volume 1, issue 1 august 2011 - tarleton state university€¦ · facilities at tarleton state...
TRANSCRIPT
Volume 1, Issue 1 August 2011
Introduction Video by Dr. Denae Dorris,
Program Manager [PDF script]
THE ACEF JOURNAL
EDITOR – DR. MARK LITTLETON
MANAGING EDITOR – HEATHER R. ORTIZ, M.ED.
NATIONAL REVIEW PANEL MEMBERS
DAVID DAGLEY, PH.D., J.D. EDUCATIONAL LEADERSHIP, POLICY &
TECHNOLOGY STUDIES
UNIVERSITY OF ALABAMA
JUDITH ADKISON, PH. D. COLLEGE OF EDUCATION
UNIVERSITY OF NORTH TEXAS
CARLA THOMPSON, ED. D. PROFESSIONAL AND COMMUNITY LEADERSHIP
UNIVERSITY OF WEST FLORIDA
BRENDA KALLIO, ED. D. DEPARTMENT OF EDUCATIONAL LEADERSHIP
UNIVERSITY OF NORTH DAKOTA
KAYLA PEAK, D. SC. FACULTY-FELLOW-FACULTY INNOVATION IN
TEACHING
TARLETON STATE UNIVERSITY
GORDON GATES, PH. D. DEPARTMENT OF EDUCATION LEADERSHIP &
COUNSELING PSYCHOLOGY
WASHINGTON STATE UNIVERSITY
EDITOR’S MESSAGE: Greetings!
This is the inaugural issue of the ACEF Journal, a
journal dedicated to research on the planning, design,
construction, maintenance, and operation of educational
facilities. Although there is a tremendous amount of very
useful craft knowledge regarding educational facilities,
there are also numerous avenues for that knowledge to
be shared with practitioners and researchers. Yet, there
are few publications dedicated to educational facility
research. We offer the ACEF Journal as a means to share
that research.
Upon occasion, leaders in research on educational
facilities will share their insights in the ACEF Journal.
So, complimentary to the primary dedication to articles
on facility research, at times you will see a section of the
journal dedicated to these prominent scholars. In this
issue, Dr. Tak Chan and Dr. Mike Dishman will share
their views as Featured Scholars on Maintaining a Safe
and Healthy School Environment for Learning. The
other Featured Scholars in this edition are Dr. Glen
Earthman and Dr. Linda Lemasters who offer their
insights on Planning and Implementing a Theory-based
Research Program: The Relationship Between Student
Performance and School Building Conditions, 18 Years
in Development (1993-2011).
In addition to the Featured Scholars, the ACEF Journal
presents two manuscripts dedicated to facility research.
Each manuscript was vetted by a national review panel
of scholars. Indeed, I and the ACEF Staff are grateful for
the hard work of the review panel, and we are very
appreciative of their feedback on the content and quality
of the research and writing. I hope that these
manuscripts spur additional research on educational
facilities, and the impact that facility design,
construction, and maintenance has on student learning.
Sincerely,
Mark Littleton, Director
Texas Center for Educational Facilities
The contents of this journal were developed under a
grant from the Department of Education. However, such
contents do not necessarily represent the policy of the
Department of Education, and you should not assume
endorsement by the Federal Government.
AMERICAN CLEARINGHOUSE ON EDUCATIONAL FACILITIES
INFORM TRAIN ASSIST
In 1998, the U.S. Department of Education
established the Educational Facilities Clearinghouse
(EFC) program to provide information on planning,
design, finance, construction, improvement, and
maintenance of safe, healthy, high performance
schools. In 2010, the Texas Center for Educational
Facilities at Tarleton State University was awarded
the authority to continue the EFC initiative—the
American Clearinghouse on Educational Facilities.
ACEF’s guiding mission is to provide facility
support, training, and resources to public early
childhood schools, K-12 schools, and institutions of
higher education on issues related to educational
facility planning, design, financing, construction,
improvement, operation, and maintenance. ACEF
will provide nationwide leadership in educational
facilities through the ACEF website, social media,
webinars, podcasts, and web-based content delivery lessons. ACEF will collect and disseminate the latest research on effective educational facilities
practices and develop resources regarding the maintenance of safe, healthy, high performance
(green) educational facilities. A few of the ACEF services are: an online clearinghouse with
facility support via email, phone, or live chat; RSS feed, an online nationally refereed journal,
national trainings, on-site facility support visits, distance learning events, and various resource
materials.
Affiliate/Support Organizations: American Association of School Administrators (AASA,
www.aasa.org) and National School Board Association (NSBA, www.nsba.org)
ACEF cordially invites you to visit our website at www.acefacilities.org.
FOLLOW ACEF:
THE ACEF JOURNAL
An Educational Facilities Journal dedicated to the dissemination of research on effective
educational practices regarding the planning, design, construction, improvement, operations, and
maintenance of safe, healthy, high-performing educational facilities.
2011 VOLUME 1, ISSUE 1
COPYRIGHT © 2011
PG # MANUSCRIPT TITLE AUTHOR
5 [Featured Scholar] Maintaining a Safe and Tak Cheung Chan
Healthy School Environment for Learning Mike Dishman
15 [Featured Scholar] The Influence of School Building Glen I. Earthman
Condition on Students and Teachers: Linda K. Lemasters
A Theory-Based Research Program – 1993-2011
39 School Facility Age and Classroom Huston J. Gibson
Technology: The Influence of Stakeholder
Participation in the Technology Planning
Process
51 The Relationships Between the Conditions of Martin G. Sheets
School Facilities and Certain Educational
Outcomes
Tarleton State University is an EEO/AA Employer and Educator
Tarleton State University is an Equal Employment Opportunity and an Affirmative Action Employer and
is committed to excellence through diversity. All qualified applicants will receive consideration for
employment without regard to sex, race, creed, color, age, national origin, religion or physical or mental
disability.
Tak Cheung Chan The ACEF Journal
Mike Dishman Vol. 1, No. 1, 2011, pp. 5-13
5
Maintaining a Safe and Healthy School
Environment for Learning
Abstract
President Obama’s Education Blueprint of March, 2010 pinpointed safety and health conditions
of school facilities as essential elements to improve school learning environment. The Blueprint
concluded with increased flexibility and use of data to target health and safety needs of schools.
This paper explored the current literature about school safety and health environment issues and
discussed how safe and healthy school environment could be created. In addition to budget
constraints, poor design, poor construction, poor supervision, poor maintenance, high abuse,
high vandalism, high maintenance, and high risks are identified as challenges to school safety
and health conditions. Implementation of flexibility and use of data to achieve a safe and
healthy school environment for learning was also discussed.
roviding a safe and healthy school environment is fundamental to student learning. This
is fully documented by Maslow (1943) who identified safety needs and physiological needs
being the basic needs of his Hierarchy of Needs of Human Motivation. However, what is
disturbing is, according to School Facilities: American’s Schools Report Differing Conditions
(Government Accounting Office, 1996), about one-third of the school buildings in the United
States were in extensive repair or replacement conditions. Many of these conditions constitute
clear safety code violations. The same report also found that more than half of U.S. schools have
unsatisfactory environmental conditions. Recent literature has also provided sufficient evidence
that safety and health conditions at school threaten the learning environment of students
(Schneider, Walker, & Sprague, 2000; Tanner & Lackney, 2006). President Obama’s Education
Blueprint particularly pinpoints safety and health conditions of school environment as essential
elements to improve student learning (U.S. Department of Education, 2010a). In support of the
Blueprint, the U.S. Department of Education elaborated the President’s direction to include
increasing flexibility and use of data as essential approaches to target health and safety needs of
schools (U.S. Department of Education, 2010b). It is clear that safe and healthy conditions of
schools have become essential school issues educational leaders need to address expeditiously.
In addition, as educational accountability is becoming more and more demanding, school
leaders, not only are held responsible for the safety and the healthfulness of students in school,
but also are closely scrutinized for how they proactively and reactively respond to safety and
health issues in school.
A Safe and Healthy Environment and Student Learning
Current literature is abundant with documents in support of safe and healthy school
environment for learning. Studies have indicated that most young children were at higher risk of
safety at school than elsewhere (Kelly, 2010; Kingsley, 2000). As reported by Schneider,
Walker, and Sprague (2000), increasing number of students had been killed and injured on
school grounds since 1993. Walker and Eaton-Walker (2000) analyzed that schools encountered
vulnerabilities to their safety and security in four major areas: (a) the design, supervision and
P
Maintaining a Safe and Healthy School
August 2011 / ACEF 6
use of school space; (b) the administrative operations and practices of the school; (c) the
neighborhoods and surrounding environments of the school; and (d) the behavioral
characteristics and histories of the enrolled students. In view of continued crisis in school, to
maintain a safe learning environment, Kerr (2009) formulated a model for school crisis
prevention and intervention to include such components as prevention, preparation, response,
and recovery.
School cleanliness is related to the design and health conditions of the environment as
well as the health of the school building occupants (Tanner & Lackney, 2006). Schmidt (1994)
pointed to floor carpet acting as a sink to collect and entrap soil, micro-organisms, plant and
fungal spores, pollen, chemicals, and other allergens. The U.S. Environmental Protection
Agency (2000) warned that moisture trapped in rooms could become a primary source of
microbial growth which frequently results in adverse human health effects. Dunklee and
Silberman (1991) recommended specific procedures to ensure healthy indoor air quality. The
Responsible Industry for a Sound Environment (1999) focused on the importance of pest control
to maintain a healthy school building. A comprehensive plan was developed by Marx and
Wooley (1998) to lay out steps to create a healthy school environment. In plain language,
Shideler (2001) simply states that a clean school is a healthy school that supports learning.
Creating a Safe School Environment
A safe school environment consists of physical safety and strategic safety. Physical
safety refers to the safety of school buildings that house the students. School buildings continue
to deteriorate as they are aging. The physical conditions of school buildings need to be inspected
on a timely basis to ensure student safety. Daily and periodic checklists have been developed by
Chan and Richardson (2005) to serve as essential tools to detect building deficiencies. No school
leader could afford the consequence of students getting hurt in school as a result of negligence in
school building inspection. School building emergencies need to be reported to School
Maintenance Department immediately. The school safety hotline has to be connected with
School District Security Department, Police Department, Fire Department, and Hospital System
for speedy assistance. To examine the security and fire safety of school buildings, Ornstein,
Moreira, Ono, Franca, and Nogueira (2009) have focused in the following areas: (a) the
possibility of evacuating in case of emergency, (b) the building fire safety issue, (c) the safety
and security against vandalism, (d) the security against thefts and invasion, (e) the safety against
accidents within the building, (f) the safe use of staircases, and (g) the feeling of protection
inside the building.
Strategic safety relates to planning for procedures to prepare for accidental and
detrimental happenings. Today, intrusion alarms, motion detectors, security lights, and
surveillance cameras have been installed in most schools as a means of protection. All school
districts have established policies to require their schools to develop fire safety plans, bomb
threat plans, tornado safety plans, and gun-fire safety plans to be submitted for review and
approval. Rules also require schools to conduct drills of these plans to test for practicality and
effectiveness. Any irregularities detected during the drills need to be well documented and
corrected immediately (Crisler & Chan, 2007). Although the ―what‖, the ―when‖ and the ―how‖
of school accidents cannot be forecasted, at least, school leaders are prepared to address the
situations with all available connections and resources. A school safety audit helps assess where
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the school stands in safety preparation (Folks & Hirth, 2009). This is the least that parents
expect school leaders to do to fulfill their professional responsibilities.
Creating a Healthy School Environment
A healthy school environment goes far beyond basic cleanliness of the entire facility. To
start with, school buildings should be constructed of materials free from asbestos and other
harmful materials. Special attention has to be paid to cleaning restrooms and food serving areas
per sanitary standards. Paint used in schoolhouse has to be lead free to meet the Standards of
Building Code. Periodic steam cleaning of carpet is needed to extract the pool of bacteria
embedded in carpet fabrics (Chan, Richardson, & Jording, 2001).
Food service equipment such as cooler, freezer, warmer, and dishwasher have to be kept
at the right temperature to meet satisfactory sanitary standards. Drinking water fountains have to
be made available everywhere in school (Fahey, 2000) and water needs to be periodically
checked for possibilities of excessive lead contents which is injurious to health. In food supply,
the provision of healthy breakfasts and lunches and the stop of junk food sales in school will help
promote good diet practices.
