A blog about teaching Programming to non-CompSci students by Tim Love (Cambridge University Engineering Department). I do not speak on behalf of the university, the department, or even the IT group I belong to.

Tuesday, 6 May 2014

Which computing language for engineers?

At our site we teach general engineering - students amongst other things can learn AI, Economics, and bridge-building. Which language should they be taught? Though their needs are different from those of Computing students and of more specialist (e.g. Electrical) Engineering students, their programming needs may be extensive. In Teaching Introductory Programming in Tertiary Engineering Education M.G. Rashed points out that "Computers are increasingly used for a variety of purposes in engineering and science including control, data analysis, simulations and design optimization. It is therefore becoming more important for engineering students who are computer science non-major, to have a robust understanding of computing and to learn how to program". It's over 15 years since we last changed the primary language (I've found a document from 1996 which addresses the issue - Teaching Programming in the Engineering Tripos). In that time much has changed in the world of engineering, so a review of our language choice is timely.

1985Pascal as a 1st language
1996?Matlab as a 2nd language
1997C++ as a 1st language
???Compulsory computing questions
in the 1st year exams.
2008Vacation C++ exercise
20101st week Lego Mindstorms (Matlab)
2012C++ course flipped - 25% more labs
at the expense of lectures
2014Scratch used in a prelim exercise


Firstly then, what factors could influence our choice, and how have those influences changed over the years? Here are a few -

  • The history and culture of the department - the department tends to teach the fundamentals in a non-specialist way for the first 2 years of a student's career
  • The value of programming in general - When I was taught Latin at school I was told that it was good for me, it trained my mind. Nowadays Mandarin might be taught on the grounds that it's a common language, or Esperanto because it's an easily learnt, well-designed one. Similar differences of opinion apply to the reasons for teaching computing languages. Programming skills might have intrinsic value or be widely transferable. According to its advocators, Computational Thinking "involves a set of problem-solving skills and techniques that software engineers use to write programs ... However, computational thinking is applicable to nearly any subject. Students who learn computational thinking across the curriculum begin to see a relationship between different subjects as well as between school and life outside of the classroom. Specific computational thinking techniques include: problem decomposition, pattern recognition, pattern generalization to define abstractions or models, algorithm design, and data analysis and visualization".
  • The value of programming for engineering - M.G. Rashed thinks that "The primary target in teaching computing is to enable the students to convert engineering problems into pseudo-code. ... The conversion of this pseudo-code into a program written in one programming language is of secondary importance because it is, in principle, an algorithmic procedure and requires less intellectual effort. ... In the teaching practice, the algorithmic problem- solving and implementation tasks are often entangled simply because the students need to test an algorithm they invented by implementing it. Consequently, the choice of the teaching language should be governed by which language provides the best support to the student in performing the implementation part of the problem-solving task by removing any extra stumbling blocks. For this reason the usefulness of the language after graduating or speed of execution will not be the prime factors when making the choice."
  • Requirements of other courses - some other courses assume specific aspects of computing competence.
  • Students' previous experience - A long time ago many students arrived with some programming experience thanks to home micros running BASIC and schools equipped with BBC micros. Then skills fell away. More recently, with free Linux being available, and raspberry Pi kits on sale, there's been a recovery in programming skills, but only amongst the computer literate, meaning that the distribution of our intake's computing skills is more bi-polar than ever.
  • Students' expectations -Though they may program less than earlier generations did, they use computers far more. In particular they rather expect there to be an app for everything - to supply documentation, to provide an interface to hardware (instead of a remote being provided, etc). They may hope that what they produce looks rather like an app.
  • Industry relevance - Anecdotal comments from staff suggest that some companies aren't convinced that we are preparing our students for programming. C is more useful for embedded systems than C++. Matlab experience is often requested. One problem is that the needs of industry change, and aren't easy to predict long enough in advance. The invention of the WWW and cheap, small processors has led to the use of GPS and intelligent sensors in civil engineering projects. Google Maps and Google Apps enrich projects as well as aid communication between workers. One student wrote to me that "surely as a professional chartered engineer if you need to do some programming/coding you would hire a professional who would do it in no time at all plus do it correctly" but it would be a shame if the engineer got ripped off because they hired professionals to write trivial or poorly-spec'd software.
  • Language features - ease of use, expressiveness - Despite the popularity of languages such as FORTRAN and C/C++, there has been much debate about the suitability of these languages for education, especially when introducing programming to novices. These languages have not been designed specifically for educational purpose, nor do they make for easy use of the WWW or creation of GUIs. Interpreted languages are growing in popularity (the image is from the M.G. Rashed paper).
  • Programming paradigm - Our approach emphasises the procedural aspects of C++, downplaying O-O in order to introduce more problem-solving practise.
  • Availability of compilers, IDEs, and teaching materials - We've had some trouble providing easily-installed C++ IDEs across platforms. All the teaching materials are on the WWW. Web2 technology has been exploited -
    • Documentation for the 1AC++ Mich course is now WWW-based with online PHP-based teaching aids.
    • A 2nd year C++ course went a step further, incorporating online marking.
    • The Mars Lander project uses CamTools to host documentation and student-staff communication
    Sometimes (to facilitate automated assessment for example) the presentation framework imposes limits on the nature of the course.
  • Availability of teaching staff - With class sizes of 90 or so, computing practicals require several skilled helpers.
  • Learning styles - Teaching remains based on practicals with demonstrator support. There are fewer lectures. Independent study has been encouraged by providing the MDP disc, giving help to students installing compilers on their own machines, and changing teaching material so that documentation is on the WWW, the exercises requiring the minimum of extra libraries.


