Autorregulación del Aprendizaje en Estudiantes de Educación Tecnológica Self-Regulation of Learning in Technological Education Students
Autorregulação da Aprendizagem em Estudantes da Educação TecnológicaContenido principal del artículo
El objetivo del estudio fue analizar la autorregulación del aprendizaje en estudiantes de educación tecnológica superior, utilizando el Cuestionario de Autorregulación del Aprendizaje (CAR) de Pichardo et al. (2014), basado en el modelo cíclico de Zimmerman (2000), que contempla tres fases: planificación, ejecución y autorreflexión. Se adoptó un enfoque cuantitativo con diseño preexperimental, aplicando el instrumento a 70 estudiantes de la carrera de emergencias médicas. Los datos, recopilados mediante Google Forms, se analizaron con medidas de tendencia central y dispersión. Los resultados muestran un nivel moderado a alto de autorregulación (M = 56.4, DE = 8.67), aunque el 25.7 % de los estudiantes obtuvo puntajes bajos, evidenciando dificultades en la toma de decisiones y el aprendizaje de los errores. Las dimensiones más altas fueron “Metas” y “Perseverancia”, mientras que “Toma de decisiones” mostró mayor variabilidad. Se concluye que es necesario fortalecer estrategias metacognitivas y autorregulatorias en la formación tecnológica.
This study examines learning self-regulation in higher technological education students through the Learning Self-Regulation Questionnaire (CAR) by Pichardo et al. (2014), grounded in Zimmerman’s (2000) cyclical model, which involves planning, performance, and self-reflection phases. A quantitative approach with a pre-experimental design was employed, involving 70 students from the emergency medical technician program. Data were collected via Google Forms and analyzed using measures of central tendency and dispersion. Findings indicate a moderate to high level of self-regulation (M = 56.4, SD = 8.67); however, 25.7% of students scored low, reflecting challenges in decision-making and learning from mistakes. The highest-performing dimensions were “Goals” and “Perseverance,” whereas “Decision-making” showed the greatest variability. These results highlight the need to strengthen metacognitive and self-regulatory strategies within technological education.
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