Big data for social media learning analytics: potentials and challenges
Stefania Manca, Institute of Educational Technology, National Research Council of Italy ; Luca Caviglione, Institute for Intelligent Systems for Automation, National Research Council of Italy ; Juliana Raffaghelli
Journal of e-Learning and Knowledge Society Volume 12, Number 2, ISSN 1826-6223 e-ISSN 1826-6223 Publisher: Italian e-Learning Association
Today, the information gathered from massive learning platforms and social media sites allow deriving a very comprehensive set of learning information. To this aim, data mining techniques can surely help to gain proper insights, personalize learning experiences, formative assessments, performance measurements, as well as to develop new learning and instructional design models. Therefore, a core requirement is to classify, mix, filter and process the involved big data sources by means of proper learning and social learning analytics tools. In this perspective, the paper investigates the most promising applications and issues of big data for the design of the next-generation of massive learning platforms and social media sites. Specifically, it addresses the methodological tools and instruments for social learning analytics, pitfalls arising from the usage of open datasets, and privacy and security aspects. The paper also provides future research directions.
Manca, S., Caviglione, L. & Raffaghelli, J. (2016). Big data for social media learning analytics: potentials and challenges. Journal of e-Learning and Knowledge Society, 12(2),. Italian e-Learning Association. Retrieved December 10, 2018 from https://www.learntechlib.org/p/173464/.
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Dodzi Amemado & Stefania Manca
Journal of e-Learning and Knowledge Society Vol. 13, No. 2 (May 29, 2017)
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