Future direction for the CSCL field: Methodologies and eight controversies

Ludvigsen, Sten; Creß, Ulrike; Law, Nancy; Stahl, Gerry; Rosé, Carolyn Penstein

doi:10.1007/s11412-017-9268-4

Cited by 10 publications

(9 citation statements)

References 12 publications

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“…Making evidence of team activity available for inspection and assessment has been proposed by the CSCL community as an effective way to encourage team members to reflect on and learn from their own experiences (Knipfer, Prilla, Cress, and Hermann, 2011). As a result, there has been a growing interest in embracing learning analytics methodologies and innovations in CSCL (Ludvigsen, Cress, Law, Stahl, and Rosé, 2017;Wise et al, 2015;Wise, Knight, & Buckingham Shum, 2021;Wise & Schwarz, 2017). For example, van Leeuwen, Janssen, Erkens, and Brekelmans have investigated the effects of various CSCL visualization designs on teachers' ability to diagnose students' participation within groups (2014) and to monitor and regulate multiple groups of students (2015).…”

Section: Learning Analytics and Collaborative Learningmentioning

confidence: 99%

“…Instead, it is intended to show the variety of classic and emerging methods from other fields (i.e., CSCW, team science, AIED, ITS, and EDM) that the learning analytics community can use to provide data-informed support in teamwork training and collaborative learning situations. For example, this has been one of the key arguments to connect CSCL and learning analytics in recent vision papers (e.g., Ludvigsen et al, 2017;Wise & Schwarz, 2017), yet some concerns have been raised. Wise and Schwarz (2017) warned the community about the risk of creating sophisticated group models based on lowlevel data (e.g., clickstreams and eye-gaze saccades) that cannot be translated into forms comprehensible to teachers and learners.…”

Section: Learning Analytics and Collaborative Learningmentioning

confidence: 99%

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What Do You Mean by Collaboration Analytics? A Conceptual Model

Martínez-Maldonado

Gašević

Echeverria

et al. 2021

JLA

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Using data to generate a deeper understanding of collaborative learning is not new, but automatically analyzing log data has enabled new means of identifying key indicators of effective collaboration and teamwork that can be used to predict outcomes and personalize feedback. Collaboration analytics is emerging as a new term to refer to computational methods for identifying salient aspects of collaboration from multiple group data sources for learners, educators, or other stakeholders to gain and act upon insights. Yet, it remains unclear how collaboration analytics go beyond previous work focused on modelling group interactions for the purpose of adapting instruction. This paper provides a conceptual model of collaboration analytics to help researchers and designers identify the opportunities enabled by such innovations to advance knowledge in, and provide enhanced support for, collaborative learning and teamwork. We argue that mapping from low-level data to higher-order constructs that are educationally meaningful, and that can be understood by educators and learners, is essential to assessing the validity of collaboration analytics. Through four cases, the paper illustrates the critical role of theory, task design, and human factors in the design of interfaces that inform actionable insights for improving collaboration and group learning.

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Section: Learning Analytics and Collaborative Learningmentioning

confidence: 99%

Section: Learning Analytics and Collaborative Learningmentioning

confidence: 99%

What Do You Mean by Collaboration Analytics? A Conceptual Model

Martínez-Maldonado

Gašević

Echeverria

et al. 2021

JLA

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“…The study has been developed through a mixed-method approach based on the epigenetic analysis of the CreaCube CSCL activity, by comparing the Strijbos' ( 2009) VMT coding schema VMT coding schema (Strijbos 2009) and the Guilfords' (1967) AUT creative components (Guilford 1967) that we applied to the CreaCube task. In CSCL, the group process has been analyzed mainly through text-and math-based environments (Stahl 2006;Ludvigsen et al 2017). However, text-based environments might present limits and constraints to learners with language difficulties.…”

Section: Methodsmentioning

confidence: 99%

“…Despite the importance of understanding the group processes in collaborative learning tasks, the assessment of the processes remains a methodological challenge (Jeong and Hmelo-Silver 2010;Ludvigsen et al 2017). In the context of computersupported collaborative learning (CSCL) activities, group processes are mediated by the technological environments, such as online forums, to support the collaborative activity (Wang et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Group processes and creative components in a problem-solving task with modular robotics

2020

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Group process assessment is one of the methodological challenges in computer-supported collaborative learning (CSCL). The aim of this study is to analyze the group process dimensions in a problem-solving task with modular robotics in which creative components of fluidity, flexibility and innovation can be observed. The analysis of group process dimensions in relation to the creative components aims to understand the way group processes can support the creativity process in a problem-solving task. For this objective, 24 dyads of in-service teachers in a creative problem-solving task with modular robotics were engaged. The group process dimensions of conversation, social interaction and problem-solving was identified based on a CSCL coding schema developed for the Virtual Math Team environment. The creative components of fluidity, flexibility and innovation are operationalized based on Guilford’s Alternate Uses Test’s components. The results show the creative component of innovation is related to interactions of support within the dyad. Moreover, the participants dedicating more time to solve the task are engaged not only in more problem-solving interactions with their dyad but also in building more innovative figures, and they also make more figures together. Those results lead us to consider the importance of a positive emotional environment in the context of collaborative creation.

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“…Furthermore, feelings of isolation are a common cause of drop out (Yuan and Kim, 2014). Other research has discussed problems related to sociability, for example in designing for social inclusion, a sense of belonging, and proximity in interpersonal connections (Cocquyt et al, 2019;Ludvigsen et al, 2017;Peacock and Cowan, 2019).…”

Section: Theoretical Considerationsmentioning

confidence: 99%

A social capital design for delivering online asynchronous professional development in a MOOC course for science teachers

Yoon

Miller

Richman

et al. 2020

ILS

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Purpose The overarching goal of the research is to understand strategies that can support utility and access to high-quality teacher professional development (PD). This study aims to examine the design and delivery of an online asynchronous course for science teachers using the edX massively online open course (MOOC) platform. The conceptual framework considers three areas of research: high-quality PD characteristics for K12 teachers, the development of social capital and known challenges in MOOC and computer-supported collaborative learning and participation. Design/methodology/approach This is an empirical mixed-methods study that details the design of the PD course and implementation strategies that instantiate the conceptual framework. The authors collected three data sources from 41 teachers who completed the course. These included post course satisfaction surveys, teacher semi structured interviews and discussion board contributions. Findings Survey findings revealed high satisfaction among teachers in the areas of overall course design, module construction and delivery and usability of materials in teaching. Interview findings showed positive perceptions of the social capital framing in developing tie quality, trust, depth of interactions and access to expertise. Analyses of discussion board contributions also demonstrated high degrees of information exchange resulting from prompts intentionally constructed to foster collaboration. Practical implications This study offers a set of strategies to build networked teacher PD communities in asynchronous online PD platforms and shows promising evidence of addressing quality and access issues. Social implications Designing experiences to build teachers’ social capital shows promising potential to support high quality PD that may, in turn, raise the quality of science education for students and classrooms both locally in the US and globally. Originality/value The conceptual framework provides a novel approach to theorizing and operationalizing best practices for teacher PD and online participation.

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Future direction for the CSCL field: Methodologies and eight controversies

Cited by 10 publications

References 12 publications

What Do You Mean by Collaboration Analytics? A Conceptual Model

What Do You Mean by Collaboration Analytics? A Conceptual Model

Group processes and creative components in a problem-solving task with modular robotics

A social capital design for delivering online asynchronous professional development in a MOOC course for science teachers

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