Category Archives: Engineering

Engineering idiom

Many of us, either as students or as instructors, will have experienced the phenomenon that students are more likely to give a correct answer when the context is familiar [Linn & Hyde, 1989; Chapman et al 1991].  Conversely, a lack of familiarity may induce students to panic about the context and fail to listen in a lecture [Rosser, 2004] or to appreciate the point of a question in an examination.  Your dictionary probably gives two meanings for context: ‘surrounding conditions’ and ‘a construction of speech’.  You would think that the importance of teaching by reference to the surrounding condition is so obvious as to require no comment; except professors forget that conditions experienced by students are different to their own, both now and when they were students [Nathan, 2005 & ‘Creating an evolving learning environment’ on February 21st, 2018].  To get an appreciation of how different consult the ‘Mindset List‘ produced each year by Beloit College; for example as far as the class of 2020 are concerned robots have always been surgical partners in the operating room [#55 on the 2020 Mindset List].

What about the construction of speech?  I think that there is an engineering idiom because engineering education has its own ‘language’ of models and analogies.  Engineering science is usually taught in the context of idealised applications, such as colliding spheres, springs and dashpots, and shafts.  It would be wrong to say that they have no relevance to the subject; but, the relevance is often only apparent to those well-versed in the subject; and, by definition, students are not.  The result is a loss of perceived usefulness of learning which adversely influences student motivation [Wigfield & Eccles, 2000] – they are more likely to switch off, so keep the language simple.

References:

Chipman S, Marshall S, Scott P. Content effects on word problem performance: A possible source of test bias? American Educational Research Journal, 28(4), 897-915, 1991.

Linn M, Hyde J, Gender, mathematics, and science, Educational Researcher, 18(8), 17-19, 22-27, 1989.

Nathan R, My freshman year: what a professor learned by becoming a student, Cornell University Press, Ithaca, New York, 2005.

Rosser SV, Gender issues in teaching science, in S. Rose. and B. Brown (eds.), Report on the 2003 Workshop on Gender Issues in the Sciences, pp. 28-37, 2004.

Wigfield A, Eccles JS, Expectancy-value theory of motivation, Contemporary Educational Psychology, 25(1): 68-81, 2000.

 

CALE #7 [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]

Motivated by fruitful applications

In my series of posts on creating a learning environment [CALE #1 to #5, so far], I have mentioned Everyday Engineering Examples frequently, but what are they?  In the workshops on which the series is based, I define them as ‘familiar real-life objects or situations used to illustrate engineering principles’.  We have found in our research that the level of difficulty had no significant influence on the effectiveness of the examples in supporting student learning.  In the research, we combined them with 5E lesson plans and tested them alongside control classes [see Campbell et al., 2008].   So, it is not necessary to simplify the example to use as a part of lecture; instead the level of idealisation should be minimised to retain the relevance and context from the students’ perspective.

The choice of example is critical: there must be a transparent connection to the students’ experience and simultaneously the example must provide a straightforward implementation of the engineering principle being taught.  The subsequent exploration, explanation, elaboration and evaluation in the 5E lesson plan should pose questions with useful or interesting answers because the absence of a useful or interesting end-point creates a risk of presenting a tedious intellectual exercise.  And, perceived usefulness of learning influences students motivation [Wigfield & Eccles, 2000].

So what we are looking for are ‘fruitful applications’, in the words of Art Heinricher, Dean of Undergraduate Studies & Professor of Mathematical Sciences, WPIFor lots of Everyday Engineering Examples, see https://realizeengineering.blog/everyday-engineering-examples/.

Reference:

Wigfield A, Eccles JS, Expectancy-value theory of motivation, Contemporary Educational Psychology, 25(1): 68-81, 2000.

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

 

CALE #6 [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]

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 [https://realizeengineering.blog/everyday-engineering-examples/].  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].

References:

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!