Computational thinking as a key tool for problem solving

Abstract

The digital age has increased the need for technological skills in students, posing challenges for educational institutions. Education requires a shift in pedagogical approaches, especially after the COVID-19 pandemic, which accelerated social isolation and expanded the need to master digital environments within educational communities. This context has strengthened computational thinking (CT) as an effective strategy, adopted in the MIT-Harvard model since 2012, which has a clearly established theoretical framework.

The purpose of this research was to assess the level of development of computational thinking competencies aimed at problem-solving. To achieve this, a quantitative study with a non-experimental cross-sectional design was conducted, examining the relationship between three dimensions of computational thinking: conceptual, practical, and perspectival, and their impact on the development of competencies for problem-solving. The results showed positive correlations greater than 0.466, 0.384, and 0.681 with a significance of 0.000, evidencing a strong connection between the theoretical foundation, practice to consolidate learning, and the development of skills for making appropriate decisions in the search for solutions.

This study was conducted at a public university in Peru with 175 engineering students. The diagnostic instrument, validated with 8 problems, assessed the necessary skills to generate competencies aligned with the Peruvian education system, which promotes learning in three key areas: knowing, knowing how to do, and knowing how to be. The results provide valuable information for creating a virtual learning ecosystem to support the students' comprehensive development.