ARCCA Archives, Specialist|

[Originally published in 4th quarter 2004, in arcCA 04.4, “School Daze.”]  

Photo by Ragina Johnson.

Author Lisa Heschong is a principal of Heschong Mahone Group and a licensed architect who has divided her professional practice between energy research, writing, and building design. Her publications include Residential Windows: A Guide to New Technologies and Energy Performance (WW Norton), and Thermal Delight in Architecture (MIT Press), and she is a co-author of the Advanced Lighting Guidelines, the CHPS Best Practices Manual, and the Skylighting Guidelines, all web-based publications. As a lighting expert, she developed the successful web-based training program for the Federal Energy Management Program and conducted workshops across the country for DOE. She has published scholarly papers, written for trade magazines, and conducted numerous lectures and workshops across the country on issues of daylighting, high performance design, energy efficiency, and human comfort.
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This study, undertaken on behalf of the California Energy Commission’s Public Interest Energy Research (PIER) program, investigates whether daylight and other aspects of the indoor environment in elementary school student classrooms have an effect on student learning, as measured by their improvement on standardized math and reading tests over an academic year. The study uses regression analysis to compare the performance of over 8,000 3rd through 6th grade students in 450 classrooms in the Fresno Unified School District, located in California‘s Central Valley. Statistical models were used to examine the relationship between elementary students’ test improvement and the presence of daylight in their classrooms, while controlling for traditional education explanatory variables, such as student and teacher demographic characteristics. Numerous other physical attributes of the classroom were also investigated as potential influences, including ventilation, indoor air quality, thermal comfort, acoustics, electric lighting, quality of view out of windows, and the type of classroom, such as open or traditional plan or portable classroom.
Previous Studies
This study is the third in a series of studies looking at the relationship between daylighting and student performance. The first, Dayliqhtinq in Schools, which was completed for Pacific Gas and Electric In 1999, examined school districts in three states. In Seattle, Washington, and Fort Collins, Colorado, where end-of-year test scores were used as the outcome variable, students in classrooms with the most daylighting were found to have 7% to 18% higher scores than those with the least. In San Juan Capistrano, California, where the study was able to examine the improvement between fall and spring test scores, we found that students with the most daylighting in their classrooms progressed 20% faster on math tests and 26% faster on reading tests in one year than in those with the least.
A second study, the Daylighting in Schools Reanalysis Report, completed for the California Energy Commission in 2001, further investigated the results from the Capistrano school district. We investigated whether better teachers were being stationed in more daylit classrooms and thereby inflating the importance of the daylight variable. In that district, we found that there was no assignment bias of better teachers to more daylit classrooms. Furthermore, the addition of information about teacher characteristics to the original student performance models did not reduce the significance or magnitude of the daylight variables. Among twelve models considered in that study, we identified a central tendency of a 21% improvement in student learning rates from those in classrooms with the least amount of daylight to those with the most.
Fresno Study
This study’s primary goal was to examine another school district, one with a different climate and curriculum, to see whether the original methodology and findings would hold. We collected more information about the lighting and daylighting conditions in the classrooms, to allow us to test which attributes of a daylit classroom were more likely to contribute to a “daylight effect,” if any. We also wished to understand how other aspects of the indoor environment affected student performance and interacted with daylight. To accomplish these goals, this study gathered detailed information about classroom conditions, including lighting and daylighting, HVAC, ventilation, windows, surface coverings, view, and indoor air quality. Whereas we had done on-site surveys of only a sample of classrooms for the previous studies, for this study we went on-site to measure attributes in every classroom, surveying a total of 500 classrooms in 36 schools.
The preliminary statistical analyses replicated the structure or the models used in the previous studies. They used a holistic variable called the Daylight Code to rate classrooms by the amount of daylight available throughout the school year. In these replication models, the Daylight Code was not significant in predicting student performance for Fresno. It had the least explanatory power of the variables considered, and lowest significance level. Thus, we could not replicate the Capistrano findings based on a similar model structure. We proceeded with more detailed statistical analysis to see if we could identify specific influences of school or classroom design on student performance and perhaps gain some insight as to why the Daylight Code was not significant in Fresno as it had been in Capistrano, Seattle, and Fort Collins.
We used multi-linear regression analysis to test a wide variety of variables to see which provided the best explanation of student performance. of the variables describing the physical conditions of classrooms and schools, characteristics describing windows were generally quite stable in their association with better or worse student performance. Variables describing a better view out of windows always entered the equations as positive and highly significant, while variables describing glare, sun penetration and lack of visual control always entered the models as negative.
In addition, attributes of classrooms associated with acoustic conditions and air quality issues followed a similar pattern. Those variables representing sources of internal noise, such as a loud HVAC system or a loud ballast hum from the lighting system, were consistently associated with negative student performance, while increasing the amount of carpet (which reduces acoustic reverberance) in the classroom was associated with better student performance m reading. Variables related to indoor air quality showed that in Fresno automatically controlled mechanical ventilation (No Teacher Control of Fan) was positive, while visible water damage or a surveyor assessment of musty air in the classroom was negative.
Summary of Study Findings
The findings of regression models in this study support the general conclusions that:

  • The visual environment is very important for learning.
  • An ample and pleasant view out of a window, which includes vegetation or human activity and objects in the far distance, supports better outcomes of student learning.
  • Sources of glare negatively impact student learning. This is especially true for math learning, where instruction is often visually demonstrated on the front teaching wall. Per our observations, when teachers have white marker boards, rather than black or green chalk boards, they are more likely to use them, and children perform better in math.
  • Direct sun penetration into classrooms, especially through unshaded east- or south-facing windows, is associated with negative student performance, likely causing both glare and thermal discomfort.
  • Blinds or curtains allow teachers to control the intermittent sources of glare or visual distraction through their windows. When teachers do not have control of their windows, student performance is negatively affected.
  • The acoustic environment is also very important for learning. Situations that compromise student focus on the lessons at hand, such as reverberant spaces, annoying equipment sounds, or excessive noise from outside the classroom, have measurable negative effects on learning rates.
  • Poor ventilation and indoor air quality also appear to negatively affect student performance. However, in FUSD these issues are almost hopelessly intertwined with thermal comfort, outdoor air quality, and acoustic conditions. Teachers often must choose to improve one while making another aspect of the classroom worse.

The Importance of School Design Choices
These findings suggest the importance school planners should give to the architectural design of schools. The statistical models repeatedly demonstrate that physical conditions of classrooms and schools are just as likely to affect student learning as many other factors commonly given much more public policy attention. Variables describing the physical conditions of classrooms, most notably the window characteristics, were as significant and of equal or greater magnitude as teacher characteristics, number of computers, or attendance rates in predicting student performance.
Even though the physical characteristics of a classroom have a very minor potential influence on the performance of a given individual they will reliably affect hundreds or thousands of students over the life of the building, typically fifty years. Since the design of classrooms is entirely within the control of the school district much more so than student or teacher demographics, optimized design of schools should be a central concern for all new school construction.
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AIA California
AIA California
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