Air quality of school buildings is a major concern (McPhee, 2005; Spencer, 1998). In air
circulation, air exhaust systems need to be installed in all laboratories, restrooms, art room kiln
area, homemaking room cooking areas, and the school kitchen for ventilation. School indoor air
has to be periodically checked to ensure that it is free from pollution by radon, carbon dioxide,
formaldehyde, and other poisonous gases (Johnson, 2007). Moisture of school building interiors
not only causes bodily fatigue but also provides a warm bed for the growth of mildew leading to
human sickness. Therefore, interior moisture control of school buildings has to be monitored on
a daily basis to maintain an adequate comfort level for mankind (U.S. Environmental Protection
Agency Indoor Environments Division, 2004).
In all the science laboratories, chemicals must be kept in secured storage to avoid spilling
or leakage. Smoke disposal chambers need to be installed in science laboratories. Eye-washer
and emergency shower devices need to be installed in science laboratories in case of accidents.
Additionally, a fully equipped health care room is needed in schools to provide a restful
and comfortable environment for sick children to receive treatment. The room needs to be
centrally located within the school, equipped with first-aid medical supplies and equipment, and
staffed by a full time licensed nurse for medical emergencies.
Challenges to Safe and Healthy Environment in School
Budget issue. Tight school budget problems have laid constraints to many school
projects including creating a safe and healthy environment for learning. Consequently, many
school districts cannot afford to maintain the safety and healthfulness services as needed. This
results in reduced management staffing, limited functional crime detection devices, less
frequency in checking for facility safety, and fewer times inspecting health conditions of the
school environment (Chan & Richardson, 2005). This is absolutely shocking to hear that the
safety and health environment of a school is compromised for budget shortages? We strongly
urge that school administrators place school safety and health conditions as top priorities of
education business.
Maintaining a Safe and Healthy School
August 2011 / ACEF 8
Poor design. Poorly designed school buildings create unsafe and unhealthy conditions
for students. Sharp corners, rough walls, hidden areas, and slippery floors are typical examples
of unsafe conditions. Hard to clean floors, inadequate air flow, and water with excessive lead
contents create hazardous health conditions for students (Roberts, 2009). Unfortunately, some of
the poor school building designs either are difficult to modify or cannot be modified.
Poor construction. Inferior construction quality of a school building could create safety
and health problems for the students. Leaky roof, inefficient heating and air-conditioning
system, faulty wiring, and flooding conditions as a result of poor workmanship could be both
dangerous and unhealthy for the building occupants. While certain construction materials have
warranties extended beyond one year, in most cases, workmanship has a typical one year
warranty. Contractors should be held responsible for correction within the building warranty
period.
Poor supervision. Student injuries are very often caused by poor supervision of student
activities by teachers and staff. Many playground and laboratory accidents could have been
avoided if close supervision had been exercised. Schools could mobilize community volunteers
to help supervise student activities.
Poor maintenance. Poor school maintenance could be the result of ineffective planning,
plain ignorance, procrastination, and misjudgment. The price to pay for poor maintenance could
be costly because of the domino effect that one system failure leads to another (Vasfaret, 2002).
Repair work to school buildings needs to be done soon after it is reported.
High abuse. Highly abused school buildings could cause unsafe and unhealthy
conditions to occur. Types of high abuse could consist of excessive uses and misuses. Using
storage rooms for instructional purposes, placing student workstations in hallways, and damaged
floors in high traffic areas are typical examples of high abuse.
High vandalism. Vandalism to school buildings certainly is the cause of unsafe and
unhealthy conditions to students. Unfortunately some schools are located in high crime areas of
the community. Damage to school grounds and school building exteriors are commonly
detected. Vandalism to the school building interior is mostly the result of violence caused by
student fights and bullies. Vandalized school properties need to be repaired as soon as possible
to avoid continued vandalism attempts (Cooze, 1995).
High maintenance. High maintenance areas refer to areas in the school building that
have low durability. These are caused by either poor choice of construction materials or
incorrect installation procedures. Frequent replacement is not only costly but also posts unsafe
and unhealthy conditions while waiting for repair.
High risk. The use of temporary classroom buildings, though inevitable in growing
schools, places students in higher risk than those in permanent buildings. Student safety and
health conditions in temporary classrooms have been the problems of study by educators and
environmental scholars (Choremiotis, 1993; Shelton, 2003). Plans need to be developed to
replace temporary classrooms with permanent classrooms in a reasonable number of years.
Meanwhile, increased patrol and security lighting could help reduce crimes in the surrounding
areas.
Implementation of “Increase of Flexibility and Use of Data”
President Obama’s Blueprint highlighted two significant strategies to meet the school’s
need for safety and healthfulness: increase of flexibility and use of data. In budget-tight years,
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when resources for facility management are limited, it makes good sense to play smart on the
flexibility and data-driven principles to improve school safety and health conditions. It is an
interplay of the two strategies that works out best for the efficient use of resources. It has to be
remembered that increase of flexibility and use of data are more than operational practices. The
increase of flexibility and use of data in school safety and healthfulness indicates a change in
administrators’ and policy-makers’ mindset. Educational leaders have to be convinced that
flexibility and data-driven principles are the ways to school safety and healthy environments.
Some of the flexibility and use of data examples and implementation of school safety and health
conditions are discussed in the following:
“Increase of flexibility” strategy. Increase of flexibility starts with the use of funds in
addressing school safety and health issues. When a school maintenance budget is finally
approved after repeated cuts, it is almost down to the minimum. The deplorable budget can
easily be overspent. For any special incidents threatening school safety and health conditions,
school administrators should be given the authority to transfer funds from other accounts at their
discretion to protect all school children by ensuring that they are housed in safe and healthy
facilities. In addition, as Grebow, Greene, Harvey, and Head (2000) suggested, school health
policies need to be established to ensure that health plans survive in the face of budget cuts and
personnel changes.
In scheduling maintenance work, flexibility should be allowed to prioritize school safety
and health problems on top of others. Since school safety and health conditions are critical
issues, they need to be handled with no delay. In addition, flexibility has to be exercised in
minimizing the bureaucratic procedure of requesting, reporting, and processing to accommodate
a quick response to address the problems (Chan & Richardson, 2005).
In designing a school building, planners need to pay attention to the flexibility in the use
of the classroom spaces. It is anticipated that changes in educational programs will occur during
the long life expectancy of school buildings (Earthman, 2009). When educational programs
change, the built-in flexibility would allow an easy conversion of existing classroom spaces to
meet the new program needs. Without that flexibility, it is not unusual to see that, in crowded
schools, many storage spaces are turned into classroom use and wide fire escape corridors are
blocked with study stations. Violations of life safety codes as such pose a direct threat to student
safety in school.
“Use of data” strategy. The use of school facility data to monitor the school
maintenance needs is nothing new but unfortunately has not been given much attention for years.
When a new school building is completed and put to use, little attention is paid to the life-long
maintenance of the building. Data of the school building components can be analyzed and
projected for life-expectancy and scheduled for routine services. School building components
such as the roofing system, HVAC system, refrigeration system, floor system, and exhaust
system need regularly scheduled maintenance to keep its functional use and life-expectancy. All
data need to be well maintained for warranty purposes and problem diagnosis for the future
(Castaldi, 1994). Well maintained school building systems with effective use of a database keep
the school building safe and healthy.
Shoop (2004) created an inventory of major life-safety school building information for
emergency use, such as utility supply systems, surveillance controls, emergency buttons,
communication networks, fire safety zones, school building floor plans, and public agency
contacts. All emergency school data are compiled and stored in a disk for emergency use.
Maintaining a Safe and Healthy School
August 2011 / ACEF 10
At the same time, data from student injuries in the past year should be well documented.
An analysis of accumulated student injury data will yield useful outcomes to indicate how and
where the students get hurt (Schneider, Walker, & Sprague, 2002). Student injury data have
become an important source of information to trace the origin and development of certain
building problems to ensure student safety and healthfulness.
Another set of school building data that could impact student safety and healthfulness is
the student enrollment and building capacity figures. Most school buildings are not designed for
expansion and placement of portable classrooms. The core facilities including the office
complex, media center, cafeteria, gymnasium, restrooms, and major hallways are usually
designed to comply with minimum standards to stay within the construction budget. When
student enrollment grows out of school building capacity, temporary portable classrooms need to
be brought in to house the students. Eventually, a new addition of permanent classrooms will be
constructed to meet the projected growth. Projected student enrollment and building capacity
data could be employed as useful references to upgrade the core facilities to meet the safety and
health standards (Georgia Department of Education, 1996).
In addition, periodically scheduled testing of water and air quality is a needed procedure
to ensure that water and air in school are kept up to the approved national health standards.
Historical data need to be well maintained to provide a continued record of environmental
conditions (Shaw, 2000). In this way, any discrepancy of testing results can be easily detected.
A well maintained dataset will help develop drastic measures to address critical health conditions
at school in a timely manner.
Finally, the U.S. Department of Education (2010b) also recommends the use of school
climate surveys to determine the nature of specific needs in schools. With data generated from
the surveys, determination can be made to allocate resources to meet the health and safety needs.
Conclusion
President Obama’s Blueprint of increasing flexibility and use of data to target health and
safety needs of schools calls national attention to the importance of creating a safe and healthy
school environment for learning. This is echoing school leadership responsibilities as outlined in
Standard 3 of the Educational Leadership Constituent Council (ELCC) Standards that highlights
the promotion of creating safe and healthy learning environments in schools (National Policy
Board for Educational Administration, 2002). Additionally, the Blueprint clearly provides two
directions (increasing flexibility and use of data) school leaders could pursue in achieving the
goal of maintaining safe and healthy school environments. What is really needed at this time is
to follow Obama’s directions by seeking sufficient resources to develop and implement practical
plans to protect our children from unsafe conditions and unhealthy environments at school.
Almost all the school districts nationwide require their schools to develop emergency plans to
deal with possible risks that threaten student safety and healthfulness. In developing school
emergency plans, school leaders are reminded to seriously consider implementing the two
strategies directed by President Obama. School safety and environment specialists have also
prompted school administrators to take a data-driven practical approach to prepare for incidents
that endanger the safe and healthy conditions for learning (Berry, 2002; Schiffbauer, 2000).
In his Education Blueprint, President Obama also calls upon American communities to
exercise their commitment in support of education. School communities, including school
partners, social leaders, parents, and public agencies can draw great resources to build a strong
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11 Vol. 1, No. 1, 2011
hold for safety and health conditions at school (Chan, 2002; Marx & Northrop, 2000). Educators
cannot afford school disasters of any magnitude at any time. In implementing their ―flexibility
and use of data‖ strategies, school leaders may find school communities most reliable in
achieving their school goal of maintaining a safe and healthy environment for learning.
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Vasfaret, G. (2002). Preventive maintenance. School Business Affairs, 68(11), 6-10.
Walker, H. M., & Eaton-Walker, J. (2000). Key questions about school safety: Critical issues
and recommended solutions. NASSP Bulletin, 84(614), 46-55.
Dr. Tak Cheung Chan, Professor of Educational Leadership, Kennesaw State University, Georgia,
is a graduate of the University of Georgia. He was a classroom teacher, assistant school principal,
school principal, and district office administrator. His previous experience in higher education
includes serving as an assistant professor at Valdosta State University, and an associate professor at
Georgia Southern University. His research interests include educational planning, facility planning,
school business administration, school finance, and international education.
Dr. Mike Dishman is an attorney whose practice has centered upon the representation of public
schools for more than a decade. A requested speaker at state and national education conferences,
Dr. Dishman writes on law, leadership and policy in education. He is the co-author of six (6) books,
the most recent of which are The Family Educational Rights and Privacy Act: A Guide for Schools
and Colleges and Leading Schools During Crisis. He holds a J.D. from the University of Mississippi
(1996) and an Ed.D. in Leadership and Policy from Vanderbilt University (2007). He serves on the
editorial board of the Peabody Journal of Education, and previously served as an assistant
professor of education law and ethics at the University of Alaska (1998-2001).
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Glen I. Earthman The ACEF Journal
Linda K. Lemasters Vol. 1, No. 1, 2011, pp. 15-36
15
The Influence of School Building Conditions on Students and Teachers:
A Theory-Based Research Program (1993-2011)
Abstract
A theory-based research program is a dedicated effort to focus research studies on certain
aspects of organizational life so that a coherent knowledge corpus can be developed. Such an
effort also can add to and strengthen the theory under consideration. A focused research
program is difficult to plan from the beginning. Even after the goal of the plan is agreed upon,
developing the theoretical construct of the plan is painstaking work. Considerable input must be
given to establishing the bounds of the theory to be explored. Implementation of such a program
is equally difficult, again for several reasons. The first reason is the difficulty in enlisting more
than one researcher to participate in such an effort. A theory-based research program requires
a commitment of several individuals who agree with the basic theoretical constructs under
investigation. Second, funding for such a program in the social sciences field is extremely
difficult to attain because of the lack of funding sources. In addition, it is difficult to enlist
university students to complete studies directly related to the theory under consideration. The
theory-based program presented in this paper can be considered a paradigm, a model to
investigate how school buildings influence their users. The paradigm consists of a series of
relationships that explain how school authorities are responsible for the condition of the school
building and how the condition of the school building influences faculty, administrators, parents,
and students. Further, it explains how the condition of the building influences the attitudes and
achievement of the students who attend school in the building. Theory in the field of educational
administration is used to try to explain, in the absence of empirical evidence, how humans and
organizations behave. The theoretical model used in this paradigm tries to explain human
phenomena related to how the physical environment influences humans. The model explains
how school buildings come to be in their current conditions and how the conditions then
influence school staff, parents, and students.
or over 18 years research based upon a theoretical model to explain relationships between
building condition and the health and productivity of the users has been promoted in the
Commonwealth of Virginia. The systematic efforts of professors and students have resulted in a
large quantity of valuable research produced from the model and presented here.
