School Green Space and Its Impact on Academic Performance: A Systematic Literature Review
Abstract
:1. Introduction
- (1)
- What is the strength of evidence tying school green space to academic performance?
- (2)
- How do study findings differ by the measure of academic performance considered?
- (3)
- How do study findings on this topic differ by the measure of green space considered?
- (4)
- What effect do confounding and moderating variables have on green space and academic performance associations?
2. Materials and Methods
- (1)
- Report at least one objective measure of green space within or around school campuses. In this paper, we use the phrase “green space” to describe areas of vegetation, such as forests, street trees and parks, and gardens [33]. We define “within or around school campus” as the area describing students’ experience of nature at school. This includes not only the school property but also the 25 m buffer around the property. This larger area represents the viewshed in which students may visually or physically access green space during the school day [28].
- (2)
- (3)
- Perform any type of inferential statistical test (i.e., correlations, regressions, t-tests) to examine the relationship between green space around schools and academic performance.
- (4)
- Present original research findings in peer-reviewed journals written in English.
3. Results
3.1. Article Selection
3.2. Descrition of Articles
3.3. Study Design and Quality
3.4. Differing Associations by Outcome and Green Space Measure
3.5. Differing Associations by Confounders and Moderators
4. Discussion
4.1. Overview of Study Limitations
4.2. Patterns Linking Green Space to Academic Performance
4.3. Future Research
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Database | Keyword Search |
---|---|
Web of Science | ALL FIELDS: ((“green space” OR “greenness” OR “greenspace” OR “tree cover*” OR “natural environment*” OR “nearby nature”) AND (“academic performance” OR “academic achievement” OR “test score*” OR “standardized test*” OR “semester grade*”)). Indexes: SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, IC. a |
Scopus | TITLE-ABS-KEY ((“green space” OR “greenness” OR “greenspace” OR “tree cover*” OR “natural environment*” OR “nearby nature”) AND (“academic performance” OR “academic achievement” OR “test score*” OR “standardized test*” OR “semester grade*”)) AND DOCTYPE (ar) |
Education Resources Information Center (ERIC) | (“green space” OR “greenness” OR “greenspace” OR “tree cover*” OR “natural environment*” OR “nearby nature”) AND (“academic performance” OR “academic achievement” OR “test score*” OR “standardized test*” OR “semester grade*”) |
First Author | Academic Outcome | Green Space Measure | Distance | Association between Green Space and Outcome |
---|---|---|---|---|
Beere | Math | Green land | Schoolyard | Negative |
Beere | Math | Green land | 3000 m | Negative |
Beere | Reading | Green land | Schoolyard | Negative |
Beere | Reading | Green land | 3000 m | Negative |
Beere | Writing | Green land | Schoolyard | Negative |
Beere | Writing | Green land | 3000 m | Negative |
Browning | Math | Greenness | 500 m | Negative |
Browning | Math | Greenness | 3000 m | Negative |
Browning | Math | Greenness | 250 m | Negative |
Browning | Math | Greenness | 1000 m | Negative |
Hodson | Math | Grass | 3000 m | Null |
Hodson | Math | Shrub | 3000 m | Null |
Hodson | Math | Tree | 3000 m | Null |
Hodson | Reading | Grass | 3000 m | Null |
Hodson | Reading | Shrub | 3000 m | Null |
Hodson | Reading | Tree | 3000 m | Positive |
Kuo | Math | Tree | Schoolyard | Positive |
Kuo | Math | Tree | 3000 m | Null |
Kuo | Reading | Tree | Schoolyard | Null |
Kuo | Reading | Tree | 3000 m | Null |
Kweon | Math | Grass | Schoolyard | Null |
Kweon | Math | Tree | Schoolyard | Positive |
Kweon | Reading | Grass | Schoolyard | Null |
Kweon | Reading | Tree | Schoolyard | Positive |
Leung | Math | Green land | 500 m | Positive |
Leung | Math | Green land | 250 m | Positive |
Leung | Math | Green land | 2000 m | Positive |
Leung | Math | Green land | 1000 m | Positive |
Leung | Math | Greenness | 500 m | Positive |
Leung | Math | Greenness | 250 m | Positive |
Leung | Math | Greenness | 2000 m | Positive |
Leung | Math | Greenness | 1000 m | Positive |
Leung | Reading | Green land | 500 m | Positive |
Leung | Reading | Green land | 250 m | Null |
Leung | Reading | Green land | 2000 m | Positive |
Leung | Reading | Green land | 1000 m | Positive |
Leung | Reading | Greenness | 500 m | Positive |
Leung | Reading | Greenness | 250 m | Positive |
Leung | Reading | Greenness | 2000 m | Positive |
Leung | Reading | Greenness | 1000 m | Positive |
Li | College | Tree | 500 m | Positive |
Li | College | Tree | 3000 m | Positive |
Li | College | Tree | 3000 m | Positive |
