International Journal of
Information and Education Technology

Abstract

Emerging technologies, such as the Artificial Intelligence of Things (AIoT), pose challenges in education, particularly when students struggle to connect theoretical concepts with practical applications. This gap limits their ability to engage with AIoT and develop computational thinking competencies, such as Critical Thinking, Algorithmic design, Problem-solving, Creativity, and Cooperativity. To address this issue, the Advance Organizer Integrating Visual-Based Programming for Artificial Intelligence of Things (AOVP-AIoT) model, was developed. The model combines structured scaffolding with visual programming to make AIoT concepts more accessible and engaging, fostering computational thinking skills applicable in formal and informal learning settings, including university courses, online training, and professional workshops. The study was conducted in two phases. Phase I involved designing the AOVP-AIoT model by synthesizing data from research publications (2003–2023). Expert review rated the model highly (mean = 4.39, SD = 0.69) across input components, learning processes, and computational thinking competencies. Phase II involved constructing the AOVP-AIoT platform, following the AIoT System Development Life Cycle (AIoT-SDLC) across eight iterative stages. Unlike existing approaches, the platform emphasizes on personalized learning pathways and interactive AI assistance, enchancing adaptability and real-time support. Evaluation results indicated very high quality in infrastructure, intelligence organizer-based management, learning tracking, and performance assessment (mean = 4.69, SD = 0.43). By equipping learners with transferable computational thinking skills, the AOVP-AIoT model addresses educational challenges in AIoT and prepares students for success in industries increasingly shaped by AI and IoT innovations.