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A Data-Driven Study on the Associati...
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Kabirikopaei, Adel.
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A Data-Driven Study on the Association of Classrooms' Indoor Air Quality, Thermal Environment, and Students' Academic Performance.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A Data-Driven Study on the Association of Classrooms' Indoor Air Quality, Thermal Environment, and Students' Academic Performance./
作者:
Kabirikopaei, Adel.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
162 p.
附註:
Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:
Dissertations Abstracts International82-11B.
標題:
Architectural engineering. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28490171
ISBN:
9798728257196
A Data-Driven Study on the Association of Classrooms' Indoor Air Quality, Thermal Environment, and Students' Academic Performance.
Kabirikopaei, Adel.
A Data-Driven Study on the Association of Classrooms' Indoor Air Quality, Thermal Environment, and Students' Academic Performance.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 162 p.
Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2021.
This item must not be sold to any third party vendors.
Indoor air quality (IAQ) and thermal environment factors of 220 classrooms in the United States midwestern region were measured during two academic years in three seasons and during occupied and unoccupied periods. Measurements during occupied times included indoor CO2 and formaldehyde concentrations, coarse and fine particle counts, temperature, relative humidity, and globe temperature. Unoccupied measurements consisted of air velocity, carbon monoxide, nitrogen dioxide, ozone, and total volatile organic compounds (TVOC). Student-level data for 1468 elementary students and 1239 middle and high school students related to socioeconomic background and academic performance were also collected. This dataset included gender, ethnicity, lunch-pay status, English language learners, mathematics, and reading scores.To calculate ventilation rates from the collected CO2 data, three main methods were used: (1) steady-state; (2) decay rate; and (3) build-up. An uncertainty analysis was performed for all three methods. The study shows that the steady-state method has the least uncertainty in ventilation rate calculations, while the decay and build-up methods had the lowest and highest values for ventilation rates, respectively.To investigate if classrooms' IAQ and thermal factors vary on the classroom level or the school level, an analysis of variance (ANOVA) was performed. Based on the results, in the schools with multi-zone systems, fewer measurements for CO2 concentrations, coarse particles, and air velocity measurements (in school-level) may be sufficient to represent the condition of the school. Finally, a multilevel model was used to investigate the associations between IAQ, thermal data, and students' scores using demographic and performance variables as controls. The results revealed associations between student scores and ventilation rates, globe temperature, temperature, fine particle counts concentrations. There are also interaction effects between demographic, performance variables, and IAQ, thermal variables in the classroom.This research will provide information to school districts and design engineers. The results of this study can be adopted to design experiments for causality relationships and to confirm the effects of IAQ, Thermal environment factors on student academic performance.
ISBN: 9798728257196Subjects--Topical Terms:
3174102
Architectural engineering.
Subjects--Index Terms:
Academic performance
A Data-Driven Study on the Association of Classrooms' Indoor Air Quality, Thermal Environment, and Students' Academic Performance.
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Indoor air quality (IAQ) and thermal environment factors of 220 classrooms in the United States midwestern region were measured during two academic years in three seasons and during occupied and unoccupied periods. Measurements during occupied times included indoor CO2 and formaldehyde concentrations, coarse and fine particle counts, temperature, relative humidity, and globe temperature. Unoccupied measurements consisted of air velocity, carbon monoxide, nitrogen dioxide, ozone, and total volatile organic compounds (TVOC). Student-level data for 1468 elementary students and 1239 middle and high school students related to socioeconomic background and academic performance were also collected. This dataset included gender, ethnicity, lunch-pay status, English language learners, mathematics, and reading scores.To calculate ventilation rates from the collected CO2 data, three main methods were used: (1) steady-state; (2) decay rate; and (3) build-up. An uncertainty analysis was performed for all three methods. The study shows that the steady-state method has the least uncertainty in ventilation rate calculations, while the decay and build-up methods had the lowest and highest values for ventilation rates, respectively.To investigate if classrooms' IAQ and thermal factors vary on the classroom level or the school level, an analysis of variance (ANOVA) was performed. Based on the results, in the schools with multi-zone systems, fewer measurements for CO2 concentrations, coarse particles, and air velocity measurements (in school-level) may be sufficient to represent the condition of the school. Finally, a multilevel model was used to investigate the associations between IAQ, thermal data, and students' scores using demographic and performance variables as controls. The results revealed associations between student scores and ventilation rates, globe temperature, temperature, fine particle counts concentrations. There are also interaction effects between demographic, performance variables, and IAQ, thermal variables in the classroom.This research will provide information to school districts and design engineers. The results of this study can be adopted to design experiments for causality relationships and to confirm the effects of IAQ, Thermal environment factors on student academic performance.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28490171
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