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Un marco multimodal para comprender los procesos de diseño colaborativo
IEEE transactions on visualization and computer graphics
|January 16, 2026
Resumen
Este estudio presenta un marco para analizar talleres de diseño colaborativo, utilizando IA y herramientas visuales para integrar diversas fuentes de datos para una mejor comprensión de la toma de decisiones y los resultados grupales.
Área de la Ciencia:
- Interacción Humano-Computadora
- Estudios de Diseño
- Trabajo Cooperativo Asistido por Computadora
Sus antecedentes:
- El análisis de los procesos de diseño colaborativo es crucial para comprender los resultados y la toma de decisiones.
- Los métodos actuales a menudo se basan en datos textuales consolidados de entrevistas u observaciones, enfrentando desafíos con el volumen y la heterogeneidad de los datos.
- La integración de diversas fuentes de datos de los talleres sigue siendo un desafío importante en la investigación de diseño.
Objetivo del estudio:
- Proponer un marco práctico, modular y adaptable para el análisis de talleres.
- Introducir un sistema de análisis visual interactivo, reCAPit, para la integración de datos multimodales.
- Mejorar la metodología para la adquisición rica en datos, la extracción basada en IA y el análisis visual de talleres de diseño colaborativo.
Principales métodos:
- Desarrolló un marco que abarca la configuración del taller, la adquisición de datos multimodales, la extracción de artefactos basada en IA y el análisis visual.
- Creó el sistema reCAPit, integrando modalidades como video, audio, notas y datos de la mirada.
- Realizó seis talleres sobre diversos temas y analizó dos estudios de caso en detalle.
Principales resultados:
- El sistema reCAPit permite la combinación flexible de datos multimodales para el análisis.
- Un streamgraph multimodal visualiza la actividad y la atención, mientras que las tarjetas de temas resumen las discusiones.
- Las técnicas de desglose permiten la inspección de datos sin procesar de varias fuentes.
Conclusiones:
- El marco propuesto extiende la metodología de los talleres de diseño colaborativo con adquisición rica en datos.
- La extracción combinada basada en IA y el análisis visual interactivo ofrecen una difusión transparente de los resultados.
- Este enfoque facilita una comprensión más profunda de la colaboración y la toma de decisiones en los procesos de diseño.
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