Delgoshaei, Parhum, Engineering Education, Lohani, Vinod K., Griffin, Odis Hayden Jr., Goff, Richard M., and Mahajan, Roop L.
In this dissertation, the design, implementation, and educational applications of a real-time water and weather monitoring system, developed to enhance water sustainability education and research, are discussed. This unique system, called LabVIEW Enabled Watershed Assessment System (LEWAS), is a real- world extension of various data acquisition modules that were successfully implemented using LabVIEW into a freshman engineering course (Engineering Exploration, ENGE 1024) at Virginia Tech. The outdoor site location measures water quality and quantity data including flow rate, pH, dissolved oxygen, conductivity, and temperature -- as indicators of stream health - for an on-campus impaired stream in real-time. In addition, weather parameters (temperature, barometric pressure, relative humidity and precipitation) are measured at the LEWAS outdoor site. The measured parameters can be accessed by remote users in a real-time through a web-based interface for education and research. LEWAS is solar powered and uses the campus wireless network through a high-gain antenna to transmit data to remote clients in real-time. Its power budget consisting of consumption (14 W), electrical storage, and generation (80 W, peak) is balanced to enable 24/7 operation regardless of weather conditions. An embedded computer with low power consumption and modules for communicating and storing data are installed in the field and it is programmed to process measured environmental parameters to be delivered to remote users. This computer is programmed both using a field programmable gate array (FPGA, for low power consumption and robust operation) and traditional microprocessor programming (for more flexibility). The environmental sensors of the system are routinely calibrated using established procedures. A LEWAS Development Platform was established to develop and test the system and to train and mentor several undergraduate and graduate students who helped in its implementation. A number of design and implementation challenges were overcome including extending campus Internet access to a location not included on the network and integrating hardware and software from three different sensor manufacturers into a unified software platform accessible over the Internet. To study the educational applications of LEWAS, an observational study was conducted as the system was gradually introduced to students in ENGE 1024 between 2009 and 2011. Positive student attitudes on the role of LEWAS to enhance their environmental awareness informed an experimental design implemented to study the motivational outcomes associated with the system. Accordingly, appropriate educational interventions and a hands-on activity on the importance of environmental monitoring were developed for both control and experiment groups, with only the latter given access to LEWAS to retrieve the environmental parameters for the activity. An instrument was developed on the theoretical foundation of the expectancy value theory of motivation and was administered to control and experimental groups in ENGE 1024. Altogether, 150 students participated in the study. Exploratory Factor Analysis (EFA) was applied which resulted in factors that group questions together based on interest, importance, real-time access, and cost (feasibility of monitoring). After conducting parametric and nonparametric statistical analyses, it was determined that there exists a statistically significant difference between control and experimental groups in interest, real-time, and cost factors. This finding implies that providing real-time access to environmental parameters can increase student interest and their perception of feasibility of environmental monitoring -- both major components of motivation to learn about the environment. Future extensions and applications of the system at Virginia Tech and beyond are discussed. Ph. D.