Development of Computational Thinking by Learning Python Programming: A Bibliometric Analysis with VOSviewer and Bibliometrix R.

Abstract

This bibliometric study examines the production of scientific literature on the intersection of computational thinking and Python programming for education; for this purpose, a longitudinal descriptive bibliometric analysis was developed, yielding 126 scientific documents published from 2009-2023. The results focus on frequency, patterns, and collaboration networks in the publications, highlighting an annual growth in research interest of 20.43%, revealing a rapidly growing field, with publications that have tripled since 2010, reaching 343 authors and 339 keywords, highlighting thematic diversity, author collaboration with an average of 3.08 coauthors per document, and the influence of studies with an average of 4.254 citations per document. Specialized conferences predominate as a means of dissemination. Semantic mapping highlights the consolidation of computational thinking and Python as a thematic core, with robust links toward problem solving, logical thinking, and analytical skills. This finding highlights the predominance of learning and teaching Python and its close interrelation with current educational trends and advanced programming skills.