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AFEL - Analytics for Everyday Learning

The rise of the Web had a tremendous impact on how learning and knowledge acquisition takes place, specifically in social environments such as LinkedIn or Slideshare, where exchange of knowledge or resources are among the key motivations for interaction. Understanding the needs of all involved stakeholders, such as users, learners, job seekers, training or resource providers, remains a challenging problem. This is due not least to the scale, diversity and heterogeneity of data on the Web, where the extraction and analysis of relevant information poses significant scientific challenges. The goal of the H2020 project AFEL (Analytics for Everyday Learning) is to develop methods and tools to understand informal/collective learning as it surfaces implicitly in online social environments. To this end, AFEL will develop solutions for retrieving, extracting, enriching and analysing data from the Web to shape the understanding of loosely defined learning activities in online social environments.

Description

The rise of the Web had a tremendous impact on how learning and knowledge acquisition takes place, specifically in social environments such as LinkedIn or Slideshare, where exchange of knowledge or resources are among the key motivations for interaction. Understanding the needs of all involved stakeholders, such as users, learners, job seekers, training or resource providers, remains a challenging problem. This is due not least to the scale, diversity and heterogeneity of data on the Web, where the extraction and analysis of relevant information poses significant scientific challenges. The goal of the H2020 project AFEL (Analytics for Everyday Learning) is to develop methods and tools to understand informal/collective learning as it surfaces implicitly in online social environments. To this end, AFEL will develop solutions for retrieving, extracting, enriching and analysing data from the Web to shape the understanding of loosely defined learning activities in online social environments.

Team
Research area
Intelligent Access to Information
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