-rEdEs SoCiAlEs De ApReNdIzAjE eN iNtErNeT-

The social networks of learning are pages that, as its name indicates, offer the services of a social network in which the users share the interest to study one or several foreign languages.

Until now, the social networks consider like a method of informal learning; said of another form, it is considered that the formal learning (the academic one) uses methods different from the informal learning (to which is acquired in the work); you efforts of the social networks are based on combining in informal learning with the formal one.

This learning is the one that would be due to apply in the formal learning, includes a new element solely; the roll of the professor like mediator between the social network and the student; of this form new expectations of innovation in the academic formation are expected.

Currently Computer Supported Collaborative Learning (CSCL) systems are very applied in learning contexts. CSCL is based on social theories of learning, which emphasize the relevance of social interaction and context as a main aspect on the building of learning. These interactions among the participants are totally or partially mediated by computers.

In CSCL scenarios the interaction analysis of participatory aspects is one important aspect to analyse in order to support the understanding of the collaborative learning processes, and offering different functionalities as participants self-regulation, teachers supervision tasks or assessment of learning. Social Network Analysis (SNA) is an appropriate discipline for the study of these forms of participation, focus on the analysis of the interrelationships among individuals in groups. In this paper we present an experience performed in a real CSCL authentic learning scenario where we apply SNA to data obtained from different data sources including ethnographic and automatically data collected.

The results of this analysis were provided to teacher and students during the collaborative activity in order to support participants regulation. We have provided social networks and indexes using data obtained from different data sources including ethnographic and automatically collected data. The participants of this experience have assessed positively and they consider the information received was easy to understand and useful to achieve self-regulation, to know the impact of their works and to detect collaboration problems during the development of the activity.