Computational Thinking and Programming Learning among University Students in Latin America: A Critical Review of Trends, Strategies, and Challenges in Higher Education

Abstract

Computational thinking has become a relevant cognitive framework for problem solving in digitally mediated environments, while programming is one of its most visible means of externalization, practice, and assessment in higher education. In Latin America, the expansion of programs related to computing, engineering, science, education, and digital technologies has increased the need to understand how computational thinking development is connected with introductory programming learning, particularly among university students who move from heterogeneous school experiences to courses that demand abstraction, algorithmic reasoning, debugging, and modeling. This article aims to critically analyze recent literature on the relationship between computational thinking and programming learning among university students in Latin America, identifying conceptual trends, teaching strategies, empirical findings, tensions, and research gaps. A critical bibliographic review was conducted, mainly covering publications from 2021 to August 2026, prioritizing peer-reviewed articles, systematic reviews, Latin American empirical studies, and reports from international organizations. Findings indicate that instruction focused exclusively on syntax is insufficient; the most promising experiences shift attention toward problem solving, algorithm construction, active learning, visual programming, educational robotics, and formative feedback. Prior knowledge, self-efficacy, the quality of instructional scaffolding, and digital divides also condition learning outcomes. The emergence of generative artificial intelligence expands opportunities for personalized support but introduces risks of cognitive dependence and weakened reasoning processes when pedagogical mediation is absent. The review concludes that Latin American universities need curricular designs that explicitly integrate computational thinking and programming as related but non-equivalent processes, supported by multidimensional assessment, faculty development, and institutional policies focused on equity and deep understanding of code.