Much of engineering education requires a sound basis of mathematics as well as practical understanding and insight. But many recent changes in secondary education resulted in a perceived drop in the underlying skills and knowledge of the students in such areas as higher level mathematics and programming skills. This, combined with students coming from a larger geographical distribution, results in a much less uniform initial skill set among students in a course.
A second challenge is tied to the increased complexity of engineering systems (and systems of systems) that newly qualified engineers will be expected to analyse, design, and test in their career. It is no longer adequate merely to have an understanding of the underlying principles. A graduating engineer now must have a much deeper working knowledge of the processes involved in designing these complex systems.
Addressing the growing gap between the uneven skills of incoming students and higher expectations of graduating students within the limited duration of typical engineering courses is an increasingly difficult challenge for institutions of higher education.
To foster such a transformation, university courses need to integrate computational thinking into all aspects of the engineering science curriculum. Computational thinking skills include reformulating seemingly difficult problems, reduction, embedding, transformation and simulation in conjunction with abstraction, and decomposition in tackling a large complex task.
The experiences of a number of leading academic institutions in the United Kingdom and Germany among others demonstrate that when this is done systematically, students quickly learn mathematical concepts early on using symbolic and numeric software tools. Further, the students acquire a deeper understanding of programming and systems engineering with hands-on project-based learning linked with real hardware. Students also learn to think independently, investigate and explore environments, and apply tools used by practicing engineers.
Programming and numerical simulation platforms such as MATLAB and Simulink can act as catalysts to bring about the transition from traditional engineering courses to modern courses in which the requirements of engineering analysis as defined by accreditation bodies are met.
Such platforms enable the integration of computational thinking and tools to promote a deeper understanding of engineering principles through spiral curricula. They also support the use of simple “Apps” to bring concepts to life before encouraging and empowering students to develop their own.
Most students today are comfortable using computers as they begin their studies, but few are comfortable applying them to solve engineering problems. To close this gap, computational thinking and the development of associated skills must be integrated throughout the engineering curriculum. Examples of this integration are cited here and a number of practices for achieving optimal results are included.
While the mathematical foundation for engineering education is relatively stable, the complexity and multidisciplinary nature of engineering problems today requires engineering programs to satisfy multiple learning goals at the same time. The ability to use software tools is not only a requirement for today’s engineers, it also a solution that enables students to put the theory they have learned into practical use on real systems.
Experience with a variety of tools can help students broaden their horizons, but this benefit must be weighed against the ability to explore engineering concepts in greater depth by using—and gaining experience with—the same tool environment in each year of their studies. Instructors worldwide have found that using the same set of software tools from the first year through graduate studies enhances the learning experience—particularly when those same tools are used by practicing engineers working on real-world problems in industry.
Rather than starting in the first year of study with abstract programming constructs, students are introduced to computing via simulation, and experience engineering concepts directly using hardware platforms such as LEGO Mindstorms NXT. This introduction fosters retention and helps bridge the knowledge gap in mathematical and engineering topics that are typically covered in later semesters. Programming skills are then honed in the early semesters in math and physics courses, which serve as prerequisites to enter the engineering sequence.
As the students’ comfort level in programming rises and the complexity of engineering problems increases, the computing component is extended to include a simulation platform such as Simulink. Engineering curricula typically culminate in a series of applied lab-based courses in which students are encouraged to demonstrate the problem solving skills they have acquired with full-blown, real-world hardware projects.
By helping generate excitement, establish purpose early, and introduce skills that are reinforced later, the integration of computational thinking serves to engage students at progressively higher levels, enhance learning, and increase retention.
To read more of this external content, download the complete paper from the online archives at the European Society for Engineering Education (SEFI).