Abstract:
Data is shaping educational practice and being used as a mechanism of school reform and improvement. These practices incite a number of questions that need to be addressed, such as the appropriateness of data for certain tasks, centralization of educational policy and detachment from learning contexts, and stakeholder data literacy. We argue that developing a better understanding and increased visibility of the life and journey of data, where data is used appropriately or inappropriately, the spaces where expectations of data as evidence may be problematic, can be identified to better understand the datafication of education, improve data-informed policy and support stakeholder decision making.The aim of this paper is to employ Bates et al.'s (2016) data journeys methodology as a novel way to explore the complexity of educational data production, processing, and distribution. The 'data journey' focuses on how data is repurposed through production, processing and various activities. In the current analysis, this approach is used to consider how standardized testing data from the National Assessment Program Literacy and Numeracy (NAPLAN), as explicated in a mandatory NSW school improvement policy, is employed by stakeholders and for what purposes over four years. The original purpose of NAPLAN data was to follow student progress. The scope of usage has since extended. Current policy explains that school leadership and teachers can select pre-processed NAPLAN data, made available through a controlled departmental data platform, to use as evidence of school improvement. The data may then be linked with other data sources. In a new form and linked, possibly 1-3 years later, it may be used to draw conclusions and support school decision making. At the end of the process, data is returned to the Department in another form, as evidence of progress on school improvement, via a second departmental online platform. In this paper, we will present a full data journey and its implications for stakeholders work in schools and education policy. Ultimately, the intention of this analysis is not to limit the use of educational data, but rather to use the data journeys approach to surface ‘data justice’ concerns and, in doing so, highlight the “societal transformations that are associated with datafication and the implications these have on people’s lives” (Dencik et al., 2019, p. 876). Bates, J., Lin, Y.-W., & Goodale, P. (2016). Data journeys: Capturing the socio-material constitution of data objects and flows. Big Data & Society, 3(2), 1–12. https://doi.org/10.1177/2053951716654502Dencik, L., Hintz, A., Redden, J., & Treré, E. (2019). Exploring Data Justice: Conceptions, Applications and Directions. Information, Communication & Society, 22(7), 873–881. https://doi.org/10.1080/1369118X.2019.1606268