AN ANDROID-BASED LEARNING TOOL FOR TRAFFIC SIGN RECOGNITION AMONG STUDENTS WITH DISABILITIES

This study presents the design of Traffic App, an Android-based application aimed at enhancing the understanding of traffic signs among students with disabilities. The research used a design-based research (DBR) method with four stages: analysis, design, iteration, and reflection. The Traffic App incorporates augmented reality (AR) and is tailored to the needs of disabled students because it provides accessible features such as customizable text size, audio support, and 3D media that facilitate easier comprehension. Expert validations confirmed the app’s feasibility because the design aligns with the cognitive and sensory needs of the target users. However, broader testing is still necessary to fully evaluate its effectiveness. This study is significant because it contributes to inclusive education by offering adaptive learning tools that support the independence and safety of students with disabilities in understanding traffic signs.