Recent studies suggest that computational thinking, composed of the skills of abstraction, decomposition, algorithmization, debugging, and problem-solving, is the fundamental skill for scientific, technological, and economic development for the twenty-first century. However, this diagnosis that is unveiled in rich countries remains nebulous for poor countries. The problem is that education in computational thinking is fundamental for countries to insert themselves in the international arena in an advantageous way and thus achieve the welfare goals for the population of each country. The objective of this research was to make a bibliographic review that shows the state of the art in the teaching of computer programming and computational thinking in the 5 continents. In the review, the advances in the countries of Europe, North America, Oceania, and Asia were observed, whereas in Latin America and Africa, the advances are still basic in some countries and non-existent in others. This review is based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). The main search terms were “Computational thinking” and “Teaching computer programming.” The search was performed in the ACM, Conference on Computational Thinking Education (Hong-Kong), Google Scholar, WOS, and SCOPUS databases, from October until December 2020, whose publication year was from 2016 onward. One of the main results found is that the teaching of computational thinking in England was implemented in schools in 2014; in Germany, it has been implemented since 2016 at a transversal level in universities; in South Korea, China, and Taiwan, it has been implemented since 2016. However, in Latin America and Africa governments, the subject is still not considered.

This research studies the effects of the application of didactics to the teaching of computer programming, focusing on programming skills in the Python computer language. The problem arises from the failure and dropout rates of students in computer programming in computer science careers in INACAP and the consequent interest in promoting better learning. The general objective is to study the effects of an innovative methodology, based on Brown and Wilson's didactic principles, on the teaching process of Python programming in computer science students at INACAP. The theoretical framework is based on the didactics of teaching computer programming and the concepts of computational thinking skills of various theoretical references, and in particular on the didactic principles of Brown and Wilson. This research is carried out with a quantitative methodology of explanatory scope and with a quasi-experimental design, with a purposive sample, for the experimental stage the sample will consist of 100 first year undergraduate students of Computer Science, of which 50 will be the experimental group and 50 will be the control group. The hypothesis proposed is that “The students in the experimental group obtain a higher performance when applying Brown and Wilson's didactic principles than the students in the control group who are taught in a traditional way.” The data collection technique used will be a 45-question multiple-choice test. The data analysis will be performed by applying statistical criteria, comparison of means and variances, among others.