Challenges in Teaching Computer Sciences Engineering Courses with Matlab & Simulink

Silvio Simani, Engineering, University of Ferrara

In recent years, we have been working with students who seem to be lacking in abstraction ability. It implies that they seem unable of transforming a real-life situation into a collection of workable paradigms. Computational teaching should be able to impart problem-solving skills. These characteristics, which are particularly crucial for future Engineers, often entail methodical means of presenting issues and processes leading to their answers. In specifically, regarding Information and Communication Technologies (ICT), they include conceptual skills and procedures for inventing algorithms that make computers perform our work, as well as methodologies for describing and understanding the world as a complex of information processes. Computational abilities are an important element and essential capacity for the Engineering community. These skills should include the ability to translate real-life obstacles into problems that can be addressed using a computer, as well as the ability to apply computer-based answers to questions at hand. However, we often identified pupils who were unable to convert real-world issues into theoretical and numerical answers. They seemed to be restricted to certain parts of their Engineering courses. On the one hand, this approach is essential to practically every technical endeavour. However, teaching computational skills is significantly more difficult, particularly if done online. As a result, while developing courses for Engineering curriculum, educators must consider an expanding number of duties. ICT advancement necessitates the study, design, and construction of ever big and sophisticated systems. Engineering working settings and activities need interdisciplinary and multidisciplinary contexts. Computational instruction must take these issues into account, while the requisite abilities must be acquired implicitly or explicitly. Furthermore, depending on the courses in the engineering curriculum, correct teaching approaches may help students to build or improve computational abilities via methodical introduction of elementary and sophisticated computational tools.
Simple online tactics, particularly for the Computer Sciences Engineering domain, may be used to develop computational thinking in engineering education. Different teaching styles have been employed in basic and optional courses for Computer Sciences Engineering degrees. Three essential techniques in particular have the potential to improve learning effectiveness. A successful teaching activity must be supported by a (i) 'learning by doing' method, which increases the development of theoretical and practical abilities provided to the students by means of 'guided tours'. On the other hand, (ii) using 'real and realistic application examples' drawn from various technical backgrounds helps to engage students and pique their interest in challenging theoretical tasks. Furthermore, (iii) the construction of 'suitable manual and semi-automated methods' that are adapted to the studied application examples helps to motivate students to understand the more appropriate engineering approach to solving practical issues. The use of appropriate software resources, such as MATLAB, improves the creation of these tools. In reality, MATLAB provides for the implementation of algorithms, the design of functions, and the development of user interfaces. Although MATLAB is mainly designed for numerical computation, an optional toolbox provides access to symbolic computing capabilities. Simulink, a separate software, includes graphical multi-domain simulation and model-based design for dynamic and embedded systems.
Finally, the development of computational abilities may be aided by the incorporation of the instructional concepts and computational tools designed to aid students in obtaining information and developing problem-solving skills. Simultaneously, soft skills are developed to better communication and the translation of real-world problems into the technical realm and technical difficulties back into common language.

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