Li | College | Tree | 250 m | Positive |
Li | College | Tree | 2000 m | Positive |
Li | College | Tree | 2000 m | Positive |
Li | Grades | Tree | 500 m | Null |
Li | Grades | Tree | 3000 m | Null |
Li | Grades | Tree | 3000 m | Positive |
Li | Grades | Tree | 250 m | Positive |
Li | Grades | Tree | 2000 m | Null |
Li | Grades | Tree | 2000 m | Null |
Markevych | Math | Agriculture | 500 m | Null |
Markevych | Math | Agriculture | 1000 m | Null |
Markevych | Math | Green land | 500 m | Null |
Markevych | Math | Green land | 1000 m | Null |
Markevych | Math | Greenness | 500 m | Null |
Markevych | Math | Greenness | 500 m | Null |
Markevych | Math | Greenness | 1000 m | Null |
Markevych | Math | Greenness | 1000 m | Null |
Markevych | Math | Tree | 500 m | Null |
Markevych | Math | Tree | 500 m | Null |
Markevych | Math | Tree | 500 m | Null |
Markevych | Math | Tree | 1000 m | Null |
Markevych | Math | Tree | 1000 m | Null |
Markevych | Math | Tree | 1000 m | Null |
Markevych | Reading | Agriculture | 500 m | Null |
Markevych | Reading | Agriculture | 1000 m | Null |
Markevych | Reading | Green land | 500 m | Null |
Markevych | Reading | Green land | 1000 m | Null |
Markevych | Reading | Greenness | 500 m | Null |
Markevych | Reading | Greenness | 500 m | Null |
Markevych | Reading | Greenness | 1000 m | Null |
Markevych | Reading | Greenness | 1000 m | Null |
Markevych | Reading | Tree | 500 m | Null |
Markevych | Reading | Tree | 500 m | Null |
Markevych | Reading | Tree | 500 m | Null |
Markevych | Reading | Tree | 1000 m | Null |
Markevych | Reading | Tree | 1000 m | Null |
Markevych | Reading | Tree | 1000 m | Null |
Matsuoka | College | Grass | Schoolyard | Null |
Matsuoka | College | Green land | View | Positive |
Matsuoka | Grades | Grass | Schoolyard | Null |
Matsuoka | Grades | Green land | View | Positive |
Sivarajah | Math | Tree | Schoolyard | Null |
Sivarajah | Reading | Tree | Schoolyard | Null |
Sivarajah | Writing | Tree | Schoolyard | Positive |
Tallis | Math | Agriculture | Schoolyard | Null |
Tallis | Math | Agriculture | 500 m | Null |
Tallis | Math | Agriculture | 1000 m | Null |
Tallis | Math | Greenness | Schoolyard | Null |
Tallis | Math | Greenness | 500 m | Null |
Tallis | Math | Greenness | 1000 m | Null |
Tallis | Math | Tree | Schoolyard | Null |
Tallis | Math | Tree | 500 m | Null |
Tallis | Math | Tree | 1000 m | Null |
Tallis | Reading | Agriculture | Schoolyard | Null |
Tallis | Reading | Agriculture | 500 m | Null |
Tallis | Reading | Agriculture | 1000 m | Null |
Tallis | Reading | Greenness | Schoolyard | Null |
Tallis | Reading | Greenness | 500 m | Null |
Tallis | Reading | Greenness | 1000 m | Null |
Tallis | Reading | Tree | Schoolyard | Null |
Tallis | Reading | Tree | 500 m | Null |
Tallis | Reading | Tree | 1000 m | Null |
Tallis | Writing | Agriculture | Schoolyard | Null |
Tallis | Writing | Agriculture | 500 m | Null |
Tallis | Writing | Agriculture | 1000 m | Null |
Tallis | Writing | Greenness | Schoolyard | Null |
Tallis | Writing | Greenness | 500 m | Null |
Tallis | Writing | Greenness | 1000 m | Null |
Tallis | Writing | Tree | Schoolyard | Null |
Tallis | Writing | Tree | 500 m | Null |
Tallis | Writing | Tree | 1000 m | Null |
Wu | Math | Greenness | 500 m | Positive |
Wu | Math | Greenness | 250 m | Positive |
Wu | Math | Greenness | 2000 m | Null |
Wu | Math | Greenness | 1000 m | Positive |
Wu | Reading | Greenness | 500 m | Null |
Wu | Reading | Greenness | 250 m | Positive |
Wu | Reading | Greenness | 2000 m | Null |
Wu | Reading | Greenness | 1000 m | Null |
Wu | Reading | Greenness | 1000 m | Null |
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Bias Category | Biases Identified |
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Study design |
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Confounding |
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Statistics |
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Exposure assessment (for geospatial studies that rely on large datasets to measure green space) |
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Citation | Sample Size | Geographic Context | Grade Level and Age | Green Space Measure(s) | Academic Outcome |
---|---|---|---|---|---|
Observational (n = 12) | |||||
Beere & Kingham (2017) [47] | 838 public schools | Cities in New Zealand | 1–6th (6–12 years old 1) | Tree cover from a local land cover database (resolution not reported) from one year on school parcel and in attendance zone | Math, reading, and writing standardized test scores |
Browning et al., 2018 [58] | 404 public schools | Chicago, Illinois, United States | 3rd (8 or 9 years old) | NDVI-derived greenness from MODIS (250 m resolution) over six years in spring, summer and fall (March, July, October) at 250, 500, 1000, and 3000 m radial buffers | Math and reading standardized test scores |
