This paper describes the application of a mixed-evaluation method, published elsewhere, to three different learning scenarios. The method defines how to combine social network analysis with qualitative and quantitative analysis in order to study participatory aspects of learning in CSCL contexts. The three case studies include a course-long, blended learning experience evaluated as the course develops; a course-long, distance learning experience evaluated at the end of the course; and a synchronous experience of a few hours duration. These scenarios show that the analysis techniques and data collection and processing tools are flexible enough to be applied in different conditions. In particular, SAMSA, a tool that processes 384 A. Martínez, Y. Dimitriadis, et al. interaction data to allow social network analysis, is useful with different types of interactions (indirect asynchronous or direct synchronous interactions) and different data representations. Furthermore, the predefined types of social networks and indexes selected are shown to be appropriate for measuring structural aspects of interaction in these CSCL scenarios. These elements are usable and their results comprehensible by education practitioners. Finally, the experiments show that the mixed-evaluation method and its computational tools allow researchers to efficiently achieve a deeper and more reliable evaluation through complementarity and the triangulation of different data sources. The three experiments described show the particular benefits of each of the data sources and analysis techniques.

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During the last decades, educational contexts have transformed into complex technological and social ecologies, with mobile devices expanding the scope of education beyond the traditional classroom, creating so-called Ubiquitous Learning Environments (ULEs). However, these new technological opportunities entail an additional burden for teachers, who need to manage and coordinate the resources involved in such complex educational scenarios in a process known as "orchestration". This paper presents the evaluation of the orchestration support provided by GLUEPS-AR, a system aimed to help teachers in the coordination of across-spaces learning situations carried out in ULEs. The evaluation, following an interpretive research perspective, relied on a study where a pre-service teacher designed and enacted an authentic across-spaces learning situation in a primary school. The situation, which illustrates the orchestration challenges of ULEs, was aimed at fostering orienteering skills. It spanned five sessions taking place in the classroom, in the school's playground and at a nearby park, using multiple technologies and devices. The evaluation showed that GLUEPS-AR helped the teacher in the multiple aspects of orchestration, including implementation of his pedagogical ideas, adaptation in runtime, and sharing of orchestration load with students. Teacher awareness during outdoor activities was the main aspect to improve upon.

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Designs of CSCL (Computer Supported Collaborative Learning) activities should be flexible, effective and customizable to particular learning situations. On the other hand, structured designs aim to create favourable conditions for learning. Thus, this paper proposes the collection of representative and broadly accepted (best practices) structuring techniques in collaborative learning. With the aim of establishing a conceptual common ground among collaborative learning practitioners and software developers, and reusing the expertise that best practices represent, the paper also proposes the formulation of these techniques as patterns: the so-called CLFPs (Collaborative Learning Flow Patterns). To formalize these patterns, we have chosen 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 is discussed in the paper, as well as our approaches towards the development of a system capable of integrating tools using IMS-LD scripts and a CLFP-based Learning Design authoring tool.