Academic performance as a driver for the development of reasoning for complexity and digital transformation competencies

Abstract

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This study analyzed the relationship between academic performance and the development of transversal competencies of reasoning for complexity and digital transformation in higher education students. The Tec21 educational model of the Tecnológico de Monterrey was used as a framework for analysis. Data from 33,319 students were analyzed following a CRISP-DM methodology, first an exploratory analysis was performed on the data to recognize and understand the presence of competencies in the educational model. Machine Learning methodologies, including Random Forest and XGBoost, were then employed to identify the most influential curricular and co-curricular variables in the acquisition of studied competencies. The results revealed a significant correlation between academic performance and the acquisition of the competencies, highlighting that high grades are consistently associated with success in developing these competencies. This study extends the understanding of how competency-focused educational interventions can facilitate professional and personal development in a labor market that demands advanced skills and adaptability. The discussion focuses on the implications of these findings for formulating educational policies and pedagogical practices that prioritize both academic achievement and the comprehensive development of essential 21st-century competencies. From a broader perspective, our work is framed in the achievement of Sustainable Development Goal 4 Quality Education and is oriented to identify variables that boost the acquisition of 21st Century Skills in higher education contexts.

Keywords

• reasoning for complexity
• educational innovation
• higher education
• digital transformation
• academic performance
• students