Abstract
The growing development of virtual learning platforms is boosting a new type of Big Data and of Big Data Stream, those ones that can be labeled as e-learning Big Data. These data, coming from different sources of Virtual Learning Environments, such as communications between students and instructors as well as pupils tests, require accurate analysis and mining techniques in order to retrieve from them fruitful insights. This paper analyzes the main features of current e-learning systems, pointing out their sources of data and the huge amount of information that may be retrieved from them. Moreover, we assess the concept of educational Big Data, suggesting a logical and functional layered model that can turn to be very useful in real life.
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Ducange, P., Pecori, R., Sarti, L., Vecchio, M. (2017). Educational Big Data Mining: How to Enhance Virtual Learning Environments. In: Graña, M., López-Guede, J.M., Etxaniz, O., Herrero, Á., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’16-CISIS’16-ICEUTE’16. SOCO CISIS ICEUTE 2016 2016 2016. Advances in Intelligent Systems and Computing, vol 527. Springer, Cham. https://doi.org/10.1007/978-3-319-47364-2_66
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