Puzzles and mysteries are a pair of words that have taken on a whole new meaning for me since reading John Kay’s and Mervyn King’s book called ‘Radical uncertainty: decision-making for an unknowable future‘ during the summer vacation [see ‘Where is AI on the hype curve?‘ on August 12th, 2020]. They describe puzzles as well-defined problems with knowable solutions; whereas mysteries are ill-defined problems, that have no objectively correct solution and are imbued with vagueness and indeterminacy. I have written before about engineers being creative problems-solvers [see ‘Learning problem-solving skills‘ on October 24th, 2018] which leads to the question of whether we specialise in solving puzzles or mysteries, or perhaps both types of problems. The problems that I set for students to solve for homework to refine and evaluate their knowledge of thermodynamics [see ‘Problem-solving in thermodynamics‘ on May 6th, 2015] clearly fall into the puzzle category because they are well-defined and there is a worked solution available. Although for many students these problems might appear to be mysteries, the intention is that with greater knowledge and understanding the mysteries will be transformed into mere puzzles. It is also true that many real-world mysteries can be transformed into puzzles by research that advances the collective knowledge and understanding of society. Part of the purpose of an engineering education is to equip students with the skills to make this transformation from mysteries to puzzles. At an undergraduate level we use problems that are mysteries only to the students so that success is achievable; however, at the post-graduate level we use problems that are perceived as mysteries to both the student and the professor with the intention that the professor can guide the student towards a solution. Of course, some mysteries are intractable often because we do not know enough to define the problem sufficiently that we can even start to think about possible solutions. These are tricky to tackle because it is unreasonable to expect a research student to solve them in limited timeframe and it is risky to offer to solve them in exchange for a research grant because you are likely to damage your reputation and prospects of future funding when you fail. On the other hand, they are what makes research interesting and exciting.
One motivation for developing Massive Open Online Courses (MOOC) has been to democratize education by giving everyone access to knowledge often presented by leading professors. It was certainly one reason why I developed and delivered two MOOCs on ‘Energy: Thermodynamics in Everyday Life‘ in 2015/16 and ‘Understanding Super Structures’ in 2017. The workload involved in supporting thousands of learners around the global is not insignificant and was unsustainable for me so I gave up after running them for a couple of years despite the intangible rewards [see ‘Knowledge spheres‘ on March 9th, 2016 and ‘A liberal engineering education‘ on March 2nd, 2016] . However, I incorporated the MOOC on energy into my undergraduate module on thermodynamics to create a blended approach to learning [see ‘Blended learning environments‘ on November 14th, 2018]. This paid dividends for me when the pandemic forced our campus into lock-down in the middle of semester last March and I already had a large number of bite-sized activities available online for our students. Most universities have had to move their teaching online due to the pandemic; but not all students are able to access the online materials as easily others. The Booker shortlisted novelist, Tsitsi Dangarembga has reported how one of her neighbours has struggled to access resources recommended to him by lecturers at his college in Bulawayo due to the cost and unreliability of Wi-Fi in Zimbabwe. She tried to help him by registering him for her hotspot package but, in common with many students, he studies mainly at night when hotspot venues are closed. The maps shows the global distribution of learners in one of the Energy MOOCs that I delivered and you can see the holes in Africa and South America which, at the time, we thought might be due to a lack of computer and internet access and Dangarembga’s account seems to support this hypothesis. So, we designed our second MOOC on Structures to be accessible via a mobile phone by using fewer videos and more audio clips that could be quickly downloaded and listened to offline. Unfortunately, we ran out of resources to complete the research on whether it was accessed more successfully in those grey areas on the map; however, the audio recordings were unpopular with the more traditional audience in the USA and UK who gave us immediate and vocal feedback!
If you looked closely at our holiday bookshelf in my post on August 12th 2020, you might have spotted ‘The Living Mountain‘ by Nan Shepherd [1893-1981] which a review in the Guardian newspaper described as ‘The finest book ever written on nature and landscape in Britain’. It is an account of the author’s journeys in the Cairngorm mountains of Scotland. Although it is short, only 108 pages, I have to admit that it did not resonate with me and I did not finish it. However, I did enjoy the Introduction by Robert MacFarlane and the Afterword by Jeanette Winterson, which together make up about a third of the book. MacFarlane draws parallels between Shepherd’s writing and one of her contemporaries, the French philosopher, Maurice Merleau-Ponty [1908-1961] who was a leading proponent of existentialism and phenomenology. Existentialists believe that the nature of our existence is based on our experiences, not just what we think but what we do and feel; while phenomenology is about the connections between experience and consciousness. Echoing Shepherd and in the spirit of Merleau-Ponty, MacFarlane wrote in 2011 in his introduction that ‘we have come increasingly to forget that our minds are shaped by the bodily experience of being in the world’. It made me think that as the COVID-19 pandemic pushes most university teaching on-line we need to remember that sitting at a computer screen day after day in the same room will shape the mind rather differently to the diverse experiences of the university education of previous generations. I find it hard to imagine how we can develop the minds of the next generation of engineers and scientists without providing them with real, as opposed to virtual, experiences in the field, design studio, workshop and laboratory.
It is about 35 years since I graduated with my PhD. It was not ground-breaking although, together with my supervisor, I did publish about half a dozen technical papers based on it and some of those papers are still being cited, including one this month which surprises me. I performed experiments and computer modelling on the load and stress distribution in threaded fasteners, or nuts and bolts. There were no digital cameras and no computer tomography; so, the experiments involved making and sectioning models of nuts and bolts in transparent plastic using three-dimensional photoelasticity [see ‘Art and Experimental Mechanics‘ on July 17th, 2012]. I took hundreds of photographs of the sections and scanned the negatives in a microdensitometer. The computer modelling was equally slow and laborious because there were no graphical user interfaces (GUI); instead, I had to type strings of numbers into a terminal, wait overnight while the calculations were performed, and then study reams of numbers printed out on long rolls of paper. The tedium of the experimental work inspired me to work on utilising digital technology to revolutionise the field of experimental mechanics over the following 15 to 20 years. In the past 15 to 20 years, I have moved back towards computer modelling and focused on transforming the way in which measurement data are used to improve the fidelity of computer models and to establish confidence in their predictions [see ‘Establishing fidelity and credibility in tests and simulations‘ on July 25th, 2018]. Since completing my PhD, I have supervised 32 students to successful completion of their PhDs. You might think that was a straightforward process of an initial three years for the first one to complete their research and write their thesis, followed by one graduating every year. But that is not how it worked out, instead I have had fallow years as well as productive years. At the moment, I am in a productive period, having graduated two PhD students per year since 2017 – that’s a lot of reading and I have spent much of the last two weekends reviewing a thesis which is why PhD theses are the topic of this post!