Data-driven improvements: stories from the schools sector

I had the pleasure of attending the #edtechuk global summit on Friday, hearing about the space where education (all sectors), technology and entrepreneurship meet. It was really interesting to be at an event where schools, HE and FE are all considered, and I picked up a couple of tales from the schools sector which I thought were relevant to our current codesign challenge on how data can be used to improve learning and teaching.

Sherry Coutu (@scoutu) is an entrepreneur, investor and adviser with an interest in raising aspiration and participation in STEM subjects, particularly in girls. She was talking about the power of data to help schools make effective interventions in raising awareness and understanding of STEM subjects and entrepreneurial skills. She highlight two applications of data which have been useful: first, that analysing longitudinal data can help to identify what the key timing and frequency needs to be for interventions (such as visiting speakers) to have the maximum impact. Secondly, she showed how Founders4Schools used geographical data about the location of start-up and scale-up companies to highlight the availability of business leader speakers to schools, particularly those in areas of social and economic variation. Together these interventions can significantly raise learner interest in STEM subjects and business.

Checking data on a smart watch

And as a reminder of the importance of straightforward activity data in helping to guide teachers and students, Colin Hegarty (@hegartymaths) an award-winning teaching and founder of Hegartymaths, gave an example of one student who left a comment on his site complaining that the questions were too difficult. Colin was able to see that the student had left it until just before school, and hadn’t viewed any of the teaching material before attempting the questions. He flagged this up to the student’s local teacher, who discussed effective strategies with the student, leading to improved study behaviours and improved scores. Hegarty summarised this something along the lines of “often the best thing about the technology is that it can help students to recognise that learning maths is hard work and they do need to put the time in.” We see this approach in the student-facing learning analytics apps, which serve to give students an unglossed picture of how much time they’re spending on various types of activity, and there’s evidence that this leads to long-term changes in behaviour.

What can we learn from these approaches in higher and further education? What are you already doing with data that effectively helps you help your students?

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