Campus score: Measuring university campus qualities

Landscape and Urban Planning 158 (2016) 166–176

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Research Paper

Campus score: Measuring university campus qualities Amir Hajrasouliha City and Regional Planning Department, Cal Poly State University, San Luis Obispo, CA, United States

h i g h l i g h t s • Physical campus characteristics can impact student satisfaction and academic performance. • Campus Score is proposed, representing campus urbanism, greenness, and on-campus living. • Campus Score has significant associations with freshman retention and graduation rates.

a r t i c l e

i n f o

Article history: Received 7 September 2015 Received in revised form 19 October 2016 Accepted 30 October 2016 Keywords: Campus score Freshman retention Graduation rate University ranking Campus design Campus planning

a b s t r a c t This research proposes an index, called Campus Score, which measures the main physical qualities of university campuses. Campus Score is composed of three latent variables representing Urbanism, Greenness, and On-Campus Living, with 10 indicators. This index has been calculated for 103 research-intensive universities in the United States of America. Two linear regressions show that Campus Score has significant associations with freshman retention and 6-year graduation rates. It is also interesting to note that, compared to the Academic Ranking of World Universities (Shanghai Ranking), Campus Score has stronger associations with freshman retention and graduation rates. The one-way ANOVA test and post-hoc analysis reveal that private universities, on average, have significantly higher Campus Scores than public universities, Research I universities have significantly higher mean scores than Research II universities, and universities in the Northeast census region have significantly higher mean scores than universities in other census regions. Exploring the relationships between Campus Score and university objectives, such as student satisfaction, safety, and campus sustainability, can give campus planners fresh insight into the impacts of campus form. © 2016 Elsevier B.V. All rights reserved.

1. Introduction The United States of America has a rich history of campus planning and design. Some of the best university campuses in the U.S. were almost fully developed in the 19th century and early 20th century. Before World War II, campus designers would follow certain formal typologies such as the quadrangle campus (e.g., University of Washington in Seattle), picturesque campus (e.g., University of Vermont), or Beaux-Arts campus (e.g., Columbia University). After World War II, with the vast expansion of university campuses, the emphasis was more on the design of freestanding buildings than on campus master plans (Coulson, Roberts, & Taylor, 2010; Dober, 1996; Turner, 1984). In recent years, most universities have re-embraced the idea of campus master plans to address their institutional objectives, such as attracting more students, increasing the quality of life of current students and faculty, promoting a learning

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and research environment, creating a sustainable environment, and benefiting the surrounding communities (Chapman, 2006; Coulson et al., 2010, 2014 ; Delbanco, 2014; Disterheft, Caeiro, Azeiteiro, & Leal Filho, 2014; Dober, 1996; Kenney, Dumont, & Kenney, 2005; Mitchell & Vest, 2007; Strange & Banning, 2001; Turner, 1984). Although campus planning and design have received extensive attention in the profession in recent years, academia has contributed little. However, evidence-based research to quantify the campus qualities that are at the center of practitioners’ interest would fill a considerable gap in the field. Many attempts have been made in the fields of urban planning, landscape architecture, and architecture to quantify the characteristics of built environments and to evaluate their impact on a wide range of environmental, behavioral, and economic variables. For example, urban sprawl development can be quantified on different scales, and its impacts on travel behavior, housing affordability, and public health have been assessed by many researchers (Custinger & Galster, 2006; Ewing, Pendall, & Chen, 2003; Hajrasouliha & Hamidi, 2016). Using Space Syntax techniques, the morphology

