InstanceCollage: A tool for the particularization of collaborative IMS-LD scripts
Current research work in e-learning and more specifically in the field of CSCL (Computer Supported Collaborative Learning) deals with design of collaborative activities, according to computer-interpretable specifications, such as IMS Learning Design, and their posterior enactment using LMSs (Learnin...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/33487 |
| Acceso en línea: | http://hdl.handle.net/10230/33487 |
| Access Level: | acceso abierto |
| Palabra clave: | CSCL script IMS Learning Design Group formation Collaborative learning flow patterns |
| Sumario: | Current research work in e-learning and more specifically in the field of CSCL (Computer Supported Collaborative Learning) deals with design of collaborative activities, according to computer-interpretable specifications, such as IMS Learning Design, and their posterior enactment using LMSs (Learning Management Systems). A script that describes such collaborative activities is typically designed beforehand in order to structure collaboration, and defines the features that determine the behavior of the LMS, for instance, the sequence of activities or the groups/role distribution. In CSCL settings, group management and composition are especially relevant and affect the chances of achieving the expected learning outcomes. This paper presents a software tool, named InstanceCollage, which aims at facilitating the configuration and population of groups for IMS-LD scripts created with the authoring tool Collage, and discusses the implications of the IMS-LD specification with respect to this task. InstanceCollage is designed to process collaboration scripts based on CLFPs (Collaborative Learning Flow Patterns). Using this type of patterns, InstanceCollage focuses on the importance of understanding the function of groups within the learning strategy of the script. This paper describes the approach taken in InstanceCollage to facilitate this understanding for non-expert users. Additionally, two case studies are presented, which represent complex authentic collaborative learning scenarios, as a proof of concept of the functionality of this tool. The case studies are also used to illustrate the requirements of group configuration tools and to show that InstanceCollage complies to such requirements. |
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