Design decisions in creating short data science courses for pre-university students - Tom Button and Ian Dickerson (United Kingdom)
Abstract
Over the past three years MEI has designed and implemented two optional data science courses for pre-university Mathematics students (aged 16-18). One of these courses is an open-access self-study course and the other is a taught programme, delivered via online lessons.
In this session we will describe the major decisions taken when designing these courses:
- How to develop students’ ability to make context-based decisions when working with data.
- How to use a programming language without the course feeling like a coding course.
- How to introduce machine learning to students working at this level.
There will be an opportunity to view some of the resources and also discuss the implications for introducing data science to learners at this level.
Bio Tom Button
Tom Button is the Mathematics Technology Specialist for MEI (an independent UK mathematics education charity).
He is leading on MEI’s Data Science courses for students. He has almost 20 years’ experience in the integration of technology into resources, professional development and assessment for mathematics. Prior to this he taught mathematics in colleges for 10 years.
Bio Ian Dickerson
Ian Dickerson taught in London secondary schools for nearly two decades before joining the founding team at Ada, the National College for Digital Skills in 2016.
In his five years as Head of Maths, he developed a pioneering approach to the level 3 curriculum that places coding front and centre. He now spends half of his time developing Data Science courses with MEI (an independent UK mathematics education charity), and the other half supporting Ada as their Data Specialist.
