This paper presents the use of wireless sensor networks (WSNs) in educational research as a platform for enhanced pedagogical learning. The aim here with the use of a WSN platform was to go beyond the implementation stage to the real-life application stage, i.e., linking the implementation to real-life applications, where abstract theory and algorithmic implementations become natural tools for the execution of application itself. Abstract theoretical concepts are illustrated through hands-on modular experiments in a host of diverse electrical and computer engineering courses. The WSN consists of Mica2 motes with on-board sensors, wireless communication antennas, and processors that are programmed using NesC. Three sets of experiments feeding into different courses [on topics such as wireless embedded networks, detection and estimation theory, stochastic processes, probability theory, statistical pattern recognition, and digital signal processing (DSP)] and illustrating different theoretical concepts are presented in detail. These experiments can be used as demos in those courses and/or can be incorporated as hands-on laboratory projects to go hand in hand with the course in which they are introduced. Also presented is the assessment of the experiments as pedagogical tools, made by means of well-designed evaluation questionnaires given to the students. Both the sensor network platform and the novel experiments built on this platform are found to be pedagogically successful tools for learning about and teaching the theoretical concepts introduced in those courses. The assessment survey shows that students who had very little knowledge on average before the demonstrations/experiments gained extensive knowledge and interest in the subject matter after going through them. (Contains 1 footnote, 1 table, and 7 figures.)