One needs to assess trends with caution. Wikipedia's Measuring programming language popularity page lists, amongst others

Within education, statistics are perhaps more reliable

  • A Snapshot of Current Practices in Teaching the Introductory Programming Sequence (2011) points out that for CS0 ("an introductory course with no prerequisites, involving at least some programming, that does not count towards the major") Alice was top, though there "is a tremendous variety in approaches". In CS1 the results were: Java 48%, C++ 28%, Python 12%.
  • An InfoWorld article (2014) quotes results from an Association for Computing Machinery survey - "Eight out of the top 10 universities now use Python to introduce programming"; "Python has been growing in popularity in the educational realm for at least the past few years, though this survey is the first to show it has eclipsed Java, which has been the dominant teaching language for the past decade".
  • A Survey of Literature on the Teaching of Introductory Programming (from the ACM Special Interest Group on Computer Science Education, 2007?) gives a useful overview and annotated bibliography. It points out that
    • "Three decades of active research on the teaching of introductory programming has had a limited effect on classroom practice"
    • "Today, C, Java and C++ top the list of the most widely used programming languages, both in industry and education"
    • "Studies have found that market appeal/industry demand/student demand is one of the most important factors affecting language choice in computer science education"

Within the general trends there's significant variation - for example, Stanford have a course based on JavaScript.

Also there's an increasing use of Moocs.

Candidate languages

The SIGCSE report mentioned above says "An appropriate language can only be chosen after course goals and learning outcomes have been specified". FYI, our 2013-14 doc said

The aims of the course are to:

  • Give a good understanding of basic design methods and techniques and emphasise, in particular, the need to produce well-structured, maintainable computer software.
  • Reinforce the IA practical classes in C++ programming and provide a firm foundation for IB practical work.

As specific objectives, by the end of the course students should be able to:

  • Understand the nature of software engineering and the software life cycle
  • Appreciate the need for structured programming in software engineering projects.
  • Be able to write well-structured programs in the C++ programming language to solve practical problems.
  • Understand the sources of errors in numerical programming and how to guard against them.
  • Appreciate the issue of complexity in algorithm design, with particular reference to searching and sorting algorithms.

I think the languages below are the most commonly mentioned at CUED as options -

  • Matlab/Octave - Students use this in week 1. Only in year 2 are they more formally taught it. Matlab has a large range of material produced by univs for ugrads, much of it with a math/engg bias. In a Mathworks newsletter, staff at Vanderbilt University write that "engineers from five major companies ... credited MATLAB with helping them become more efficient and achieve time reductions 'from a week to 15 minutes' and 'from several months to weeks'" citing an automotive engineer’s statement that "MATLAB was a de facto industry standard". Many engineering-related routines and program are available.
  • Python - According to Charles Dierbach ("Journal of Computing Sciences in Colleges" 29, 6 (June 2014)), "The Python programming language has been quickly gaining popularity over the past few years as a language of choice for CS1 courses. Some estimates put the rise in use at forty-percent a year". "The Python programming language has been around since its development by Guido van Rossum around 1991. One of the main features of the language is code readability (sometimes described as "executable pseudocode"). Python is an interactive programming language, using dynamic typing. It is also a hybrid language, supporting the imperative, object-oriented and functional programming paradigms. Although used as a scripting language, it is also used for the development of full-scale programs." The University offer courses in Python for number-crunching, etc. Many engineering-related packages are available.
  • C++/Objective-C/C# - Students use C++ for about 20 hours in year 1 and at least another 8 hours in year 2. In a Cambridge university C++ course it says "Unless you are already a programmer, you are very strongly advised to learn Python first ... learning another programming language would also do. “Programmer” does not mean in Visual Basic, Excel or even most uses of Matlab; it means in Python, Fortran, C, Pascal etc. It surprises most people, but learning simpler languages first often saves time overall. ... You can learn to use any of these (even Fortran) to a comparable level in about 20% of the time that you will need to learn C++"
  • Java - one piece of 3rd year coursework currently requires students to write Java. Their C++ experience is presumed to be a sufficient prerequisite.


Are there advantages in principle in exposing students to several languages? Ultimately it's unavoidable, though perhaps initially it confuses people. We don't compare/contrast languages. We tend to leave that to the students.

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