Davinia Hernández-Leo (2007) “A pattern-based design process for the creation of CSCL macro-scripts computationally represented with IMS LD”, Ph.D. Thesis, University of Valladolid, Spain.

 

Abstract

 

Information and Communication Technologies (ICT) in Computer-Supported Collaborative Learning (CSCL) are mainly used for mediating social interactions as key activators of learning. One of the major concerns of CSCL is however that free collaboration does not necessarily produce learning and that in several circumstances collaboration should be scaffolded so that the probability of reaching successful outcomes increases. CSCL scripts embedded in ICT systems aim at shaping the way learners interact with each other in order to elicit fruitful interactions. The specific focus of this Ph.D. Thesis is on CSCL macro-scripts which describe pedagogical methods defining flows of coarse-grained activities. This document identifies and faces up to three challenges around the problem of facilitating teachers the design of those ICT-embedded CSCL macro-scripts.

The first challenge refers to the design of the potentially fruitful scripts. This work proposes the use of patterns to capture good practices in structuring CSCL situations for the purpose of reusing them in the design of new scripts. In this sense, we present a conceptual model for CSCL scripting pattern languages and a specific pattern language that is compliant with the model. The model defines the different types of patterns and relationships among them so that it is possible to specify numerous meaningful sequences of patterns that shape the design of specific scripts.

The second challenge deals with the implementation of the scripts in ICT systems. With the aim that the scripts can be automatically interpreted without the need of developing new systems, we propose the use of IMS Learning Design (LD) specification to computationally represent the macro-scripts. This approach fosters interoperability and enables teachers participate in the design of the behaviour and functionality of the systems by providing a script adapted according to their particular situations. This work analyzes the support of this educational modelling language for expressing CSCL scripts considering the possibilities of the LD notation but also the use of related specifications and tooling.

The combination of the previous proposals enables us to propose a pattern-based design process for the creation of CSCL macro-scripts computationally represented with LD. The specific patterns considered in the approach are the so-called Collaborative Learning Flow Patterns (CLFPs), a particular type of CSCL scripting patterns that suggest generalized structures of macro-scripts. The main goal of the design process is twofold. On the one hand, it aims at enabling the conceptualization of the expected interaction focusing on CSCL critical elements through the refinement of CLFP-based templates. And on the other hand, it intends facilitating the teacher-friendly creation of LD-represented scripts by hiding LD details; thus facing up to the third challenge related to the fact that computational representations are not familiar to the majority of the teachers. The design process is implemented in an authoring tool (named Collage) which proves its feasibility and enables its proper evaluation. 

Overall, the applied research methodology is characterized by the multidisciplinary problem domain within which the dissertation is framed. Particularly, the evaluation phase is accomplished by means of a multicase study that comprises three case studies, which aim at assessing the same contributions but from different perspectives. The cases involve workshops with the target audience (teachers interested in applying CSCL) and experiences with students in authentic situations; but they also involve experts in the collaborative learning or LD fields and researchers proposing related approaches. The results of the evaluation not only show that the objectives of the dissertation have been achieved but they also offer relevant clues for future research directions.