The purpose of this manuscript is to describe this cooperative research program that is
theory-based and to illustrate the research efforts that have derived from the theoretical model
used. The research described here is a result of individuals wanting to examine the possible
relationships embodied in the theoretical model and is presented in an evolving chronological
order from the first research effort to those 18 years later using the same model. The research
resulting from the theoretical model is presented in this order, rather than organized or grouped
F
The Influence of School Building Conditions
August 2011 / ACEF 16
into separate themes or components, because the integrity of the theoretical model requires the
recognition that there is a continuum of relationships from school leadership and financial ability
influence upon building condition to the end result of subsequent influence of building condition
on student and teacher health and productivity.
A theory-based research program is a dedicated effort to focus research studies on certain
aspects of organizational life so that a coherent knowledge corpus can be developed. Such an
effort also can add to and strengthen the theory under consideration. By repeated investigations
into the possible relationships between the human effort and the work of the organization, theory
can be developed and refined. It is also possible to explore, through a theory-based research
program, new relationships that were heretofore unknown or unrecognized by researchers. A
theory-based research program requires considerable diligence and effort on the part of the
investigators to mount such an effort and to maintain the direction of research efforts once the
program is in operation.
A focused research program is difficult to plan from the beginning. If one researcher
intends to develop the plan and implement it, considerable thought must be given to developing
the theoretical construct to be investigated. If several researchers are intent on working out a
program, the task is even more difficult, because consensus must be attained on the goals of the
program, area of investigation, and reporting of results. Because several researchers must agree
to engage in the original planning effort with only a nebulous goal, similar research interests
must be identified for those individuals who might participate in the plan.
Even after the goal of the plan is agreed upon, developing the theoretical construct of the
plan requires painstaking attention to detail. Considerable input must be given to establish the
bounds of the theory to be explored. Implementation of such a program is equally difficult,
again for several reasons. The first reason is the difficulty in enlisting more than one researcher
to participate in such an effort. A theory-based research program requires a commitment of
several individuals who agree with the basic theoretical constructs under investigation.
The second reason is the extreme difficulty of attaining funding for such a program in the
field of the social sciences because of the scarcity of funding sources. In addition, there is
always difficulty in enlisting university students to complete studies or work on professor-funded
studies that are directly related to the theory under consideration. In many situations, the funding
of such a program rests upon the individual efforts of the researchers engaged in the program and
the scant resources they may gain from their organization(s). In the vernacular, the research
program in this area of study is usually carried out on the backs of individual researchers.
The theory-based program presented in this paper can be considered a paradigm, a model to
investigate how school buildings influence their users. The model is also a series of relationships
that explain how school authorities are responsible for the condition of the school building and
how the condition of the school building influences faculty, administrators, parents, and students.
Further, the paradigm explains how the condition of the building influences the attitudes and
achievement of the students who attend school in the building.
Initial planning of the paradigm took place at an initial dissertation prospectus examination
in which the student and professor proposed a research study dealing with the relationship
between the condition of a school building and student achievement and behavior. Questions
from the research committee related to how the research study would explain human activity in
an organization and at the same time relate to the actual manner in which a school organization
functioned. Thus, the goal of trying to explain all of the relationships involved in the research
study arose from the questions of the committee. Planning of the theoretical model by the
Lemasters
17 Vol. 1, No. 1, 2011
student and professor followed an intuitive model of development in that questions were raised
as to how the school building came to be in its current condition, the relationship between
precedents of building condition, and possible influences the school building condition might
have upon all users of the facility. From these questions, a theoretical model evolved, which
described the relationships among all elements identified as a part of the process.
The use of the word paradigm has Kuhnian roots (Kuhn, 1962) in that the word often is
used to mean a commonly held belief of people within a given discipline. A paradigm also can
be thought of as an example or a model that can or should be followed, or even held up to be
emulated. In educational jargon a paradigm is defined as not only a model to be followed but
also a way of thinking about certain aspects of the educative process and even the organization
itself. Thus, the educative process in the United States is a paradigm that is followed or used to
educate children and youth. In more recent decades we have heard increasingly that the
paradigm for education should be changed to accommodate new thought and philosophy.
Educators oftentimes speak of changing the paradigm, meaning that educators should not think
in the usual historical terms about how education takes place and students learn, but they should
think in terms of a new definition of how education should take place and students beneficially
learn.
Paradigms are useful in directing thought and effort regardless of the setting or
environment. Paradigms can be thought of as being very small or rather large in scope,
depending upon the subject matter or setting. The model or paradigm of research that is
described in this paper is one of small effect, but one that is consistent in noting how researchers
can produce knowledge about a very important aspect of how students learn. The model of
research as presented is based upon theoretical constructs that may explain how educators,
students, parents, administrators, and even buildings interact to influence student achievement.
This paradigm of research is very complete in that it begins the explanation of how educators
influence the condition of a building and then in turn how the building influences students,
teachers, parents, and administrators. In this manner, the paradigm is complete and self-
contained and, at the same time, based upon the theory we presently think exists in the public
schools.
Theory-Based Modeling
Theory Use
Theory in the social sciences field is used to try to explain how humans work and act in
organizations. Theory in educational administration, specifically, is used to explain how
administrators and school organizations work and act. Theory is considered a system of
assumptions about certain phenomena. Theory is based upon repeated observations of human
activity. These observations are then translated into a series of statements or abstractions that
seek to explain how humans work or organizations function. Hatch and Cunliffe (2006) referred
to this phenomenon as an explanation rooted in the specifications of the relationship between a
set of concepts. These statements or concepts can then be cast into a system of propositions
about human behavior. Theorizing is one of the first steps in developing principles and laws of
human nature and activity. The theory developed through observation needs to be tested to find
out if predictions can be made about the nature of organizations or how humans within the
The Influence of School Building Conditions
August 2011 / ACEF 18
organization act. In other words theory tries to explain or describe a part of reality in our
experiences (Hatch & Cunliffe, 2006).
Theoretical statements can be developed into a set of theories or explanations that can be
called a theoretical construct. Theoretical constructs are useful in that they explain how a
number of assumptions are interrelated. Theoretical models are derived from theoretical
constructs and used to provide a comprehensive explanation of a series of assumptions. These
are graphic explanations of the theory. From such models a series of explanatory behavior can
be used for testing.
The theoretical model presented here can be used to explain human phenomena that are
related to how the physical environment can influence humans (Figure 1). This model explains
how buildings come to be in their current condition. The model further suggests that student
behavior also is related to building condition; further, the building condition influences the
attitudes students have about their environment.
Figure 1
Model Showing the Relationship between Student Achievement and Behavior and School
Building Condition
Theoretical Model
The model can generate a series of propositions to be tested to determine the validity of
the theory. All six of these propositions can be tested individually to determine their validity in
describing behavior, which is the essence of theorizing. All of the propositions are part of a
theoretical construct that endeavors to explain human behavior in an organization and the
possible influence buildings have on individuals.
Proposition I. The leadership and financial ability of the school system determine the
efficiency and extent of maintenance and operational services provided in the school system as
well as the quality of buildings that are constructed.
The leadership of the school system includes the superintendent, central office
administrators, principals, and the school board. These individuals and groups provide the kind
of leadership in the school system that will determine eventually the condition of the school
buildings. The financial ability of the school system to support education in general is limited by
Leadership
Financial
Ability
Maintenance
Staff
Building Age
& Quality of
Materials
Custodial
Staff
Building
Condition Financial
Ability
Parent
Attitude Student
Attitudes
about their
Building Student
Behavior
Student
Achievement
Lemasters
19 Vol. 1, No. 1, 2011
the resources available, which are the taxes that can be raised locally plus available state
assistance. Local school system leadership and financial ability are the two factors that
determine how large the maintenance and operations budget and staff are and how much funding
is devoted to the care and upkeep of facilities. The demands of the local leadership to keep the
facilities clean and in good repair contribute greatly to determining the condition of the school
buildings. The interplay between the leadership and financial ability determines how well the
maintenance and operations staff functions in keeping the school buildings clean and in a good
state of repair. The school board’s reduction of the maintenance and operations portion of the
operating budget during the annual budget approval process signals to everyone that the school
board is more interested in other parts of the organization than in the wellbeing of the school
buildings. Conversely, satisfaction of the requests of the maintenance and operations
departments conveys a message that the school board believes the school buildings are important
(Earthman & Lemasters, 2004).
The condition of the building is also the result of the kind of building material used in the
construction of the structure, as well as the age of the facility. School leaders make decisions
regarding the amount of funds that will be used in the construction of the school building. Some
of these decisions can result in less-than-first-quality materials being used in the building, if the
school board is interested in keeping initial construction costs down. Inferior building material
does not hold up as well as higher quality material, and as a result the school building
deteriorates at a faster rate. In addition, decisions regarding the use of older buildings for
housing students can have a negative influence upon student and teacher health and productivity.
The school leadership and the decisions it makes, plus the financial ability of the school
system, help to determine the condition of the building used to educate students. These decisions
relate to not only how well the building is constructed, but also to how the building is utilized for
this purpose and how long the building will be used. Some of the questions these relationships
raise are the following:
What is the relationship between the leadership of the school system and the
condition of the school buildings under their charge?
What factors enter into decisions regarding the amount of funds available for
maintenance of school buildings?
What political factors, if any, enter into maintenance decisions?
What is the relationship between wealth of the school division and the condition of
the school buildings?
Is there a relationship between the amount of funds expended on upkeep of buildings
and the condition of the school buildings?
Is there a relationship between community support and the condition of school
buildings?
Will school buildings be in better condition if more aggressive leadership on the part
of the superintendent is employed in the school system?
Do the principals have a part in how the buildings are maintained?
How can leaders project their image of how the schools should look?
How much of the condition of school buildings can be attributed to effective or
ineffective leadership?
The Influence of School Building Conditions
August 2011 / ACEF 20
Proposition II. The second proposition deals with the relationships among size and
effectiveness of the maintenance and operations staff, the age of the building, and the quality of
building material used in the school.
All of these factors that have an influence on the condition of the school building can be
tested. Obviously, a maintenance and operations department that is fully staffed and budgeted
and that understands the desire of the school leadership in having a well-kept building will result
in a building that works well. Conversely, a maintenance and operations department working
with a reduced budget and staff must sacrifice the completion of some necessary maintenance
projects, thereby contributing to the eventual deterioration of the building. The condition of the
school building results from not only the efforts of the maintenance and operations staff but also
the efforts of the leadership to require school buildings to be in excellent shape. Leaders of the
school system must require and demonstrate that they desire the school buildings of the school
system to be in the best condition and to have those building components or features that
constitute a modern school facility.
The age of the structure is also a contributing factor to the condition of the building.
Research studies such as the work of Bowers and Burkett (1987), Chan (1980), Phillips (1997),
O’Neill (2000), and others have consistently found that the age of the structure is a negative
factor in explaining student achievement. This relationship has been tested repeatedly with
positive findings. It is not necessarily the age of the building, however, as much as the lack of
components in the building that are essential for good student learning. Buildings that are 50 to
100 years old usually do not have the components necessary for a modern educational program,
and as a result the building works against student efforts to learn. Even when such older
buildings have some of the necessary components, such as air-conditioning, better lighting,
acoustical control, and day-lighting, the installation of such components is not as satisfactory as
in newer buildings and often do not help the student in the learning process.
Finally, the quality of the materials used in construction of the building and the quality of
workmanship employed help to determine the eventual condition of the school building.
Decisions by school authorities to control the initial costs of buildings often determine the
quality of building material. Building material that is not of the finest grade can result in rapid
deterioration of the building. Poor workmanship in the construction of the building also can be a
contributing factor in the eventual condition of the building.
