Abstract:

Traditionally, the study of STEM (Science, Technology, Engineering and Mathematics) has been approached as if there were an "absolute" separation between the different areas of knowledge, particularly those related to the social sciences. This has meant that the different fields of knowledge have been considered as watertight compartments, with no channels of communication and no interaction between them. This vision of knowledge denies the transversality and symbiosis that exists between the different fields of knowledge, a fact that stimulates the fusion of science with social problems in the search for solutions.

In the knowledge era, this perspective of the last century has lost its validity by denying the multidimensional and interdependent nature of knowledge, in its creation and construction process and in the new configuration of the fields of knowledge, minimising the processes of integration and immersion of STEM subjects in the curricula of the Social Sciences, such as Descriptive Statistics, Inferential Statistics, Multivariate Statistics, Mathematics, Financial Mathematics, Actuarial Mathematics, Simulation, Scientific Methodology, Data Analytics, etc.

From this perspective, the development of multidisciplinary teaching-learning experiences in the Social Sciences is a fact and is manifested in the implementation of double degrees between faculties of Exact Sciences and Social Sciences, also through the nesting of STEM subjects in the curricula of the degrees, masters, specialisation courses or through complementary courses of STEM content. Hence, our aim is to investigate the perception of Social Sciences students of the role of STEM subjects in their scientific training, in the furnishing of their knowledge background and in the development of deductive and/or inductive logics in their learning, nested in the context in which their academic activities take place.

Methodologically, we used a survey to gather information on students' perceptions and opinions about the relevance of STEM subjects in building their knowledge background, developing their data analysis skills and their ability to translate knowledge into practical action. Initial findings suggest that STEM encourages inquiry-based teaching-learning and experimentation.

Keywords:

STEM, perception, automation, technology, analytics, context, experimentation.