AI-Powered Mobile Application ‘Play Home’ for Autism Education

This project describes the development of an AI-powered mobile application ‘Play Home’ which was designed as a teaching aid for children with autism. To enhance the learning process, the application employ machine learning (ML) techniques for image classification and object recognition. The AI models were trained using Google’s Teachable Machine platform which simplified and improved the model construction process. Meanwhile, the application ‘Play Home’ was built using MIT App Inventor which offers a low-code environment ideal for rapid development and deployment. ‘Play Home’ consists of five modules, each designed to help autistic children develop their cognitive and sensory skills. These modules improve attention span, recognition abilities, and overall participation through dynamic and engaging tasks. The integration of AI enables ‘Play Home’ to respond in real-time, making the learning experience more personalized and adaptable. The ‘Play Home’ includes a real-time database for progress monitoring, and performance metrics. This allows caregivers and educators to monitor learning outcomes and tailor content to individual students’ needs. Initial testing shows that the AI-powered application ‘Play Home’ works well, and has an appealing, instructive interface that caters to the special needs of children with autism. The use of interactive elements and responsive feedback has shown potential in making learning more enjoyable and accessible for the target group especially for autistic children. Future research will concentrate on real-world validation by working with autism centers to evaluate the educational impact and usability in real-world scenarios. The findings will guide further enhancements, ensuring the application meets the educational and developmental needs of children with autism.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Social Science
Published
2025-01-01
DOI
https://doi.org/10.47772/ijriss.2025.903sedu0486
Citations
1
Primary Topic
Social and Behavioral Studies
Type
article
Field-Weighted Citation Impact
2.17
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Powered Mobile Application ‘Play Home’ for Autism Education

Noor Mohd Ariff Brahin, Norezmi Jamal, Haslinah Mohd Nasir, Muhammad Azhar et al.
1 citations
International Journal of Research and Innovation in Social Science
Social and Behavioral Studies
2.17
article

AI-Powered Mobile Application ‘Play Home’ for Autism Education

Noor Mohd Ariff Brahin, Norezmi Jamal, Haslinah Mohd Nasir, Muhammad Azhar, Suraya Zainuddin, Ida Syafiza Md Isa, Nurul Syazwani binti Rohizat
article en
1 citations

Abstract

This project describes the development of an AI-powered mobile application ‘Play Home’ which was designed as a teaching aid for children with autism. To enhance the learning process, the application employ machine learning (ML) techniques for image classification and object recognition. The AI models were trained using Google’s Teachable Machine platform which simplified and improved the model construction process. Meanwhile, the application ‘Play Home’ was built using MIT App Inventor which offers a low-code environment ideal for rapid development and deployment. ‘Play Home’ consists of five modules, each designed to help autistic children develop their cognitive and sensory skills. These modules improve attention span, recognition abilities, and overall participation through dynamic and engaging tasks. The integration of AI enables ‘Play Home’ to respond in real-time, making the learning experience more personalized and adaptable. The ‘Play Home’ includes a real-time database for progress monitoring, and performance metrics. This allows caregivers and educators to monitor learning outcomes and tailor content to individual students’ needs. Initial testing shows that the AI-powered application ‘Play Home’ works well, and has an appealing, instructive interface that caters to the special needs of children with autism. The use of interactive elements and responsive feedback has shown potential in making learning more enjoyable and accessible for the target group especially for autistic children. Future research will concentrate on real-world validation by working with autism centers to evaluate the educational impact and usability in real-world scenarios. The findings will guide further enhancements, ensuring the application meets the educational and developmental needs of children with autism.

International Journal of Research and Innovation in Social Science
Openalex Percentile: Top 11%
Social and Behavioral Studies
2.17
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.