Tag Archives: education

Conversations about engineering over dinner and a haircut

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For decorative purposes: colour contour map of a face mask produced using fringe projectionRecently, over dinner, someone I had just met asked me what type of engineering I do. I always find this a difficult question to answer because I am sure that they are just being polite and do not want to hear any technical details but I find it hard to give an interesting answer without diving into details. Earlier the same day I had given a lecture on thermodynamics to about 300 undergraduate students so I told my inquisitor about this experience and explained that thermodynamics was the science of energy and its transformation into different forms. Then, I muttered something about being interested in making and using measurements to ensure that computational models of aircraft and nuclear power stations are reliable and the conversation quickly moved on. A week or so earlier, I was having my hair cut when the barber asked me a similar question about what I did and I told him that I was a professor of engineering which led to a conversation about robots. We speculated about whether we would ever lose our jobs to robots and decided that we were both fairly secure against that threat. There is a high degree of creativity in both of our roles – while I always ask for the same haircut, my hair is in a different state every time I visit the barbers’ and I leave looking slightly different every time. I don’t think that I would like the uniformity that a row of robots in the barbers’ shop might produce. And, then there is the conversation during the haircut. A robot would need to pass the Turing test, i.e., to exhibit intelligent behaviour indistinguishable from a human, which no computer has yet achieved or is likely to do so in our lifetime, at least not a cost that would allow them to replace barbers. The same holds for professors – the shift to delivering lectures online during the pandemic might have made some professors worry that their jobs were at risk as recorded lectures replaced live performances; however, student feedback tells us that students have a strong preference for on-campus teaching and the high turnout for my thermodynamics lectures supports that conclusion.

Footnotes:

For a new website I was asked to describe my research interests in about 25 words and used the following: ‘the acquisition of information-rich measurement data and its use to develop digital representations of complex systems in the aerospace, biological and energy sectors’.  Fine for a website but not dinner conversation! 

There have been some attempts to build a robot that cut your hair, for example see this video. 

Image shows a colour contour map describing the shape of a facemask produced using fringe projection which could be used as part of the vision system for a robotic barber.  For more information on fringe projection see: Ortiz, M. H., & Patterson, E. A. (2005). Location and shape measurement using a portable fringe projection system. Experimental mechanics, 45(3), 197-204 or watch this video from the INDUCE project that was active from 1998 to 2001.

Everything is in flux but it’s not always been recognised

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Decorative photograph or ruins of Fountains Abbey next to River SkellI am teaching thermodynamics to first year undergraduate students at the moment and in most previous years this experience has stimulated me to blog about thermodynamics [for example: ‘Isolated systems in nature?’ on February 12th, 2020].  However, this year I am more than half-way through the module and this is the first post on the topic.  Perhaps that is an impact of teaching on-line via live broadcasts rather than the performance involved in lecturing to hundreds of students in a lecture theatre.  Last week I introduced the second law of thermodynamics and explained its origins in efforts to improve the efficiency of steam engines by 19th century engineers and physicists, including Rudolf Clausius (1822 – 1888), William Thomson (1827 – 1907) and Ludwig Boltzmann (1844 – 1906).  The second law of thermodynamics states that the entropy of the universe increases during all real processes, where entropy can be described as the degree of disorder. The traditional narrative is that thermodynamics was developed by the Victorians; however, I think that the ancient Greeks had a pretty good understanding of it without calling it thermodynamics.  Heraclitus (c. 535 BCE – c. 475 BCE) understood that everything is in flux and nothing is at rest so that the world is one colossal process.  This concept comes close to the modern interpretation of the second of law of thermodynamics in which the entropy in the universe is constantly increasing leading to continuous change.  Heraclitus just did not state the direction of flux.  Unfortunately, Plato (c. 429 BCE – c. 347 BCE) did not agree with Heraclitus, but thought that some divine intervention had imposed order on pre-existing chaos to create an ordered universe, which precludes a constant flux and probably set back Western thought for a couple of millennia.  However, it seems likely that in the 17th century, Newton (1643 – 1727) and Leibniz (1646 – 1716), when they independently invented calculus, had more than an inkling about everything being in flux.  In the 18th century, the pioneering geologist James Hutton (1726 – 1797), while examining the tilted layers of the cliff at Siccar Point in Berwickshire, realised that the Earth was not simply created but instead is in a state of constant flux.  His ideas were spurned at the time and he was accused of atheism.  Boltzmann also had to vigorously defend his ideas to such an extent that his mental health deteriorated and he committed suicide while on vacation with his wife and daughter.  Today, it is widely accepted that the second law of thermodynamics governs all natural and synthetic processes, and many people have heard of entropy [see ‘Entropy on the brain’ on November 29th, 2017] but far fewer understand it [see ‘Two cultures’ on March 5th, 2013].  It is perhaps still controversial to talk about the theoretical long-term consequence of the second law, which is cosmic heat death corresponding to an equilibrium state of maximum entropy and uniform temperature across the universe such that nothing happens and life cannot exist [see ‘Will it all be over soon?’ on November 2nd, 2016].  This concept caused problems to 19th century thinkers, particular James Clerk Maxwell (1831 – 1979), and even perhaps to Plato who theorised two worlds in his theory of forms, one unchanging and the other in constant change, maybe in an effort to dodge the potential implications of degeneration of the universe into chaos.