All of these relationships can be tested through research studies that are crafted around
sound principles. The age factor has been tested through research previously cited. The
researchers of these studies used the age of the building as a surrogate for building condition and
in this manner tested the influence of building age on student achievement. In every study, the
researchers found that the performance of students in old buildings was below that of students in
new buildings. Although such studies did not directly test whether age of building influenced the
eventual building condition, the researchers did identify age as a surrogate for condition of the
building.
These relationships elicit several questions that could produce data to help explain the
importance of these influences:
Does the size of the maintenance staff have any relationship to the condition of school
buildings?
Does the effectiveness of the operations staff result in school buildings in better
shape?
Lemasters
21 Vol. 1, No. 1, 2011
Does the age of the building directly contribute to the condition of the school
building?
Are buildings rated as in unsatisfactory condition the result of poor building
materials?
Proposition III. The condition of the school building directly influences the attitudes of
faculty, parents, and students.
Faculty members are directly affected by their immediate surroundings and working
conditions. If they are in a facility that is rundown and lacking in certain features such as
thermal control of the environment, adequate lighting and windows, modern science equipment,
and controlled acoustical environment, among other features, their attitude will not be as positive
as that of faculty members in better kept and modern buildings. In addition, parents will have a
feeling about the building in which their child attends school. Through visits, they will conclude
that the administration of the school system either cares or does not care about the condition of
the buildings in which students are housed. If the building is not in good condition, the parents
and community will have a negative feeling about the building. This feeling or attitude will, in
turn, be communicated to their children.
The attitudes of the faculty and parents will have a bearing upon the feelings students
themselves have about the building. If the students’ feelings are negative, the attitudes of the
parents and faculty will reinforce that attitude. The students themselves will form an opinion
about how the school system feels about them as learners. All of these factors will generate an
attitude on the part of the students about their worth and value in society. They will view their
surroundings as a judgment the community makes about the value of education.
The following questions relate to stakeholders’ attitudes about school conditions:
Do the attitudes of parents regarding the condition of the building influence the
attitudes students hold about the condition of the school?
Do faculty and administrators influence student attitudes by their behavior and
attitudes towards the school building?
How can the attitudes of students regarding the school building be measured?
Does the condition of the school building influence the attitudes of students?
Proposition IV. The attitudes students have about their surroundings permeate their
feelings about the worth of the building in which they are housed and in turn influence their
feelings about their own worth.
The attitudes that are generated by the condition of the building are reflected in how
students feel about the building itself. Students take care of buildings and equipment that are in
good condition. Students feel good about their school when it looks nice and is well maintained.
Conversely, students are not apt to take good care of facilities that are in poor condition.
The following questions are reflective of these issues:
Do students in poor buildings have lower feelings of self-worth than students in better
buildings?
Is there a relationship between the condition of school buildings and student
attitudes?
The Influence of School Building Conditions
August 2011 / ACEF 22
Proposition V. The resultant attitudes students have about the school building influence
to a certain extent their achievement.
The following questions are of interest in this regard:
Do students who feel good about themselves and about their surroundings perform
better on all measures of performance than students who do not?
How do students feel about the school building in which they attend school?
Can these attitudes be compared with building condition?
How much does attitude influence student performance?
Does the lack of safety of a school building affect student attitudes, performance, or
both?
Proposition VI. In school buildings of good condition, students perform better because
of building features and condition that assist in the learning process.
Students perform better when the proper equipment is available to them, the environment
is conducive to efficient bodily functioning, and the building is clean and an inviting place to
live. Student performance can be enhanced if the building has those components that research
has demonstrated to be necessary for efficient and effective learning. These components as
identified by Earthman (2004) are good thermal, acoustical, and lighting control. Further, the
building should have student-friendly colors in the classrooms as well as functional furniture and
equipment in good condition. Finally, there should be sufficient space for the student
population, and the building should be clean and well maintained.
Proposition VI elicits the following questions:
Is there a relationship between building condition and student performance?
Is there a relationship between building condition and student behavior?
Is there a relationship between school population density and student performance?
What is the extent of a possible relationship between building condition and student
performance?
The research generated from the various theoretical propositions explicated above serve
as a corpus of research on a single topic, but with many possible relationships. The description
of the research flowing from the theoretical model is presented more on an evolving
chronological basis than on themes or concepts because of the integrity of the model. The
presentation also gives the reader an opportunity to see the development of a research program
based upon theory.
Theory-Based Research
Initial Research
The first study arising from the aforementioned theoretical model was completed by Cash
(1993), who studied high school students in satisfactory and unsatisfactory school buildings in
Virginia. Her population consisted of small, rural high schools, each of which had fewer than
100 students graduating as seniors. These schools comprised 190 buildings. Basically, Cash
Lemasters
23 Vol. 1, No. 1, 2011
(1993) was investigating the relationship between the condition of a school building and student
achievement and behavior.
An instrument titled the Commonwealth Assessment of Physical Environments (CAPE)
was developed to assess the condition of a school building. The items for the CAPE were
derived from existing research that examined and found a positive relationship between certain
building components and student achievement. The major items of the instrument dealt with
thermal environment, lighting, acoustics, color of the walls, condition of the classroom furniture
and equipment, condition of the science laboratories, and the presence of graffiti. Other items
were added to provide further information about the condition of the building, such as the
presence or absence of windows in the classroom and the type of floor covering. All of the items
on the CAPE addressed the relationship between building condition and student achievement.
Use of this instrument is an important aspect of assessing school building condition, because
subsequent researchers have used other types of instruments to assess buildings with results that
were neither consistent with nor as robust as the findings of Cash and others. Being able to
properly assess the condition of a school building in terms of its relationship to student
achievement is very important. Improperly assessing the building condition will skew the results
of the comparison with student scores.
Cash (1993) assessed the condition of 143 high school buildings; each building was
assigned a score representing its condition. She selected schools scoring in the bottom and top
quartiles to define her population of students in poor or good buildings. She then compared the
mean scaled scores on the Tests of Achievement and Proficiency (TAP) for the 11th grade
students in the two building groups.
Cash (1993) compared the achievement test results of students in buildings rated as being
in poor condition to those of students in buildings with good condition ratings. She found a
difference between the scores of students in poor buildings and students in good buildings on
several subtests of the TAP. Significant differences of four percentile points were found in
Reading Comprehension, Math Applications, and the Composite Score between students in
poorly rated buildings and those in buildings rated as being in good condition. Differences of
five percentile points were found in Science and the Total Composite Score. Differences ranged
around two to three percentile points on other subtests. These results compared favorably to
previous research on the same subject (Edwards, 1991).
In an effort to extend the research, the Cash (1993) study was replicated by Earthman,
Cash, and Van Berkum (1996). These researchers studied the high schools in the State of North
Dakota. The students in these schools were identified as being good subjects because the state
scored highly on the SAT, behind only Japan in scores. The name of the CAPE was changed to
State Assessment of Facilities in Education (SAFE), but the content remained the same.
Building assessments were completed by the principals of the schools. Data from the North
Dakota State Department of Education on the California Test of Basic Skills for 11th grade
students were used to compare achievement scores. Again, achievement test scores of students
in the two building types were compared. The researchers found significant differences at the
.05 level of confidence in scores between students in good buildings and students in buildings
rated as being poor; these differences were as high as nine percentile points in Spelling and seven
percentile points in Reading Vocabulary and Science (Earthman et al., 1996). The differences
were similar to those found by Edwards (1991) and Cash (1993) in previous research. The
consistent differences these researchers found were noted in the subtests of Reading, Math
Applications, Science, and Total Composite Scores.
The Influence of School Building Conditions
August 2011 / ACEF 24
Hines (1996) replicated the Cash study using large urban high schools in Virginia. He
used the same basic methodology as used in the previous research by comparing achievement
test scores of students in buildings rated poor and those rated good by their principals. The Iowa
Tests of Basic Skills scores were used in the comparison, and the CAPE was used to assess the
buildings. The differences in achievement scores that Hines (1996) found exceeded those found
by Edwards (1991), Cash (1993), and Earthman et al. (1996). On some subtests, Hines (1996)
found the differences to be as great as 17 percentile points, far exceeding the nine percentile
points difference found by previous researchers. The substantial differences included 17
percentile points in Math Applications, 15 percentile points in Reading Comprehension, and 14
percentile points in Total Composite Scores.
Lanham (1999) investigated the possible relationship between student achievement and
behavior and condition of the school building attended at the elementary level. For comparison
purposes, he used a modification of the CAPE to assess the condition of elementary school
buildings and test scores on the Virginia Standards of Learning tests as a measure of student
achievement. His participants were a random sample of all elementary school buildings in
Virginia. Lanham (1999) used a five-step multiple regression analysis to determine which
variable carried the most weight. He found that free and reduced-price lunch participation was
the first significant variable. This variable was followed by air conditioning, which was
significant in three of the five analyses. He found other building factors to be significant, as
well, such as ceiling type, room structure, floor type, and site size. These findings were
consistent with the findings of previous researchers, even though Lanham (1999) used different
statistical methods in his analysis.
All of the researchers previously cited found significant differences between the
performance of students in substandard buildings and those in standard buildings.
Research Compilation
Lemasters (1997) conducted a review of research as a follow-up of previous reviews.
Earlier compilations of research findings on school facilities had been completed by Weinstein
(1979) and McGuffey (1982). Her review was of research about the relationship of school
building condition to student achievement and behavior (Lemasters, 1997).
Her research project included studies of the relationship between 1982 and 1997
(Lemasters, 1997). The researcher reviewed a total of 157 separate potential studies and selected
for analysis a total of 57 separate studies, all dealing with the topic of building condition and
student achievement. Lemasters’ (1997) conclusion was that students in buildings rated as being
in satisfactory condition outperformed students in buildings rated as being in unsatisfactory
condition. This compilation of research findings served to provide information to other
researchers working in the same general area of concern.
As a follow-up of previous research reviews, a compilation of relevant studies was
completed by Bailey (2009) to incorporate the results into a comprehensive form. His work was
the latest of several reviews of research and covered the decade 1997 to 2007. He identified 127
potential studies for review, but only 57 were directly relevant to the topic of the relationship
between school building condition and student and teacher health and productivity. These
studies were analyzed according to a set schema and the results reported. He was able to state
that the sum of the research indicated the existence of a positive relationship between condition
of the school and health and performance of students and teachers. One interesting finding
Lemasters
25 Vol. 1, No. 1, 2011
Bailey (2009) identified was that researchers utilizing a building rating instrument designed to
properly evaluate those building conditions directly related to student achievement found higher
differences in student test scores between the two groups of students than did researchers in
studies involving the use of a maintenance-type building evaluation.
Bailey’s (2009) research supported the research of Lemasters (1997) and others. The
four aforementioned research review studies, Weinstein (1979), McGuffey (1982), Lemasters
(1997), and Bailey (2009), are very important works because the relevant research on this topic
has been compiled systematically and presented in a utilitarian form for other researchers to use.
The findings of the four researchers reflect a trail of evidence that supports the concept that there
is a measurable relationship between the condition of a school building and the health and
productivity of students and teachers. The evidence of this relationship has accelerated for each
research review that has been completed. Some studies have been identified that could not report
any relationship between building condition and student achievement. Although not proven, it is
surmised that methodological errors in these studies and the use of an improver building
evaluative instrument might be the reasons for not finding any relationship.
Extension of Research
Brannon (2000) extended the research to investigate the relationship between the
precursors of building condition and building condition itself. The first part of the theoretical
model explains the possible relationship between the leadership and the financial ability of the
school system in eventually determining the condition of the school buildings for which the
school leadership is responsible. Brannon (2000) asked the principals, central office staff,
superintendent, and school board members to assess the condition of the school buildings within
their school division. Brannon (2000) then assessed the high school buildings using the CAPE
instrument. His findings indicated that the principals had a better knowledge of the condition of
the school buildings than any of the other groups. This research validated principals’ use of the
CAPE to properly assess the condition of their buildings, which had occurred in previous
research and would occur in subsequent research efforts.
Another extension of research was the study of the relationship between air-conditioned
classrooms and student achievement. Lemasters and Earthman (2003) identified 10 school
buildings that had either air-conditioned or non air-conditioned classrooms. They compared the
academic achievement of students in the two types of classrooms. One of the purposes of the
research was to ascertain if the classroom conditions actually influenced their decisions about
remaining in the school. Additionally, the researchers investigated teacher attitudes about their
own wellbeing and how the classroom influenced student learning. The findings of these
researchers indicated that although there was a significant difference in attitudes of teachers in
good and poor school buildings, the condition of even the poor classrooms was not enough to
cause the teachers to consider moving from the school or leaving the profession. The teachers
did, however, indicate they thought the condition of the classroom did influence student learning.
