Only the rascals think they win

‘I learned that you always lose.  Only the rascals think they win.’ This is quote from Nausea by Jean-Paul Sartre.  ‘Rascals’ has become a cute word for a villain; but, the Merriam-Webster Dictionary defines it as ‘a mean, unprincipled person’.  It’s a rather pessimistic view of life – that everyone loses; only some people don’t see it.  Or perhaps Sartre is saying that if you are successful then it’s not as a result of your own efforts but of the efforts of others around you and the opportunities that come your way;  so, if you think you won then you must be mean and unprincipled.

I was puzzled by the always losing until I read an Op-Ed by Lilliana Mason in the New York Times on June 7th, 2018.  She explains that as individuals we hold multiple identities, as a partner, parent, employee, feminist, etc; and that some of these identities are more important to us than others.  She says that, at any one time, the most important identity tends to be the one whose status is most threatened.  This could make you feel as if you are always losing.  In other words we tend to focus on the negative – our brains are wired to blame rather than praise [see ‘Depressed by exams‘ on January 31st, 2018 and ‘Happenstance, not engineering‘ on November 9th, 2016].  Or as my editor commented: ‘we tune into the threats in our lives – it’s a matter of survival’.


Lilliana Mason, The President’s ‘winning’ is our loss, Op-Ed, New York Times, June 7th, 2018.

Jean-Paul Sartre, Nausea, translated by Lloyd Alexander, New York: New Directions Pub. Co., 2013.

Bruek H, Human brains are wired to blame rather than to praise, Fortune, December 4th 2015.

Engage, Explore, Explain, Elaborate and Evaluate

This quintet of ‘E’ words form the core of the 5Es lesson plans.  They probably appeared first in the Biological Sciences Curriculum Study of the 1980s based on work by Atkin and Karplus [1962].  They form a series of headings for constructing your lesson or lecture plan.  This framework has been used to construct all of the lesson plans posted on this blog [].  Since the lesson plans are designed for introductory engineering courses, the Engage step always incorporates an Everyday Engineering Example.  I have amended the Oxford English Dictionary definition of the 5Es below to illustrate the content of each step.

  • Engage – to attract and hold fast [the students’ attention]
  • Explore – to look into closely, scrutinize, to pry into [the topic of the lesson]
  • Explain – to unfold, to make plain or intelligible [the principle underpinning the topic]
  • Elaborate – to work out in detail [an exemplar employing the principle]
  • Evaluate – to reckon up, ascertain the amount of [knowledge and understanding acquired by the students]

The combination of 5Es and E cubed [Everyday Engineering Example] works well.  We found that they increased student participation and understanding as well as attracting higher student ratings of lecturers and the course [Campbell et al. 2008].


Atkin JM & Karplus R, Discovery or invention? Science Teacher 29(5): 45, 1962.

Little W, Fowler HW, Coulson J & Onions CT, The Shorter Oxford English Dictionary, Guild Publishing, London, 1983.

Campbell PB, Patterson EA, Busch Vishniac I & Kibler T, Integrating Applications in the Teaching of Fundamental Concepts, Proc. 2008 ASEE Annual Conference and Exposition, (AC 2008-499), 2008.


CALE #5 [Creating A Learning Environment: a series of posts based on a workshop given periodically by Pat Campbell and Eann Patterson in the USA supported by NSF and the UK supported by HEA]

Establishing fidelity and credibility in tests & simulations (FACTS)

A month or so ago I gave a lecture entitled ‘Establishing FACTS (Fidelity And Credibility in Tests & Simulations)’ to the local branch of the Institution of Engineering Technology (IET). Of course my title was a play on words because the Oxford English Dictionary defines a ‘fact’ as ‘a thing that is known or proved to be true’ or ‘information used as evidence or as part of report’.   One of my current research interests is how we establish predictions from simulations as evidence that can be used reliably in decision-making.  This is important because simulations based on computational models have become ubiquitous in engineering for, amongst other things, design optimisation and evaluation of structural integrity.   These models need to possess the appropriate level of fidelity and to be credible in the eyes of decision-makers, not just their creators.  Model credibility is usually provided through validation processes using a small number of physical tests that must yield a large quantity of reliable and relevant data [see ‘Getting smarter‘ on June 21st, 2017].  Reliable and relevant data means making measurements with low levels of uncertainty under real-world conditions which is usually challenging.

These topics recur through much of my research and have found applications in aerospace engineering, nuclear engineering and biology. My lecture to the IET gave an overview of these ideas using applications from each of these fields, some of which I have described in past posts.  So, I have now created a new page on this blog with a catalogue of these past posts on the theme of ‘FACTS‘.  Feel free to have a browse!