23 SES 09 D, School Organisation
“Good education is based on collective human judgment that is supported by a variety of evidence—both quantitative and qualitative. From the leadership point of view, if you don’t lead by small data, you will be led by big data” (Sahlberg, 2017).
The use of ‘big data’ in education systems around the world has become widespread. It has manifested through what Sahlberg (2011) calls the Global Education Reform Movement (GERM). This describes the spread (like an infection, and hence the acronym) of particular education policy ideas globally, including the standardisation of teaching and learning, the reductive focus on literacy and numeracy, the preference for curriculum prescription, and the use of test-based accountability (Sellar, 2015), resulting in countries around the world relying heavily on the use of ‘big data’ to measure educational improvement in these areas. This emphasis on ‘big data’, which is often student performance data, operates on many levels, trickling down from the global, to the national, to the school level, and transcends a variety of nations and nation-states, hence Sahlberg (2011) making it synonymous with an infection. Much attention has been focused on highlighting the problematics associated with ‘governing by numbers’ (Rose, 1991) through big data (see Anagnostopoulos, Rutledge, & Jacobsen, 2013 (the United States) ; Ball, 2003 (United Kingdom) ; Grek, 2009; Lycett, 2013; Novoa & Yariv-Mashal, 2003 (Europe) ; Lingard, 2011 (Australia); Ozga, 2009 (England)), but how can we move the discussion forward? How can the quality of education provision be discussed, and improvements in schools strived towards, without the use of ‘big data’?
Accountability is not per se the problem. Using data is not per se the problem either. The problem is the fusion of accountability with heavy reliance on ‘big data’ to foster school improvement. Following Sahlberg's (2017) above quote, I suggest turning the gaze to ‘small data’, and exploring how it can be used within the context of education to improve education provision. ‘Small data’ is quite different to ‘big data’. ‘Big data’ is associated with quantitative information that is often generated computationally. In contrast, ‘small data’ is qualitative and more observational. It is about 'understanding the human side' to a problem (Lindstrom, 2016, p. 3). It involves immersing yourself into a community to ask questions, listening to answers and finding a work-around to the problem at hand. Lindstrom (2016) suggests that small data ‘puts the humanity back’ into finding solutions. This paper is consequently focused on examining the following question: What does the use of “small data” in education look like? It will be argued that the use of ‘small data’ in schools helps to foster organizational creativity, and thus improve the quality of educational provision.
The concept of ‘small data’ is analysed through empirical data drawn from a case study school in Queensland, Australia. The case study school is part of a three year project focused on examining educational change, and how school improvement manifests in contexts that are particularly challenging, and thus subject to high levels of government scrutiny and accountability. Although located in Australia, the context is useful for discussing what the use of ‘small data’ may mean in the context of education, and this has applicability more generally for scholars in both education policy and school leadership. Semi-structured interviews conducted with the four members of the school’s leadership team, along with semi-ethnographic observations of the school leaders in situ doing their jobs, will be used to demonstrate how ‘small data’ usage provides an opportunity for schools to innovate, thus stressing the need for education policy to shift its gaze toward the generation of innovation instead of the regulation of standards.
The significance of this research is to highlight how the concept of “small data” is useful for disrupting the stronghold of accountability being synonymous with ‘big data’. Likewise, it is to show how there is a need for the notion of ‘quality’ schooling provision to be detached from standardisation, and instead linked to innovation through organisational creativity in schools.
Anagnostopoulos, D., Rutledge, S., & Jacobsen, R. (Eds.). (2013). The infrastructure of accountability: Data use and the transformation of American education. Cambridge, MA: Harvard Education Press. Ball, S. J. (2003). The teacher’s soul and the terrors of performativity. Journal of Education Policy, 18(2), 215–228. doi:10.1080/0268093022000043065 Grek, S. (2009). Governing by numbers: The PISA ‘effect’ in Europe. Journal of Education Policy, 24(1), 23–37. doi:10.1080/02680930802412669 Lingard, B. (2011). Policy as numbers: Ac/counting for educational research. The Australian Educational Researcher, 38(4), 355–382. doi:10.1007/s13384-011-0041-9 Lindstrom, M. (2016). Small data: The tiny clues that uncover big trends. London, United Kingdom: Hodder & Stoughton General Division. Lycett, M. (2013). ‘Datafication’: Making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381–386. doi:10.1057/ejis.2013.10 Novoa, A., & Yariv-Mashal, T. (2003). Comparative research in education: A mode of governance or a historical journey? Comparative Education, 39(4), 423–438. doi:10.1080/0305006032000162002 Ozga, J. (2009). Governing education through data in England: From regulation to self-evaluation. Journal of Education Policy, 24(2), 149–162. doi:10.1080/02680930902733121 Sahlberg, P. (2011). Finnish lessons. New York, NY: Teachers’ College Press. Sahlberg, P. (2017). Small data for big change: What does it mean for teachers? Available at: https://pasisahlberg.com/small-data-for-big-change-what-does-it-mean-for-teachers/ (Accessed 29/01/2018). Sellar, S. (2015). A feel for numbers: affect, data and education policy. Critical Studies in Education, 56:1, 131-146, DOI: 10.1080/17508487.2015.981198
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
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Network 25. Research on Children's Rights in Education
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