Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance

Author:

Dujić Rodić Lea1ORCID,Stančić Ivo1ORCID,Čoko Duje1ORCID,Perković Toni1ORCID,Granić Andrina2ORCID

Affiliation:

1. Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 32 Ruđera Boškovića, 21000 Split, Croatia

2. Faculty of Science, University of Split, Ruđera Boškovića 33, 21000 Split, Croatia

Abstract

This study presents the design and evaluation of a plush smart toy prototype for teaching geometry shapes to young children. The hardware design involves the integration of sensors, microcontrollers, an LCD screen, and a machine learning algorithm to enable gesture recognition by the toy. The machine learning algorithm detects whether the child’s gesture outline matches the shape displayed on the LCD screen. A pilot study was conducted with 14 preschool children to assess the usability and performance of the smart toy. The results indicate that the smart toy is easy to use, engages children in learning, and has the potential to be an effective educational tool for preschool children. The findings suggest that smart toys with machine learning algorithms can be used to enhance young children’s learning experiences in a fun and engaging way. This study highlights the importance of designing user-friendly toys that support children’s learning and underscores the potential of machine learning algorithms in developing effective educational toys.

Funder

Croatian Science Foundation

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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