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A Collaborative and Adaptive Design Pattern of the Jigsaw Method within Learning Design-Based E-Learning Systems

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Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding

Part of the book series: Studies in Computational Intelligence ((SCI,volume 350))

Abstract

This chapter presents an innovative description of the Jigsaw collaboration method, in the form of an online, adaptive collaborative design-pattern that has been constructed taking into account adaptation techniques, within the context of open-source learning design-based environments such as LAMS. This method is described with special reference to the learning of essential issues in Computer Science and especially in the area of programming languages. These issues include an understanding of: (a) basic elements of structured programming languages, (b) the rapid evolution of the area of programming languages, (c) the learning of programming languages’ levels and techniques. The innovative description of the Jigsaw collaborative method within LAMS is based on the fact that: (a) the tasks assigned to the expert groups consist of investigation of real world scenarios and not merely the study of learning material as is usually proposed, (b) adaptive techniques are integrated with the method and (c) for the design of the collaborative learning activity, an intuitive learning design tool like LAMS is used.

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Authors and Affiliations

  1. Department of Computer Engineering and Informatics, University of Patras, 26500, Rion Patras, Greece

    Maria Kordaki & Haris Siempos

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  1. Maria Kordaki
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  2. Haris Siempos
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Editors and Affiliations

  1. Open University of Catalonia, Spain

    Thanasis Daradoumis , Santi Caballé  & Angel A. Juan ,  & 

  2. Technical University of Catalonia, Spain

    Fatos Xhafa

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Kordaki, M., Siempos, H. (2011). A Collaborative and Adaptive Design Pattern of the Jigsaw Method within Learning Design-Based E-Learning Systems. In: Daradoumis, T., Caballé, S., Juan, A.A., Xhafa, F. (eds) Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding. Studies in Computational Intelligence, vol 350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19814-4_11

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  • DOI: https://doi.org/10.1007/978-3-642-19814-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19813-7

  • Online ISBN: 978-3-642-19814-4

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