From mirroring to guiding

[Jermann et al.2001] Jermann, P., Soller, A., and Mühlenbrock, M. (2001). From mirroring to guiding: a review of the state of the art technology for supporting collaborative learning. In Proceedings of EuroCSCL, pages 324–331, Maastricht.
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This paper reviews a bunch of systems for the management of collaborative interaction and propose a classification framework built on a simple model of coaching. The authors sketch four phases of the coaching collaborative interaction (supporting or managing the members’ metacognitive activities related to the interaction). These four phases gradually move from “mirroring” to “guiding” the collaborative activity. The former term refer to the system’s ability to gather data about the group members’ interaction and use this information to visualise the activity for the users. Is then up to the users to interpret and decide what to do. The latter term refer to an approach by which the system assessment is hidden to the users. The system use this information to make decisions about how to moderate the group. This second approach has to deal with a model of ideal interaction, which is not trivial to design.

We can imagine a third state which is not constraint by imposing a predefined model nor that has to deal with the in-definition of user’s expectation and understanding of the representation.

Agent Interface Structure

The following picture, taken from Hoppe (2000), illustrated their framework for providing intelligent support into collaborative interfaces. Two kinds of agents are proposed: mediator and interpreter. The former relates the visual card language to the inderlying interpretation by translating card nets into specific intepreter representations and vice versa. In addition, it aggregates and explicates information implicit in the user interface, such as time of user actions, etc. The latter, provide operational semantics for the card environment: general formalism and first order logic can be incorporated.

Agent_interface_structure

Picture taken from:
H. U. Hoppe, K. Graßner, M. Muehlenbrock, and F. Tewissen. Distributed visual language environments for cooperation and learning. Group Decision and Negotiation, 9(3), May 2000.

Distributed Visual Language Environments for Cooperation and Learning

H. U. Hoppe, K. Graßner, M. Muehlenbrock, and F. Tewissen. Distributed visual language environments for cooperation and learning. Group Decision and Negotiation, 9(3), May 2000.
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This paper was cited by \ref{Barross02}. It describes the system called CardMan, which is a framework for building and representing solution plans for physics exercises. The key idea is that argumentation is a typical mode of collaborative learning \ref{Buckingham94}. This software implements a class for Synchronization (coupling). It also provide a record and replay function of the action history which is also used as a transcripts for empirical purposes. The interesting engineering aspects of this Distributed Visual Language Environment (DVLE) are the structures used for managing the cards interchanged by the clients. Those are exchanged in a p2p mode but, more interestingly, are represented at three representational level: the specification level (content cards and connectors cards); the internal representational level (a graph structure with n-ary relations); and finally the external representational level, where card are generated accordingly to their specification.

A final interesting note is in the design of DVLE to work in accord with agents for intelligent support. The author affirm that “automathic processing should be clearly separated from the (group-)interactive functionality”. Their agent interface structure is constituted by a mediator and an interpreter agent: the former relates the visual card language to the underlying interpretation by translating card nets into specific interpreter representations and vice versa. In addition it aggregates information implicit in the user interface. The latter provide operational semantics for first order logic.

Applications of a collaborative learning ontology

B. Barros, M. F. Verdejo, T. Read, and R. Mizoguchi. Applications of a collaborative learning ontology. In C. A. C. Coello, A. deAlbornoz, L. E. Sucar, and O. C. Battistutti, editors, MICAI2002 Mexican International Conference on Artificial Inteligence, pages 301–310, Mexico City, Mexico, April 22–26 2002. Springer-Verlag.
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In this paper a computational model has been presented which express the Activity Theory in terms of a CSCL ontology. This ontology offers a conceptual knowledge level representation for describing collaborative learning systems. It is based upon the structure and the knowledge contained in previous ontologies together with knowledge which was not explicitly represented in other collaborative learning ontologies. This ontology has been designed to be reusable by different tools in many collaborative learning scenarios due to the combination of the theoretical AT framework with an underlying XML-based representation.

One of the theoretical concept of this paper is to use actions as a unit of analysis as the needed structure to make context of a situation explicit. This choice is therefore discussed over a number of other studies which made other decisions privileging more communication models or problem solving methods or learning goals. The structure of these ontology is explained, where the concepts are expressed in two different nodes: Source of information (which is itself divided into two nodes: a statistical node and an interpreted node) and Analysis method, containing three types of node (Interaction-based, Action based, Interaction-Action-Stage based). The authors, finally sketch three possible usage for this ontology: the definition and authoring of cscl environments; the analysis and identification of collaborative features and finally the guide and coach of cscl activities.

Plazes.com

Plazes is a new kind of service offering information and interaction with people and PlaZes based on your current location. The idea is, that you are where you are connected. Plazes works without GPS or any kind of other devices.

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We Built This City: Developing Students’ Understanding of Ecology Through the Professional Practice of Urban Planning

K. L. Beckett and D. W. Shaffer. We built this city: Developing students’ understanding of ecology through the professional practice of urban planning. In Y. B. Kafai, W. A. Sandoval, N. Enyedy, A. S. Nixon, and F. Herrera, editors, Proceedings of the Sixth International Conference of the Learning Sciences (ICls), page 587, Santa Monica, CA, June 22–26 2004. University of California Los Angeles, Lawrence Erlbaum Associates.
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This paper illustrates a system called Madison 2200 that hopes to support children’s learning of the environment unlike modeling programs such as StarLogo or augmented reality environments. The learning environment of this study is augmented by reality: the problem solving is guided by real-world tools and practices.

Young Children Collaborating to use Maps during Technology based Distributed Learning Activities

I. Ioannidou and A. Dimitrakopoulou. Young children collaborating to use maps during technology based distributed learning activities. In proceedings of 6th International Conference of Mathematics Teaching, Volos, Greece, October 2004.
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This paper concentrate on the theme of children’s learning of map design and construction. One of the point raised in the text is that there are lots of studies on the cognitive difficulties children have in understanding maps, while few studies concentrate on the design of learning activities aiming to develop learning on the same themes. The authors’ solution is a system in which a team of children can stand in front of a 2D digital representation of the world while another team can walk in the actual world. These two teams are connected with a walky-talky device for communication. In this way the authors have been tested several “scripts” which report significant learnings in the cognitive difficulties enumerated in previous studies. Using the same platform the authors have a chance to test several collaboration settings which enables for a zoom into intra-group or inter-group collaboration.