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dc.contributor.authorSergis, S.
dc.contributor.authorSampson, Demetrios
dc.identifier.citationSergis, S. and Sampson, D. 2016. School Analytics: A Framework for Supporting Systemic School Complexity Leadership, in Spector, M. et al (eds), Competencies in Teaching, Learning and Educational Leadership in the Digital Age: Papers from CELDA 2014, pp. 79-122. Berlin: Springer.

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.

dc.titleSchool Analytics: A Framework for Supporting Systemic School Complexity Leadership
dc.typeBook Chapter
dcterms.source.titleCompetencies, Challenges and Changes in Teaching, Learning and Educational Leadership in the Digital Age
curtin.departmentSchool of Education
curtin.accessStatusFulltext not available

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