Image: decaying ruins of Fountains Abbey beside the River Skell.  Heraclitus is reported to have said ‘no man ever steps twice into the same river; for it’s not the same river and he’s not the same man’.

Collegiality as a defence against pandemic burnout

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photograph of a flower for decorative purposes onlyMany of my less experienced colleagues ask, ‘what is collegiality?’  Collegiality is the glue that holds universities together according to Neeta Baporikar.  While Roland S. Barth suggested that if students are to learn and develop, then their teachers must also learn and develop and collegiality is the set of practices and culture that support this adult growth.  In this context, Thomas Hoerr has proposed that collegiality has five components: (i) teachers talking about students with teachers; (ii) teachers working together to develop education programmes; (iii) teachers observing one another; (iv) teachers teaching each other; and (v) teachers talking about education and working together on committees.  Neeta Baporikar echoes this view by concluding that if we hope to teach students to participate, examine issues, collaborate, think critically and synthesise new approaches then we should be their model.  

In an environment where research is a priority, it is possible to substitute ‘researcher’ for ‘teacher’ in the descriptions above.  Then collegiality becomes researchers talking about [research] students, researchers working together to develop research programmes, researchers observing one another, researchers teaching each other, and researchers talking about research and working together on committees.  The idea that collegiality is a strategy for excellence holds as well as for research as it does for teaching.

The pressures on early career academics in a research university can be intense and the temptation to focus exclusively on delivering teaching and performing research can lead individuals to work in isolation and to neglect the opportunities provided by active engagement with their colleagues.  However, leaders must also take responsibility for creating an environment in which collegiality can thrive and encouraging active participation – it is part our service to the academic community as leaders to create and maintain a culture of scholarship and excellence [see ‘Clueless on leadership style’ on June 14th, 2017].  Neeta Baporikar provides steps that heads of departments can take to nurture collegiality, including providing a vision, encouraging collaborative participation, listening to diverse opinions, building on people’s strengths, and being aware of the world outside the department.  This is similar to the shepherding approach to leadership that I wrote about in May 2017 [‘Leadership is like shepherding’ on May 10th, 2017].  However, it has all become much more difficult in a pandemic – both collegiality and leadership.  Last week an article in Nature suggested that pandemic burnout is rife amongst academics working long hours in isolation to transpose and deliver their teaching materials online, to maintain their research without the spontaneity of face-to-face discussions with their team or collaborators, and to support the well-being and mental health of students who are also at risk of burnout.  It is suggested that burnout can be managed by finding a forum to express your feelings, creating ways to detach from stress, prioritizing and normalizing conversations about mental health, and fighting the isolation through meeting with peers.  These steps are a combination of traditional collegiality and the five ways to well-being: connect, be active, take notice, keep learning and give [see graphic in ‘On the impact of writing on well-being’ on March 3rd, 2021].

