Learnerly: Educational Mobile Application Using Object Detection

Artificial Intelligence technology is now growing rapidly and has become the main driver in promoting many new models of digital innovations, especially in the education field. The injection of AI in education applications grows its popularity and might be effective as a supportive tool in teaching and learning including for early education. AI potentially acts as a form of engagement between mobile applications and the development of cognitive skills among children in the classroom. Therefore, this research proposes an application named LEARNERLY that is tailored based on Malaysia’s standard curriculum for primary school. LEARNERLY encourages active learning and offers opportunities for parent-child interaction with the advent of Artificial Intelligence deep learning and object detection. The Prototyping Model has been employed as the methodology of system development. Dart and JAVA are being used to develop the system and the custom dataset and model that has been trained using Google Colab and TensorFlow are being implemented in the application. Findings from the test conducted depict that the majority of respondents, which are 93% agree that LEARNERLY has the potential to promote active learning in class due to its achievement. LEARNERLY is also able to work accordingly with the integration of Flutter and Google Colab, to detect objects in their surroundings hence promoting hands-on exploration among children.