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of street networks can be quantified, and their relationship with both walkability and land use are well-studied research topics (Hajrasouliha & Yin, 2015; Hillier, 2007, 2009). Certain urban form variables, such as urban density, land use diversity, and street connectivity, are quantified in the transportation planning field to assess the impact of built environment qualities on travel behavior (Cervero and Kockelman, 1997; Cervero and Murakami, 2010; Ewing and Cervero, 2010; Frank et al., 2006). Urban design qualities are also quantified, and their impact on pedestrian activities is assessed (De Nisco & Warnaby, 2014; Ewing et al., 2013; Ewing & Handy, 2009; Ewing, Hajrasouliha, Neckerman, Purciel-Hill, & Green, 2015). Finally, measuring greenness (Gupta, Kumar, Pathan, & Sharma, 2012; Yao, Liu, Wang, Yin, & Han, 2014) enables a better understanding of the role of urban greenness areas in public health. Together, these cited studies suggest that single-use, lowdensity land development, disconnected street networks, and low neighborhood greenness are characteristics positively associated with auto dependence and negatively associated with air quality, walking, transit use, and physical and mental health. However, the idea of campus is unique. A university campus is not a city, a neighborhood, or a block. Therefore, describing and analyzing campus forms should be different. The missions, objectives, and governance of institutions of higher learning are not comparable to those of neighborhoods or cities. One of the most obvious distinctions between a campus and a neighborhood is in its primary purpose of providing a supportive environment for learning. EDUCAUSE, the Society for College and University Planning (SCUP), and the PKAL Learning Spaces Collaboratory have aimed to identify assessment metrics, predictive evidence, and illustrative cases that relate space to learning. Among the common insights that have emerged from these efforts are the realizations that experiential learning enhances student engagement and engaging study behaviors fosters learning (Azevedo, 2015; Gilboy, Heinerichs, & Pazzaglia, 2015). However, these works focus more on classrooms and teaching environments (micro-scale design) and less on the contextual condition of the campus environment (macro-scale design). Yet, some studies show that certain macro-scale campus qualities can have impact on students’ quality of life and academic performance as well. For example, studies have indicated that the presence of green spaces on campus, along with the perception of greenness and restorative environment (Kaplan, 1992) of a campus are associated with student quality of life (Felsten, 2009; Hipp, Gulwadi, Alves, & Sequeira, 2016). One of the potential impacts of the physical characteristics of the campus on students’ quality of life is helping them to cope with college life and to manage challenges of academic life (Dyson & Renk, 2006). A green campus may create a pleasant college experience and encourage students to spend time and socialize on campus, thus reducing their mental fatigue level. At the same time, an urban-feeling campus may increase students’ perception of social connectedness. Previous studies have shown both greenness and social connectedness to be associated with student retention (Berger & Braxton, 1998; Lounsbury & DeNeui, 1995; Naretto 1995; Styron 2010). With the goal of identifying an assessment metric, this research has generated an index, named Campus Score, by measuring physical campus qualities that may be associated with students’ retention rate and academic performance. Quantifying physical campus qualities is an attempt to answer the critical questions, “Does campus matter?” and “Which qualities of campus matter most in students’ retention and graduation?” This approach can also help to determine the relationships between campus qualities (Campus Score) and other university characteristics such as age, type, urbanization of setting, region, climate, and academic ranking. Two studies help to establish the specific conceptual foundation of this article. The first study (Hajrasouliha, 2015), through a content analysis of 50 campus master plans, conceptualized seven

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dimensions of campus form. The second study (Hajrasouliha & Ewing, 2016) operationalized the proposed campus form dimensions and assessed their relationship with the freshman retention and 6-year graduation rates for 103 research-intensive universities in the United States. That study determines the significance of the relationship between the physical campus and student satisfaction with college life, and ultimately with academic performance. One of the main differences between Hajrasouliha and Ewing (2016) research and other evidence-based studies on this subject is the scale of analysis. Most previous studies are focused on micro-scale design characteristics of the campus environment and its relationship with learning and engagement. In contrast, following X and Y, this study focuses on the contextual and macro-scale design characteristics of the physical campus. These relationships have seldom been explored. Brief summaries of both studies follow: 1.1. The morphology of the “well-designed campus” In order to construct a theoretical framework for analyzing campus form, a content analysis of 50 randomly selected university campus master plans in the United States was conducted by Hajrasouliha (2015). The analysis shows significant similarities between plans in terms of challenges, objectives, and recommendations. To avoid a subjective definition of the “well designed” campus, the top 100 common recommendations in the selected master plans were identified. Accordingly, from these recommendations, seven dimensions of campus form were inferred, as suggested in Table 1. According to these morphological dimensions, the “welldesigned” campus was conceptualized as a mixed, compact, well-connected, well-structured, inhabited, green campus in an urbanized setting (see Fig. 1). These dimensions are measurable; therefore, it is possible to quantitatively test their relationship to the desired outcomes. 1.2. The relationship of campus design with student retention and degree attainment Hajrasouliha and Ewing (2016) hypothesized that the physical campus has impact on students’ satisfaction with their college experience and their overall academic performance. To test this, they operationalized the seven morphological dimensions of campus as described in Table 1. Five dimensions were operationalized quantitatively with one or more variables. However, land use organization and spatial configuration, were rated qualitatively. A Structural Equation Model, illustrated in Fig. 2, was used in that analysis. After controlling for student selectivity, university resources, student profile and type of institution, data from 103 U.S. research universities showed strong positive associations between student retention and graduation rates and three campus qualities: Campus Living, Greenness, and Urbanism (a composite variable from dimensions of compactness, connectivity and context). Significant associations between the outcome variables and two other campus qualities, land use organization and spatial configuration, were not detected. Furthermore, no significant association between a set of control variables (age of university, campus size, affordability of education, city economic status, climate index, safety, and the degree of urbanization of setting) and student retention and graduation rates was detected (see Table 2). 2. Methods Two steps are essential to generating an index that can quantify campus qualities: adopting a theoretical framework for describing and analyzing campus form, and identifying campus form qualities that have significant associations with university objectives of

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Table 1 Operationalizing the Campus Morphological Dimensions. Description

Scale

Data Source

(1) Land Use Organization Dimension

Land use mix

Rating land use organization on campus between 1 and 10, by analyzing campus land-use maps, downloaded from universities’ website. 10 = All uses are mixed on campus, however the major athletic fields, greenhouses, barns and surface parking areas are not located at the campus core. 5 = land use is neither mixed nor segregated. For example, campus housing is located far from the campus core, but other teaching, research, and recreational uses are located in the campus core. 1 = campus has segregated areas away from the campus core for sport, research, residence, and some academic disciplines.

