Review on the teaching of programming and computational thinking in the world

Abstract

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.

Gamification and Computational Thinking in Education: A systematic literature review

“…Recent studies have proposed that video games can be the vehicle for developing computational thinking and problem-solving skills (Wu & Richards, 2011;Barbero et al, 2020;Zapata-Caceres et al, 2021;LailiFarhanaMd et al, 2021;Ehsan et. al, 2021;Belmar, 2022). Paiva et al (2020), have investigated in detail under which methodological approaches, learning could be better organized with the use of new didactic tools.…”

Expert Validation of a Python Test, Reliability, Difficulty and Discrimination Indices

“…From the reviews and articles read, the contribution made by Belmar (2022) stands out in his work entitled "Review on the teaching of programming and computational thinking in the world", in whose work he incorporates the concept of modeling and simulation as foundational skills of computational thinking, so that it includes formulating problems, organizing and analyzing data logically, representing data through models and automating solutions. Thus, looking towards school training, these skills improve attitudes such as: confidence in dealing with complexity, persistence in working with difficult problems, tolerance for ambiguity, the ability to deal with open-ended problems, and the ability to work with others to achieve a common goal and communicate it.…”

“…Thus, looking towards school training, these skills improve attitudes such as: confidence in dealing with complexity, persistence in working with difficult problems, tolerance for ambiguity, the ability to deal with open-ended problems, and the ability to work with others to achieve a common goal and communicate it. Which is complemented by Grgurina (2021) who describes computational thinking in terms of its main concepts, such as: data collection, data analysis, data representation, problem decomposition, abstraction, algorithms and procedures, automation, modeling, and simulation Belmar (2022).…”

“…When comparing the progress of countries in the teaching of computational thinking in schools, says Belmar(2022), it is necessary to see the progress of states in public policies that establish this subject in the mandatory curriculum, as is the case of England in 2013 and the countries of Europe in general since 2016, or other Asian countries such as Japan, South Korea and China where computational thinking is defined as the skills of the 21st century and will be the engine of technological and economic development. However, in developing countries, such as Latin America and Africa, although there are several initiatives of universities in doing research on the teaching of computational thinking, the states have other priorities, so the issue is not in the discussion of public policies, but rather the development of the teaching of computational thinking is done by particular initiatives of universities and some other foundation, which leaves them behind in the race to create and develop new technologies to deliver better employment alternatives and thus greater welfare to the population Belmar (2022).…”

A Study on the Role of Affective Feedback in Robot-Assisted Learning

“…There is a long history of using robots to teach computer programming to children and college students [ 1 , 2 , 3 , 4 , 5 ]. A robot is a tangible, physical device that can be programmed to make different movements, and display different behaviours.…”