InstanceCollage: A Tool for the Particularization of Collaborative IMS-LD Scripts

Abstract

Current research work in e-learning and more specifically in the field of CSCL (Computer Supported\nCollaborative Learning) deals with design of collaborative activities, according to computer-interpretable\nspecifications, such as IMS Learning Design, and their posterior enactment using LMSs (Learning Management\nSystems). A script that describes such collaborative activities is typically designed beforehand in order to\nstructure collaboration, and defines the features that determine the behavior of the LMS, for instance, the\nsequence of activities or the groups/role distribution. In CSCL settings, group management and composition are\nespecially relevant and affect the chances of achieving the expected learning outcomes. This paper presents a\nsoftware tool, named InstanceCollage, which aims at facilitating the configuration and population of groups for\nIMS-LD scripts created with the authoring tool Collage, and discusses the implications of the IMS-LD\nspecification with respect to this task. InstanceCollage is designed to process collaboration scripts based on\nCLFPs (Collaborative Learning Flow Patterns). Using this type of patterns, InstanceCollage focuses on the\nimportance of understanding the function of groups within the learning strategy of the script. This paper\ndescribes the approach taken in InstanceCollage to facilitate this understanding for non-expert users.\nAdditionally, two case studies are presented, which represent complex authentic collaborative learning\nscenarios, as a proof of concept of the functionality of this tool. The case studies are also used to illustrate the\nrequirements of group configuration tools and to show that InstanceCollage complies to such requirements.

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