Campus land-use map, downloaded from universities’ website, The researcher’s rating.a

(2) Compactness Dimension

Mass Density

Computing the total area of building footprints divided by campus areab . Note that “campus area” is not considered as the total land owned by the university. The area of the undeveloped lands, the agricultural lands, and the scattered low-density service facilities on the periphery of campus are not calculated. This calculation process for the multi-patch campuses is the same as uni-patch campuses. Conducting average nearest neighborhood distance tool in ArcGIS. The input data are building footprints.

OpenStreetMap, Google Earth images

Proximity

OpenStreetMap, Google Earth images NLCD2011 OpenStreetMap, Google Earth images

Pervious open spaces Surface parking

Computing the percentage of pervious open spaces in a quarter mile buffer around campus buildings. Computing the total area of surface parking divided by the campus area. Rooftop parking and parking structures are not included.

Campus connectivity

1) Downloading census street lines at the county level 2) Refining the maps according to Google Earth Images 3) Export maps as dxf files from ArcGIS and open it in Depthmap (Space Syntaxd Software) 4) Angular integration analysis with radius of 3, weighted by segment length; 5) Averaging integration values of campus street segments Dividing the average integration value of campus street segments with radius 3 by the average integration value of county street segment with same radius.e

Census Tiger 2010, street lines

Campus centrality

Census Tiger 2010, street lines

(4) Configuration Dimension

Campus spatial structure

Rating the strength of campus spatial structure from 1 to 10. 10 = the entire campus has organized around most of these principles: Buildings are defining open spaces. Campus spaces are connected through main corridors, courtyards, or quads. Campus has a main central space such as a plaza or a lawn, long view corridors with a land mark at the focal point, enclosed open spaces, and the entire master plan is relatively symmetric and geometric. 5 = The campus has neither organized nor disorganized layout. For example, the historical part of campus has a defined spatial structure, but the rest of the campus are free-standing buildings in open, landscaped ground. 1 = the campus has a disorganized layout.

Google Map and Google Earth images, The researcher’s ratingf .

(5) Campus Living Dimension

On-campus living

Computing the percentage of students living on-campus

US News and World Report

(6) Greenness Dimension

Tree canopy Pervious open spaces Surface parking

Computing the average percentage of tree canopy in a quarter mile buffer around campus buildings.g Described under compactness dimensionh Described under compactness dimensioni

NLCD2011

(7) Context Dimension

Activity density

Computing the density of population and employment of all census tracts neighboring the campusj

Land use entropy

Computing land use entropy of all census tracts neighboring the campus. Land use entropy was computed with the formula: Entropy = −[residential share × ln (residential share) + retail share × ln (retail share) + office share × ln (office share)]/LN (3) Computing intersection density of all census tracts neighboring the campus, computed as the number of intersections within all census tracts neighboring the campus divided by the area of census tracts

Longitudinal Employment Household Dynamic 2010Census 2010 LED 2010

Intersection density

Census Tiger 2010, street lines and census tracts

a To test the reliability of this scale, two persons rated 40 campuses. The interrater reliability test shows that this measure is reliable. A two-way mixed effects model was used, where people effects are random and measure effects are fixed. The intraclass correlation coefficient of interrater reliability is 0.865 which is above the acceptable threshold of 0.7. Please note that the two dimensions that have “researcher’s rating” as their source, are the only two dimensions that do not have significant associations with either of the outcome variables. Therefore, these two dimensions are not used in the calculation of Campus Score. b Mapping campus figure-ground in ArcGIS is used to calculate campus mass density. If the GIS file does not exist, the base-map of OpenStreetMap – an openly licensed map of the world – can be used to map main physical features, such as building footprints, and campus core boundary. These maps can be refined according to the Google Earth images to increase the accuracy of the GIS maps. c Note that the quarter mile buffer is generated only around campus buildings and not the sport fields. d Space Syntax is a set of theories and techniques for measuring the spatial configuration of street networks. The basic element in Space Syntax is the street segment between intersections, which can be derived from road center line data. With the help of Depthmap software, developed by Space Syntax., the street segments can be translated into a graph, in which segments and their connections turn into nodes and links. The most commonly used Space Syntax measure is known as integration, which measures “how close each segment is to all others under each definition of distance” (Hillier, 2009). e This measure shows the relative connectivity of campus streets to the county street network. f The interrater reliability test shows that this measure is reliable, with an intraclass correlation coefficient of 0.885. g





