Herramienta de entrenamiento para ingenieros de sistemas en su primera entrevista laboral
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Fecha
2023
Autores
Puello Blanco, José Carlos
Bravo Colina, Franklin de Jesús
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Editor
Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
En el entorno laboral actual, la principal problemática se relaciona con la dificultad que enfrentan muchos ingenieros de sistemas al buscar empleo debido a la falta de conocimientos, experiencia o habilidades blandas, las cuales son de vital importancia en la actualidad. El objetivo principal del estudio consiste en desarrollar un chatbot que simule la primera entrevista en un proceso de selección para ingenieros de sistemas.
Para lograrlo, se empleó un enfoque interactivo que ayuda a los ingenieros de sistemas a prepararse para sus entrevistas laborales. Se utilizó una técnica de procesamiento de lenguaje natural que agiliza el proceso de retroalimentación. El diseño, la recolección y el análisis de datos se basaron en la metodología presentada por Hernández, Fernández y Baptista [16]. La metodología para el desarrollo de la herramienta constó de cuatro etapas: la recolección y creación de datos en forma de preguntas, la definición del modelo, el análisis y la implementación.
Se llevaron a cabo dos sesiones de entrevistas con una muestra de 20 entrevistados en cada una. Los resultados obtenidos arrojaron un promedio de calificación de 6.8 en la primera sesión y 8.2 en la segunda, lo que demuestra una mejora en las habilidades de los entrevistados al utilizar el chatbot. A pesar de los desafíos encontrados en el entrenamiento del modelo conversacional y la complejidad de las preguntas generales en las entrevistas, el chatbot demostró ser eficaz para mejorar las habilidades de los ingenieros de sistemas.
In the current work environment, the main problem is related to the difficulty that many systems engineers face when seeking employment due to a lack of knowledge, experience, or soft skills, which are crucial in today's world. The main objective of the study is to develop a chatbot that simulates the first interview in a selection process for systems engineers. To achieve this, an interactive approach was employed to help systems engineers prepare for their job interviews. A natural language processing technique was used to streamline the feedback process. The design, data collection, and analysis were based on the methodology presented by Hernández, Fernández, and Baptista [16]. The methodology for developing the tool consisted of four stages: data collection and creation in the form of questions, model definition, analysis, and implementation. Two interview sessions were conducted with a sample of 20 interviewees in each session. The results obtained showed an average rating of 6.8 in the first session and 8.2 in the second, demonstrating an improvement in the skills of the interviewees when using the chatbot. Despite the challenges encountered in training the conversational model and the complexity of the general questions in the interviews, the chatbot proved to be effective in enhancing the skills of systems engineers.
In the current work environment, the main problem is related to the difficulty that many systems engineers face when seeking employment due to a lack of knowledge, experience, or soft skills, which are crucial in today's world. The main objective of the study is to develop a chatbot that simulates the first interview in a selection process for systems engineers. To achieve this, an interactive approach was employed to help systems engineers prepare for their job interviews. A natural language processing technique was used to streamline the feedback process. The design, data collection, and analysis were based on the methodology presented by Hernández, Fernández, and Baptista [16]. The methodology for developing the tool consisted of four stages: data collection and creation in the form of questions, model definition, analysis, and implementation. Two interview sessions were conducted with a sample of 20 interviewees in each session. The results obtained showed an average rating of 6.8 in the first session and 8.2 in the second, demonstrating an improvement in the skills of the interviewees when using the chatbot. Despite the challenges encountered in training the conversational model and the complexity of the general questions in the interviews, the chatbot proved to be effective in enhancing the skills of systems engineers.
Descripción
Palabras clave
Chatbot, Inteligencia artificial, Entrevista de trabajo, Entrenamiento, Selección de personal, Chatbot, Artificial intelligence, Job interview, Training, Recruitment