Teachers in poor buildings thought the condition of the classroom had a negative influence upon
students learning. Teachers in these buildings also thought the classroom condition caused them
some health related problems (Lemasters & Earthman, 2003).
The Influence of School Building Conditions
August 2011 / ACEF 26
Subsequent Research
Crook (2006) used a larger population than had previous researchers to investigate the
relationship between building condition and student performance. Both Cash (1993) and Hines
(1996) used different segments of the total high school building population of their respective
states as their populations. Cash (1993) studied rural high schools and Hines (1996) studied
urban high schools. Crook (2006) involved the entire population of 231 high school buildings in
Virginia for his study. The percentage of students passing the Standards of Learning tests was
used as a measure of student achievement to compare the two student bodies in poor and good
buildings, respectively. The correlations he found were significant for the subtests of Math
Concepts and Math Application. He reasoned that although his findings were not as extensive as
those of previous researchers, they did corroborate the findings of previous research studies
because the trends in differences were positive.
Thornton (2006) investigated the relationship between school building condition and the
achievement of minority and economically disadvantaged students. He used the same population
of high schools identified by Crook (2006) as buildings in poor condition and buildings in good
condition. The mean scaled score for students on the Virginia Standards of Learning tests served
as his measure of comparison between the two groups of high school students. He found that
building condition had minimal (5 of 10 subtests significantly different) influence on the
achievement of economically disadvantaged students. This finding does not coincide with
standard belief that economic status of the family of the student influences learning. Thornton
(2006) did find, however, significant differences in student achievement scores on 7 of 10
subtests between minority students in substandard and minority students in standard buildings.
Again, this is unusual because there is no research basis for indicating that racial background has
anything to do with student learning. Although he did find significant differences in
achievement test scores between students in poor buildings and those in good buildings, which
supported previous research, his findings are unusual in that they do not correspond with
common knowledge about demographic influences on student learning. His findings might well
indicate, however, that buildings in poor condition have a greater influence on minority students
than they do on the general population of students.
O’Sullivan (2006) replicated the Cash (1993) study with high schools in Pennsylvania.
He used 251 randomly selected high school buildings as his building population. The student
achievement results of the Pennsylvania System of School Assessment (PSSA) tests were used to
make the comparison between the student population in substandard and students in standard
buildings. O’Sullivan (2006) concluded that there was a significant relationship between student
academic achievement and schools that had auxiliary buildings adjacent to the school. He
further found a significant difference between student academic scores when school buildings
had graffiti on exterior walls or had recently painted interior classroom walls. The increase in
overall test performance was noted to be 55 points higher for students in schools without graffiti
than for students in schools with graffiti. The last conclusion was that there was a significant
difference between student academic achievement scores in schools that had undergone
renovations or additions and student scores in schools that had not.
Ruszala (2008) at The George Washington University (GW) used the theoretical model to
mount a correlation study to investigate the relationship between condition of school facilities
and teacher satisfaction in the metropolitan school divisions of Virginia. Two survey
instruments were utilized to answer her research questions. The CAPE, referenced earlier, was
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27 Vol. 1, No. 1, 2011
used to produce an accurate representation of the physical environment for school buildings.
The Teacher Opinionaire of Physical Environments (TOPE), designed by Ruszala (2006) to
measure teacher satisfaction in relationship to specific school building conditions, was the
second survey instrument, which was used to measure teacher attitudes. Using the Pearson
correlation coefficient, Ruszala (2008) found moderate positive correlations between the CAPE
and TOPE survey instruments results for age, paint, and light; a low positive correlation was
found for thermal conditions.
Bullock (2007) replicated the Cash (1993) study in Virginia middle schools. This school
level had not been explored in systematic fashion in studies dealing with the relationship
between school building condition and student achievement prior to Bullock’s (2007) study. He
included the students in all of the middle schools in Virginia as his subjects. He also used the
CAPE to assess the school buildings and the percentage of students passing the Standards of
Learning tests as a dependent measure of student achievement. His findings were consistent
with previous studies in finding a positive relationship between school building condition and
student achievement.
Student attitudes toward their school building condition and their subsequent academic
achievement were investigated by Earthman (2008) in an effort to ascertain a possible
relationship between these the variables. A significant difference was found in the attitudes of
students in satisfactory school buildings compared to the attitudes of students in unsatisfactory
buildings. Students in school buildings rated by principals as being in unsatisfactory condition
expressed more negative attitudes than did students in satisfactory school buildings. The
difference in attitude responses was significant at the .05 level of significance. A comparison of
the academic achievement of the two groups of students indicated a significant difference in
English scores only. Comparison of student scores in 10 other subject areas were not significant
but did show a strong trend toward differences, thereby indicating that, perhaps, with a larger
student population, differences might be more pronounced. This research supported the
theoretical model, which purported that the condition of the building would influence student
attitudes and subsequent academic achievement.
In 2009, Taylor from the George Washington University investigated whether or not a
relationship existed between the condition of school facilities in Washington, DC Public Schools
and reading proficiency, mathematics proficiency, daily attendance rate, and truancy rate. His
findings supported the tenets of the research in this paper. Using Spearman Rho correlation
coefficients he found that students in schools with acceptable facility condition ratings achieved
higher proficiencies in math, achieved higher proficiencies in reading, exhibited higher rates of
attendance, and exhibited lower rates of truancy compared to students in schools with
unacceptable ratings (Taylor, 2009).
Whitley (2009) investigated the possible relationship between expenditures of school
divisions on maintenance and operations and facilities sections of local budgets. He compared
the expenditures in these budget categories for school divisions that had either buildings in
satisfactory condition or buildings in unsatisfactory conditions. He found that school divisions
with buildings in satisfactory condition spent more totally and more on a per-pupil basis than did
school divisions with buildings in unsatisfactory condition. His findings indicate that school
divisions with satisfactory buildings spend more for maintenance and operations expenditures
than do school divisions with unsatisfactory buildings (Whitley, 2009). Yet, when the
expenditures were converted to a per-pupil basis, the school divisions with unsatisfactory
buildings had higher per-pupil expenditures. This was the case because the school divisions with
The Influence of School Building Conditions
August 2011 / ACEF 28
satisfactory buildings had growing student populations and the other school divisions had
declining populations. This research explored that portion of the theoretical model dealing with
the model’s proposed relationship between financial ability of the school division and condition
of the school building (Whitley, 2009).
The renovation of a school building inevitably causes problems for both students and
teachers while the process is ongoing. This phenomenon was studied by Shifflett (2009) in two
high schools that had undergone renovation in the same school division. The researcher found
that teachers were indeed inconvenienced while the renovation of the building took place, but
after they moved into the renovated building their attitudes were much improved. These findings
were similar to those Dawson and Parker (1998) and Maxwell (1999) found in their studies of
the renovation process. The findings of Shifflett (2009) must be accepted with some caution
because of the large number of teachers who responded in the neutral column for the survey
questions. Apparently, a large number of teachers either did not remember or experience the
renovation process or they distanced themselves from it in their responses.
Earthman and Lemasters (2009) investigated teacher perceptions of the conditions of
their classrooms and how the condition of the building influenced their work. The population for
this study consisted of the teachers in schools that were identified in the Crook (2006) study.
Crook (2006) identified 11 high schools in which the respective principals stated the buildings
were unsatisfactory. These buildings served as the population of their study and were matched
with a like number of schools in which the principals rated their respective schools as being in
satisfactory condition. The attitudes of the teachers in these two groups of school buildings were
compared through the use of an attitudinal scale developed for the project: the My Classroom
Appraisal Protocol© (Earthman, 2006) developed by the researchers. There had been other
studies concerning teachers’ perceptions about their classrooms, but this study was one of the
first to compare the perceptions of teachers in satisfactory buildings and those in unsatisfactory
school buildings. The findings of these researchers corroborated the findings of previous
researchers. Some of the teachers who participated in the study were located in the rural part of
the state, a fact that might have influenced some of the findings, because the teachers in this
study reported they would not consider moving to another school or quitting the teaching
profession (Earthman & Lemasters, 2009). This finding is in contrast with some of the other
studies that investigated teacher perceptions of their classrooms. The low response rate to the
survey also might have influenced the findings.
Bishop (2009) of The George Washington University (GW) utilized independently
derived research questions to conduct a qualitative study that suggested achievement, attitude,
and behavior are improved when stakeholders are moved into new school facilities. He included
in his study three recently opened high schools in Virginia. Although the data were triangulated
from various sources, his teacher focus groups supported the previous research in this document.
Teachers in the new buildings concurred with the findings of improved student behaviors,
improved staff behaviors, and a positive impact on student achievement (Bishop, 2009).
Harrison (2009), also at GW, conducted a study of school building conditions and student
achievement in Virginia schools. The relationship was approached through the premise of the
growing body of research that connected equal access to clean, safe, and educationally
appropriate facilities (Oakes, 2002) to equity for all children, such as that proposed by the
Elementary and Secondary Education Act of 1965 and renewed by the No Child Left Behind Act
of 2001 (USDE, 2003). The use of adequate building condition as a resource for ensuring
optimal student achievement was investigated, particularly in high-poverty, low-achieving
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29 Vol. 1, No. 1, 2011
schools in Virginia. The role of the principals of high-poverty, low-performing schools was
examined through research concerning the impact of accountability and effectiveness on their
perceptions of essential conditions for optimal student achievement. Harrison (2009) found that
all principals did not equate the importance of building condition to eight of the nine essential
elements of school improvement. Further, principals in above-standard buildings reported that
building condition did not affect their ability to engage in any of the seven effective schools
practices, whereas principals in below-standard buildings reported that building condition did
affect implementation of these practices. The principal’s perception of the condition of the
building influences how the principal perceives any possible influence the building may have
upon school practices.
Research in the Making
Researchers continue to examine and expand the boundaries of the theoretical model.
Listed in this document are some of the researchers and their research topics that are progressing
in the Commonwealth of Virginia. Researchers in other states and at other universities are
conducting studies using the same basic methodology and building assessment instrument that
were used in the original Cash (1993) study.
Barry Hollandsworth, a student at Virginia Tech, is currently investigating student
attitudes toward buildings in various conditions. There have been a limited number of previous
research projects measuring student attitudes in satisfactory and unsatisfactory buildings at the
elementary school level, but Hollandsworth’s study will investigate the possible relationship
between attitudes at the high school level. The instrument Student School Building Attitude
Scale© (Earthman, 2007) was developed expressly for high school students with a level of
language commensurate to those grades. This instrument will be used to measure attitudes of
students in both satisfactory- and unsatisfactory-rated school buildings.
Paul McLean at Virginia Tech is investigating the relationship between condition of the
school building and selected student and teacher demographic factors. The researcher will
identify high- and low-performing schools as measured by annual yearly progress determined by
the Virginia Department of Education. Possible differences in building condition, teacher
quality, and student attendance will be measured and compared. This study should shed some
light on the differences between these demographic factors of teachers and students in good
buildings and those in poor buildings. One of the limitations of the previous research cited in
this paper is control of teacher quality. McLean may be able to produce some results that help
explain some of the features of this limitation of the quality of the faculty or at least shed some
light on the measurement of the quality of faculty.
Several student researchers are currently initiating studies to investigate the knowledge
level of principals regarding the relationship between building condition and student
achievement. It is reasoned that those principals who are knowledgeable about research findings
will then be able to translate that knowledge into action in securing resources to keep their
respective buildings in good condition. Another student researcher is organizing a study to
determine if there is a difference in perceptions between architects and principals about the
importance of selected safety designs in school buildings. This researcher reasons that there may
be differences of opinion between the user and the designer of a building regarding design
features of schools that promote or hinder student safety. If the principal of a school has
concerns about the influence of certain design features upon student safety, the designer of the
The Influence of School Building Conditions
August 2011 / ACEF 30
building should try to eliminate these features when designing a new building. The study will
ascertain if there are differences between principals and architects in perceptions of the
importance of design features. Finally, another student at GW is conducting a study of the
personal constructs related to how teachers, students, parents, and the community make meaning
of a regional alternative day school facility that is 87 years old.
What Is Known About Our Research?
1. To date, the research on the subject of the relationship between building condition and
student achievement and behavior that has been cited here has been highly focused upon the
various relationships as shown in the theoretical model. The results of these studies have been
encouraging and have demonstrated how a concerted effort to investigate identified relationships
between the condition of the school building and student and teacher productivity can provide
very useful data. The significant differences between the scores of students in unsatisfactory
buildings and students in satisfactory buildings have been found to measure from 2 to 17
percentile points. These differences represent findings for one year. Because of changing
student populations, it has not been possible to measure the influence of poor school buildings
upon students year after year. Nevertheless, such differences in scores are very important and
statistically significant.
