Bridging the Gap: Applying AI and Bayesian Statistics to Traditional Educational Leadership Training
DOI:
https://doi.org/10.31637/epsir-2024-916Palabras clave:
Leadership, Artifical Intelligence, Higher Education, Bayesian Analysis, project-based learning, educational estrategies, curricular development, professional sucessResumen
Introduction: In the dynamic landscape of modern organizations, leadership is a vital competency. However, traditional uniform approaches often fail to address the diverse challenges posed by contemporary environments. Social, educational, and technological transformations, including the rise of artificial intelligence (AI), necessitate a shift toward more adaptive leadership styles. Methodology: This study explores situational leadership in higher education, focusing on its responsiveness to AI-driven resource management and its role in fostering professional success. Using Bayesian analysis, the study evaluates the effectiveness of project-based learning (PBL) in developing leadership qualities. Data from 404 educators across 28 institutions were analyzed, covering ten variables related to leadership and PBL. Results: The results offer insights into curricular development and educational strategies to equip students with essential skills for professional success. Discussion: Situational leadership, as developed by Hersey and Blanchard, emphasizes adapting leadership styles to follower maturity and specific situations, highlighting the need for flexibility in dynamic environments. Conclusions: The model's focus on follower maturity distinguishes it from static leadership models, underscoring its enduring relevance.
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