The evolution of the automotive industry as well as the increase of demand for functionalities generated the need of implementing more electronic control modules, which were integrated in complex architectures with dedicated sensors and actuators. The aim of this paper is to highlight a set of methodological guidelines aiming to improve learning experience for automotive students. The described framework is beneficial from a teaching perspective and could be further enhanced within computer-aided instruction. A study case consisting of a laboratory experiment including complex automotive architectures to Computer Science and Engineering master level students is presented. This exercise is based on automotive sensors, actuators, ECUs and scanners. One particular way to describe these architectures and to make them almost self-explanatory to students is by using consumer electronics, such as smartphones, development boards, IoT devices, cameras and single board computers in a contrastive analysis with professional devices. All these categories of devices gather data from the ECUs and sensors and make it readable by the users, in different description formats. Consequently, students may further develop their own projects with the help of these devices and by means of programming languages and GitHub or NuGet repositories.