Calibración de juicios metacognitivos: Un análisis comparativo en estudiantes de educación superior

• Autores: Zapata Zapata, Adiela, Vesga Bravo, Grace Judith
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Católica San Pablo
• Repositorio: Revistas - Universidad Católica San Pablo
• Lenguaje: español
• OAI Identifier: oai:revistas.ucsp.edu.pe:article/1694
• Enlace del recurso: https://revistas.ucsp.edu.pe/index.php/psicologia/article/view/1694
• Nivel de acceso: acceso abierto
• Materia: Metacognitive judgments; Metacognitive accuracy; Educational intervention; Juicios metacognitivos; Precisión metacognitiva; Estrategias de estudio

Metacognitive judgements are crucial for monitoring and improving learning processes, as they allow students to evaluate their knowledge, methodologies and academic performance. These judgements contribute to the search for strategies for successful learning. This research analysed the metacognitive accuracy between predictive judgements and actual performance in university students (N= 56) after a metacognitive intervention during one semester. The intervention allowed students to explore various study strategies, planning and monitoring activities. A quantitative methodology was used with an experimental design, including a control group and an experimental group. Predictive judgements were recorded, such as expected grade estimates and the level of confidence in those estimates, as well as actual grades obtained in four cut-offs during the semester. These data were used to measure the calibration of metacognitive judgements. The results showed that the experimental group, which received the metacognitive intervention, improved the accuracy of their metacognitive judgements compared to the control group. However, in both groups there was a tendency to overestimate grades, being more pronounced in the control group that did not receive the intervention. Thus, the analysis of the results indicates that metacognitive strategies to increase awareness of one's own learning have a positive impact on the improvement of learning processes, reflected in higher accuracy, accurate confidence levels and higher calibrations.