Smart system model for the recruitment of teachers

• Autores: Rojas Romero, Karin Corina, Auccahuasi, Wilver, Herrera, Lucas, Meza, Sandra, Ovalle, Christian, Plasencia, Ivette, Barrera Loza, Ana, Figueroa Revilla, Jorge, Flores Peña, Pedro, Montes Osorio, Yuly, Fuentes, Alfonso, Urbano, Kitty
• Formato: objeto de conferencia
• Fecha de Publicación: 2022
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/6402
• Enlace del recurso: https://hdl.handle.net/20.500.12867/6402
• Nivel de acceso: acceso abierto
• Materia: Employee selection; Teachers; Artificial neural networks; https://purl.org/pe-repo/ocde/ford#2.00.00

Times change, for many reasons, due to technological development, new ways of doing things and in some cases forced by a global condition, is the case of the present case, where we analyze the teacher selection processes, although many of the Academic activities are developed at a distance, the selection processes also accompany this model, in this process factors that must be presented according to the profile required by the institution are analyzed, in this work a technique is proposed to be able to classify the best candidates in a Teacher selection process, the methodology consists of analyzing three groups of characteristics that the candidates must present, such as the writing exercises, the group interview and finally a demonstration class, in each of them particular criteria are evaluated, a demonstrative example It is presented as a demonstration, where it can be conditioned according to the criteria of each ins As a result, we have a computational model based on neural networks, where the best candidates can be pre-selected or classified in a teacher selection process, the prototype can be scaled and used in different sectors.