References

Neeta Baporikar, Collegiality as a strategy for excellence in academia, IJ Strategic Change Management, 6(1), 2015.

Roland Barth, Improving schools from within, Jossey-Bass, 2010.

Virginia Gewin, Pandemic burnout is rampant in academia, Nature, 591: 489-491, 2021.

Thomas R. Hoerr, Principal Connection: The Juggler’s Guide to Collegiality, Communication Skills for Leaders, 72(7): 88 -89, 2015.

Reduction in usefulness of reductionism

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decorative paintingA couple of months ago I wrote about a set of credibility factors for computational models [see ‘Credible predictions for regulatory decision-making‘ on December 9th, 2020] that we designed to inform interactions between researchers, model builders and decision-makers that will establish trust in the predictions from computational models [1].  This is important because computational modelling is becoming ubiquitous in the development of everything from automobiles and power stations to drugs and vaccines which inevitably leads to its use in supporting regulatory applications.  However, there is another motivation underpinning our work which is that the systems being modelled are becoming increasingly complex with the likelihood that they will exhibit emergent behaviour [see ‘Emergent properties‘ on September 16th, 2015] and this makes it increasingly unlikely that a reductionist approach to establishing model credibility will be successful [2].  The reductionist approach to science, which was pioneered by Descartes and Newton, has served science well for hundreds of years and is based on the concept that everything about a complex system can be understood by reducing it to the smallest constituent part.  It is the method of analysis that underpins almost everything you learn as an undergraduate engineer or physicist. However, reductionism loses its power when a system is more than the sum of its parts, i.e., when it exhibits emergent behaviour.  Our approach to establishing model credibility is more holistic than traditional methods.  This seems appropriate when modelling complex systems for which a complete knowledge of the relationships and patterns of behaviour may not be attainable, e.g., when unexpected or unexplainable emergent behaviour occurs [3].  The hegemony of reductionism in science made us nervous about writing about its short-comings four years ago when we first published our ideas about model credibility [2].  So, I was pleased to see a paper published last year [4] that identified five fundamental properties of biology that weaken the power of reductionism, namely (1) biological variation is widespread and persistent, (2) biological systems are relentlessly nonlinear, (3) biological systems contain redundancy, (4) biology consists of multiple systems interacting across different time and spatial scales, and (5) biological properties are emergent.  Many engineered systems possess all five of these fundamental properties – you just to need to look at them from the appropriate perspective, for example, through a microscope to see the variation in microstructure of a mass-produced part.  Hence, in the future, there will need to be an increasing emphasis on holistic approaches and systems thinking in both the education and practices of engineers as well as biologists.

For more on emergence in computational modelling see Manuel Delanda Philosophy and Simulation: The Emergence of Synthetic Reason, Continuum, London, 2011. And, for more systems thinking see Fritjof Capra and Luigi Luisi, The Systems View of Life: A Unifying Vision, Cambridge University Press, 2014.

References:

[1] Patterson EA, Whelan MP & Worth A, The role of validation in establishing the scientific credibility of predictive toxicology approaches intended for regulatory application, Computational Toxicology, 17: 100144, 2021.

[2] Patterson EA &Whelan MP, A framework to establish credibility of computational models in biology. Progress in biophysics and molecular biology, 129: 13-19, 2017.

[3] Patterson EA & Whelan MP, On the validation of variable fidelity multi-physics simulations, J. Sound & Vibration, 448:247-258, 2019.

[4] Pruett WA, Clemmer JS & Hester RL, Physiological Modeling and Simulation—Validation, Credibility, and Application. Annual Review of Biomedical Engineering, 22:185-206, 2020.