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Learning Analytics: Trends and Issues of the Empirical Research of the Years 2011–2014

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9307))

Abstract

In very recent years, the advent of Learning Analytics (LA) has resulted in a number of publications reporting on empirical research. This literature overview identifies the mainstream of empirical LA research, and emphasizes insufficiently investigated directions that display a higher innovation potential. The mainstream consists of learning trajectory visualizations aimed to predict learner success. Single studies prove innovative by addressing in particular: informal educational settings, video and audio records as data sources, automated assessment and error/misconception analysis. A central issue of empirical LA research consists of the frequent lack of an explicit theoretical framework from educational perspective. We maintain that educational and psychological theories are urgently needed for significant progress of upcoming LA research.

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Notes

  1. 1.

    The model can be explored online at http://monet.informatik.rwth-aachen.de/DVita?id=3001

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Correspondence to Nicolae Nistor .

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Nistor, N., Derntl, M., Klamma, R. (2015). Learning Analytics: Trends and Issues of the Empirical Research of the Years 2011–2014. In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, E. (eds) Design for Teaching and Learning in a Networked World. EC-TEL 2015. Lecture Notes in Computer Science(), vol 9307. Springer, Cham. https://doi.org/10.1007/978-3-319-24258-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-24258-3_39

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  • Online ISBN: 978-3-319-24258-3

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