Case-based learning in materials engineering: the ouija board of the devil

Abstract

The training of the students of electrical mechanical engineering is based on the acquisition of disciplinary knowledge in the areas of thermodynamics, mechanical, electrical and electronic design, quality control, safety and hygiene and materials. Bringing the application of this knowledge to the solution of real problems requires higher-order cognitive skills such as the development of complex thinking among others. Case-based Learning (CBL) is a methodology that favors active learning and the construction of arguments, allowing students to see theory in the practice in a real-life context. In materials engineering, characterization techniques allow to evaluate the properties of the materials and thereby determine if the material is useful for a given application. Traditionally students learn this content from following procedures, but deciding which technique to use causes those difficulties, especially when it is necessary to define the variables to be measured. Within the course of materials engineering, a case-based educational strategy was applied to a group of 19 students of electrical mechanical Engineering at a public University of San Luis Potosi, Mexico with the purpose of evaluating the knowledge acquired in the subject. The solution of the case "the Ouija of the Devil: the Molecular detector GT200", allowed to identify the level of knowledge on characterization techniques, the variables involved, the limitations and necessary parameters to carry out the measurements, on the other Side, the importance of scientific knowledge was identified to solve problems and its impact on decision-making in public policies and resource management. As this is a case associated with the acquisition of equipment by the Mexican government, whose functions were totally false, it allowed exploring the attitudes of t students towards the corruption and the necessary values to practice the profession. The proposed methodology was that of CBL, the learning evidence was analyzed under a qualitative approach.