<![CDATA[Number recognition is a critical skill in early education, laying the foundation for digital literacy and mathematical understanding. However, traditional methods of teaching number recognition often lack the interactivity and engagement necessary for effective learning, particularly for young learners. This study proposes the development of a deep learning-based Android application aimed at enhancing the number recognition process by providing an interactive and visual learning experience. The application utilizes a Convolutional Neural Network (CNN), a type of deep learning model, to recognize handwritten numbers, offering users an innovative and engaging way to learn and practice number recognition.In the proposed application, users can draw numbers on their devices, and the system will immediately provide feedback regarding the accuracy of the drawn numbers. The CNN model will be trained on a comprehensive dataset of handwritten digits to ensure high accuracy in recognition. This real-time feedback loop is designed to help users learn the correct form of numbers while also introducing the foundational concepts of deep learning. The main objective of this application is to provide an accessible, interactive platform for learning number recognition, especially for novice learners who may be unfamiliar with basic concepts in machine learning and digital literacy. By integrating deep learning technology, the application not only supports the learning of number recognition but also serves as an introduction to artificial intelligence (AI) concepts in a practical, easy-to-understand format. Furthermore, the application is designed to be user-friendly, ensuring that it is suitable for a wide range of learners, including children and beginners. The application aims to combine the fundamental principles of deep learning with a practical, hands-on learning experience, fostering a deeper understanding of both number concepts and the potential of AI in everyday life.]]>
