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Data analytics and decision making in education: towards the educational data scientist as a key actor in schools and higher education institutions

In: Handbook of Contemporary Education Economics

Author

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  • Tommaso Agasisti
  • Alex J. Bowers

Abstract

In this chapter, we outline the importance of data usage for improving policymaking (at the system level), management of educational institutions and pedagogical approaches in the classroom. We illustrate how traditional data analyses are becoming gradually substituted by more sophisticated forms of analytics, and we provide a classification for these recent movements (in particular learning analytics, academic analytics and educational data mining). After having illustrated some examples of recent applications, we warn against potential risks of inadequate analytics in education, and list a number of barriers that impede the widespread application of better data use. As implications, we call for a development of a more robust professional role of data scientists applied to education, with the aim of sustaining and reinforcing a positive data-driven approach to decision making in the educational field.

Suggested Citation

  • Tommaso Agasisti & Alex J. Bowers, 2017. "Data analytics and decision making in education: towards the educational data scientist as a key actor in schools and higher education institutions," Chapters, in: Geraint Johnes & Jill Johnes & Tommaso Agasisti & Laura López-Torres (ed.), Handbook of Contemporary Education Economics, chapter 9, pages 184-210, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:17209_9
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    Cited by:

    1. Trinidad, Jose Eos, 2022. "Meaning-Making, Negotiation, and Change: Reviewing the Organization and Ecology of School Accountability," SocArXiv ywm8b, Center for Open Science.
    2. Jacek Maślankowski & Łukasz Brzezicki, 2020. "The use of social media by higher education institutions," Post-Print hal-04414200, HAL.

    More about this item

    Keywords

    Economics and Finance; Education;

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