International Journal of Computer-Supported Collaborative Learning

An in-depth analysis of collaborative problem solving (CPS) patterns contributes to understand team dynamics and effective paths to conflict resolution. However, there remains the lack of a perspective in the field of CPS research that organically combines the cognitive, meta-cognitive, and social-communicative dimensions. Moreover, the analysis of CPS sequences has primarily focused on the temporal dimension while overlooking the differences in spatial dimensions. To shed further light on the nature of CPS in computer-based environments, this study collected discourse data generated by 24 university students through an online synchronous chat tool. They were student teachers from a variety of disciplines (math, history, English, etc.) who were required to accomplish two tasks: instructional design and multimedia courseware development. Specifically, a three-stage analytical framework was proposed to code, cluster, and analyze these discourse data to further explore the differences in CPS patterns. We clustered time sequences by calculating the distance similarity metric via the dynamic time warping (DTW) method, which took into account both the spatial and temporal characteristics of the time sequences. Consequently, 16 time sequences of CPS processes were divided into 2 kinds of clusters (CPS subgroups), i.e., cluster 1 and cluster 2. From the statistical analysis, both clusters actively used the skills included in the meta-cognitive dimensions. Cluster 1 was oriented toward the solution of the problem whereas cluster 2 focused primarily on the requirements of the collaborative problem itself. From the process mining analysis, solution-driven cluster 1 tended to focus on expressing specific ideas and evaluating and summarizing them, intermittently monitoring and regulating task progress. Problem-driven cluster 2 tended to express specific ideas intermittently, and lacked the process of summarizing and evaluating different ideas to further filter out the best solutions. Finally, we summarized the implications of this study from theoretical and practical perspectives and discussed future research directions with regard to the limitations of this study.

Collaborative skills are crucial in knowledge-rich domains, such as medical diagnosing. The Collaborative Diagnostic Reasoning (CDR) model emphasizes the importance of high-quality collaborative diagnostic activities (CDAs; e.g., evidence elicitation and sharing), influenced by content and collaboration knowledge as well as more general social skills, to achieve accurate, justified, and efficient diagnostic outcomes (Radkowitsch et al., 2022). However, it has not yet been empirically tested, and the relationships between individual characteristics, CDAs, and diagnostic outcomes remain largely unexplored. The aim of this study was to test the CDR model by analyzing data from three studies in a simulation-based environment and to better understand the construct and the processes involved (N = 504 intermediate medical students) using a structural equation model including indirect effects. We found various stable relationships between individual characteristics and CDAs, and between CDAs and diagnostic outcome, highlighting the multidimensional nature of CDR. While both content and collaboration knowledge were important for CDAs, none of the individual characteristics directly related to diagnostic outcome. The study suggests that CDAs are important factors in achieving successful diagnoses in collaborative contexts, particularly in simulation-based settings. CDAs are influenced by content and collaboration knowledge, highlighting the importance of understanding collaboration partners’ knowledge. We propose revising the CDR model by assigning higher priority to collaboration knowledge compared with social skills, and dividing the CDAs into information elicitation and sharing, with sharing being more transactive. Training should focus on the development of CDAs to improve CDR skills.

This study analyzed collaborative invention projects by teams of lower-secondary (13–14-year-old) Finnish students. In invention projects, student teams design and make materially embodied collaborative inventions using traditional and digital fabrication technologies. This investigation focused on the student teams’ knowledge creation processes by examining how they applied maker practices (i.e., design process, computer engineering, product design, and science practices) in their co-invention projects and the effects of teacher and peer support. In our investigations, we relied on video data and on-site observations, utilizing and further developing visual data analysis methods. Our findings assist in expanding the scope of computer-supported collaborative learning (CSCL) research toward sociomaterially mediated knowledge creation, revealing the open-ended, nonlinear, and self-organized flow of the co-invention projects that take place around digital devices. Our findings demonstrate the practice-based, knowledge-creating nature of these processes, where computer engineering, product design, and science are deeply entangled with design practices. Furthermore, embodied design practices of sketching, practical experimenting, and working with concrete materials were found to be of the essence to inspire and deepen knowledge creation and advancement of epistemic objects. Our findings also reveal how teachers and peer tutor students can support knowledge creation through co-invention.

In online learning at scale, wherein instructional videos play a central role, interactive tools are often integrated to counteract passive consumption. For example, the forum or discussion board is widely used, and an emerging functionality, danmaku, which enables messages to be synchronized with video playback, has also been utilized recently. To explore how mass participation is accommodated and what categories of interaction learners implement, this study utilizes analysis of interaction and manual content analysis through learner-generated text data from two specific tools employed in a massive open online course (MOOC) setting: the discussion board (N = 739) and danmaku (N = 2435). Results of the analysis of interaction indicate that mass participation is managed differently by the tools: danmaku fosters a collective space for massive participants, while the discussion board organizes them into threaded small groups. In addition, results of the content analysis show danmaku primarily supports indirect interaction with a focus on the socio-emotional dimension, while the discussion board serves as a platform for direct discussions, particularly in the cognitive dimension. Furthermore, within the context of large-scale engagement, various levels of joint interaction, in addition to collaboration, are discerned and discussed in both socio-emotional and cognitive interactions. The findings offer insights for developing sociable and scalable socio-technical environments in computer-supported collaborative learning (CSCL), addressing emerging educational trends. Practical implications for educational design based on these findings are also discussed.