TNC = total number of 30 × 30 meter cells in the buffer; TCi = the percentage of tree canopy in a given cell i; “Tree Canoy Percentage” = ni=0 TCi /TNC .

h The percentage of pervious open space is positively related to greenness and negatively related to compactness. As an exogenous variable in SEM, this dimension can be loaded into two different latent variables with generating separate coefficient estimates. i The percentage of surface parking areas is negatively related to both greenness and compactness. j Note that activity density, land use entropy, and intersection density are calculated only for census tracts neighboring the campus with population density more than 100 per square mile. Census tract that contains the core of campus and census tracts with population density less than 100 per square mile are not included.

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(3) Connectivity Dimension

c

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Fig. 1. Campus form dimensions.

high retention and graduation rates. As a first step toward generating Campus Score, the theory of the “well-designed campus” (Hajrasouliha, 2015) has been adopted. For the second step, the three qualities of urbanism, greenness, and campus living have been selected to generate the Campus Score, based on the findings of Hajrasouliha and Ewing (2016). In addition, this study used the same dataset as Hajrasouliha and Ewing (2016). The research population consisted of 206 universities in the United States with high or very high levels of research activity according to the 2010 Carnegie Classification. One hundred and three campuses were randomly selected, stratified by census regions, Northeast, South, Midwest, and West, and type: Research I (very high research activity) and Research II (high research activity). Universities with more than one campus that are formally very different were not selected. The University of Michigan in Ann Arbor was the only case with this quality in the sample, and was there-

fore replaced by another university. Fig. 3 shows the location of the selected campuses in the United States. In order to calculate Campus Score, a composite score was developed from the three latent variables of Urbanism, Greenness, and Campus Living (see Fig. 2). These three latent variables were first standardized with a mean of 0 and a standard deviation of 1. The composite score is generated with the following formula: CampusScore = 0.177 × Urban + 0.215 × Green + 0.251 × Living The multipliers are the standardized regression weights on freshman retention rate, obtained from modeling freshman retention rate with maximum likelihood estimation (see Hajrasouliha & Ewing, 2016). For ease of interpretation, the overall score and latent variables were converted to have a mean of 100 with variance of 50.

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Fig. 2. Modeling student retention and graduation rates.

Table 2 Control variables and their data source. Variable

Proxy Variable

Data Source

University Resources

Percentage of classes with fewer than 20 students the average faculty pay SAT Score Year founded Campus Size Public, Private for-Profit, Private not-for-profit Research II (high research activities), Research I (very high research activities) Enrollment Profile Classification 2010 0 = (Not classified) 1 = ExU2: Exclusively undergraduate two-year 2 = ExU4: Exclusively undergraduate four-year 3 = VHU: Very high undergraduate 4 = HU: High undergraduate 5 = MU: Majority undergraduate 6 = MGP: Majority graduate/professional 7 = ExGP: Exclusively graduate or professional 0,1,2, and 7 are not in the samples Percentage of undergraduate enrollment: the total number of undergraduates divided by the total number of students Average total indebtedness of 2013 graduating class The median household income of city 2013 the total cooling days of city in 2014 the total heating days of city in 2014 Crime rate of City in 2013 4 = City 3 = Suburban 2 = Town 1 = Rural

US News and World Report American Association of University Professors (AAUP) College Navigator US News and World Report OpenStreetMap refined by Google Earth images Carnegie Classification 2010 Carnegie Classification 2010

Student Selectivity Age of university Campus Size Type of Institution

Student Profile

Affordability of Education City Economic Status Climate Index Safety The degree of urbanization of setting

Next, the predictive power of the Campus Score was tested for student retention and graduation rates. Two linear regression analyses were conducted. First, the freshman retention rate was modeled with Campus Score and the same control variables as in the Hajrasouliha and Ewing (2016) study: the average SAT score, the percentage of classes with fewer than 20 students, university type (Research I or II), and the total number of undergraduates. Second, the 6-year graduation rate was modeled with the freshman retention rate and Campus Score. None of the other control variables was significant in this model.

