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J. A. Larusson, B. White (eds): Learning Analytics: From Research to Practice

Springer Science+Business Media, New York, 2014, DOI:10.1007/978-1-4614-3305-7

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References

  • Baker, R., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3–17.

    Google Scholar 

  • Berland, M., Baker, R. S., & Blikstein, P. (2014). Educational data mining and learning analytics: Applications to constructionist research. Technology, Knowledge and Learning, 19, 205–220.

    Article  Google Scholar 

  • Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic analytics: A new tool for a new era. Educase Review, 42(4), 41–57.

  • DiCerbo, K., & Behrens, J. (2012). Implications of the digital ocean on current and future assessment. In R. Lissitz & H. Jiao (Eds.), Computers and their impact on state assessment: Recent history and predictions for the future (pp. 273–306).

  • Ferreira, S. A., & Andrade, A. (2014). Academic analytics: Anatomy of an exploratory essay. Education and Information Technologies, 20, 1–15.

  • Hawksey, M. Baker, R., Jeffery, N., Behrens, J. T., & Pea, R. (2013). Educational data scientists: a scarce breed. Proceedings of the Third International Conference on Learning Analytics and Knowledge, 278–281.

  • Martin, S., Diaz, G., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (2011). New technology trends in education: Seven years of forecasts and convergence. Computer and Education, 57, 1893–1906.

    Article  Google Scholar 

  • Peña-Ayala, A. (2014). Education data mining: Applications and trends (p. 524). Newyork: Springer.

    Book  Google Scholar 

  • Pitey, P. J., Hickey, D. T., & Bishop, M. J. (2014). Educational data sciences: framing emergent practices for analytics of learning, organizations, and systems. Proceedings of the Fourth International Conference on Learning Analytics and Knowledge, 193–202.

  • Romero, C., & Ventura, S. (2013). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(1), 12–27.

    Google Scholar 

  • Romero, C., Ventura, S., Pechenizky, M., & Baker, S. (2010). Handbook of educational data mining. Boca Raton: CRC Press, Taylor & Francis Group.

    Book  Google Scholar 

  • Siemens, G., & Baker, R. (2012). Learning analytics and educational data mining: Towards communication and collaboration. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 252–254.

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Authors and Affiliations

  1. Department of Computer Science, University of Cordoba, Cordoba, Spain

    Cristóbal Romero & Sebastián Ventura

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  1. Cristóbal Romero
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  2. Sebastián Ventura
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Correspondence to Cristóbal Romero.

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Romero, C., Ventura, S. J. A. Larusson, B. White (eds): Learning Analytics: From Research to Practice. Tech Know Learn 20, 357–360 (2015). https://doi.org/10.1007/s10758-015-9244-x

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