DEVELOPMENT OF MOBILE APPLICATION LEARNING FOR TODDLERS USING MACHINE LEARNING MODEL

The early stages of childhood development are important for cognitive growth and foundational learning. This project presents the development of a mobile learning application for toddlers that leverages machine learning models to deliver an adaptive and engaging educational experience. The application features a simple and interactive user interface enhanced with sound to sustain toddlers’ attention and interest. The system tracks each toddler’s learning progress and engagement levels using machine learning algorithms that analyze interaction patterns and facial expressions to evaluate understanding and emotional responses. Based on these insights, the application provides adaptive feedback and personalised rewards to promote continuous motivation and participation. Furthermore, it generates insightful reports and recommendations for caregivers, supporting informed guidance in early childhood learning and development. The backend of the system is developed using the Claude Anthropic SDK, which is well-suited for data analysis, machine learning, and API development, ensuring efficient data processing and intelligent model integration. The frontend is developed using React Native, providing a cross- platform, responsive, and user-friendly interface that enhances accessibility and usability. The application focuses on teaching basic alphabet, numbers, shapes, and arithmetic concepts through interactive exercises. By integrating machine learning, the system adapts dynamically to each child’s learning pace, ensuring a personalised, enjoyable, and effective educational experience. Overall, this study demonstrates how intelligent mobile applications can transform early education by combining machine learning, modern development frameworks, and adaptive learning to nurture foundational skills in young learners.