Carnegie Classification 2010

US News and World Report US News and World Report Census Bureau NOAA’s National Climatic Data Center NOAA’s National Climatic Data Center FBI Uniform Crime Reports Carnegie Classification 2010

3. Results The final rankings of all 103 campuses with their scores are presented in Table 3.

3.1. The relationship of campus score with student retention and graduation rates Scatter plots (see Fig. 4) suggest strong quadratic relationships between both Campus Score and freshman retention rate and Cam-

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Table 3 Ranking 103 research universities based on their Campus Score. Rank

University Name

Urban Score

Green Score

Living Score

Campus Score (Composite score)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76

Columbia University Princeton University Lehigh University Duke University Emory University Boston University Stanford University Yale University College of William & Mary Clarkson University Case Western Reserve University Brandeis University University of Connecticut Fordham University New York University Washington University in St. Louis University of Notre Dame Syracuse University Rice University Cornell University U of Massachusetts Amherst U of New Hampshire, Main Campus Binghamton University Tufts University University of Dayton University of Virginia, Main Campus University of Vermont University of California, Los Angeles University at Albany, SUNY University of Rhode Island Miami University Illinois Institute of Technology Georgia Institute of Technology U of California, Santa Barbara Carnegie Mellon University University of Denver University of Maryland, College Park U of Illinois at Urbana Champaign University of Maine North Carolina State University Pennsylvania State University University of Florida University of California, San Jose George Mason University University of California, Irvine Indiana University Bloomington Ball State University Portland State University U of North Carolina at Greensboro University of Wisconsin, Madison Missouri University of Science Drexel University Oklahoma State U, Stillwater Bowling Green State University Temple University University of Washington, Seattle University of California, Davis San Diego State University University of Tennessee U of Cincinnati, Main Campus Texas A&M University University of Iowa Ohio State University, Main Campus Southern Illinois University University of Kansas University of Oregon University of Alabama Virginia Commonwealth University University of Colorado Boulder University of Memphis Rutgers–Newark Kansas State University University of California, Riverside University of Wyoming Idaho State University University of Minnesota, Twin Cities

248.84 100.17 97.86 63.93 69.06 200.79 106.34 153.21 36.62 15.08 112.79 82.29 35.84 204.34 310.10 132.01 93.06 122.25 130.59 52.27 42.95 41.27 48.26 159.42 87.30 72.44 81.49 137.01 55.85 38.80 68.41 134.05 151.54 75.58 149.96 129.23 75.96 102.53 33.93 55.92 77.73 69.70 82.61 53.84 90.93 87.43 77.55 157.20 120.11 104.34 76.43 194.81 84.26 69.46 216.54 118.37 90.52 176.84 96.20 144.93 70.97 72.43 128.05 28.34 65.95 116.40 71.37 157.57 84.91 63.79 193.58 71.47 73.78 78.16 70.28 113.66

93.52 187.36 219.43 193.08 223.07 89.84 126.42 86.96 217.00 209.99 91.77 140.63 195.96 91.97 29.44 94.16 119.44 98.13 89.93 186.92 172.06 187.75 177.14 75.27 111.31 178.72 135.88 108.46 124.54 174.15 139.63 51.03 51.06 147.91 85.60 84.81 130.28 91.64 162.83 170.70 126.18 166.82 98.25 161.37 90.51 129.61 105.58 47.12 91.80 119.54 95.94 38.92 80.41 90.64 33.31 99.23 113.24 61.56 75.07 69.69 119.06 114.62 65.56 134.80 114.80 83.78 105.51 34.70 83.43 134.88 37.36 96.94 79.83 94.71 63.41 61.54

216.79 223.12 161.89 191.45 159.78 176.67 210.45 202.01 172.45 193.56 206.23 185.12 170.33 138.66 117.55 183.00 187.23 176.67 168.22 134.44 153.44 140.77 142.89 151.33 170.33 104.88 123.88 100.66 142.89 111.21 117.55 142.89 128.11 98.54 98.54 113.32 111.21 123.88 102.77 75.32 96.43 66.87 113.32 75.32 109.10 77.43 104.88 98.54 85.88 71.10 109.10 73.21 113.32 111.21 56.31 68.98 71.10 52.09 96.43 62.65 71.10 71.10 73.21 83.76 71.10 60.54 73.21 71.10 77.43 45.76 37.31 71.10 83.76 66.87 98.54 66.87

238.25 226.66 204.03 193.20 191.68 188.92 187.96 182.08 181.83 181.79 169.19 168.70 168.61 167.37 167.32 164.32 163.30 158.04 151.91 148.11 147.92 147.66 146.34 146.08 145.45 133.81 126.58 121.74 120.96 120.19 118.68 115.95 114.41 114.30 113.71 113.38 112.92 111.83 106.39 103.07 102.02 101.75 99.72 97.02 96.53 96.12 96.05 95.89 95.54 94.18 92.96 92.16 90.69 88.27 88.09 88.03 84.49 82.96 82.35 79.77 78.87 77.09 76.65 76.37 74.27 73.27 72.97 71.71 69.69 68.09 67.80 66.97 66.75 66.07 65.63 63.91

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A. Hajrasouliha / Landscape and Urban Planning 158 (2016) 166–176

Table 3 (Continued) Rank

University Name

Urban Score

Green Score

Living Score

Campus Score (Composite score)

