Integrating CDIO and Problem Based Learning Frameworks for Industrial Internet of things Training Course Development

Industrial sector has shifted from traditional to more advanced industries, focusing on integrating technology and developing skills to enhance productivity. Previous studies highlighted that the CDIO approach was suitable for technical training but faced complexity, time constraints, and challenges in adapting to the needs of learners and instructors. This paper proposed a new learning model that tackled these issues by integrating problem-based learning, using real learner problems as the foundation for skill development. This model was applied in training for Internet of Things education in the industrial sector, combining app-based learning with practical training. It began with identifying learner needs through group discussions, followed by curriculum design and app-supported theoretical learning, culminating in practical exercises. Results showed that this model simplified curriculum development, enhanced adaptability, and reduced learning time, increasing learning efficiency by up to 71.43 percent. While learners were satisfied and engaged, further skills such as programming and platform usage needed development. Flexibility and ongoing teaching innovation are crucial for the CDIO model to meet current and future workforce needs.