Category Archives: Learning & Teaching

Puzzles and mysteries

Detail from abstract by Zahrah ReshPuzzles 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.

Image: Extract from abstract by Zahrah Resh.

Democratizing education

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!

Source:

Tsitsi Dangarembga, Protest and prizes, FT Weekend, 26/27 September 2020.

Patterson EA, Using everyday engineering examples to engage learners on a massive open online courseInternational Journal of Mechanical Engineering Education, p.0306419018818551

 

Shaping the mind during COVID-19

Books on a window sillIf 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.

Source:

Nan Shepherd, The Living Mountain, Edinburgh: Canongate Books Ltd, 2014 (first published in 1977 by Aberdeen University Press)

 

Tacit hurdle to digital twins

Tacit knowledge is traditionally defined as knowledge that is not explicit or that is difficult to express or transfer from someone else.  This description of what it is not makes the definition itself tacit knowledge which is not very helpful.  Management guides resolve this by giving examples, such as aesthetic sense, or innovation and leadership skills which are elusive skills that are hard to explain [see ‘Innovation out of chaos‘ on June 29th 2016 and  ‘Clueless on leadership style‘ on June 14th, 2017].  In engineering, there are a series of skills that are hard to explain or teach, including creative problem-solving [see ‘Learning problem-solving skills‘  on October 24th, 2018], artful design [see ‘Skilled in ingenuity‘ on August 19th, 2015] and elegant modelling [see ‘Credibility is in the eye of the beholder‘ on April 20th, 2016].  In a university course we attempt to lay the foundations for this tacit engineering knowledge; however, much of it is gained in work through experience and becomes regarded by organisations as part of their intellectual assets – the core of their competitiveness and source of their sustainable technology advantage.  In our work on integrated nuclear digital environments, from which digital twins can be spawned, we would like to capture both explicit and tacit knowledge about complex systems throughout their life cycle which will extend beyond the working lives of their designers, builders and operators.  One of the potential advantages of digital twins is as a knowledge management system by duplicating the life of the physical system and thus allowing its safer and cheaper operation in the long-term as well as its eventual decommissioning.   However, besides the very nature of tacit knowledge that makes its capture difficult, we are finding that its perceived value as an intellectual asset renders stakeholders reluctant to discuss it with us; never mind consider how it might be preserved as part of a digital twin.  Research has shown that tacit knowledge sharing is influenced by environmental factors including national culture, leadership characteristics and social networks [Cai et al, 2020].  I suspect that all of these factors were present in the heyday of the UK civil nuclear power industry when it worked together to construct advanced and complex systems; however, it has not built a power station since 1995 and, at the moment, new power stations are cancelled more often than built, which has almost certainly depressed all of these factors.  So, perhaps we should not be surprised by the difficulties encountered in establishing an integrated nuclear digital environment despite its importance for the future of the industry.

Reference: Cai, Y., Song, Y., Xiao, X. and Shi, W., 2020. The Effect of Social Capital on Tacit Knowledge-Sharing Intention: The Mediating Role of Employee Vigor. SAGE Open, 10(3), p.2158244020945722.