77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103

Auburn University, Main Campus Colorado State University Brigham Young University Northern Arizona University Cleveland State University Louisiana State University University of North Dakota University of Illinois at Chicago University of Wisconsin, Milwaukee University of Alaska Fairbanks Oregon State University University of Louisville Utah State University University of Akron, Main Campus Arizona State University, Tempe University of Utah University of North Texas University of Missouri, Kansas University of Missouri, St. Louis Indiana University, Purdue U University of Houston New Mexico State U, Main Campus Wayne State University University of Texas at San Antonio University of Texas at Arlington University of Colorado Denver University of Nevada, Las Vegas

57.96 79.57 107.16 73.85 197.32 53.22 74.56 158.17 122.07 43.55 71.76 100.04 76.44 135.60 103.29 72.93 63.61 120.36 67.64 114.46 110.98 53.13 130.37 32.94 78.95 118.89 121.34

111.08 82.53 74.08 67.77 22.00 101.11 77.17 25.50 53.82 90.79 83.72 40.56 90.88 36.27 37.79 83.16 74.08 51.25 91.95 48.00 29.67 68.82 9.73 101.29 41.56 22.05 17.87

62.65 71.10 58.43 85.88 37.31 71.10 75.32 54.20 52.09 75.32 58.43 75.32 45.76 47.87 66.87 45.76 58.43 35.20 37.31 39.42 56.31 56.31 39.42 28.87 41.53 28.87 28.87

63.22 62.73 62.45 61.52 61.07 61.03 60.24 56.14 54.02 53.72 51.76 51.68 49.69 47.81 46.22 43.88 42.81 41.04 40.91 39.30 38.49 33.85 25.51 24.98 21.11 20.33 19.15

pus Score and 6-year graduation rate. Campus Score has a skewed distribution; therefore, natural log transformation was conducted on Campus Score before exploring its predictive power. The first linear regression model had an adjusted R2 of 0.802, and all coefficient estimates were significant at 0.05 or beyond. The unstandardized coefficient of Campus Score was 6.893, and the standardized coefficient was 0.414. This means that a 1% increase in Campus Score is related to an increased freshman retention rate of 0.0689. The second model had an adjusted R2 of 0.917, and all coefficient estimates were significant at 0.001. The unstandardized coefficient of the freshman retention rate was 1.483, and standardized coefficient was 0.745. The unstandardized coefficient of the

natural log-transformed Campus Score was 8.989, and standardized coefficient was 0.271. This means that a 1% increase in Campus Score is related to an increased 6-year graduation rate of 0.0899. No multicollinearity or outlier impact has been detected in these models. 3.2. The relationship of campus score with the external factors: age, urbanization of setting, climate, region, and academic ranking Fifteen external factors such as university resources, affordability, safety, and campus size are considered in modeling Campus Score (see Table 2). Only four present statistically significant asso-

Fig. 3. Distribution of the selected campuses.

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Fig. 4. Left: Scatter plot. X: Campus Score, Y: Freshman Retention Rate. R2 = 0.530; Scatter plot. X: Campus Score, Y: 6-Year Graduation Rate. R2 = 0.663.

Table 4 The relationship of Campus Score and the age of campus and the urbanization of setting. Gray cell indicates that the mean of a given group is significantly higher than other groups. Frequency

Mean of Urban Score

Mean of Green Score

Mean of Living Score

Mean of Campus Score

Age of campus Pre Civil War 1800s, Post Civil War 1900s, Pre WWII Post WWII Total

40 35 14 14 103

103.78 94.10 103.72 100.20 100

119.36 91.4089 83.6265 82.5194 100

122.77 90.64 80.74 77.58 100

126.87 86.65 80.39 76.18 100

Setting City Large City Midsize City Small Suburb Large Suburb Midsize and Small Town and Rural Total

34 16 25 13 8 7 103

138.92 102.62 79.65 82.70 52.85 63.57 100

66.78 89.24 113.25 137.85 145.68 116.06 100

86.99 95.37 92.97 142.23 107.51 111.81 100

91.04 92.33 93.59 139.94 108.57 99.92 100

ciations with student retention and graduation rates (see Fig. 2). However, ANOVA test and Post-hoc analysis show that pre-Civil War campuses have a statistically higher mean Campus Score compared to newer campuses (see Table 4). Comparing the means of Urban, Green, and Living Scores reveals that the difference between historic campuses (pre Civil War) and newer campuses is mainly due to their high Living Score. Commuter campuses became more prevalent in the twentieth century, quite possibly explaining the lower Living Score of the newer campuses. Although campuses in large suburbs generally have a higher Campus Score, there is no statistically significant difference in Campus Score for different urbanization settings. However, as expected, campuses in large cities have a significantly higher Urban Score, and suburban campuses have significantly higher Green and Living Scores. Climate is an interesting external factor. When investigating its impact on Campus Score the first question that comes to mind is whether it makes sense to compare the greenness of a campus in the northeast region with, for example, a desert campus in Arizona or Nevada. Is a different degree of greenness required for optimum satisfaction in various climates? Perhaps. Nevertheless, although many studies have found associations between mental and physical health and greenness, there is no study to test these associations across different climates. However, from this sample of 103 campuses only four are in a desert or semi-arid climate (Table 5). The sample size of desert campuses is thus too small to test any modification in the definition of greenness or weighting by climate.

