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  • Modelling and exploiting taxonomic knowledge for developing mobile learning systems to enhance children’s structural and functional categorization

Sección IA: Inteligencia artificial Bibliografía

Modelling and exploiting taxonomic knowledge for developing mobile learning systems to enhance children’s structural and functional categorization

MuhammadAzeem Abbas
Gwo-Jen Hwang
Saheed Ajayi
Ghulam Mustafa
Muhammad Bilal
2021
Computers & Education: Artificial Intelligence
2
https://www.sciencedirect.com/science/a…
artículo
estudio experimental
estudio empírico
inteligencia artificial
tecnología educativa
educación infantil
cognición y procesamiento
IA y aprendizaje
estudio empírico

Texto completo

The recent decade has seen increased attention focused on understanding category formation–a cognition ability of preschool aged children. Children organize their knowledge about real-world objects by categorizing them under some common properties or functions. The advancement and popularity of mobile devices with touch screens provide a good opportunity for young children to learn and practice. In this study, an approach that models structural and functional categorization knowledge for developing mobile learning systems with dynamic categorization exemplars is proposed. A mobile application was implemented based on the proposed model for pre-schoolers (aged 3–6 years). Moreover, the quasi-experimental pre-test and post-test method was used to evaluate the effectiveness of the proposed knowledge-based application in terms of categorization ability learning. The results show that the children who experienced dynamically created categorization exemplars from the modelled knowledge achieved increased scores compared to those who followed the traditional teaching using books and worksheets.

Texto completo en abierto (CC BY-NC-ND 4.0).
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