2. Studies did produce results showing a positive relationship between building condition
and student performance. The results in most cases were not large; nevertheless, it is significant
that any results were found. These results bode well for further research and the need for
extended research efforts.
3. The most positive results have been noted for the subject areas of mathematics and
science. Students in poor-condition buildings scored lower in these areas than did students in
buildings in good condition.
4. The condition of the school building does influence the attitudes students have about
their schooling. Although the evidence is small, a difference in responses to an attitude scale
was found between students in poor buildings and those in good buildings.
5. The most productive research studies have used an instrument based upon research
findings to evaluate school buildings in contrast to some studies that used maintenance-needs
evaluative instruments.
6. The condition of the classroom does influence the attitudes of teachers. Teachers in
poor buildings have a more negative attitude than do teachers in good buildings.
7. Researchers who use maintenance-related evaluation instruments to determine the
condition of a building in investigating the relationship between school building condition and
student performance have not been able to consistently find differences in student scores.
These latter assessment instruments evaluate numerous building components not directly
related to student achievement. These components then have equal weight in the overall scoring
with the weight of important components such as air conditioning, lighting, acoustics, proper
furniture, modern equipment, and safety features. This uneven approach to evaluating the
condition of a school building undoubtedly produces results that can be considered skeptical.
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31 Vol. 1, No. 1, 2011
Research Limitations
There are limitations to the research that has been completed. The most common
limitation is the inability to control all of the variables associated with student and teacher
performance. The quality of the teachers, the effectiveness and relevance of the curricular
materials, as well as other factors related to the school experience are extremely important to
student learning and yet are difficult to control in a research study. These variables are usually
under regulation of the school; yet control of these variables is extremely difficult. In the matter
of measuring teacher quality, most of the measures researchers have identified are subjective and
prone to error. The degree of influence the parents, home, and community have upon students is
also difficult to measure and verify. It is well known that these variables control a great deal of
the variance associated with student learning, yet researchers have limited means to control for
the influence of these variables. The measures available to a researcher to control these variables
are at best associational and not precise. The most common measure for controlling for the
socioeconomic status of students is the percentage of students participating in the federal
government free and reduced-price lunch program. Even though this measure is used
extensively by researchers, this measure reflects a great deal of error, especially at the secondary
school level. That is because the typical high school student does not participate in the program
as fully as possible. There are difficulties in trying to control for all of the confounding variables
associated with student and teacher performance.
Research in public schools is becoming much more difficult to conduct each year. The
requirement to protect students, teachers, and others associated with the schools is very
important and yet that effort, as justified as it might be, is exactly what prevents researchers from
completing certain studies. Research using students as subjects must pass many levels of
consent and approval within the organization before the research can begin, and even then the
safeguards of confidentiality require that the researcher be extremely careful in gathering data.
Many school systems simply refuse to entertain research requests because of the possible
interruption in class activities or because of the frequency of requests. Even the cooperation of
departments of education in various states is not necessarily an assurance that researchers will
have access to needed data. Obtaining the cooperation of the local teachers’ union, as did
Buckley, Schneider, and Shang (2004), has helped, in some cases, to reach individual teachers to
gain responses. Nevertheless, researchers will need to work in a sensitive, diligent, and
persistent manner with public school authorities to get permission to complete a study.
The March Goes On: Research Needs
There is a great deal of research in the area of the relationship between building condition
and student and teacher performance and health. Yet there is a need for further research. The
theoretical model that has driven the aforementioned research has not been fully explored.
Studies need to be mounted successively with regard to all the relationships identified in the
theory model. In addition to those relationships that have been initially investigated, there are
some very exciting areas that require attention. Some of the major areas that need new research
efforts are noted in the following paragraphs.
The relationship between fiscal capacity of local school systems and the condition of
school buildings needs to be further studied. Although studies of production function have not
demonstrated overwhelmingly any significant relationship between funds spent and measurable
The Influence of School Building Conditions
August 2011 / ACEF 32
outcomes, there has been some work in Great Britain suggesting that money spent on building
maintenance does have a relationship to student achievement (PricewaterhouseCoopers, 2001).
The relationship between the school leadership and financial ability of the school system to
maintain good school buildings needs further exploration because it represents the point at which
the condition of the school building is normally determined. More research using sophisticated
measures of leadership and financial effort is needed in this area. The amount of money a school
system spends to keep the building in good shape may have a subsequent relationship to student
attitudes and achievement, and this needs more attention.
Further investigations of the possible relationship between school building condition and
student attitudes using the Student School Building Attitude Scale© (Earthman, 2007) are
needed to expand our knowledge of how the physical environment influences student attitudes.
This endeavor should be accompanied by research efforts to investigate the possible relationship
between student attitudes and achievement and behavior.
The influence of the physical environment, as represented by the classroom, upon the
performance and health of the teacher is still rather virgin territory that needs attention because
of the possible stress placed upon teachers. Teachers are being held more accountable for the
progress of students, and the influence of the building upon the performance of a teacher, as well
as the student, should be further explored. Some enlightening evidence has been shed upon this
relationship by Buckley et al. (2004). Their findings indicate that buildings in poor condition
can so influence teachers that there is a high rate of absenteeism and a foreboding loss of
teachers to the profession. These findings are startling and discouraging at the same time.
Additional research regarding the influence of the building upon teacher attitudes and health is
required to validate these findings.
There have been sufficient studies not only in Virginia but also in several other states and
localities, using the same basic methodology and the same instrument to assess the condition of a
school building, that a meta-analysis could be completed. A meta-analysis would provide
considerable insight into the possible relationship between building condition and student
achievement that individual studies cannot. Such a study should have a high priority for
researchers interested in this area of investigation because of the potential for solidifying the
findings of previous studies.
Three rather important instruments have been developed and used in the corpus of
research discussed in this paper. All of these instruments should be further validated and their
reliability further established. The Commonwealth Assessment of Physical Environments© has
successfully been used to evaluate the condition of school buildings. The CAPE has been and is
currently being used in research studies in various states in this country and in at least two
overseas countries. This instrument has been peer validated for content but needs to have
reliability established. The two other instruments were designed and used to measure teacher
and student attitudes about school building condition. The My Classroom Appraisal Protocol©
for teachers and the Student School Building Attitude Scale© have been used successfully in
previous studies. Both of these instruments have been validated by a panel of experts but need to
be submitted to further evaluation for validity and reliability. Research focused on this area of
evaluation is needed.
Case studies of school divisions, examining their operating and capital spending patterns
over a decade, would shed some light on the relationship between capital expenditures and
school building condition. In addition to such studies, a very important area of research would
Lemasters
33 Vol. 1, No. 1, 2011
involve investigation of the politics of decision making related to the funding of school building
maintenance and the condition of school buildings.
It is roughly estimated that during the past year, nine researchers in various states in this
country and one or two in England were conducting studies similar to those discussed in this
paper regarding the relationship between school building condition and student achievement. In
many of these situations, the researcher was using the CAPE and the same basic methodology
used in the original Cash (1993) study. Additional statewide studies of the relationship between
student performance and school building condition are needed to help build a strong corpus of
research findings. At the present time there has been research on the relationship between
building condition and student achievement in seven states plus two major cities. At the end of
2010 the number of studies completed in additional states and cities will be evident. This
activity speaks to the need for a meta-analysis of the studies that have been completed using
similar methodology and comparable data.
All of the aforementioned studies are meaningful examples of research on this subject.
The present cadre of studies provides sufficient evidence that a relationship does exist between
school building conditions and students and teachers, thereby indicating that educational
practitioners should use the results of research to improve school buildings to enhance the
educational opportunities of students attending the schools. Yet, in the best tradition of the
research profession, there is always a need for additional research to strengthen the body of
knowledge regarding these phenomena and to further examine and explain the concepts
contained in the theoretical model. The model presents many relationships between the various
components that need further fruitful investigation. By using a theory-based plan to investigate
sequential elements of a model, researchers are able to focus their efforts and thereby produce
better findings. The key to such a fruitful research program is the element of planning
successfully to arrive at a goal. This planning goal is to fully explore all relationships of the
accepted research model. Systematic planning ensures that such exploration will occur and will,
therefore, better explain how humans work in an organization.
The research presented was derived from one theory-based model that was used to
explain some relationships about school building condition and user health and productivity.
This research was described as an evolving effort of many different researchers from one state.
As such, the corpus of resulting research has but one theme, but several different facets of
research. The main theme might be: ―How do school buildings get in the condition they are in
and how does that influence the users of the building?‖ This might be the most profitable way to
view the research as a total effort to investigate relationships.
The work of these multiple researchers demonstrates that a systematic research program
based upon theoretical concepts and propositions can be developed and maintained. The
researchers in one state were able to produce a research program based upon a single theory to
explain how buildings become what they are and how such structures influence the health and
productivity of students and teachers, and perhaps other users.
The Influence of School Building Conditions
August 2011 / ACEF 34
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August 2011 / ACEF 36
PricewaterhouseCoopers. (2001, January). Building Performance: An empirical assessment of
the relationship between schools capital investment and pupil performance. London,
England: Department of Education and Employment. (ED 461-980)
Ruszala, J. A. (2006). The Teacher Opinionaire of Physical Environment. Unpublished survey
form.
Ruszala, J. A. (2008). The conditions of the high school facilities in the Commonwealth of
Virginia’s metropolitan school divisions and the relationship to teacher satisfaction
(Doctoral dissertation). Retrieved from Dissertation Abstracts International. (UMI
Document ID 3297152)
Shifflett, Jr., D. W. (2009). A study of teacher experience during a renovation project
(Unpublished doctoral dissertation). Virginia Polytechnic Institute and State University,
Blacksburg, VA.
Taylor, R. G. (2009). School facilities in the nation’s capital: An analysis of student
achievement, attendance, and truancy (Doctoral dissertation). Retrieved from
Dissertation Abstracts International. (UMI Document ID 3349627)
Thornton, J. C. (2006). School building condition and student achievement of minority and
economic challenged students in Virginia (Unpublished doctoral dissertation). Virginia
Polytechnic Institute and State University, Blacksburg, VA.
US Department of Education. (2003). No Child Left Behind: Accountability and Adequate Yearly
Progress (AYP). Retrieved from http://www.ed.gov
Weinstein, C. S. (1979, Fall). The physical environment of the school: A review of the research.
Review of Educational Research, 49(4), 577-610.
Whitley, T. A. (2009). The relationship between building expenditures and building conditions
among select school divisions in the Commonwealth of Virginia (Unpublished doctoral
dissertation). Virginia Polytechnic Institute and State University, Blacksburg, VA.
Glen I. Earthman is Professor Emeritus at Virginia Polytechnic Institute and State University
where he continues to advise doctoral students on research. He has also served as the Director of
the US Department of Education sponsored National Clearinghouse for Educational Facilities. His
research interests extend to all phases of school facilities, but he has concentrated on exploring the
relationship between school building condition and student and teacher health and productivity.
Linda K. Lemasters is an Associate Professor of Educational Leadership and Policy Studies at The
George Washington University in Washington, DC. She also serves as Program Coordinator for
Educational Administration and Leadership and is president elect of the International Society for
Educational Planning. Drs. Lemasters and Earthman have worked together on many research
studies about the places where students learn, as well as having authored books and articles on the
same.
TEXAS CENTER FOR
EDUCATIONAL FACILITIES In 2008, Tarleton State University formed a unique
business partnership with a local architectural firm to
create the Tarleton Research Laboratory on Educational
Facilities (TRLEF). The primary goal of TRLEF was to
provide evidence-based research to Texas public schools
regarding the educational impact of facility design on
student learning.
In 2010, TRLEF was awarded a grant from the United
States Department of Education to develop the national
clearinghouse on educational facilities. The American
Clearinghouse on Educational Facilities (ACEF)
provides multiple services regarding the various stages
of facility design, planning, construction, and
maintenance. The website offers three unique access
points to information concerning educational facilities: a
biannual, nationally reviewed journal; research-based
information; and practitioner "craft" knowledge from
various trades. In addition, ACEF provides on-site
trainings, technical assistance, and distance learning
events through applications such as webinars, podcasts,
and blogs.
In 2011 TRLEF was renamed the Texas Center for
Educational Facilities (Facilities Center) by the Texas
A&M University System Board of Regents. The
Facilities Center is a continuation of TRLEF and
manages the federally funded ACEF project. The
Facilities Center is housed in Room 115 of the E.J.
Howell Building on the campus of Tarleton State
University. The Facilities Center operates under the
direction Dr. Mark Littleton, Director, and Dr. Denae
Dorris, Center Manager. The Facilities Center staff
remains committed to providing research that result in
improved physical learning environments to enhance
student engagement and learning.
