Today, more than ever before, learning is social. It develops in community and the activity of learning is conceived as a conversation that takes place among student and other members of the educative community and society. But this idea is not a current issue. Gavriel Salomon, in 2000, considered the intelligent learning as a constructive process of guided knowledge building supported by team work. However, in his opinion, it is reasonable to wonder whether Web-bases activities allow authentic construction of knowledge. But himself, in a previous idea formulated in the same paper but independent of the intelligent learning concept, gave us the answer: What technology does or fails to do in education depends far less on what it can do and far more on what education allows it to do.
This effective and productive activity carried out by students on the Net which at the beginning of the 2000s was a matter of hesitation, is an unquestionable reality in 2013. The new users of the net are introduced as active developer of information, committed to a change of paradigm in which they can control and manipulate the information in a collaborative way, being part of social networking and participating in the construction of genuine virtual communities of learning. This way, social media and this new idea about learning -more social, dynamic and contextualized- are contributing to get the social community closer to school, and to develop this conversation demanded by students, teachers and the educative community.
Based on those principles, several research lines have emerged. On the one hand, to study the didactic and technological conditions which allow to define didactic strategies according to collaborative and active methodologies; secondly, to replan the teacher training in some methodological aspects by means of ICT-teaching situations; and, finally, to develop educative innovation projects using ICT in which students have an active role. On the other hand, other research lines focus on analysing the learning, emphasizing its social and collaborative dimensions. Some recent research give away the value that the configuration of collaboration networks has in learning. ECAR Study of Undergraduate Students and Information Technology 2013 reflects in its outcomes that technology helps to make students feel more connected to the Institution (64%), teacher (60%) and other students (54%). In a recent local research carried out at the University of Murcia, most of undergraduate students (81%) said that their classmates are those who have had more influence in their learning. Social dimension of learning is being analysed by Open University researchers in depth in its SocialLearn project. This project expects to define social learning models based on the possibility to share open content and to build new knowledges, to create social networks in educative contexts and to develop techniques for active participation from students. That is the reason why we consider that it is neccesary to analyse the social learning from several aspects.
The recent NMC Horizon Report 2013 Higher Education report shows Learning analytics as a future educative trend (adopted in 2 or 3 years). Learning analytics is the measurement, collection and analysis of data about learners and their contexts, with the aim of understanding and optimising the learning process and the environments in which it occurs. Although its implementation could promote the adaptation of software to learning needs, I consider that we could benefit from the analysis of the social dimension of learning, the so-called Social Learning Analytics, for personalizing learning environments and defining new learning environments based on the use of ICT, more effective from the point of view of communication and collaboration.
In 2011, Siemens and Long wrote a interesting paper about Analytics in Learning y Education, where they emphasized the social dimension of learning because they proposeD a cycle to reflect analytics in learning with several levels: course-level, educational data mining, intelligent curriculum, adaptative content, and adaptative learning. Among them, the first level (course-level) includes the social network analysis in the classroom, and the latter (adaptative learning) analysed social interactions, learning activity and learner support.
In another report, Buckingham y Ferguson (2012) have given a qualitative step defining the dimensions of Social Learning Analytics. They consider that in Social Learning Analytics we use the “data generated by learners´online activity in order to identify behaviours and patterns within the learning environment related to effective process” (p. 10). The authors identify two types of inherently social analytics and three socialised analytics. The types of inherently social analytics are Social Networks Analytics and Discourse Analytics, i.e., the lenguage analysis used in the negotiations and construction of knowledge processes. With respect to the types of socialised analytics, they identify the Content analytics, the student disposition to learn (Disposition analytics), and the Context analytics, in which the new learning environment develop by the mobile learning are included.
The challenge now is to define and apply models and tools to analyse the social learning in order to carry out research that complete information about the learning needs of our students, and personalize their learning enviroments in formal, non formal and informal contexts. The NMC Horizon Report 2013 Higher Education listed some experiences related to the practice of Learning Analytics such as the Jpoll at the University of Griffith; the Predictive Analytics Reporting Framework (PAR) developed by the American Public University System (APUS); and, finally, the Multimodal Learning Analytics project developed by the Transformative Learning Technologies Lab from Standford University. But this is only the starting point, we still have further to go from research to know the authentic repercussion of Learning Analytic.
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