ABSTRACT
In its simplest sense, computational thinking is considered as a series of specific skills that programmers use to do their homework. They are also useful to people in their professional and personal lives, as a way of organizing the resolution of their problems, and of representing the reality that surrounds them. In a more elaborate scheme, this complex of skills constitutes a new literacy - or the most substantial part of it - and an inculturation to deal with a new culture: digital culture in the knowledge society. We have seen how Bayesian Probability is used in epidemiology models to determine models of data evolution on contagion and deaths in COVID. We have also seen it in natural language processing. We could also see it in many cases in the most varied scientific and process analysis fields. In this way, with the automation of Bayesian methods and the use of probabilistic graphical models, it is possible to identify patterns and anomalies in voluminous data sets in fields. Fields as diverse as linguistic corpus, astronomical maps, adding functionalities to the practice of magnetic resonance imaging, or to the habits of buying with cards, online or smartphones. In this new way of proceeding, big data analysis and Bayesian theory are associated.. If we consider that Bayesian thinking (this way of proceeding) as one more element of computational thinking, then, to what has been said on previous occasions, we must now add the idea of generalized computational thinking, which goes beyond education It is no longer about aspects purely associated with professional or vital practice to deal with life and the world of work, but as a preparation for basic research and for a research methodology in almost all disciplines. Thus defined, computational thinking is influencing research in almost all areas, both in the sciences and the humanities. An instruction focused on this component of computational thinking, or including it, at an early stage, in Secondary, would allow to activate these learnings as very valuable and very complex components at a later stage. In professional or research activity, in the training phase, undergraduate and postgraduate degrees, of these professions. Those that train for these activities and professions.