CLFP intrinsic constraints-based group management of blended learning situations

When applying a Collaborative Learning Flow Pattern (CLFP) to structure sequences of activities in real contexts, one of the tasks is to organize groups of students according to the constraints imposed by the pattern. Sometimes,unexpected events occurring at runtime force this pre-defined distribution to be changed. In such situations, an adjustment of the group structures to be adapted to the new context is needed. If the collaborative pattern is complex, this group redefinitionmight be difficult and time consuming to be carried out in real time. In this context, technology can help on notifying the teacher which incompatibilitiesbetween the actual context and the constraints imposed by the pattern. This chapter presents a flexible solution for supporting teachers in the group organization profiting from the intrinsic constraints defined by a CLFPs codified in IMS Learning Design. A prototype of a web-based tool for the TAPPS and Jigsaw CLFPs and the preliminary results of a controlled user study are alsopresented as a first step towards flexible technological systems to support grouping tasks in this context.

Computational Representation of Collaborative Learning Flow Patterns Using IMS Learning Design

The identification and integration of reusable and customizable CSCL (Computer Supported Collaborative Learning) may benefit from the capture of best practices in collaborative learning structuring. The authors have proposed CLFPs (Collaborative Learning Flow Patterns) as a way of collecting these best practices. To facilitate the process of CLFPs by software systems, the paper proposes to specify these patterns using IMS Learning Design (IMS-LD). Thus, teachers without technical knowledge can particularize and integrate CSCL tools. Nevertheless, the support of IMS-LD for describing collaborative learning activities has some deficiencies: the collaborative tools that can be defined in these activities are limited. Thus, this paper proposes and discusses an extension to IMS-LD that enables to specify several characteristics of the use of tools that mediate collaboration. In order to obtain a Unit of Learning based on a CLFP, a three stage process is also proposed. A CLFP-based Unit of Learning example is used to illustrate the process and the need of the proposed extension.

Reusing IMS-LD formalized best practices in collaborative learning structuring

Designs of CSCL (Computer Supported Collaborative Learning)activities should be flexible, effective and customizable toparticular learning situations. On the other hand, structureddesigns aim to create favourable conditions for learning. Thus,this paper proposes the collection of representative and broadlyaccepted (best practices) structuring techniques in collaborative learning. With the aim of establishing a conceptual common ground among collaborative learning practitioners and softwaredevelopers, and reusing the expertise that best practicesrepresent, the paper also proposes the formulation of these techniques as patterns: the so-called CLFPs (CollaborativeLearning Flow Patterns). To formalize these patterns, we havechosen the educational modelling language IMS Learning Design (IMS-LD). IMS-LD has the capability to specify many of the collaborative characteristics of the CLFPs. Nevertheless, the language bears limited capability for describing the services that mediate interactions within a learning activity and the specification of temporal or rotated roles. This analysis isdiscussed in the paper, as well as our approaches towards thedevelopment of a system capable of integrating tools using IMSLDscripts and a CLFP-based Learning Design authoring tool.