Case Study
Title: Combining problem solving and computational skills in physics: honing a new approach
Author(s): Dr D I Westwood
Department/School/Faculty/College: School of Physics and Astronomy
Institution: Cardiff University
Abstract:
Although problem solving skills are considered to be a great strength of physics graduates, training
them to fully exploit the power of modern computers poses a number of difficulties. One such
major problem is fragmentation, for example we used to teach Easyplot (graphics), MathCad (high
end calculator) and C++ (programming). As a result, outside of computing modules most students
tended to default back to using EXCEL when faced with “real” problem solving.
In response to a course review, it was decided to make use of recent software advances and teach
computing skills through one package (Python) and to embed its use in laboratory and taught
modules. ‘Python’ in its own right is a very important programming language, but it is also
recognised as an excellent first language to learn.
What you did
Two undergraduate students were employed on a summer placement in order to help develop, test
and refine the course material for the first year computing course. The requirement was to develop
a new first year single module course based on 11, two hour computing laboratory classes. It was
decided to write the course in the form of web pages which in principal could be widely
disseminated in the future. Over 50% of the module was in place by the end of the project.
The placement students were involved in presenting their “final” polished course material to staff
and post graduate students. As such a two hour ‘training session’ was delivered on 21st September
2011. Over 20 people attended; a mixture of academic, research and support staff.
The new learning module was finished in autumn 2011 and presented for the first time to first year
students in Spring 2012.
Why you did it
The overall aim of this project is to improve the educational experience of our student cohort, to
improve their standing as physicists and to provide them with transferrable skills that will make
them attractive and useful in the modern workplace
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The first year module developed through this project is a vital component of the new course
structure which places greater emphasis on problem based learning and on interaction between
different areas of the curriculum. One aim of the module and for computing in general is to
encourage students to regularly solve physics problems with computers in their other module, not
just with pen and paper
Existing computing courses have not been effective at making links to other modules. For example
having been taught C++ programming in year 2, students would only use these skills in their 3rd and
4th year projects if they were heavily theoretical and their supervisor was well versed in C++. The
Python program brings together computing, statistics and laboratory work. Improvements in the
educational experience and transferrable skills of the undergraduate cohort are expected.
What you learned
The summer placement position was shared between two students. In hindsight this sharing of the
post appears to have been a very good idea - mainly because of the ability to discuss ideas, thoughts
and difficulties. Weekly meetings with the project team ensured aims and targets for the placement
students were outlined. When the course content was near completion staff in the physics
department tested the course content, making comments and suggestions in order to develop the
final version. This proved an extremely helpful feedback tool.
The staff training session proved extremely useful in a number of ways; it introduced staff to Python;
showed them around the website (so that they can use it to teach themselves Python); provided
valuable feedback on the course and provided a good test of the facilities.
In preparation for the course, there was an understanding that the vast majority of new, incoming
students will have used EXCEL (or similar) in school to perform simple mathematical manipulations
and plot graphs but most will not have experience of writing computer programs. A survey at the
start of the course confirmed this view, with~95% of students having no prior programming
experience. There was a (slight) concern as to how the experienced ~5% would find the course.
Interestingly, and for us surprisingly, they appear to have it very rewarding. The reason being that
its highly numerical nature made it quite different from the programming that they were generally
used to.
How you evaluated to determine if the activity was successful (or not)
The students who were employed in the summer placement reported that they found the
experience ‘enjoyable and rewarding’. On a personal level the students reported that they felt that
the placement had improved their ‘problem solving, team working and communication skills’ and
had provided an opportunity to develop ‘more transferrable skills’ making them ‘more employable
in the future’.
The time frame of the project only allowed for the development of the course content (June to
September 2011) and there was not an opportunity to undertake a proper evaluation with the new
student cohort. It is hoped that over the next three years, evidence in the form of improvements in
the student cohorts’ transferable skills and educational experience will prove the course to be a
success.
However, outside of the computing module, a Python based data analysis experiment was prepared
for the 1st year practical laboratory. With limited support provided by the lab script; the first
sessions running this were a scary prospect and a good test of the website and the training of
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supervisors and demonstrators. With retorts such as “OK, now I understand what least squares
fitting is all about” it was deemed a success.
What you will do in the future, either differently or otherwise
The first year module is just the start. It will be built upon in subsequent years with a compulsory
second year module and probably an optional 3rd year module. It will be embedded widely in non
computing modules, starting with the practical laboratories and core modules. There will also (as
before) be the possibility of students gaining further (advanced) computing skills through the choice
of their 3rd and 4th year projects.
Outputs:
Tested and honed computational material suitable for release to first year Physics Student in 20112012.
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