TCEF Introduction Video by Dr. Mark Littleton,
Program Director [PDF script]
American Clearinghouse
on Educational Facilities
WWW.ACEFACILITIES.ORG
A project of Tarleton State University’s Texas Center for Educational Facilities.
The Educational Facilities Clearinghouse Funded by the United States Department of Education.
Follow ACEF:
Who is ACEF?
The American Clearinghouse on Educational Facilities
(ACEF) is the educational facilities clearinghouse
funded by the United States Department of Education.
ACEF provides the educational community with reliable
resources related to educational facility planning, design,
financing, construction, improvement, operations, and
maintenance of safe, healthy, high performing
educational facilities.
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upon request.
Huston John Gibson The ACEF Journal
Vol. 1, No. 1, 2011, pp. 39-50
39
School Facility Age and Classroom Technology:
The Influence of Stakeholder Participation in the
Technology Planning Process
Abstract
This study begins by examining the relationship between public K-12 school facility age and
student access to modern classroom technological resources, driven by questioning “newer
equals better” assumptions. The method of analysis employed is multivariate cross-sectional
regression. The unit of analysis is the individual school, by school type (elementary, middle,
high). Academic school year 2004/05 data are used. The study geography is the Orlando,
Florida area (Orange and Seminole Counties). The findings indicate that classroom technology
measures, while positively associated with newer school facilities, have no statistically
significant relationship with school facility age. Instead, however, having more participants
involved in the school technology planning process is found to be the most statistically
significant variable included in the model, in relation to greater measures of technology in the
school classroom. These findings are intended relevant for educational facility discourse on
school facility age and classroom technology.
ewer built school facilities are often perceived to be ―better‖ than older school
facilities. Largely, this is due to the assumption that the newest facilities will possess the most
current, and thereby the ―best,‖ technological resources available (Baum, 2004; Briggs, 2005;
Gibson, 2009; Gurwitt, 2004). This ―newer equals better‖ perception transfers into residential
location choice and monetary housing value. In the 2005 Orlando, Florida metro area, newer
schools are found to be significantly positively associated with higher home prices. When all
other attributes are held constant, the 2005 monetary impact of a newer elementary school (built
during the 1990s or 2000s) added $13,130.22 to average housing value, compared to schools
built pre-1990s (Gibson, 2009).
A quality education is a life opportunity for children (Briggs, 2005). Classroom
technological resources are known important factors on student achievements. Betts (1995)
analyzes five years (1987-1992) of the Longitudinal Study of American Youth (LSAY), which
surveys learning environments and assessments for seventh and tenth grade students. The survey
takes place during 1987, at 52 different high and middle schools, in four different regions, and
covered urban, suburban, and rural communities. The purpose of Betts’ study is to investigate
which specific school facility attributes are important to student achievements. Using multiple
regression analysis, Betts (1995) finds that classroom technological resources and teacher
qualifications are the most important influential school attributes on student achievements.
In a study of sixth grade student achievements in the Philadelphia school district,
Summers and Wolfe (1977) found that student inputs, such as socio-economic status (SES), tend
to trump school resources, class sizes, and faculty quality (based on education level) when it
comes to overall student achievements. However, they point out that the schools with more
N
School Facility Age and Classroom Technology
August 2011 / ACEF 40
facility resources, smaller class sizes, and with higher faculty quality do tend to be in
neighborhoods of higher SES make-up and produce greater student performance. They as well
used multiple regression analysis in their study and reported the results for sixth graders.
Cash (1993) compares 43 high schools in rural Virginia between 1991 and 1992 and
found that school facility conditions have an association with 11th grade student achievements.
Her study is later followed by Hines (1996) who compares 66 high schools in urban Virginia.
Hines (1996) also found that school facility conditions have an association with student
achievements. Harter (1999) conducted a Texas statewide study of 2,860 elementary schools
and found that comparatively, the amount of money spent on school renovations has a positive
association with fourth grade student achievements. Morgan (2001), using multiple regression
analysis, looked at 139 elementary, middle, and high schools in Milwaukee, Wisconsin and
found that a school facility’s infrastructure conditions has a relationship with student
achievements for 4th, 8th, and 10th graders on standardized test scores.
Furthermore, there is evidence suggesting that newer school facilities are positively
associated with student performance. When Plumley (1978) investigated the relationship of
school facility age on student achievement for Georgia fourth graders, he found a negative
relationship for older facilities by comparison. Chan (1979) found similar results in his more
robust follow-up study. Chan surveyed principals in Georgia schools containing eighth graders
to assess each school’s ―modernized‖ condition. Comparatively, he found that the more
―modernized‖ schools have greater eighth grade achievements on standardized test scores.
School facility age was found to explain a 3% difference in student achievements in Georgia
schools (McGuffey & Brown, 1978). Studies in Tennessee and Virginia produced similar
findings as well, finding school facility age to inversely correlate with student achievement
(Bowers & Burkett, 1987; Ikpa, 1992). What these studies do not address however is the
relationship between the school facility age and the classroom technology available in that
school; which is at the foundation of the ―newer equals better‖ perception (Baum, 2004; Briggs,
2005; Gibson, 2009; Gurwitt, 2004).
This phenomenon is perhaps best described by Mac McLelland, of the Michigan Land
Use Institute, when discussing new suburban school facilities and growth. He explains that once
a new school is built, families begin to say ―Hey! They’ve got a nice new school, let’s move
there‖ (Gurwitt, 2004, p. 24). The idea here is that these families perceive ―newer‖ as ―better,‖
and will locate residentially to capitalize on the better, newer facility. Briggs (2005) ties this
sentiment, in part, to the unequal [technological] resources assumed to be in the new suburban
school facilities, versus the deteriorating older inner city facilities. Baum (2004) goes one step
further and focuses on the inverse of this notion, turning to school facilities as a tool to manage
suburban expansion. He advocates that if our nation’s inner city schools are renovated when
expanded facilities are needed, instead of building our new schools in peripheral suburban areas,
this will both help curb ―sprawl‖ and address de facto socio-economic segregation in the public
school system. This notion rests on the premise that families who would otherwise move to the
newly built schools in the suburbs, will instead stay in town to attend the improved, newly
renovated inner city schools, with the ―better‖ [technological] resources (Baum, 2004).
Another important factor to consider in regard to school facilities and classroom
technology is the role of stakeholder participation in the strategic planning process. Since the
Coleman (1966) study, local populations are thought to have great influence on their schools. In
order to engage local populations in their communities, since Arnstein (1969), the proper
involvement of stakeholder participation has been at the forefront of community planning
Gibson
41 Vol. 1, No. 1, 2011
discourse. When implemented properly, stakeholder participation in the strategic planning
process is able to produce robust ideas and plans for their respective audiences (Arnstein, 1966;
Briggs, 2003; Bryson, 1995). It is partly due to the notion that the last several decades have seen
much increase in stakeholder engagement in policy planning, moving from traditional ―top-
down‖ practices (Briggs, 2003).
Stakeholder participation and strategic planning promotes tactical thought for purposes of
forward-thinking growth and addressing barriers of institutional challenges, with the hopes of
being tailored to and benefiting all involved. This process is fostered by bringing in outside
input and expertise and keeping organizations and communities current and relevant (Bryson,
1995). It is expected that this benefit will not be lost on educational facility planning.
Methodology
This study addresses the assumption that the newest facilities will possess the most
current, and thereby ―best,‖ technological resources: controlling for stakeholder participation and
other external factors. This study asks: Do newer school facilities comparatively have greater
student access to modern classroom technological resources?
Analysis Plan
To test the function of school facility age on classroom technology, controlling for other
potential influencing factors, a cross-sectional multivariate ordinary least squares (OLS)
regression is employed. Regression analysis is appropriate for this analysis due to the ability of
statistically measuring specific relationships amongst individual variables, while controlling for
external factors (Hoffman, 2004). In this case, the association of school facility age on
classroom technology is being measured, controlling for student population demographics,
stakeholder participation, school funding sources, available technological guidance and training
for teachers, and tech support personnel. The regression model (hereby known as the ―model‖)
is as follows:
classroom technology = B0 + B1(school facility age) + B2(student minority rate) +
B3(Title I status) + B4(stakeholder participation) + B5(funding) +
B6(guidance and training) + B7(personnel) + e
To support the hypothesis that newer school facilities will comparatively have greater
student access to modern classroom technological resources, the coefficient for ―school facility
age‖ should be positive and significantly different than 0 at alpha level .05 in the model
(Hoffman, 2003).
Sample
The unit of analysis is the individual school, by school type (elementary, middle, high).
Elementary pertains to grades ―K‖ (kindergarten) though 5, middle pertains to grades 6 through
8, and high pertains to grades 9 through 12. The study population contains all kindergarten
through 12th grade elementary and secondary public schools in the core Orlando, Florida area
(Orange and Seminole Counties) during school year 2004/05. The Florida Department of
School Facility Age and Classroom Technology
August 2011 / ACEF 42
Education and local public school district data records were used for study. There are 204 total
schools in the study population, consisting of 144 elementary schools, 38 middle schools, and 22
high schools. Of these schools, 59 elementary, 24 middle, and 17 high schools have complete
data for analysis; and thereby constitute the study sample.
Variables
The System for Technology Accountability and Rigor (STAR), under the operation of the
Florida Department of Education (FL-DOE), administrates a statewide school technology survey
in October/November of each year. For analysis, classroom technology is the dependent variable
in the model. Classroom technology is the ratio of modern computers (less than five years old at
the time of survey that were internet and multimedia capable) in the school’s classrooms for
student use, divided by the student enrollment at the time of the survey. Students spend the
majority of their time in ―regular‖ educational classrooms as opposed to other locations, such as
computer labs or media centers, and therefore Florida Innovates, the direct administrators of the
STAR survey, advocate that this figure is the best survey indicator of student technology access,
as a snapshot of how technology is integrated into daily curriculum by way of indicating of how
much technology students have access to during the bulk of the school day.1
The average classroom technology ratio for elementary schools in the study population is
.13 modern computers per student, with a standard deviation of .10 modern computers per
student (N = 144). The lowest classroom technology ratio is zero modern computers per student,
the highest .53 modern computers per student. The average classroom technology ratio for
middle schools in the population is .11 modern computers per student, with a standard deviation
of .10 modern computers per student (N = 38). The lowest classroom technology calculated
index figure is zero modern computers per student, the highest .39 modern computers per
student. The average classroom technology ratio for high schools in the population is .09
modern computers per student, with a standard deviation of .08 modern computers per student
(N = 22). The lowest classroom technology ratio is zero modern computers per student, the
highest .36 modern computers per student. In other words, on average there are roughly 10
students per modern computer in the overall population’s school classrooms; but there is a wide
range of deviation between individual schools within all three school types, from no modern
computers at all, to two or three students per computer. In all three cases there is a positive
skew, but due to the central limit theorem this is not a problematic analytic concern (Agresti &
Finlay, 1997).
The primary independent variable of interest is school facility age. This variable is
calculated in two ways. First, the year the school building originally was built or fully re-built is
determined. Respectively, this is referred to as the ―built‖ age. Second, the averaged overall age
of the facility is determined. This is referred to as the ―effective‖ age. The Florida Department
of Education (2008a, 2008b), Florida Inventory of School Houses (FISH), Facility Inventory
Report is reviewed to calculate facility ages. The built age is simply the year the school facility
opened or re-opened (if re-built). The effective age is an addition and division of facility square
feet by years (plural) built. For example, if a 20,000 square foot facility was originally built in
1950 and then a 20,000 square foot addition was added in the year 2000, if no other
1 This is based on telephone and email correspondence with a Florida Innovates Program Specialist.
Gibson
43 Vol. 1, No. 1, 2011
improvements were made to the building during this time, the effective age is 1975 ([(20,000 *
1950) + (20,000 * 20000) / 40,000] = 1975). The built age in this example is 1950.
At the time of the study, the average area elementary school in the study population was
built in 1975, with a standard deviation of 19.25 years (N = 144). The oldest elementary school
was built in 1924, and the newest was built in 2005. The average middle school was built in
1982, with a standard deviation of 20.59 years (N = 38). The oldest middle school was built in
1926, and the newest was built in 2005. The average high school was built in 1979, with a
standard deviation of 16.18 years (N = 22). The oldest high school was built in 1951, and the
newest was built in 2003.
The average elementary school effective year is 1982, with a standard deviation of 14.23
years (N=144). The oldest effective year is 1943, the newest 2005. The average middle school
effective year is 1988, with a standard deviation of 12.15 years (N = 38). The oldest effective
year is 1968, the newest 2005. The average high school effective year is 1988, with a standard
deviation of 8.69 years (N = 22). The oldest effective year is 1971, the newest 2003.
