Joint interactions in large online knowledge communities: The A3C framework

Jeong, Heisawn; Creß, Ulrike; Moskaliuk, Johannes; Kimmerle, Joachim

doi:10.1007/s11412-017-9256-8

Cited by 44 publications

(47 citation statements)

References 48 publications

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“…Instructors can enhance social interactions through choice of online platform-for example, discussion board versus social media (Clarke & Kinne, 2012;Hou, Wang, Lin, & Chang, 2015;Salmon, Ross, Pechenkina, & Chase, 2015)-and type of discussion question posed (Ke, 2010), as well as by incorporating structured collaborative activities and assessments of collaboration (Collazos, Gonzalez, & Garcia, 2014) and focusing on life experience or case-study analysis (Liu & Yang, 2014). Jeong et al (2017) developed a framework for interactions more broadly in online knowledge communities focused on learning and knowledge co-construction, including Wikipedia, citizen science projects, and cMOOCs. As xMOOCs incorporate social learning and knowledge co-construction and, thus, become slMOOCs, such a framework may be helpful in understanding types of interactions and in designing courses consistent with social learning pedagogy.…”

Section: Social Learning In Moocsmentioning

confidence: 99%

“…Social presence and peer-to-peer interaction in MOOCs can promote learning though sharing among students and through learners contributing to the collective knowledge (Margaryan, Bianco, & Littlejohn, 2015). Focusing more broadly on online communities in which participants learn and co-create knowledge (e.g., Wikipedia, citizen science, cMOOCs), Jeong, Cress, Moskaliuk, and Kimmerle (2017) proposed four increasingly intense levels of interactions varying in the degree to which community members share common goals, processes, and outcomes: attendance, coordination, cooperation, and collaboration (A3C). Although the A3C knowledge community framework was developed in the context of large, open online communities, the authors suggest that it could have value for smaller and face-to-face groups (Jeong et al, 2017).…”

mentioning

confidence: 99%

“…Focusing more broadly on online communities in which participants learn and co-create knowledge (e.g., Wikipedia, citizen science, cMOOCs), Jeong, Cress, Moskaliuk, and Kimmerle (2017) proposed four increasingly intense levels of interactions varying in the degree to which community members share common goals, processes, and outcomes: attendance, coordination, cooperation, and collaboration (A3C). Although the A3C knowledge community framework was developed in the context of large, open online communities, the authors suggest that it could have value for smaller and face-to-face groups (Jeong et al, 2017). Importantly, interactions among students may not only help address cultural barriers and enhance learning but also have the potential to add "local" knowledge to MOOCs, which otherwise may exclude non-Western forms of knowledge.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Small Groups in a Social Learning MOOC (slMOOC): Strategies for Fostering Learning and Knowledge Creation

Krasny

DuBois²,

Adameit³

et al. 2018

OLJ

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Social support and face-to-face learning may enhance outcomes for students who face barriers in accessing Massive Open Online Courses (MOOCs). In this study, we investigated how self-identified volunteer leaders guide and foster interactions among small groups of students who face technical and conceptual barriers in accessing MOOC content. Several months prior to the start of the MOOC (Environmental Education: Trans-disciplinary Approaches to Addressing Wicked Problems), we asked for volunteers among the registered students to lead groups for participants whose primary language was other than English and where limited Internet access, culture, or other barriers curtailed access to and understanding of course materials and pedagogy. Based on a survey and open-ended interviews (n=10), we found that group leaders were instrumental in overcoming barriers related to language, content, cultural ways of learning, access, and time. They also fostered cooperative learning strategies, which helped students acquire course content, and encouraged collaborative group projects leading to their groups adopting some features of online knowledge communities. We propose the term social learning MOOC (slMOOC) to capture a growing trend of incorporating collaborative learning strategies in xMOOCs.

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Section: Social Learning In Moocsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Small Groups in a Social Learning MOOC (slMOOC): Strategies for Fostering Learning and Knowledge Creation

Krasny

DuBois²,

Adameit³

et al. 2018

OLJ

View full text Add to dashboard Cite

show abstract

“…While most of the earlier studies have dealt with dyads or small groups of learners, we aim to apply the concept of socio-cognitive conflict to large groups. We argue that a certain amount of conflict is instrumental for driving complex dynamic processes in mass collaboration environments (Jeong et al 2017;Kimmerle et al 2015).…”

Section: Productive Friction In the Social Webmentioning

confidence: 96%

“…In the tradition of Piaget, the term socio-cognitive conflict has been used (e.g., Mugny and Doise 1978) to indicate that disturbances of individuals' cognitive systems can, among others, result from other people's differing cognitive schemas. For positive consequences of conflicts in large-scale social settings with many collaborators (see Jeong et al 2017), we suggest using the term productive friction that originally has been introduced in organization science (Hagel 3rd and Brown 2005; for an application in the educational context see Ward et al 2011). Productive friction refers to the process of overcoming obstacles in a productive way that, in turn, leads to individual learning and collaborative knowledge construction (Kimmerle et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Using big data techniques for measuring productive friction in mass collaboration online environments

Holtz

Kimmerle

Creß

2018

Intern. J. Comput.-Support. Collab. Learn

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The advent of the social web brought with it challenges and opportunities for research on learning and knowledge construction. Using the online-encyclopedia Wikipedia as an example, we discuss several methods that can be applied to analyze the dynamic nature of knowledge-related processes in mass collaboration environments. These methods can help in the analysis of the interactions between the two levels that are relevant in computer-supported collaborative learning (CSCL) research: The individual level of learners and the collective level of the group or community. In line with constructivist theories of learning, we argue that the development of knowledge on both levels is triggered by productive friction, that is, the prolific resolution of socio-cognitive conflicts. By describing three prototypical methods that have been used in previous Wikipedia research, we review how these techniques can be used to examine the dynamics on both levels and analyze how these dynamics can be predicted by the amount of productive friction. We illustrate how these studies make use of text classifiers, social network analysis, and cluster analysis in order to operationalize the theoretical concepts. We conclude by discussing implications for the analysis of dynamic knowledge processes from a learning sciences perspective.

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Knowledge order in an online knowledge community: Group heterogeneity and two paths mediated by group interaction

Qiu

Zuo

Wang

et al. 2021

Asso for Info Science & Tech

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Knowledge order in an online knowledge community (OKC) refers to a consensual version of collective knowledge in the creation of shared knowledge representation. Much previous research has been conducted in the context of the ordered structure of objective knowledge systems, but this does little to explain the microlevel order of knowledge after users contribute knowledge and achieve consensus through online interactions in OKC. Based on interactive team cognition theory and the stigmergy coordination mechanism, our research aims to investigate how knowledge and experience heterogeneity affect knowledge order effectiveness and efficiency through collaborative and communicative interaction. To test our hypotheses, we randomly collected the records of 250 articles from the English version of Wikipedia. Partial least squares structural equation modeling indicated that OKC favoring online collective knowledge order by limiting communicative interaction, as collaborative interaction is very effective in achieving knowledge order and in achieving it in a fast way. From our findings, scholars and practitioners are advised to pay attention to online knowledge order in the management and design of OKC.

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Joint interactions in large online knowledge communities: The A3C framework

Cited by 44 publications

References 48 publications

Small Groups in a Social Learning MOOC (slMOOC): Strategies for Fostering Learning and Knowledge Creation

Small Groups in a Social Learning MOOC (slMOOC): Strategies for Fostering Learning and Knowledge Creation

Using big data techniques for measuring productive friction in mass collaboration online environments

Knowledge order in an online knowledge community: Group heterogeneity and two paths mediated by group interaction

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