Hodson & Sander (2017) [55] | 222 public schools | Twin Cities, Minnesota, United States | 3rd (8 or 9 years old) | Grass, shrub, and tree cover from NLCD (30 m resolution) in one year on school parcel and in attendance zone | Math and reading standardized test scores |
Kuo et al., 2018 [28] | 318 public schools | Chicago, Illinois, United States | 3rd (8 or 9 years old) | Grass/shrub and tree cover from UTC (0.6 m resolution) in one year on school parcel and in attendance zone | Math and reading standardized test scores |
Kweon et al., 2017 [54] | 219 public schools | Washington, D.C., United States | 2–10th (7 to 16 years old) | Grass/shrub and tree cover from UTC (0.6 m resolution) in one year on school parcel | Math and reading standardized test scores |
Leung et al., 2019 [59] | 3054 public schools | Massachusetts, United States | 3–10th (ages 8–16) | NDVI-derived greenness from MODIS (250 m resolution) over eight years in spring and fall at 250, 500, 1000, and 2000 m radial buffers; Green land cover from a local database (0.5 m resolution) in one year at 250, 500, 1000, 2000 m radial buffers | Math and reading standardized test scores |
Li et al., 2019 [60] | 624 public schools | Illinois, United States | 9–12th (ages 14–18) | Tree canopy cover from NLCD (30 m resolution) in one year at 400, 800, 1600, 3200, and 4800 m radial buffers | American College Test (ACT), a standardized test administered at the end of high school to evaluate preparation for college, which includes math, reading, and science; End-of-semester grades as determined by percent of students on-track for college with no more than one “F” letter grade after at least ten semesters of high school |
Markevych et al., 2018 [51] | 2429 students | Munich and Wesel areas, Germany | NR (age 10 and age 15) | NDVI-derived greenness from MODIS (250 m resolution) over eight years in summer months (May to August) at 500 and 1000 m radial buffers; Tree cover from Copernicus (20 m resolution) [62] at 500 and 1000 m radial buffers; Green land cover from local land use dataset for one year | Math and reading standardized test scores |
Matsuoka, 2010 [48] | 101 public schools | Southeast Michigan, United States | 9–12th (ages 14–18) | Green view from cafeteria window; Grass cover on school parcel from aerial imagery | Michigan college preparatory exam for high school students; End-of-semester grades as determined by graduation rates, which require minimum letter grade average [63] |
Sivajarah et al., 2018 [61] | 387 public schools | Toronto, Ontario, Canada | 3th and 6th (ages 8–9 and 11–12) | Tree canopy cover from UTC (0.6 m resolution) in one year on the school parcel; Number tree species and biodiversity from tree inventory | Math, reading, and writing standardized test scores |
Tallis et al., 2018 [53] | 495 public schools | California, United States | 5th (ages 10–11) | NDVI-derived greenness and agricultural cover from NAIP (1 m resolution) in one year in summer at 50, 100, 300, 500, 750, and 1000 m radial buffers | Composite index of math, reading, and writing standardized test scores |
Wu et al., 2014 [52] | 6333 public schools | Massachusetts, United States | 3rd (8 or 9 years old) | NDVI-derived greenness from MODIS (250 m resolution) over six years in spring, summer and fall (March, July, October) at 250, 500, 1000, and 3000 m radial buffers | Math and reading standardized test scores |
Experimental (n = 1) | |||||
Benfield et al. (2015) [49] | 567 students | University in Pennsylvania, United States | College (age M = 18.9, SD = 1.57) | Green view vs. fogged view (no view but daylight present) from classroom windows | End-of-semester grades |
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Browning, M.H.E.M.; Rigolon, A. School Green Space and Its Impact on Academic Performance: A Systematic Literature Review. Int. J. Environ. Res. Public Health 2019, 16, 429. https://doi.org/10.3390/ijerph16030429
Browning MHEM, Rigolon A. School Green Space and Its Impact on Academic Performance: A Systematic Literature Review. International Journal of Environmental Research and Public Health. 2019; 16(3):429. https://doi.org/10.3390/ijerph16030429
Chicago/Turabian StyleBrowning, Matthew H. E. M., and Alessandro Rigolon. 2019. "School Green Space and Its Impact on Academic Performance: A Systematic Literature Review" International Journal of Environmental Research and Public Health 16, no. 3: 429. https://doi.org/10.3390/ijerph16030429
APA StyleBrowning, M. H. E. M., & Rigolon, A. (2019). School Green Space and Its Impact on Academic Performance: A Systematic Literature Review. International Journal of Environmental Research and Public Health, 16(3), 429. https://doi.org/10.3390/ijerph16030429