Fig. 5. Means of Campus Score for each census region and university type.

Interestingly, a closer look at these four campuses shows that their Green Scores are low, but they are not necessarily the l“east green campuses. Except for one case, their overall Campus Score ranking is lower than their Green Score ranking. The distribution of campuses with higher scores is not geographically consistent. The one-way ANOVA test of means and Post-hoc analysis reveal large and significant differences between

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Fig. 6. a: Scatter Plot of Campus Score Ranking and Shanghai Ranking, R2 = 0.125; b: Scatter Plot of Campus Score Ranking and Freshman Retention Rate, R2 = 0.539; c: Scatter Plot of Shanghai Ranking and Freshman Retention Rate, R2 = 0.464; d: Scatter Plot of Campus Score Ranking and Graduation Rate, R2 = 0.661; e: Scatter Plot of Shanghai Ranking and Graduation Rate, R2 = 0.427.

Table 5 Campuses in desert and semi-arid climate, their Green Score, and Campus Score. Campuses in desert and semi-arid climate

Rank of Green Score

Green Score

Rank of Campus Score

Campus Score

New Mexico State University Northern Arizona University Arizona State University, Tempe University of Nevada, Las Vegas

77 78 92 102

68.82 67.77 37.79 17.87

98 80 91 103

33.85 61.52 46.22 19.15

the means of Northeast campuses and campuses in the other three census regions. The mean Campus Score for Northeast universities is 149.03, while only 85.65 for the Midwest and 91.16 for the West. The lowest mean Campus Score is 75.91 for Southern universities. The high mean score for the Northeast may driven by the built environment that is in general more urbanized, the universities that are the most historic and well-established in the country and their long tradition of on-campus housing. Significant difference was also found using a one-way ANOVA between the mean Campus Score for

Research I universities (112.32) and Research II Universities (86.41) and between Campus Score for private universities (161.68) for public universities (80.23). Fig. 5 shows the means plot of Campus Scores stratified by type and region. The highest mean belongs to Northeast Research I universities with 163.02, and the lowest mean belongs to South Research II with 62.79. The relationship of Campus Score with a well-known university quality index, Academic Ranking of World Universities, also known as the Shanghai Ranking (as a proxy for academic and research

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Fig. 7. standardized values of morphological dimensions of University of Utah’s Campus based on the total samples (left) and just Research I universities in the West region (right).

performance) was also investigated. The Shanghai Ranking is conducted by researchers at the Center for World-Class Universities of Shanghai Jiao Tong University (CWCU). This index considers Nobel prizes, Fields medalists, highly cited researchers, and papers published in Nature or Science. Out of the 103 universities in this sample, 73 were ranked among the top 500 universities in the world. Bivariate correlation was conducted between Shanghai Ranking and the ranking based on Campus Score. This resulted in a correlation coefficient of 0.35, significant at the 0.01 level. Yet, as Fig. 6 reveals, rankings based on Campus Score have a stronger association with freshman retention rate and graduation rate than the Shanghai Ranking. The relationship of other commercial rankings such as that of U.S. News and World Report with retention and graduation rates is not relevant to this study, since retention and graduation rates are the main indicators of their rankings.

phological dimensions of the University of Utah’s campus based on the total sample (left) and Research I universities in the West region (right). Positive values are above the mean and negative values are below the mean. Fig. 7 shows that the biggest strength of the University of Utah’s campus is ‘high percentage of land covered by tree canopy,’ and its biggest weaknesses are qualities such as “high percentage of land covered by surface parking areas,” “low campus mass density,” and “low percentage of students living on campus.” Recognizing the strengths and weaknesses of a campus can also help physical planners to identify the main opportunities and threats. Such quantitative metrics provide a helpful starting point for campus design assessments, but they are less reliable as measures of what is needed in the future. Qualitative data gathered through individual and group interviews would constitute a complementary analysis to establish a clear picture of user needs and identify critical campus projects for optimal efficiency.

