AFEL

Analytics for Everyday Learning

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.

Partners

• L3S
• KMRC
• Know Center
• GNOSS

Kiran Parmar

John Domingue

Mathieu d'Aquin

Mathieu d'Aquin

Adamou, A., Daga, E. and Isaksen, L. (eds.) (2016) WHiSe 2016 - Humanities in the Semantic Web, Workshop: 1st Workshop on Humanities in the Semantic Web (WHiSe 2016) at 13th ESWC Conference 2016, Anissaras, Greece, 1608, CEUR-WS.org

Mouromtsev, D. and d'Aquin, M. (eds.) (2016) Open Data for Education: Linked, Shared, and Reusable Data for Teaching and Learning Open Data for Education: Linked, Shared, and Reusable Data for Teaching and Learning, Springer

d'Aquin, M. (2016) On the Use of Linked Open Data in Education: Current and Future Practices Open Data for Education: Linked, Shared, and Reusable Data for Teaching and Learning, eds. Dmitry Mouromtsev and Mathieu d'Aquin