Abstract
PurposeThis study aims to investigate the organisational structure to exploit data analytics in the educational sector. The paper proposes three different organisational configurations, which describe the connections among educational actors in a national system. The ultimate goal is to provide insights about alternative organisational settings for the adoption of data analytics in education.Design/methodology/approachThe paper is based on a participant observation approach applied in the Italian educational system. The study is based on four research projects that involved teachers, school principals and governmental organisations over the period 2017–2020.FindingsAs a result, the centralised, the decentralised and the network-based configurations are presented and discussed according to three organisational dimensions of analysis (organisational layers, roles and data management). The network-based configuration suggests the presence of a network educational data scientist that may represent a concrete solution to foster more efficient and effective use of educational data analytics.Originality/valueThe value of this study relies on its systemic approach to educational data analytics from an organisational perspective, which unfolds the roles of schools and central administration. The analysis of the alternative organisational configuration allows moving a step forward towards a structured, effective and efficient system for the use of data in the educational sector.
Highlights
The datafication phenomenon is shaping different sectors because of the increasing number of automated systems, which store data from different sources (Jarke and Breiter, 2019)
The present study explores the organisational dimensions that affect the exploitation of data analytics in education taking a national-level perspective
Discussion and concluding remarks The study analyses the organisational implications of data analytics in education, by proposing three alternative organisational configurations that can be adopted at the national level
Summary
The datafication phenomenon is shaping different sectors because of the increasing number of automated systems, which store data from different sources (Jarke and Breiter, 2019). The education sector is one of the most noticeable domains affected by datafication, given the underlying potential of data for supporting effective teaching and learning and for transforming the ways in which future generations (will) construct reality with and through data (Namoun and Alshanqiti, 2021; Jarke and Breiter, 2019). The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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