School Analytics: A Framework for Supporting Systemic School Complexity Leadership

Data-driven decision-making in education has received an increasing level of attention on a global scale, especially with the raising interest on big data. This trend has led to the development of two core analytics strands, namely Academic Analytics and Learning Analytics. The former focuses mainly...

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Main Authors: Sergis, S., Sampson, Demetrios
Format: Book Chapter
Published: 2016
Online Access:http://hdl.handle.net/20.500.11937/50439
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author Sergis, S.
Sampson, Demetrios
author_facet Sergis, S.
Sampson, Demetrios
author_sort Sergis, S.
building Curtin Institutional Repository
collection Online Access
description Data-driven decision-making in education has received an increasing level of attention on a global scale, especially with the raising interest on big data. This trend has led to the development of two core analytics strands, namely Academic Analytics and Learning Analytics. The former focuses mainly on the macro layer of the organization and is addressed to higher education, while the latter focuses mainly on the micro/meso layers of the organization. Considering the diverse focal points and contexts of application of the two existing analytics strands, the ecosystemic nature of K-12 schools as social complex adaptive systems, as well as, the need for data-based evidence-driven school complexity leadership, we claim that a holistic decision support approach for addressing the full spectrum of school leaders’ tasks is required, beyond the existing analytics strands. Therefore, in this book chapter, we introduce the concept of School Analytics as a holistic, multilevel analytics framework aiming to integrate data collected from all micro-, meso- and macro- organizational layers. We analyze them in an intertwining manner towards providing continuous feedback loops and systemic decision support to K-12 school leaders.
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spelling curtin-20.500.11937-504392019-09-10T06:25:52Z School Analytics: A Framework for Supporting Systemic School Complexity Leadership Sergis, S. Sampson, Demetrios Data-driven decision-making in education has received an increasing level of attention on a global scale, especially with the raising interest on big data. This trend has led to the development of two core analytics strands, namely Academic Analytics and Learning Analytics. The former focuses mainly on the macro layer of the organization and is addressed to higher education, while the latter focuses mainly on the micro/meso layers of the organization. Considering the diverse focal points and contexts of application of the two existing analytics strands, the ecosystemic nature of K-12 schools as social complex adaptive systems, as well as, the need for data-based evidence-driven school complexity leadership, we claim that a holistic decision support approach for addressing the full spectrum of school leaders’ tasks is required, beyond the existing analytics strands. Therefore, in this book chapter, we introduce the concept of School Analytics as a holistic, multilevel analytics framework aiming to integrate data collected from all micro-, meso- and macro- organizational layers. We analyze them in an intertwining manner towards providing continuous feedback loops and systemic decision support to K-12 school leaders. 2016 Book Chapter http://hdl.handle.net/20.500.11937/50439 restricted
spellingShingle Sergis, S.
Sampson, Demetrios
School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title_full School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title_fullStr School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title_full_unstemmed School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title_short School Analytics: A Framework for Supporting Systemic School Complexity Leadership
title_sort school analytics: a framework for supporting systemic school complexity leadership
url http://hdl.handle.net/20.500.11937/50439