engage. Participants (N = 120) were 10th graders enrolled in their physics course, randomly distributed in dyads. They were asked to draw concept maps related to the conservation of energy law, by using CSCCM with different instructional designs (i.e., control, Exp. 1 and Exp. 2). In the control condition, dyads worked collaboratively all the time. In both Exp. 1 and Exp. 2, dyads worked first individually (one week) and then collaboratively (two weeks). However, in Exp. 2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved significantly for learners in all three experimental conditions, especially in Exp. 2. Statistically significant differences were found in students' knowledge co-construction among the three conditions. Dyads in the control group showed a significantly higher use of quick consensus-building. Dyads in Exp. 1 showed a significantly higher reliance on externalization and elicitation. Dyads in Exp. 2 showed a significantly higher enacting of integration- and conflict-oriented consensus building. Accordingly, an instructional design like Exp. 2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.
•Computer-supported collaborative concept mapping (CSCCM) enhances conceptual learning.•Instructional designs of CSCCM condition students' knowledge co-construction process.•An individual concept mapping preparation phase enhances CSCCM learning outcomes.•Sharing the individual concept map with the peer fosters cognitive group awareness.•A shared individual concept map optimizes students' CSCCM learning outcomes.
Online collaboration is becoming increasingly more common in work life and education, a development that is accentuated by the Covid-19 pandemic. It is thus imperative that students learn to work in ...and as teams in online settings, and that teachers and educational researchers and policymakers understand how online environments enable and constrain student collaboration. However, what has been missing in research on online student collaboration is a focus on students as agents rather than passive learners as well as a lack of focus on student teams as self-organizing teams. This paper reports on a study that investigated the experiences of 1611 graduate students in 315 teams enrolled in an interdisciplinary project-based course during their (forced) transition from face-to-face to online collaboration due to the COVID-19 pandemic. We explored how the transition to online learning affected social interaction and how teams changed their practices to support and sustain social interaction in the online environment. The findings show that the changed conditions of the learning environment influenced social interaction in negative ways, but also that team reflection seemed to enable the students to reverse some of the adverse effects and develop practices that supported both the cognitive and socio-emotional dimensions of social interaction. Theoretically, this study suggests possible causes for why social interaction was reduced and provides in-depth knowledge about the relationships between social interaction, social presence, and social space. The study also provides support for theories of learning that emphasize the need to consider students as active agents rather than merely users of the affordances of a virtual learning environment or guided by the teacher's interventions. It makes a unique contribution to the scarce empirical literature on virtual self-organizing student teams in higher education and provides practical implications for teachers and educational researchers and policy makers.
•315 student teams during transition from face-to-face to online collaboration.•Reduced social interaction in the socio-emotional and the cognitive dimension.•Teams developed practices that supported social interaction.•Importance of integrating team reflection as part of course design.•Need to consider students as active agents rather than passive users of affordances.
The analysis of the processes and elements articulating effective Computer Supported Collaborative Learning (CSCL) constitutes a focal research stream in education. Following these streams, ...satisfaction and perceived impact on learning have already been stablished as determining aspects of any type of learning and, particularly, of CSCL. The goal of this study was to identify factors affecting students' satisfaction and perception of impact on learning in CSCL. The Partial Least Squares technique was used, applying a questionnaire to 701 students in a virtual university. The proposed model exhibited high predictive performance, confirming the 13 hypotheses established. The variables confirmation, perceived usefulness, and perceived enjoyment positively and significantly influenced students’ satisfaction with CSCL. Perceived ease of use and perceived usefulness positively and significantly influenced attitude, and attitude, together with perceived enjoyment, were determining factors in perceived impact on learning. These are factors that should be considered when designing CSCL to be implemented both at the institutional and class level, and teachers and students should be aware of these interdependencies for CSCL to be successful.
•We identified factors influencing satisfaction and perceived learning in CSCL students.•Confirmation and perceived usefulness positively influence students' satisfaction with CSCL.•Satisfaction significantly influences the perception of the impact of learning in CSCL.•Perceived usefulness and ease of use influence attitudes towards CSCL.•Attitude and perceived enjoyment are variables that predict perceived impact on learning.
Multimodal learning analytics (MMLA) research has made significant progress in modelling collaboration quality for the purpose of understanding collaboration behaviour and building automated ...collaboration estimation models. Deploying these automated models in authentic classroom scenarios, however, remains a challenge. This paper presents findings from an evaluation of collaboration quality estimation models. We collected audio, video and log data from two different Estonian schools. These data were used in different combinations to build collaboration estimation models and then assessed across different subjects, different types of activities (collaborative‐writing, group‐discussion) and different schools. Our results suggest that the automated collaboration model can generalize to the context of different schools but with a 25% degradation in balanced accuracy (from 82% to 57%). Moreover, the results also indicate that multimodality brings more performance improvement in the case of group‐discussion‐based activities than collaborative‐writing‐based activities. Further, our results suggest that the video data could be an alternative for understanding collaboration in authentic settings where higher‐quality audio data cannot be collected due to contextual factors. The findings have implications for building automated collaboration estimation systems to assist teachers with monitoring their collaborative classrooms.
