Abstract:

This work presents the design and implementation of an active learning experience aimed at developing decision-making skills in engineering through the statistical analysis of real industrial data. Its main contribution is an open educational platform based on free software, designed to improve the critical interpretation of results in contexts of process improvement and system reliability, while also incorporating accessibility criteria, bilingual materials, and transversal competences linked to sustainability and digital competence.

The proposal was implemented in a university teaching context through practical activities, problem-solving, and collaborative work supported by interactive digital tools. Its pedagogical impact was evaluated using a mixed-methods approach, combining quantitative and qualitative indicators: student self-assessments and analysis of evidence of collaboration in forums and group assignments.

The results show an improvement in student engagement and in the technical quality of the projects developed. In particular, the experience demonstrates that the use of open resources and active methodologies fosters not only the acquisition of specific competences in data analysis applied to engineering, but also knowledge transfer and teaching innovation across areas and departments. These findings support the sustainability and scalability of the proposed model in higher education contexts in engineering.

Keywords:

Active Learning, digital learning tools, inclusive education.