Introducing students and teachers to data science
Data science is effecting a revolution in the way we do business, access knowledge, communicate, and understand the world. This revolution is underpinned by mathematics.Royal Society
MEI has specialist expertise in introducing data science to secondary students and adult learners. We provide curriculum enrichment, taught courses and other support for schools and colleges.
Data Science at Key Stage 5
Our Key Stage 5 courses are designed to be taken primarily by A level Mathematics and Core Maths students, but are also suitable for students studying other quantitative subjects. They provide a hands-on introduction to the field, develop understanding of data analysis, including the A level Large Dataset (LDS), and raise students’ awareness of the broad and burgeoning careers in the field.
Introduction to Data Science is a free online self-study course whose development was funded by the Arm School Program. The course provides six short self-study sessions to support students’ working with the LDS. It introduces them to key ideas and techniques in data science through simple exercises using Python in Kaggle, a web-based data and programming platform. Sessions include videos of data scientists demonstrating their work in fields ranging from football to the media and environmental and medical sciences.
Our Data Science Taught Course is a 10-week series of lessons delivered online by MEI tutors, with supporting tasks and study materials including student assessment and certification. Students work with real data taken from a variety of contexts, including the environment, health, commerce, and world development indicators. The course deepens students’ knowledge and skills and develops their understanding of statistics, data analysis and machine learning. For the final assessment, students build a model based on a real dataset and undertake a timed written examination.
Data Science at Key Stage 3 and Key Stage 4
We’re also introducing data skills to younger students.
In 2022 MEI participated in an international initiative to pilot data skills with Key Stage 3 students. The Data Explorers programme was sponsored by the technology company NetApp and developed in conjunction with TERC, the leading US-based STEM education organisation. MEI led the UK pilot of an after-school club targeted at disadvantaged students to develop their data skills using the CODAP platform. Over 50 Key Stage 3 students took part in the UK pilot, working hands-on with social issues data and sharing insights in final presentations. We are grateful to the schools that took part, Lampton School and Northwood School.
We’re also contributing to STEM Learning’s project with Deepmind to develop young people’s awareness and skills in artificial intelligence (AI). We have developed a collection of materials in CODAP for teachers of Key Stage 3 or 4 to use with students of AI-enabling subjects, such as mathematics and computing. The resources are designed to support awareness of basic concepts in machine learning and AI through the use of data. Teaching resources will be used by partnerships of schools in the project.
Data science skills in the workplace
MEI has worked with East Kent College Group to develop and trial an online taught course to introduce non-specialists to data analysis and using big data in the workplace. The course comprises six modules, including: quantitative skills and introduction to statistical analysis; working with big datasets in Excel; data analysis and visualisation in Excel and Power BI; and building models from data in Python. The course is designed to support towards Level 2 and 3 Gateway qualifications in Mathematics, Digital and IT Skills, and Data Analytics.
Your support is important
We have been able to develop our data science work though the generosity of donor and project funding. Please get in touch to find out more about our work in this area and how you can support it.
 Royal Society (2023) A New Approach to Mathematics and Data Education, p.3. Royal Society: https://royalsociety.org/topics-policy/projects/mathematical-futures/