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GHIA: Modelado de Estudiantes, Analítica de Aprendizaje, Atención a la Diversidad y e-Learning

  • Xavier Alamán [1] ; Rosa M. Carro [1] ; Ruth Cobos [1] ; Javier Gómez [1] ; Francisco Jurado [1] ; Pablo Molins-Ruano [1] ; Germán Montoro [1] ; Jaime Moreno [1] ; Álvaro Ortigosa [1] ; Pilar Rodríguez [1] ; Juan C. Torrado [1]
    1. [1] Universidad Autónoma de Madrid

      Universidad Autónoma de Madrid

      Madrid, España

  • Localización: IE Comunicaciones: Revista Iberoamericana de Informática Educativa, ISSN-e 1699-4574, Nº. 30 (Julio-Diciembre), 2019, págs. 78-89
  • Idioma: español
  • Enlaces
  • Resumen
    • español

      En este documento se resumen las principales líneas de investigación del grupo GHIA en el ámbito de la informática educativa y se describen los trabajos realizados en este contexto durante los últimos años. Estos trabajos se centran principalmente en los siguientes aspectos: adquisición automática e inferencia de información (emociones, sentimientos, personalidad, etc.) para crear o alimentar modelos de estudiantes a partir de fuentes diversas; analítica de aprendizaje para la predicción del riesgo de fracaso o abandono de los estudiantes e intervención; diseño y desarrollo de aplicaciones y recursos para el aprendizaje y el entrenamiento de habilidades (juegos, robótica, realidad mixta, mundos virtuales, etc.); y creación de asistentes personales para la vida cotidiana (vestimenta, desplazamientos, tareas laborales, gestión de emociones, etc.). Los beneficiarios de los resultados de esta investigación son individuos o grupos que reciben aplicaciones y recursos adaptados a sus características y necesidades concretas, con especial énfasis en personas y colectivos con necesidades especiales y específicas.

    • English

      This document summarizes the main lines of research of the GHIA group in the field of educational informatics and describes the work carried out in this context during the last years. This work focuses mainly on: automatic acquisition and inference of information (emotions, feelings, personality, etc.) to create or feed student models, getting information from various sources; learning analytics for predicting the risk of failure or dropout of students and intervention; design and development of applications and resources for learning and skill training (games, robotics, mixed reality, virtual worlds, etc.); and creation of personal assistants for everyday life (clothing, travelling, work tasks, emotion management, etc.). The beneficiaries of the results of this research are individuals or groups that receive applications and resources adapted to their particular features and needs, with special emphasis on people and groups with specific needs.

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