Developing Complex Thinking through Interactive Simulations Applied to Sensor Networks in Higher Education

Abstract

This study addresses the critical issue of fragmented learning in engineering education by framing sensor network design not as a collection of isolated technical problems, but as a multidimensional process. Grounded in Edgar Morin’s principles of Complex Thinking, the research implements an interactive simulation experience where students navigate decisions with systemic implications across energy, communications, and data processing. The pedagogical intervention targeted final-year telematics engineering students, transitioning them from high-level Python abstractions to the friction points of resource-constrained systems using the Contiki-NG operating system and Cooja simulator. The curriculum was structured across four distinct dimensions: infrastructure (C/IPv6), physical context (spatial emulation), communications (DODAG collective intelligence), and data processing through cloud-integrated protocols. Quantitative results revealed a non-linear learning curve; student performance dropped significantly from a mean of 83.68 to 62.47 points upon encountering the non-unidimensional reality of the simulator, before recovering to 71.57 points as students synthesized the complexity. Qualitative analysis indicated that while 56\% found the tasks difficult and 11\% considered them very complex in terms of simulator usage, 83\% felt the pace was adequate, and the majority agreed the simulation helped bridge the gap between theory and practice. Correlation analysis suggests that student interest and lecturing clarity are primary drivers of successful theoretical integration. Ultimately, simulated environments offer a sustainable, high-fidelity alternative to hardware for mastering real-world network constraints.