We hear a lot about Big Data and Analytics these days. Data-driven organisations use analysed data to predict future behaviour of society as a whole, groups of people, and individuals. They use it to intervene in ways that decrease the likelihood of the ‘worst’ happening and accelerate the likelihood of the ‘best’ happening.
“Big Data is considered a key part of social reform. Eventually, it will predict those most likely to suffer social ills as children, those educationally deprived, those in households where violence is most likely to emerge. Early interventions can be staged - even before the problems emerge.”NZ Herald, 2014
“When it comes to reaching your fitness goals, steps are just the beginning. Fitbit tracks every part of your day—including activity, exercise, food, weight and sleep—to help you find your fit, stay motivated, and see how small steps make a big impact.” Fitbit, 2016
Big Data is described as the huge sets of electronic data that is available for analysing. Industry analyst Doug Laney articulated the now-mainstream definition of big data as the three Vs.
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. Hadoop which is an open-source software framework, is an example of this technology.
In New Zealand we can see this trend in data driven organisations. The government has set up the New Zealand Data Futures Forum to guide thinking about the use of data in response to questions such as “Who has what data about me/us and what will they be doing with it?” “What data do I/we have access to that can help us?”. NZ Data Future Forum’s vision is to set an “agenda to significantly advance New Zealand’s ability to unlock the latent value of our data assets and position us as a world leader in the trusted and inclusive use of shared data to deliver a prosperous society.” The forum identified that “Harnessing the benefits of data sharing and use requires a trusted, transparent, and balanced environment – one where privacy is paramount and trust maintained.” They recommended four principles to help New Zealanders navigate the data future.
Value: New Zealand should use data to drive economic and social value and create a competitive advantage.
Inclusion: All parts of New Zealand society should have the opportunity to benefit from data use.
Trust: Data management in New Zealand should build trust and confidence in our institutions.
Control: Individuals should have greater control over the use of their personal data.
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. Governments are using it and businesses are selling it. For example:
And in each case, the expectation is that the analytics will guide next steps. There is an expected ‘now what?’ response. Governments are guided to improve in their education system, schools are guided to know which students need targeted support and teachers are guided to know what the focus of support should be.
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 becuase of student success) (NZC and expanded in ERO indicators).
For learning organisations to be data driven organisations, all assumptions should be transparent and checked that they align with the purpose of education and the outcomes we want for our young people:
The assumptions brought to these questions are embedded worldviews, and beliefs about young people, education, pedagogy and curriculum. We need to ask ourselves
“ Do the analytics we use support all learners to develop the knowledge and capabilities needed to be confident, connected, actively involved, life-long learners, and all educators to provide young people with holistic educational experiences or are we using them in ways that will perpetuate inequality and will not realise potential?”
If the purpose of analytics is to provide feedback as to whether the intent of the teacher/ leader/ implementers/policy makers’ actions is the reality in learner outcomes then analytics can change education in at least three positive ways.
What does being a data driven organisation mean for our organisation? The following questions may be a useful guide for the conversations.
The following graphic may be useful for these discussions.
How do schools harness the potential power of student data while addressing concerns around how it’s used?
A post about the problems with big data in education and about something new: small data.
Dan Beckham: “We need the qualitative perspectives of 'big anthropology' to balance the quantitative insights of big data.”