4. Discussion: the application of campus score for campus planners

5. Conclusions

Exploring the relationships between Campus Score and desired outcomes, such as student satisfaction, safety, and campus sustainability, can give campus planners fresh insight into the possible impacts of campus form. In addition, quantifying dimensions of campus form can inform campus planners about the norms of campus design for different university types in different census regions. For example, the percentage of surface parking areas or the percentage of pervious surfaces of one campus can be compared to the mean value of these variables for similar institutions. However, first and foremost, Campus Score can inform campus planners about how their campus compares to peers. For example, the University of Utah’s ranking is 93 out of 103 campuses. By looking at its three scores on Urban, Green, and Living, it becomes clear why the University of Utah has such a low rank: its Urban Score is 73, its Green Score is 83, and its Living Score is 46. As a reminder, note that the mean value of scores for all samples is 100. Although all three scores are below average, the Living Score is considerably low. In addition, note that the three scores are computed from 10 campus-form variables (see Table 1). Therefore, for more detailed analysis, one can compare the value of these 10 variables for the University of Utah to the mean of all samples. Fig. 7 shows standardized values of mor-

The biggest limitation of this research is data availability. Although data on institutional characteristics are diverse and relatively accessible, very little information on the built environment characteristics of university campuses is available. Information such as building height and architectural quality of campus buildings is not publicly available and therefore not included in this research. Moreover, the administrative policies of universities can have a critical impact on the achievement of different institutional objectives. Proxies such as “type of institution” or “enrollment profile” cannot fully represent the complexity of administrative policies in addressing institutional missions. Universities in the Northeast census region have significantly higher mean scores than universities in other census regions, but this may not be because of the eminence of their institutions; it may be related to the type of urbanism in that region and, most importantly, the age of the campuses. Most campuses in that region were almost fully developed before the mid-20th century when the mode of campus planning was to follow certain established formal typologies rather than be dominated by auto-oriented development patterns and star architects. However, not all universities in the northeast region have high Campus Scores. For example, the

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Rutgers campus ranking is only 71, and seven of the top 20 campuses are not in the northeast: Emory University (rank 5), Stanford University (rank 7), College of William & Mary (rank 9), Case Western Reserve University (rank 11), Washington University in St. Louis (rank 16), University of Notre Dame (rank 17), and Rice University (rank 19). In addition, it is an interesting finding that Campus Score ranking, compared to Shanghai ranking, had stronger associations with freshman retention and graduation rates. This indicates that compared with its overall reputation, an institution’s physical campus qualities may have a stronger impact on student satisfaction and academic performance. Private universities have significantly higher mean scores than public schools, and Research I universities have significantly higher mean scores than Research II universities. This finding may raise certain questions. Primarily, whether campus form has any true influence on freshman retention and 6-year graduation rates, or is it simply that better institutions have better campuses, and physical campus has no true influence on students’ overall satisfaction or graduation rate. While Campus Score had significant associations with freshman retention and graduation rates after controlling for a set of external factors (as described in Table 2), the causal relationship is uncertain. There might be a simple explanation for these relationships. Although it is hard to imagine that one student decides not to continue his or her education solely due to the campus qualities, it is much more likely that a green, urban-feeling, and livable campus provides a “restorative environment” (Kaplan, 1992) for the students where they can reduce their overall level of mental fatigue, and consequently perform better academically. The increased pressure on students for “direct attention” (Stuss & Benson, 1986) leaves them susceptible to fatigue. A well-designed campus can be a fascinating place to be and allows students to rest and enjoy their college life. Taking a short walk in a park-like setting of campus (Green dimension), or visiting coffee shops and galleries adjacent to campus, or simply watching a vital street (Urban dimension) or taking a short nap in an accessible dorm (Living dimension) may have a positive impact on students’ mental health. The perceived restorative qualities of campuses can be measured with self-report rating scales. Therefore, as a subject of future research it would be possible to investigate whether or not the restorative qualities of campuses can explain the observed relationship between Campus Score and retention/graduation rates. Literature suggests that the physical campus should be designed and managed as a restorative environment for students to reduce their mental fatigue and consequently improve their quality of life and academic performance. Accordingly, understanding the potential payoffs for student satisfaction and academic performance is of significant importance when an institution plans its physical campus. In other words, better understanding of these relationships would be of value for campus planners in an evidence-based practice. Campus Score can act as a tool to pave the path for investigation of particular campus design approaches and to identify the effects of investments in specific campus forms/strategies. References Azevedo, R. (2015). Defining and measuring engagement and learning in science: Conceptual, theoretical, methodological, and analytical issues. Educational Psychologist, 50(1), 84–94. Berger, J. B., & Braxton, J. M. (1998). Revising Tinto’s interactionalist theory of student departure through theory elaboration: Examining the role of organizational attributes in the persistence process. Research in Higher Education, 39(2), 103–119. Cervero, R., & Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design. Transportation Research Part D: Transport and Environment, 2(3), 199–219. Cervero, R., & Murakami, J. (2010). Effects of built environments on vehicle miles traveled: Evidence from 370 US urbanized areas. Environment and Planning A, 42(2), 400–418.

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