Data Driven Design and the Process of STEM


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In order to create an environment which supports success in Science, Technology, Engineering, and Mathematics (STEM) in my small middle school classroom, the emphasis is on process, and not product, and iterative workflows are the key to continuous improvement.

Committing to any iterative inquiry or design cycle will help move students and teachers away from a performance (fixed) mindset toward a mastery (growth) mindset because students will learn to engage more with the process than the product – because it is the process that reveals the data that they need to continually improve.

Data Driven Design for middle and senior students is about getting kids to move away from caring so much about the products they make for school, to reflecting about what went well, and what didn’t so much, during the creative process.

It is about showing students how to apply the data that they have collected and interpreted to continually improve their products within an iterative workflow.

It is about getting them to see their products as what Pixar calls their ‘Most Recent Worst Versions’, and not simply a reason to ‘chase their marks’

Most importantly, it is about teachers showing students how to get data that belongs to them – and this changes the dynamic between teacher and student to allow for a growth mindset to occur for both.  This is how we will build an economy serviced by innovative and resilient people.

I have for many years been of the side of process versus product, and it was through this type of curriculum planning that I discovered that students need not be in control of the product, and that iterative inquiry cycles provide the structure needed to guide students through inquiry based learning projects where at the outset the products are unknown.

This is a paradigm shift for middle and senior students, parents, teachers and schools –  but it is a critical shift that needs to occur if we are to produce critically versatile thinkers and doers.  In this sense, the process frees the mind from a performance based attitude toward education (where normative standards are the measure of success) – to a growth mindset where the product is the student’s ‘Most Recent Worst Version’, and where the data collected to inform design becomes more important that the summative evaluation, or mark, given subjectively by the teacher.

In other words, formative assessment can and will override summative assessment in terms of importance once students see the value of it to inform their designs. Students can do this by becoming experts at collecting, organizing, and interpreting data to realize their visions and passions, and no longer get stuck on making something for the teacher. They will thus become ‘hungry for their own data’, because the data now serves their needs.

This is one place where entrepreneurial education and arts education intersect.  In DDD, the ‘bootstrapping checklist’ provides an explicit phase for data collection to inform the design process.  In art-making, ensuring that the critical analysis process is conducted during the art making process also provides students with valuable feedback to inform their works. And in all subjects, peer and teacher feedback occurs directly in the digital document that students are working in, and this feedback allows for these decisions to happen almost immediately.

Feedback actually leads to improvement, and a student who values this type of learning will exist in a growth mindset and will have the skills to navigate our ever increasingly competitive global marketplace.


“Following a structured approach to developing new ideas is critical for having a shot at actually being able to measure impact and value.”

Kristan ‘Krispy’ Uccello – software engineer at Google in CA



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