Advances in Learning Analytics and Educational Data Mining

Description

The growing interest in recent years towards Learning Analytics (LA) and Educational Data Mining (EDM) has enabled novel approaches and advancements in educational settings. The wide variety of research and practice in this context has enforced important possibilities and applications from adaptation and personalization of Technology Enhanced Learning (TEL) systems to improvement of instructional design and pedagogy choices based on students needs. LA and EDM play an important role in enhancing learning processes by offering innovative methods of development and integration of more personalized, adaptive, and interactive educational environments. This has motivated the organization of the ESANN 2015 Special Session in Advances in Learning Analytics and Educational Data Mining. Here, a review of research and practice in LA and EDM is presented accompanied by the most central methods, benefits, and challenges of the field. Additionally, this paper covers a review of novel contributions into the Special Session.

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