Acknowledging the pivotal role of noticing in teachers’ professional work, it is noteworthy that its application in dialogic activities remains an area that has yet to be studied. In this study, we examine mathematics teachers’ noticing of dialogue among peers working together on problem-solving tasks and investigate the impact of a professional development intervention focused on dialogue on teachers’ noticing practices. Through think-aloud interviews, 14 teachers provided insights into their noticing practices by attending to and responding to video excerpts of dyads engaged in collaborative problem-solving in computer-supported learning environments. Their noticing practices were analyzed using a Bakhtinian-informed dialogic framework. Subsequently, the teachers participated in a professional development intervention centered around dialogue and were interviewed again using the same video excerpts. The second round of interviews was also analyzed using the same dialogic framework. The findings shed light on the initial state of teachers’ noticing and indicate a discernible improvement in their ability to notice specific dialogic attributes. These findings offer valuable insights into how collaboration and dialogue between students can be effectively supported. Additionally, the study discusses how teachers envision dialogue and considers the capacity and limitations of incorporating a dialogic vision into the noticing paradigm.

Successful computer-supported collaborative learning (CSCL) relies on collaborative group engagement, a complex construct characterized by multifaceted, dynamic, socio-emotional, and socio-cognitive processes. This paper provides a detailed analysis of collaborative group engagement, with a particular focus on nonverbal behaviors as indicators of high versus low group engagement. Using video observations and a multi-method approach, we examine in detail the relationships between different dimensions of group engagement (i.e., behavioral, social, cognitive, and conceptual-to-consequential engagement) and nonverbal behaviors. Using qualitative case analysis, we also provide a rich examination of selected cases to identify the role that nonverbal behaviors play in high-engagement sequences compared with low-engagement sequences. Our findings shed light on specific nonverbal behaviors, including nodding, laughing, and eye contact, as significant indicators of high versus low collaborative group engagement. Notably, more of these nonverbal behaviors are evident in high-engagement sequences, suggesting mutual reinforcement on each dimension of engagement—with the exception of behavioral engagement, where increased laughing or smiling is evident in low-engagement sequences, but still serves a productive group process. The paper concludes with a discussion and implications of the findings. By demonstrating the role of nonverbal behaviors as important indicators, this work contributes to the understanding of the complex, dynamic, and contextualized nature of collaborative group engagement in CSCL settings.

Knowledge building (KB) competencies are crucial for undergraduates’ creative knowledge work and academic success. While there is substantial research on KB discourse, there are limited efforts in examining how KB competencies in the conceptual, metacognitive, socio-emotional, and epistemic dimensions are demonstrated in KB discourse and how the competencies can be scaffolded. Previous studies suggest the effectiveness of reflective assessment on sustainable and productive KB discourse. This study developed a framework for analyzing KB competencies using KB discourse moves. It also examined whether a KB design augmented by reflective assessment enriched by analytic tools and artifacts could foster undergraduates’ KB competencies, and if so, how. This KB design involves principle-based pedagogy with the participants engaging in collaborative inquiry and discussion on Knowledge Forum, and reflective assessment using (a) super synthesis notes, (b) KB interaction rubrics, and (c) learning analytics visualization tools. Qualitative tracking and lag sequential pattern analysis of Knowledge Forum’s discourse revealed that implementing reflective assessment supported by analytics and artifacts could help the undergraduate students develop KB competencies manifested in discourse with evidence of conceptual advance, epistemic engagement, metacognition, and productive socio-emotional interactions with a collective focus. The thematic analysis illustrated the dynamics through which the design enriched by standards and visualizations helped the undergraduates develop KB competencies: leveraging synthesis super notes to promote conceptual and metacognitive advancement and epistemic engagement; employing KB interaction rubrics to cultivate metacognitive, socio-emotional, and epistemic competencies; and harnessing KBDeX visualizations to promote metacognitive and conceptual advancement and to facilitate epistemic engagement. The implications of scaffolding students’ epistemic agency, metacognition, productive collaborative inquiry, and developing KB competencies in a technology-supported metacognitive learning environment are discussed.

In this study, we investigate how pre-service teachers’ group dialogues emerged and intersected across time and space as students collaboratively constructed a video-based mind map to prepare for oral exams in a pedagogy course. The study was conducted as part of a design-based research project investigating the ways that video-based mind maps can support learning as both a collaborative activity and a classroom resource. We applied interaction analysis methods to recordings taken during the production of the mind map as well as the videos made by students within the mind map itself to analyze synchronous and asynchronous dialogues among group members as they viewed, recorded, and uploaded videos. The findings offer an in-depth understanding of how collaboration occurs in different space-time configurations within and across groups as mediated by video resources. We discuss how these findings contribute to computer-supported collaborative learning (CSCL) research on the ways collaboration can emerge across different levels of activity as well as the pedagogical implications for introducing video-based dialogues into the classroom.

Team cohesion is critical in driving successful outcomes for teams in collaborative learning settings. It shapes team behaviour, fostering shared perceptions, group synchrony and a common goal-oriented approach. This affinity becomes evident in dynamic interactions, offering insights into team behaviour through interaction data analysis. Interpreting interaction data proves complex, hampering our understanding and insights into shared team perceptions and task cohesion development. This paper used temporal motif analysis to examine the changes in team members’ cohesive perceptions and behaviours, including task cohesion, performance outcomes, engagement and group synchrony. Trace data from an online work-integrated learning environment captured learning behaviours, while responses to a questionnaire at different stages of a study program captured task cohesion and cohesive perceptions. The findings reveal teams with strong task cohesion and high performance tend to share similar cohesive perceptions driven by interdependent interactions. Conversely, teams with different cohesion perceptions have lower interaction interdependence and poorer performance. Through analysing team interaction data, this study uncovered key insights to promote positive adjustments aligning team perceptions, enhancing collaborative learning and offering support for improved performance, engagement and synchrony among teams, ultimately benefiting learning outcomes and the cultivation of skills and competencies.