Big Data is described as the huge sets of electronic data that is available for analysing, whereas Analytics, according to Wikipedia, is "the discovery and communication of meaningful patterns in data." New technologies make it all possible, as they provide massive storage for any kind of data, enormous processing power, and the ability to handle virtually limitless concurrent tasks or jobs.
What does this mean for education?
Analytics profoundly shape the educational reality that they measure. What is measured and reported through the use of infographics or dashboards becomes more important than what is not reported. All levels of education are becoming data-driven organisations. ‘Big Data’ and the use of analytics can provide insights into some of the gnarly challenges associated with improving equity and excellence.
The key thing is human assumptions underpin data collecting, analysing, interpreting, and reporting, and these assumptions are then applied to the tools and analytics. For example, in the national and international analytics it is assumed that literacy, mathematics, and science achievement are essential life skills and signal that a country is preparing young people for the future. One problem with this is that readers of the reports may ‘forget’ things such as literacy is of service to the curriculum (and is not the curriculum). For example, in New Zealand, student success is about students being “confident, connected, actively involved, lifelong learner” (and achievement both leads to and is because of student success) (NZC and expanded in ERO indicators).
For learning organisations to be data-driven organisations, all assumptions should be transparent and checked to ensure that they align with the purpose of education and the outcomes we want for our young people: