How machine learning is revolutionising materials science

Suitable for 14 to 19-year-olds (secondary and high schools, and college), this article and accompanying activity sheet can be used in the classroom or shared with students online.

This resource links to KS4 and KS5 Engineering, Physics and Computer Science.

It can also be used as a careers resource and links to Gatsby Benchmarks:
Gatsby Benchmark 2: Learning from career and labour market information
Gatsby Benchmark 4: Linking curriculum learning to careers

• This teaching resource explains the work of Professor Dane Morgan and Dr Ryan Jacobs from the University of Wisconsin-Madison in the US who are investigating the opportunities and challenges posed by machine learning for the field of materials science and engineering (MS&E).
• This resource also contains interviews with Dane and Ryan. If you or your students have a question for them, you can submit it online – go to the article using the Futurum link below and scroll to the bottom of the page. Dane and Ryan will reply!
• The activity sheet provides ‘talking points’ (based on Bloom’s Taxonomy) to prompt students to reflect on Dane and Ryan’s research, and tasks them to research how machine learning has impacted different fields of research.
• The animation summarises their research and is accompanied by a script for accessibility.

This resource was first published on Futurum Careers, a free online resource and magazine aimed at encouraging 14-19-year-olds worldwide to pursue careers in science, tech, engineering, maths, medicine (STEM) and social sciences, humanities and the arts for people and the economy (SHAPE).

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