Above is an aircraft wing which has picked up ice on the leading edge of its wing. This is of course is not ideal, especially for an aircraft in the air. You don’t want large amounts of ice forming along the leading edge of the wing in flight, it will add weight and make the wing less able to generate lift. I think there were particular worries about this during the Second World War, possibly because planes were flying higher and faster as the war drove rapid advances in aircraft design and performance. So the United States Army Air Force turned to the dream team of a Nobel-prize winner, Irving Langmuir, and the first woman to obtain a PhD in physics from the University of Cambridge, Katherine Blodgett. They worked to understand the following problem.
Gavin Williamson, the Secretary of State for Education and so my boss has been sharing his opinions on the coming university academic year. One thing he said that I agree with is
Parents would find it “odd” if students could go to other social activities but were not allowed back into lecture halls, the education secretary told the Universities UK conference.
Students may also find it odd, if they can cram into a nightclub, but are asked to socially distance in a lecture theatre, which has a reduced seating capacity due to University-imposed COVID-19 restrictions.
Semester is starting to loom large, lessons start in four weeks. I will be teaching several things, including biological physics – a course where I also try and blend in some learning of estimation. Of course, for biological physics I currently have no shortage of real-world examples. So let’s look at one that involves some estimation. Question: If Guildford’s nightclub Casino is full to capacity, what is the probability* that none of the patrons are asymptomatic carriers of COVID-19? Casino’s capacity is 1,500. ONS data on the fraction of the population that are infected is here. A reasonable estimate for the fraction of people infected with COVID-19, that do not know it, is somewhere in the range say one in five to one in three.
I am teaching second-year physics students computational physics; I have been doing this for 20 years. One of things that has frustrated me for a few years is students asking me to check results, when they just want to know if the answer is right or wrong. When I help students who ask this question I do try and take students through my reasoning. For example, if the correct result of the calculation is a Gaussian function, I briefly describe what a Gaussian looks like.
This blog post combines/builds on two earlier posts: One where I looked at using Google Colab to host Jupyter notebooks for my autumn teaching, and one where I messed around with a Jupyter notebook that can generate a university league table with almost any university at the top. I have tidied up the league table generating Jupyter notebook and you should now be able to see it on Google Colab here and the spreadsheet it needs with the University data is available here.
Today I am reading both Calling Bullshit by Jevin West and Carl Bergstrom, and of a “growing crisis” over Scottish Higher results — presumably a similar crisis will happen for A levels when the results are released in a few days. I have got to the bit in Calling Bullshit where West and Bergstrom talk about bullshitting via statements that superficially look rigorous, but in reality are pretty flaky. In this blog post I want to suggest, possibly controversially, that the distinctions at the root of the growing crisis in Scotland, between a grade A and B in a Scottish Higher*, or a B and C, etc, have a slight whiff of bullshit about them.
Last year I changed my second-year computing teaching to Jupyter Python notebooks. I think Jupyter notebooks worked well at teaching how to do useful stuff like analyse data. The notebooks were hosted on the Micrsoft service Azure which wasn’t great but basically worked. However, not only is Azure far from perfect, it is also being binned around about week 2 of semester.
A sixth form teacher, Niamh Sweeney has an interesting and passionate call for schools and colleges to use the impetus provided by the sudden corona-virus-imposed changes, for good. It is in today’s The Guardian. I teach the products of these schools. I get frustrated by some attitudes I see in students that they may have learnt in the “testing hamster wheel” she refers to. So I hope that the impetus does get used for good in the UK’s schools and colleges.
With excellent timing, just as I prepared to tell students in my biological physics lectures that we are roughly 20% protein (by mass), and that gelatin is a very abundant protein, which holds our tissues together, The Guardian ran an article on how cool gelatin desserts, aka jellies are. The article included the, slightly odd in my opinion, YouTube video above.
One of the classic mistakes you can make as a teacher is to spot what you fondly think is a small gap in the curriculum, and then commit to filling it. The not-so-small gap is in our teaching of data analysis. Analysing data is, as I just said to our second years, a key part of doing science. As I also said to them, it is poor practice to use formulas or software such as Excel without knowing what they are doing. Both of these statements are true. The problem is that data analysis is a huge subject, and it is underpinned by lots of maths whose details I don’t know myself and will not be teaching to the students. So, by committing to do one extra lecture to try and improve matters here, I bit off a bit more than I could chew.