Smart System Model for the Recruitment of Teachers

Wilver Auccahuasi, Lucas Herrera, Karin Rojas, Sandra Meza, Christian Ovalle, Ivette Plasencia, Ana Barrera Loza, Jorge Figueroa Revilla, Pedro Flores Peña, Yuly Montes Osorio, Alfonso Fuentes, Kitty Urbano

Research output: Contribution to journalConference articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)68-74
Number of pages7
JournalCEUR Workshop Proceedings
Volume3269
StatePublished - 2022
Event2022 Workshop on Intelligent Systems, WINS 2022 - Virtual, Online, India
Duration: 22 Apr 202224 Apr 2022

Keywords

  • Artificial intelligence
  • method
  • neural networks
  • selection
  • teachers

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