| There has been a longtime belief, that those buildings with good to excellent lighting, acoustics, and controlled environments enhance the functional productivity of the building. For schools this includes the short- and long-term performance of students to learn and be “educated”, the health, comfort, attendance of students, teachers, administrators and supporting staff, life cycle cost, and energy efficiency.; One method for evaluating the relationship or effect of improved lighting and environmental systems and control on teacher and student performance to learn or achieve education can be to measure performance on standard tests. The data can be gathered and a methodology developed to evaluate the link or relationship to health, attendance, energy efficiency, and comfort.; During the 1995–1996 school year, 31 of 240 schools for the Houston Independent School District had their lighting and central cooling systems renovated and their air handling systems and controls cleaned and tuned. The change in the number and percent of students passing the standardized Texas Assessment of Academic Skills (TAAS) tests for Reading, Math, and Writing; for student attendance, promotion, and disciplinary rates; and for teacher attendance was evaluated using the Smirnov Test Statistic, the Lilleifors Test Statistic, chi-squared analysis, Pearson Correlation Coefficient, and a least squares linear regression model. These evaluations were accomplished between the renovated and non-renovated schools. The teacher and student performance and demographic information was available for two years prior to the renovation and three years after the renovation for all schools.; While the chi-squared analysis showed a statistically significant association between renovation and student performance (p-value < 0.05), the association was not significant in the least square linear regression analysis. Therefore, the null hypothesis of no change between renovated and non-renovated schools was accepted. Differences in the pre-renovation data sets and the limited size of the data set were identified as the primary reason a significant association was not consistently found. This included a greater regression to the mean effect in the non-renovated schools. |
