We definitions of data analytics (DA) as a process of ‘engaging creatively in exploring data, including big data, to understand our world better, to draw conclusions, to make decisions and predictions, and to critically evaluate present/future courses of actions‘.
At the heart of our conceptual framework for DA in schools Figure below is this cyclic process of acts we expect when students engage in DA.
For example, DA associated with data-driven decision making also needs gaining a better understanding of data that is essential to exploring data. This starts with understanding the system that the data come from and defining the problem (see PPDAC investigative cycle i). Then engaging in data exploration involves extracting and categorizing data and analyzing them through data visualization tools and appropriate calculations. This leads to drawing conclusions by using data as evidence for generalizations beyond describing the given data. These earlier steps guide making decisions/predictions with an articulation of uncertainty. Then evaluating courses of actions takes place with a connection to the problem defined earlier in the process.
The investigative cycle is complemented with various skills and competencies that are in line with “Framework for 21st Century Learning” (http://www.p21.org/about-us/p21-framework) by the Partnership for the 21st Century Learning (P21) or Data analytics such as statistical literacy, ICT literacy, and so on.
In 2018-19 we will start our teaching experiments with our partnership schools and hopefully, our students will experience this DA process with authentic data and real-life related DA questions!