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Lesson 2, Task 2 - The Joy of Data




The focus of Sir Michael Barber’s presentation is in addressing the four misconceptions around data:

  1. The growing ubiquity of data in our lives undermines our creativity and inspiration
  2. The data tells you what to do
  3. Data replaces professional judgment
  4. Personal data will be abused by governments and businesses so we should make sure it is not collected

For Barber, data as fun is shallow, while data as joyful is deep. The missing link between the two is learning and the success that data affords. Data provides the evidence that allows a coach to analyse in order to take us further.

Data is at the heart of creativity and inspiration, with top performance coming through effort and data. Using the analogy of battle, Barber explains that victory often comes through the use of some sort of information. Good data allows more focus on inspiration.

Data provides the means for humans to exercise informed judgments. For Barber this allows for the unleashing of greatness.

Data allows control for the informal learner, providing a means of benchmarking yourself against others. It puts the science into the science of learning. Education is not just about tomorrow, it is about every day. That is why data matters.

Looking ahead to the future, Barber ends with a description of a world where the collection of data is inconspicuous and unobtrusive. The focus is on providing humans with the ability to make informed choices needed for a democratic society. For this to happen, data needs to be accessible. It should be less about governmental regulations and more about informing organisations to make efficient and effective decisions.



In a recent book, The End of Average, Todd Rose focuses on a more nuanced way of looking at data. Discussing the creation of the ‘average’ man, Rose highlights the way in which error and ranking have come at a cost to individuality. In lieu of this average, he puts forward the ‘case for individuality’. This focuses on measuring our jagged profiles, looking at things within a context and having divergent pathways for learners to follow.

Although Barber talks about individuals benchmarking themselves against others, the real challenge is to collect data on ourselves in order to identify our own areas for development. Building on the work of Peter Molenaar, Rose discusses the idea of dynamic systems which focus on a process of 'analyse then aggregate'. This to me seems akin to the work done by Project Zero team around Reggio Emilia and Visible Thinking, where the focus is on bringing together documentation and then aggregating the learning.

Moving into the future that the discussion will be between Rose's individual approach and Barber's more system-wide stance. Although data will be ingrained, hopefully it will encompass the personal, jagged, more informal aspects of learning collected in a systematic way? The question that remains is what that means for things such as benchmarking, progression data, analyse and other such forms of assessment? There are many questions that we still need to work through. 
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