Prototipo de análisis de sentimiento de retroalimentación textual entre pares

• Maricela Pinargote-Ortega ^[1] ; Lorena Bowen-Mendoza ^[1] ; Jaime Meza ^[1] ; Sebastián Ventura ^[2]
  1. [1] Universidad Técnica de Manabí

     Universidad Técnica de Manabí

     Portoviejo, Ecuador

     
  2. [2] Universidad de Córdoba

     Universidad de Córdoba

     Cordoba, España

     
• Localización: RISTI: Revista Ibérica de Sistemas e Tecnologias de Informação, ISSN-e 1646-9895, Nº. Extra 61, 2023, págs. 322-337
• Idioma: español
• Títulos paralelos:
  • Peer Feedback Sentiment Analysis Prototype
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    Las instituciones de educación superior se enfrentan actualmente a varios retos frente a los sistemas de evaluación informatizados para conseguir llegar al conocimiento inmerso de textos no estructurado. La aplicación de análisis de sentimiento mediante aprendizaje automático favorece la exploración de textos no estructurado para la gestión educativa. El propósito de este artículo fue modelar un prototipo de predicción de sentimiento de la retroalimentación textual generada en el proceso de evaluación entre pares. Se aplicó el método de modelación y se probó en la Universidad Técnica de Manabí (Ecuador). Los resultados muestran que es viable aplicar el prototipo, puesto que la mayoría de los estudiantes pudieron evaluar la tarea por cada criterio de la rúbrica justificando las razones de colocar tal puntación numérica según la temática. Se postula como una herramienta útil para evaluar no solo las competencias cognitivas sino también las reflexivas, criticas, y colaborativas en el proceso de enseñanza-aprendizaje.

  • English

    Higher education institutions currently face several challenges in the face of computerized assessment systems to reach the immersed knowledge of unstructured texts. The application of sentiment analysis through machine learning favors the exploration of unstructured texts for educational management.

    This article aimed to model a sentiment prediction prototype of the textual feedback generated in the peer assessment process. Was applied the modeling method and tested at the Technical University of Manabi (Ecuador). The results show that it is viable to apply the prototype since most of the students were able to evaluate the task by each rubric criterion, justifying the reasons for placing such numerical scores according to the theme. It is postulated as a helpful tool to assess cognitive, reflective, critical, and collaborative skills in the teachinglearning process

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