Modelo predictivo del rendimiento académico y el aprendizaje basado en estrategias metodológicas en una universidad pública peruana

José Alfredo Herrera Farfán, Regina Jiménez Chinga, Adolfo Zeta Vite, Adolfo Antenor Jurado Rosas, Lemin Abanto Cerna

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The study proposes to the academic community a model that explains the academic performance and learning (deep learning and superficial learning) of the students based on the learning process and that this in turn is explained by the methodological strategies. To contrast the theoretical model, a questionnaire was applied to the students of the Faculty of Administrative Sciences and information was obtained on satisfaction with the academic indexes used by teachers For the analysis, descriptive indicators and the SEM model was used, including measures of model fit (absolute fit, incremental fit and parsimony fit) and multiple correlations. The results confirm the proposal of the model, that is, academic performance and learning is mediated by the learning process; however, the final model does not present more evidence regarding surface learning.

Título traducido de la contribuciónPredictive model of academic performance and learning based on methodological strategies in a Peruvian public university
Idioma originalEspañol
Título de la publicación alojadaProceedings of the 22nd LACCEI International Multi-Conference for Engineering, Education and Technology
Subtítulo de la publicación alojadaSustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0., LACCEI 2024
EditorialLatin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)9786289520781
DOI
EstadoPublicada - 2024
Evento22nd LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2024 - Hybrid, San Jose, Costa Rica
Duración: 17 jul. 202419 jul. 2024

Serie de la publicación

NombreProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
ISSN (versión digital)2414-6390

Conferencia

Conferencia22nd LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2024
País/TerritorioCosta Rica
CiudadHybrid, San Jose
Período17/07/2419/07/24

Palabras clave

  • academic performance
  • learning
  • satisfaction
  • teachers
  • university

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