Inicio
todoELE
  • Inicio
  • Materiales
    • πŸ“‹ Actividades
    • πŸ“ Conjugación
    • πŸ“Š Corpus
    • πŸ“” Diccionarios
    • βœ… Evaluación
    • βš™οΈ Gramática
    • πŸ“— Manuales
    • ✍️ Ortografía
    • πŸ“… Programación
    • πŸ—£οΈ Pronunciación
    • πŸ“ Recursos
    • πŸ”€ Vocabulario
    • πŸ’» Herramientas digitales
  • Formación
    • πŸ“š Bibliografía
    • πŸ‘₯ Congresos
    • πŸŽ“ Cursos
    • 🏫 Centros
    • 🏒 Organizaciones
    • πŸ“° Revistas
    • 🌍 Atlas de ELE
  • Trabajo
    • πŸ’Ό Ofertas de trabajo
    • ℹ️ Trabajo - Recursos
  • En la red
    • 🌐 Sitios ELE
    • πŸ“° Agregador
    • πŸ“§ Formespa
  • IA
    • ✨ Nuevos contenidos
    • πŸ“š Bibliografía IA
    • 🧰 Herramientas IA
    • πŸ’¬ Prompts
    • πŸ§ͺ Experiencias IA
    • 🌐 Sitios web IA
    • πŸ“° Actualidad IA
  • Comunidad
    • πŸ“° Actualidad ELE
    • 😊 Anécdotas ELE
    • πŸ“ Blog
    • πŸ“ŒTablón de anuncios
  • Buscar

Ruta de navegación

  • Inicio
  • Bibliografia
  • Immersive multi-modal pedagogical conversational artificial intelligence for early childhood education: An exploratory case study in the wild

Sección IA: Inteligencia artificial Bibliografía

Immersive multi-modal pedagogical conversational artificial intelligence for early childhood education: An exploratory case study in the wild

Sinem Aslan
Lenitra M. Durham
Nese Alyuz
Eda Okur
Sangita Sharma
Celal Savur
Lama Nachman
2024
Computers & Education: Artificial Intelligence
6
https://www.sciencedirect.com/science/a…
artículo
estudio de caso
estudio empírico
inteligencia artificial
educación infantil
chatbots
multimodalidad
juegos
aprendizaje colaborativo
IA y aprendizaje
chatbots
estudio empírico

Texto completo

Educational technology research has found that parents of young children widely share concerns about extended screen time, lack of physical activity, and lack of social interaction. Kid Space was developed to address these concerns by enabling multi-modal and immersive collaborative play-based learning. Kid Space utilizes multiple sensing technologies with an immersive physical space through a human-scale wall projection and incorporates a conversational AI agent to interact with children, understand individual progress, and personalize learning experiences in a blended physical and digital environment. To evaluate Kid Space in the wild, we conducted a multi-method user study involving a quasi-experimental design and exploratory case study with 14 students and three educators in an elementary school. Mixed methods for data collection and analysis were used to understand the students' and educators' perceptions of Kid Space and its impact on the students’ educational outcomes (learning engagement, experience, and performance). The findings showed (1) positive perceptions toward Kid Space, (2) high levels of engagement - with decreased screen time (41% of the time), increased physical activity (99.3% of the time), and increased social interactions with conversational AI agent and the other collaborating student (52% of the time), and (3) significant learning gains after experiencing Kid Space (24% gain, paired t-test: p < 0.01). These positive results are accompanied by critical user insights for improving future iterations of Kid Space to validate long-term educational outcomes.

Texto completo en abierto (CC BY-NC-ND 4.0).
  • Inicie sesión para enviar comentarios

Enviar publicación

Contenidos relacionados

  • An early investigation of collaborative problem solving in conversational AI-mediated learning environments
  • A mixed-methods analysis of AI scaffolding patterns and student inquiry profiles in a middle-school agriculture-STEM classroom
  • Designing conversational Agents for adaptive instructional support in business simulation gaming
  • LLaVA-docent: Instruction tuning with multimodal large language model to support art appreciation education
  • AI chatbots in programming education: Students’ use in a scientific computing course and consequences for learning
  • Generación de estrategias de lectura inferencial de textos académicos mediante herramientas de IA
Sobre Todoele Índice Publica Contacto: todoele@gmail.com
Política de privacidad Créditos