Durham School of Architectural Engineering and Construction


First Advisor

Lily M. Wang

Date of this Version


Document Type



A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Architectural Engineering, Under the Supervision of Professor Lily M. Wang. Lincoln, Nebraska: April, 2019.

Copyright (c) 2019 Kieren Smith


The classroom environment influences the ability of children to learn. To ascertain the effect of indoor environment parameters on student achievement, a large-scale project was launched, collecting time-logged data from 220 k-12 classrooms in the eastern Nebraska region for six days each. Data were collected from a variety of disciplines, including acoustics, lighting, indoor air quality, and thermal comfort. This thesis focuses on the acoustic parameters, looking first at how overall classroom values--including average sound levels and room reverberation time--influence student achievement. Using structural equation modeling, the average sound level during times with speech present was discovered to have a negative effect on math achievement scores while room reverberation time had no statistical effect on either math or reading in the sample. Second, the time--logged data within each measured day were explored, observing specifically how the fluctuations over time correlate to the fluctuations in the data from other disciplines, including indoor air quality, thermal comfort, and illuminance measures. Indoor air quality parameters, including carbon dioxide concentration and particulate matter counts, were found to be most closely correlated with sound level over time. Finally, the effect of ventilation system type was analyzed, observing how it affects both overall values and time logged correlations. Classrooms with unit ventilators were observed to have the highest overall non-speech sound levels and a higher likelihood of finding a strong correlation between sound level and fine particulate matter.

Advisor: Lily M. Wang