AFEL Vision and Approach

AFEL Vision

The goal of AFEL (Analytics for Everyday Learning) is to develop methods and tools to understand informal/collective learning as it surfaces implicitly in online social environments. While Learning Analytics and Educational Data Mining traditionally rely on data from formal learning environments, studies have for a long time demonstrated that learning activities happen for a large part online, in a variety of other platforms. The aim of AFEL is therefore to devise the tools for exploiting learning analytics on such learning activities, in relation to cognitive models of learning and collaboration that are necessary to the understanding of loosely defined learning processes in online social environments.

To achieve this, AFEL gathers a range of skills in a consortium funded by the EU Horizon 2020 programme including experts in data analytics, interaction with data, cognitive models of learning and collaboration, as well as the developers of online social platforms. Concretely, the objectives of this consortium are to 1) develop the tools necessary to capture information about learning activities from online social environments; 2) create methods for the analysis of such informal learning data, based on combining visual analytics with cognitive models of learning and collaboration; and 3) demonstrate the potential of the approach in improving the understanding of informal learning, and the way it can be better supported.


AFEL Approach

Learning technologies (including Technology Enhanced Learning and eLearning) have for a long time been focusing on formal learning environments, proposing technologies and standards to be applied within
educational institutions and schools. In the continuity of these areas, Learning Analytics and Educational Data Mining have mostly, until now, been applied on information and data captured in closed educational environments. In parallel to that, however, many studies in the last couple of decades have been focusing on a large part of the learning process which is not captured by educational systems, and not included within any formal learning environment: informal and incidental learning, These studies show that there is a continuum, including workplace learning, collective learning, social learning, etc., from the most basic ‘classroom experience’ to the much more common ways of learning as a side effect of interacting with others and the environment To completely support learners, whether or not they are enrolled in a formal learning programme, requires technologies and models that can take fully into account this spectrum.

Therefore we will focus in AFEL on the part which has received less attention by the Technology Enhanced Learning community, especially from the point of view of Learning Analytics and Educational Data Mining, taking a multidisciplinary approach that relies, on the one hand, on cognitive models of collective informal learning, and on the other hand, on social web data techniques to make emerge and capture the necessary evidence of learning for such models to be used in an analytics process.

To summarise, the approach taken by the AFEL project to focus on online social environments, to employ social network analysis and web data to extract features of learning activities from these social environments based on semantics, and to align these features to emerging models of learning in social communities to support their analysis. The research conducted in the project will extensively rely on the GNOSS platform ( an existing informal and social online learning platform, providing us with data about the activities of thousands of users grouped in hundreds of communities. GNOSS will also act as a testbed and as one of the channels for the usage of the results of the project.