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Maths helps maths graduates get professional jobs

The Destination of Leavers of Higher Education (DLHE, pronounced ‘deli’) survey sends a questionnaire to all UK university graduates six months after graduation and this gives some idea of what happens to students once they graduate. It is flawed, but has a high response rate and is an interesting tool.

There is a second type of DLHE survey, which is longitudinal. This surveys graduates 3.5 years after graduation, and the 2010/11 longitudinal data has just been released. This deserves some investigation and I don’t have time right now, but I did notice a couple of tables that make me proud of my subject.

Programming to investigate Quarto

I was invited to contribute to a special issue of The Mathematics Enthusiast on ‘Risk – Mathematical or Otherwise‘, guest edited by Egan J Chernoff. I wrote about the Maths Arcade and programming strategies for a game we play there called Quarto. Really, I was sketching an outline of an idea to encourage student project work.

My title is ‘Developing Strategic and Mathematical Thinking via Game Play: Programming to Investigate a Risky Strategy for Quarto‘ and the abstract is below.

Physics with hidden calculus

Crossing campus this afternoon, a student whose exam is later this week asked me “when you ask a real-world question on the exam and you want us to solve an ODE, can we just do it using formula we memorised from A-level physics?” Like what? “Like with one of the distance questions we might just use $v^2 = u^2 + 2as$.” I said that if they were relying on a result we didn’t use in the module and that they hadn’t proven, this would be a problem.

In the latest Taking Maths Further podcast (Episode 19: Computer games and mechanics), we had a puzzle that we say could be answered roughly, but the precise answer 23.53 (2 d.p.) required a little calculus. On Twitter, @NickJTaylor said

π approximation: Machin’s formula

In the excellent $\pi$ approximation video, Katie Steckles asked for $\pi$ approximations. I teach a first year techniques module (mostly calculus and a little complex numbers and linear algebra). This year I have changed a few bits in my module; in particular I gave some of my more numerical topics to the numerical methods module and took in return some of the more analytic bits from that module. This gives both modules greater coherence, but it means I have lost one of my favourite examples, from the Taylor series topic, which uses a Maclaurin series to approximate $\pi$.