Meaning making is central to the interactions that take place in CSCL settings. The collaborative construction of shared meaning is a complex process that has not previously been analyzed in detail despite the fact that it is often acknowledged as being the distinguishing element in CSCL. Here, a three-minute excerpt from a discussion among three students is considered in some detail. The students are reflecting on their analysis of mathematical patterns in a synchronous online environment with text chat and a shared whiteboard. Several interaction methods and group cognitive processes are identified. The analysis suggests a number of conditions and preconditions of such interaction. These are necessary for achieving the potential of CSCL as the accomplishment of high-order cognitive tasks by small groups of learners. An understanding of the conditions and preconditions of the small-group meaning-making process may aid in the design and analysis of CSCL activities, as well as in the development of a theory of group cognition.

This work is based on the premise that the interactional construction of meaning is as important in online settings as it is face-to-face, especially in collaborative learning. Yet most studies of online learning use quantitative methods that assign meaning to contributions in isolation and aggregate over many sessions, obscuring the situated procedures by which participants accomplish learning through the affordances of online media. Methods for studying the interactional construction of meaning are available, but have largely been developed for brief episodes of face-to-face data, and need to be adapted to online learning where media resources, time scale, and synchronicity differ. In order to resolve this tradeoff, we have prototyped an abstract transcript notation to support sequential and interactional analysis of distributed and asynchronous interactions. The paper describes applications to data derived from asynchronous interaction of dyads and small groups. 1.

Abstract. Collaborative learning has been hypothesized to be related to the cognitive effort engaged by co-learners to build a shared understanding. The process of constructing this shared understanding requires each team member to build some kind of representation of the behavior, beliefs, knowledge or intentions of other group members. This contribution reports interesting findings regarding to the process of modeling each other. In two empirical studies, we measured the accuracy of the mutual model, i.e. the difference between what A believes B knows, has done or intends to do and what B actually knows, has done or intends to do. In both studies, we found a significant correlation between the accuracy of A's model of B and the accuracy of B's model of A. This leads us to think that the process of modeling one's partners does not simply reflect individual attitudes or skills but emerges as a property of group interactions. We describe on-going studies that explore these preliminary results.

Abstract: This work is based on the premise that the interactional construction of meaning is as important in online settings as it is face-to-face, especially in collaborative learning. Most studies of online learning use quantitative methods that assign meaning to contributions in isolation and aggregate over many sessions, obscuring the situated procedures by which participants accomplish learning through the affordances of online media. Methods for studying the interactional construction of meaning are available, but have largely been developed for brief episodes of face-to-face data, and need to be adapted to online learning where media resources, time scale, and synchronicity differ. In order to resolve this tradeoff, we have developed an abstract transcript notation to support sequential and interactional analysis of distributed and asynchronous interactions. Building on recent analytic work within our laboratory, we propose a framework for analysis that is founded on the concepts of media coordinations and uptake, and utilizes an abstract transcript representation, the dependency graph, that is suitable for use by multiple analytical traditions and supports examination of sequential structure at larger scales. Examples are provided using data derived from asynchronous interaction of dyads and small groups 1

The study of the process of meaning making is central to Computer Support Collaborative Learning (CSCL). Jurong Junior College and the National Institute of Education (Singapore) Learning Sciences Laboratory have recently conducted several collaborative maths problem solving sessions using the Virtual Math Team Chat, a quasi-synchronous chat medium used to facilitate the process of mathematical knowledge construction. The maths problems were designed based on the Guided Collaborative Critique (GCC) framework. The GCC framework requires students to analyse maths problems with "solutions " that contained conceptual or oversight errors, critique these problems with mathematical arguments and amend the "solutions " collaboratively. Our past research focused on the analysis of face to face (FTF) social interaction of groups working on maths problems using the GCC framework in traditional classrooms setting. In this study, the GCC framework is extended to the VMT chat medium which consists of a shared whiteboard, chat message box and tools for students to construct mathematical representations. The analyses of these sessions were based on the Collaboration Interaction Model (CIM), a model designed to study the knowledge construction process of complex chat transcripts. This paper will mainly discuss how participants mediate shared understanding of mathematical representations and form mathematical arguments to construct new knowledge in the chat medium, using the CIM as the key instrument of analysis.

This study’s aim is to describe and explore how 40 teacher students, engaged in courses in web-based learning environments, successively develop a collective competence to collaborate during two 15-credit courses in a period of 40 weeks. The collective competence of collaboration is here defined as the level of learning ability, a group of students express, when using dialogues as a tool for their own and other’s learning in a web-based learning environment. The students ’ contributions to the course assignments, the group responses and the collaborative discussions and dialogues were analysed and interpreted based on Bakhtin’s (1986, 2004) and Rommetveit’s (2003) theories on dialogic interactions and meaning potentials. The results describes three levels of thematic pattern in the dialogues as a competence to collaborate within the group. Keywords: Collaborative-, collective learning, asynchronous dialogues, dialogic interactions

CSCL and the study of social practices Ever since Lave and Wenger’s paradigm-shaking book on Situated Learning (Lave & Wenger, 1991), discussions about how people learn have included considerations of how participation in communities-of-practice and in related social institutions evolves. Learning is no longer conceived as a simple accumulation of facts in the heads of individuals, independent of the identity and behavior of the learners within their socio-cultural settings. Unfortunately, the theory of situated learning is too often construed as a questionable assumption of communities-of-practice everywhere, or as an antiquated romanticizing of apprenticeship. But Lave’s perspective is rooted in a serious philosophy of social praxis. To understand phenomena related to learning, one must study the ways in which people interact with one another. The consideration of social practices seems particularly relevant to collaborative learning. Individual learning may take countless forms and can be analyzed in terms of the manifold theories of psychology and education; it is highly dependent upon mental conceptions, personal attitudes, modes of content presentation, etc. Learning that takes

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Abstract. In computer-supported collaborative learning (CSCL) environments, learners in problem solving contexts constantly engage in information seeking, information sharing, and information use. However, these activities have not been well investigated in CSCL research. We have studied information behavior of small groups of middle school students engaged in online math problem solving. More specifically, we examined how participants negotiate and coconstruct their information needs, how they seek information, and how they make sense of discovered information and use it for their task at hand. We argue that for learners in a CSCL environment, information is essentially a social achievement that emerges through the interactions of the group. Information only becomes information for participants when it is interactionally constructed to be meaningful and intelligible in their local situation. Analyzing learners’ information behavior from such an interactional perspective can help us understand their practices of doing collaboration and learning. This has significant implications for designing CSCL environments and information resources to support small groups ’ information behavior and collaborative learning.

In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended learning approaches in CSCL; (b) blended learning for collaboration in various contexts including the narrative accounts of blended learning approaches in CSCL given by the Delphi panelist; and (c) the future of blended learning in CSCL, via three-phases of online survey questions. Implications for design issues and future research into blended learning and CSCL are also included.