Traditional agricultural education has predominantly relied on conventional teaching methods. However, the evolving demands of the modern workforce need the integration of advanced technologies, such as the Internet of Things (IoT), Big Data, and Artificial Intelligence, to enable more precise and efficient management of crops and plantations. Recognizing the growing need for digital competences and IoT skills, various organizations have developed frameworks to guide the teaching of these technologies. This shift has transformed the educational paradigm, moving from a theoretical approach to a more practical, hands-on model.

In this study, we focused on a module titled "Proximity Sensors for Crop Monitoring" within the Precision Agriculture Master's program at the Universidad Politécnica de Madrid. Drawing on the DigComp 2.2 and the EU-IoT Skills Frameworks, we designed and implemented sessions aimed at enhancing postgraduate students' digital competences and IoT skills. Initially, students exhibited limited familiarity with IoT technologies. These sessions were structured to test a novel framework for teaching advanced technologies in higher education settings.

Sessions began with a lecture introducing fundamental IoT concepts, followed by practical programming examples to encourage active participation and code interpretation. Then, students were provided with IoT hardware components, including microcontrollers, sensors, and actuators, and tasked with autonomously developing an IoT system. Instructors offered guidance only when technical issues arose, fostering an environment of collaborative problem-solving.

Post-sessions, individual surveys were conducted to assess students' perceptions of their acquired digital competences and IoT skills. The results indicate that the framework employed in this case study holds promise as a foundational model for teaching digital competences and IoT skills to postgraduate students in agriculture. This approach not only bridges the gap between theoretical knowledge and practical application but also aligns with the evolving demands of the agricultural sector, preparing students for the technological challenges of the future.

Keywords: Internet of Things, Digital Competences, Precision Agriculture, Higher Education, Practical Learning.