Sistema de recomendación de matrículas en asignaturas basados en perfiles de docentes, alumnos y asignaturas en la escuela profesional de ingeniería de sistemas de la universidad Nacional de San Agustín

Translated title of the contribution: Recommender system of enrollments in subjects based on profiles of teachers, students and subjects in the Professional School of Systems Engineering of the National University of Saint Agustine

Estudiante Jerson Erick Herrera Rivera, Magíster Eveling Castro Gutiérrez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Translated title of the contributionRecommender system of enrollments in subjects based on profiles of teachers, students and subjects in the Professional School of Systems Engineering of the National University of Saint Agustine
Original languageSpanish
Title of host publicationProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9780999344316
DOIs
StatePublished - 2018
Event16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology - Lima, Peru
Duration: 18 Jul 201820 Jul 2018

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2018-July
ISSN (Electronic)2414-6390

Conference

Conference16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Country/TerritoryPeru
CityLima
Period18/07/1820/07/18

Bibliographical note

Funding Information:
En [10] se desarrolló un RS para determinar la productividad de aprendizaje del estudiante basado en parámetros fisiológicos, psicológicos y de comportamiento/movimiento. Se genera miles de recomendaciones basados en Persistencia educacional, motivacional y tablas de aprendizaje social y selecciona la opción más razonable de estas para una situación específica del estudiante. El RS proporciona a un estudiante una evaluación en tiempo real de su propia productividad de aprendizaje e interés en el aprendizaje.

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