Analytics Framework for K-12 School Systems

Analytics Framework for K-12 School Systems

Machi Raju Varanasi (University of Newcastle, Australia), John C. Fischetti (University of Newcastle, Australia) and Maxwell W. Smith (University of Newcastle, Australia)
Copyright: © 2018 |Pages: 28
DOI: 10.4018/978-1-5225-3188-3.ch011
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Abstract

With the growth in the use of information systems in schools and school systems, there has been a significant increase in the volume and variety of data that are captured, stored, and harnessed to improve student learning and school effectiveness. Most school systems are in a nascent stage in implementing analytic initiatives to create more value for students, parents, and the broader community. Guiding frameworks to assist schools and school systems are still in the early stages of development. This chapter proposes and builds a case for a new analytics framework for school education systems. This chapter proposes a six-lens educational analytics framework based on a successful implementation in a large school system in Australia. Examples from empirical analysis are provided to demonstrate its relevance and value to a range of internal and external stakeholders and as a practical guide for school leaders and teachers embarking on major analytics initiatives.
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Introduction

Governments everywhere are seeking more intensive control on educational outputs and outcomes and schools and school systems are using sophisticated information management systems to comply with legislative reporting and funding requirements (Hudson, 2007). For example, curriculum and assessment authorities, boards of studies, government departments in education, health and family services, and universities have introduced regulatory requirements relating to operations, sources of funds, capital expenditure, student attendance, and school performance in standardised tests. Data are present everywhere in schools and their operational activities generate large amounts of data in daily routines (Spillane, 2012). Data is the collective description for quantitative and qualitative information describing all that is captured, counted, stored, measured, analysed, and reported by an organisation. Analytics is the systematic use of data (Davenport & Harris, 2007).

Data and analytics are gaining prominence in the minds of policy-makers, practitioners, and service providers in school education (Hamilton et al., 2009). Theories, models, and frameworks about analytics are being put forward regularly to guide organisations in their respective analytics strategies (Campbell & Oblinger, 2007; Siemens, 2013). The newly-developed Educational Analytics Framework is the focus of this chapter.

The objectives of this chapter are to:

  • 1.

    Review the importance of using data and analytics in school education.

  • 2.

    Discuss the differences in the analytical focus of key educational stakeholders.

  • 3.

    Discuss the need for conceptual frameworks to guide analytics strategies.

  • 4.

    Propose the six lenses and their potential uses in the analytics framework for school systems.

  • 5.

    Interpret visualisations and generate insights for action.

Student administration and course information systems, online learning and assessment, interactive learning environments, learning management systems, student response systems, intelligent tutoring systems, e-portfolio systems, and virtual learning environments used in schools generate vast amounts of digital data that can be used to inform student and teacher effort and student success (Greller & Drachsler, 2012; Swan, 2012). Improved data culture in schools has given further impetus to schools to improve teaching and learning and contribute to greater student success.

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Analytics In School Education

Data use and data-based decision making are increasingly popular mantras in public policy around the world today (Spillane, 2012). The education sector, especially school education, has seen significant growth in the collection, storage and flow of quantitative data. Some of the accelerators to the vast growth of data in education include: the advent of standardised testing of school students in the domains of reading, numeracy, and writing; the rising interest in comparative analysis of countries based on student performances in tests such as PISA (Programme for International Student Assessment); and the increased use of accountability measures to ensure institutional transparency and to monitor public investments in education (Moss, 2014). Most Kindergarten to Year 12 (K-12) school education systems are in the nascent stage in implementing analytics initiatives. With the advent of recent technologies in blending and visualising data in real time, analytics in school education can take a further leap in improving and even transforming schools and school systems. Analytics is defined as the systematic analysis of data to discover, interpret, visualize, and communicate patterns and trends to derive actionable insights (Campbell & Oblinger, 2007). Analytics has come into prominence in the last decade with the growth in data in all spheres of commercial and personal activity.

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