Author:
Soncin Mara,Cannistrà Marta
Abstract
Purpose
This 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/approach
The 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.
Findings
As 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/value
The 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.
Subject
Accounting,Business and International Management
Reference54 articles.
1. Data analytics and decision making in education: towards the educational data scientist as a key actor in schools and higher education institutions,2017
2. Using statistical analytics to study school performance through administrative datasets;Data Analytics Applications in Education,2017
3. Data science in the design of public policies: dispelling the obscurity in matching policy demand and data offer;Heliyon,2020
4. Data competence maturity: developing data-driven decision making;Journal of Research in Innovative Teaching and Learning,2018
5. The PERLA framework: blending personalization and learning analytics;International Review of Research in Open and Distributed Learning,2019
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