Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance
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 machin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/8/1951 |
| _version_ | 1797605675888541696 |
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| author | Lea Dujić Rodić Ivo Stančić Duje Čoko Toni Perković Andrina Granić |
| author_facet | Lea Dujić Rodić Ivo Stančić Duje Čoko Toni Perković Andrina Granić |
| author_sort | Lea Dujić Rodić |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T05:04:27Z |
| format | Article |
| id | doaj.art-d31a2b2632f24860a3d2ca975190251b |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T05:04:27Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-d31a2b2632f24860a3d2ca975190251b2023-11-17T19:03:12ZengMDPI AGElectronics2079-92922023-04-01128195110.3390/electronics12081951Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and PerformanceLea Dujić Rodić0Ivo Stančić1Duje Čoko2Toni Perković3Andrina Granić4Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 32 Ruđera Boškovića, 21000 Split, CroatiaFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 32 Ruđera Boškovića, 21000 Split, CroatiaFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 32 Ruđera Boškovića, 21000 Split, CroatiaFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 32 Ruđera Boškovića, 21000 Split, CroatiaFaculty of Science, University of Split, Ruđera Boškovića 33, 21000 Split, CroatiaThis 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.https://www.mdpi.com/2079-9292/12/8/1951IoTsmart toymachine learningearly childhood educationgeometryusability |
| spellingShingle | Lea Dujić Rodić Ivo Stančić Duje Čoko Toni Perković Andrina Granić Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance Electronics IoT smart toy machine learning early childhood education geometry usability |
| title | Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance |
| title_full | Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance |
| title_fullStr | Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance |
| title_full_unstemmed | Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance |
| title_short | Towards a Machine Learning Smart Toy Design for Early Childhood Geometry Education: Usability and Performance |
| title_sort | towards a machine learning smart toy design for early childhood geometry education usability and performance |
| topic | IoT smart toy machine learning early childhood education geometry usability |
| url | https://www.mdpi.com/2079-9292/12/8/1951 |
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