Factores determinantes de la movilidad virtual en universidades de América Latina: un análisis de modelo estructural [Determining factors of virtual mobility in Latin American universities: A structural model analysis]
DOI:
https://doi.org/10.36366/frontiers.v38i2.1184Keywords:
Higher education, internationalization, Latin America, structural model, virtual mobility, América Latina, educación superior, internacionalización, modelo estructural, movilidad virtualAbstract
This study analyzes the institutional factors that determine the consolidation of virtual mobility in Latin American universities through a structural equation model. Forty-nine universities from the Latin American Academic Exchange Program (PILA) were evaluated, examining three factors: management and organizational structure (F1), technological infrastructure (F2), and regulatory framework (F3). Results reveal extremely high correlations between factors (r > 0.96, p < 0.001) and exceptional internal consistency (α = 0.976). Multiple regression analysis and the Structural Equation Model (SEM) confirm that F1 exerts the greatest influence (β = .640), explaining 98.2% of variance in virtual mobility, while F2 (β = 0.264) and F3 (β = 0.107) show smaller effects, operating primarily indirectly. Findings validate Knight's (2004, 2021) systemic internationalization model and demonstrate that institutional management capabilities constitute the primary enabling factor for successful development of virtual mobility programs in the region.
Abstract in Spanish
Este estudio analiza los factores institucionales que determinan la consolidación de la movilidad virtual en universidades de América Latina mediante un modelo de ecuaciones estructurales. Se evaluaron 49 universidades del Programa de Intercambio Académico Latinoamericano (PILA), examinando tres factores: gestión y estructura organizacional (F1), infraestructura tecnológica (F2) y marco normativo (F3). Los resultados revelan correlaciones extremadamente altas entre los factores (r > 0.96, p < 0.001) y consistencia interna excepcional (α = 0.976). La regresión múltiple y el Modelo de Ecuaciones Estructurales (SEM) confirman que F1 ejerce la mayor influencia (β = 0.640), explicando 98.2% de la varianza en movilidad virtual, mientras F2 (β = 0.264) y F3 (β = 0.107) presentan efectos menores, operando principalmente de forma indirecta. Los hallazgos validan el modelo sistémico de internacionalización de Knight (2004, 2021) y demuestran que las capacidades de gestión institucional constituyen el factor habilitador primario para el desarrollo de programas de movilidad virtual en la región.
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