Practitioners notes
What is already known about this topic
Multimodal learning analytics researchers have established several features as potential indicators for collaboration quality, e.g., speaking time or joint visual attention.
The current state of the art has shown the feasibility of building automated collaboration quality models.
Recent research has provided preliminary evidence of the generalizability of developed automated models across contexts different in terms of given task and subject.
What does this paper add
This paper offers collaboration indicators for different types of collaborative learning activities in authentic classroom settings.
The paper includes a systematic investigation into collaboration quality automated model's generalizability across different tasks, types of tasks and schools.
This paper also offers a comparison between different modalities' potential to estimate collaboration quality in authentic settings.
Implications for practice
The findings inform the development of automated collaboration monitoring systems for authentic classroom settings.
This paper provides evidence on across‐school generalizability capabilities of collaboration quality estimation models.
This descriptive study focuses on using voice activity detection (VAD) algorithms to extract student speech data in order to better understand the collaboration of small group work and the impact of ...teaching assistant (TA) interventions in undergraduate engineering discussion sections. Audio data were recorded from individual students wearing head‐mounted noise‐cancelling microphones. Video data of each student group were manually coded for collaborative behaviours (eg, group task relatedness, group verbal interaction and group talk content) of students and TA–student interactions. The analysis includes information about the turn taking, overall speech duration patterns and amounts of overlapping speech observed both when TAs were intervening with groups and when they were not. We found that TAs very rarely provided explicit support regarding collaboration. Key speech metrics, such as amount of turn overlap and maximum turn duration, revealed important information about the nature of student small group discussions and TA interventions. TA interactions during small group collaboration are complex and require nuanced treatments when considering the design of supportive tools.
Practitioner notes
What is already known about this topic
Student turn taking can provide information about the nature of student discussions and collaboration.
Real classroom audio data of small groups typically have lots of background noise and present challenges for audio analysis.
TAs have little training in how to productively intervene with students about collaborative skills.
What this paper adds
TA interaction with groups primarily focused on task progress and understanding of concepts with negligible explicit support on building collaborative skills.
TAs intervened with the groups often which gave the students little time for uptake of their suggestions or deeper discussion.
Student turn overlap was higher without the presence of TAs.
Maximum turn duration can be an important real‐time turn metric to identify the least verbally active student participant in a group.
Implications for practice and/or policy
TA training should include information about how to monitor groups for collaborative behaviours and when and how they should intervene to provide feedback and support.
TA feedback systems should keep track of previous interventions by TAs (especially in contexts where there are multiple TAs facilitating) and the duration since previous intervention to ensure that TAs do not intervene with a group too frequently with little time for student uptake.
Maximum turn duration could be used as a real‐time metric to identify the least verbally active student in a group so that support could be provided to them by the TAs.
Increasingly, universities are using technology to provide students with more flexible modes of participation. This article presents a cross-case analysis of blended synchronous learning ...environments—contexts where remote students participated in face-to-face classes through the use of rich-media synchronous technologies such as video conferencing, web conferencing, and virtual worlds. The study examined how design and implementation factors influenced student learning activity and perceived learning outcomes, drawing on a synthesis of student, teacher, and researcher observations collected before, during, and after blended synchronous learning lessons. Key findings include the importance of designing for active learning, the need to select and utilise technologies appropriately to meet communicative requirements, varying degrees of co-presence depending on technological and human factors, and heightened cognitive load. Pedagogical, technological, and logistical implications are presented in the form of a Blended Synchronous Learning Design Framework that is grounded in the results of the study.
•Seven cases involving blended synchronous learning in university settings were analysed.•The cross-case analysis revealed 27 emergent design and implementation factors.•Students reported more active learning, enhanced co-presence, and greater flexibility.•The majority of students felt they learnt the same or more than in normal classes.•Tool performance, increased cognitive load, and equity between cohorts were issues.
► Arguing, critical thinking and reasoning are essential objectives in education. ► Learning to argue and arguing to learn have been CSCL research focus. ► Online learning environments lend ...themselves for constructing and sharing arguments. ► Classification of ABCSCL research (108 publications) based on Biggs’ (2003) model. ► Overview of ABCSCL studies on design, curricula, analysis, focus, subject, location.
Learning to argue is an essential objective in education; and online environments have been found to support the sharing, constructing, and representing of arguments in multiple formats for what has been termed Argumentation-Based Computer Supported Collaborative Learning (ABCSCL). The purpose of this review is to give an overview of research in the field of ABCSCL and to synthesize the findings. For this review, 108 publications (89 empirical studies and 19 conceptual papers) on ABCSCL research dating from 1995 through 2011 were studied to highlight the foci of the past 15 years. Building on Biggs’ (2003) model, the ABCSCL publications were systematically categorized with respect to student prerequisites, learning environment, processes, and outcomes. Based on the quantitative and qualitative findings, this paper concludes that ABCSCL environments should be designed in a systematic way that takes the variety of specific conditions for learning into account. It also offers suggestions for educational practice and future research.
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