Diagnostics demonstrate that overall the effective school facility age has a more direct
linear relationship with classroom technology when compared to the built school facility age for
all three school types, due to less clustering. This relationship is mild at best; yet variable
transformations result in no substantial improvements. As a result, only effective school facility
age is included for analysis.
Besides effective school facility age, conceptualized control variables are included to
account for other possible influences on school classroom technology provision. Chiefly, these
variables are intended to address possible issues of demographic and administrative
discrepancies between schools.
First, school student minority rate and Title I status are included to control for
student/neighborhood characteristics. Race has long been a part of the discourse on public
school equality (Briggs, 2005; Coleman, 1966). The school’s student minority rate measures the
school’s race composition by reflecting the percentage of students who are not listed as ―White,
non-Hispanic.‖ This information is published annually in the School Accountability Reports
(Florida Department of Education, 2004, 2005b). The average area student minority rate for
elementary schools in the study population is 61.98%, with a standard deviation of 23.42% (N =
144). The lowest student minority rate is 12.5%, the highest 100%. The average student
minority rate for middle schools is 59.49%, with a standard deviation of 21.67% (N = 38). The
lowest student minority rate is 25.4%, the highest 98.1%. The average student minority rate for
high schools is 55.78%, with a standard deviation of 21.51% (N = 22). The lowest student
minority rate is 24.4%, the highest 95.5%.
Alongside race, socio-economic status has also been a major part of the public school
equality discourse (Briggs, 2005; Coleman, 1966). By definition, Title I schools are those that
have been identified under Title I of the federal Elementary and Secondary Education Act of
1965 as ―disadvantaged‖ and ―in need of improvement‖ (U.S. DOE, 2008, 2009). By default,
the Title I label of a school serves as a proxy for low student income composition. In the study
population, 36% of the elementary schools are Title I (N = 144), 29% of the middle schools are
Title I (N = 38), and 4% of the high schools are Title I (N = 22).
Who the stakeholders in a process are (stakeholder participation) will likely have great
influence on the outcome. Thus stakeholder participation is accounted for in the model. For
analysis, the stakeholders in schools’ technology planning processes are measured as a
percentage of participation by stakeholder type. The Florida STAR Survey asks each school to
School Facility Age and Classroom Technology
August 2011 / ACEF 44
indicate which stakeholders were involved in their school’s technology planning process (Florida
Department of Education, 2005a). The options to select from are 1) administrators, 2) business
leaders, 3) community members, 4) consortia, 5) district technology leaders, 6) parents, 7)
students, 8) teachers, 9) technology specialists, or none. For the purposes of the model, these
variable categories are first tested as dummy variables to see if the presence of any particular
party has a significant association, and then the number of ―checked‖ categories are added to
form a participation score (0-9). This value is entered into the model to assess if there is positive
or negative association of having more or less participants. Data are not available for all schools
in the study population for this variable.
The average stakeholder participation calculated index figure for elementary schools in
the study sample is 3.74, with a standard deviation of 1.32 (N = 91). The lowest stakeholder
calculated index figure is one, the highest nine. The average stakeholders calculated index figure
for middle schools is 4.03, with a standard deviation of 1.35 (N = 30). The lowest stakeholders
calculated index figure is one, the highest nine. The average stakeholder calculated index figure
for high schools is 4.22, with a standard deviation of 1.52 (N = 18). The lowest stakeholders
calculated index figure is two, the highest eight.
Another possible influence to technology is a school’s monetary funding. The STAR
survey asks each school to identify any additional technology funding sources (other than funds
generally provided from the school district, including sales tax proceeds), again selecting from a
provided list. This list includes 1) business partnerships, 2) district grants, 3) donations, 4)
federal or state grants, 5) foundations, 6) fund-raisers, 7) private grants, 8) Parent-Teacher
Organizations (PTOs) or other school-related ―booster‖ organizations, 9) A+ / school recognition
funds, 10) profits from school ventures such as cell towers, after-care, vending machines,
yearbook sales, etc., 11) Title I money, 12) additional district sanctioned school improvement
funds, and 13) other. Again, for the purposes of the model, these variable categories are first
tested as dummy variables to see if the presence of any particular party has a significant
association, and then the number of ―checked‖ categories are added to form a participation score
(0-13). This value is then entered into the model to assess if there is a positive or negative
association of having more or less funding sources.
The average funding calculated index figure for elementary schools in the population is
2.81, with a standard deviation of 2 (N = 144). The lowest funding calculated index figure is
zero, the highest eight. The average funding calculated index figure for middle schools is three,
with a standard deviation of 1.66 (N = 38). The lowest funding calculated index figure is zero,
the highest six. The average funding calculated index figure for high schools is 3.31, with a
standard deviation of 2.46 (N = 22). The lowest funding calculated index figure is zero, the
highest nine.
User (teacher) instruction is controlled for with the addition of a technology guidance
and training measure. The STAR survey asks each school to select which guidance and training
options the school’s instructional technology specialists (whoever they may be) provides. The
options to select from are 1) guidance for teachers in directing student use of technology in class,
2) guidance for teachers in using technology to prepare and deliver lessons, 3) modeling
technology integration, 4) technology skill training for teachers, 5) technology support to
administrators, or none. These variable categories are first tested as dummy variables to assess if
the presence of any particular party has a significant association, and then the number of selected
categories is added to form a guidance and training score (0-5). This value is then entered into
Gibson
45 Vol. 1, No. 1, 2011
the model to assess if there are positive or negative associations of having more or less guidance
and training options.
The average guidance and training calculated index figure for elementary schools in the
study population is 1.34, with a standard deviation of 1.34 (N = 97). The lowest guidance and
training calculated index figure is zero, the highest five. The average guidance and training
calculated index figure for middle schools is 4.11, with a standard deviation of 1.23 (N =2 8).
The lowest guidance and training calculated index figure is zero, the highest five. The average
guidance and training calculated index figure for high schools is 4.33, with a standard deviation
of 1.11 (N = 21). The lowest guidance and training calculated index figure is two, the highest
five.
Finally, whether or not a school has dedicated technical support (personnel), as opposed
to a faculty member with other responsibilities may also reasonably influence classroom
technology use in daily activities, and thereby the technology capacity as measured by the
classroom technology variable, again do to user (teacher) resources. The tech personnel variable
is a choice of 1) faculty member with other responsibilities, 2) part-time dedicated, but not an
additional staff/faculty member, 3) full-time dedicated, but not an additional staff/faculty
member, and 4) full-time dedicated, additional staff/faculty member, or none. Because this is not
an accumulative variable as with the previous technology measures, for the purposes of the
model, these variable categories are only tested as dummy variables to assess if any particular
personnel type has a significant association to the classroom technology measure. Having no
personnel ―none‖ is the reference category in the model.
For comparative purposes, the average personnel calculated index figure for elementary
schools in the study population is 2.74, with a standard deviation of .82 (N = 144). The lowest
personnel calculated index figure is zero, the highest four. The average personnel calculated
index figure for middle schools is 2.86, with a standard deviation of .88 (N = 38). The lowest
personnel calculated index figure is zero, the highest four. The average personnel calculated
index figure for high schools is 3.45, with a standard deviation of .51 (N = 22). The lowest
personnel calculated index figure is three, the highest four.
Diagnostics and Adjustments
Ordinary Least Squares (OLS) assumptions are checked prior to analysis. Besides
dropping built school age from the analysis in favor of effective school facility age, no further
issues with the model are identified. In addition, the robust standard errors are used to down-
weigh any possible unknown influential observations in the regression, allowing cautious and
conservative inferences to be concluded from the findings (Chatterjee & Hadi, 2006; Hoffman,
2004). Finally, as noted in the sample description, only complete cases are included for analysis.
Findings
Regression outputs are examined for all model variables, on classroom technology, for all
three separate school types (elementary, middle, and high); displayed in Table 1 and explained in
the following text. The overall model has the most collective explanatory power at the middle
school level, explaining approximately 64% of variation in classroom technology (R-squared
.6363). The model’s explanatory value at the high school level is approximately 46% (R-squared
.4609), and 13% (R-squared .1316) at the elementary school level. However, within the model,
School Facility Age and Classroom Technology
August 2011 / ACEF 46
only one variable, stakeholder participation, emerges as being a significant individual predictor
for classroom technology.
The quantity of stakeholders in the technology planning process is statistically significant
(p < .05) at the elementary and middle school levels. This predictor has a positive directional
relationship to the classroom technology measure for all school types (elementary .018172,
middle .048035, and high .006564). Notably, at the high school level, while the stakeholder
participation coefficient displays a positive direction in regard to classroom technology, it is not
statistically significant in the model. This could, in part, be due to the smaller sample size for
high schools.
Table 1
Regression Outputs of School Facility Variables on Classroom Technology by School Type
Variable Coefficients
Elementary Middle High
School facility (effective] age .000643 .000623 .003374
Student minority rate .000747 .001798 .002251
Title I status schools versus non-Title I status
schools .012253 .084990 -.048672
Stakeholder participation .018172* .048035* .006564
Funding -.004604 .008850 .008057
Guidance & training .004579 .005766 .016098
(Personnel Category 1)
Faculty member with other responsibilities
versus dedicated full-time staff member .007141 -- --
(Personnel Category 2)
Part-time dedicated, non-staff/faculty member
versus dedicated full-time staff member -.026022 -.002438 --
(Personnel Category 3)
Full-time dedicated, non-staff/faculty member
versus dedicated full-time staff member -.048431 -.033886 .024705
Note: N for Elementary = 59; Middle = 24; High = 17; ―--‖ = no observations
R-squared for Elementary = .1316; Middle = .6363; High = .4609; *Significance at the .05 level
Interestingly, no one particular category of stakeholder emerges as being more important
than another. Thus while it may not be concluded which specific stakeholders are the most
Gibson
47 Vol. 1, No. 1, 2011
influential from these results, it may be inferred that an increase in stakeholder participation is
related with an increase in classroom technology at the associated school facility.
Specifically, this indicates that with each added stakeholder participant in the school
technology planning process, there is a slight increase in the ratio of modern computers per
student in that respective school. For this sample, this ratio statistically equates to .02 modern
computers per student per added stakeholder participant at the elementary school level, and .05
modern computers per student per added stakeholder participant at the middle school level.
Thus, while this association is effectively small in size, it is of larger significance, empirically
indicating that simply getting multiple/more parties involved in a planning process will influence
its outcome towards a stated goal (in this case, technology in school facilities).
Contrarily, the effective school facility age is not statistically significant in the model for
any school type. Based on this finding for effective school facility age, along with the lack of
virtually any linear relationship between built school facility age and classroom technology in
the study sample, it is reasonable to conclude that a school’s facility age has little, if any relation
to classroom technology available in the 2005 Orlando, Florida area studied.
Also of importance, neither school student minority rate nor Title I status show to be
positively associated with classroom technology for any school type. Perhaps the presence of
available grants and funds specifically targeted for minority and lower socio-economic
neighborhoods to enact improvement programs are accountable for this finding. The number of
funding sources is also not statistically significant for any school type. It is expected that this
result may be interpreted to mean that the ―quality‖ of the actual funding source is more
important than the sheer number of sources. Although, no one particular source type emerges as
being of consistent statistical significance either. Thus, likely, this is a case by case issue. As
well, the amount of guidance and training provided does not show statically significance; with no
one particular type of guidance and training practice emerging as being consistently, statistically
significant. Finally, the type of technology personnel available also produces no signs of
statistical significance, with no type, not even a dedicated full time staff member, being
statistically more important than the other in regard to classroom technology level at a given
school. However, notably, not all types of technology personnel are present at each of the three
school levels in the model.
In summation, the best explanatory variable in the model for determining the level of
classroom technological resources in a given school facility available for student access is the
amount of overall stakeholder participation in the school’s technology planning process.
However, the lack of statistical significance for school facility age, student race and socio-
economic characteristics, funding sources, the amount of guidance and training offered to
teachers for the use of technology, and the level of technology assistance available to teachers is
just as fundamental of a finding to educational facility discourse on technology.
Conclusion
Finding classroom technology to have no relationship with school facility age is contrary
to the expectations of ―newer equals better‖ (Baum, 2004; Briggs, 2005; Gibson, 2009; Gurwitt,
2004). A logical explanation for this is that individual school policies will influence school
technology levels more so than does facility age. For example, a principal of a school will
receive a budget, then it is decided whether to spend that money on new computers or new
playground equipment. Therefore it is the principal and other decision-makers, not the age of the
School Facility Age and Classroom Technology
August 2011 / ACEF 48
facility, which will have the most influence over the school’s classroom technological resources.2
This is likely why it is found that schools with more stakeholder participants in the school
technology planning process have greater classroom technology resources in this study,
regardless of the age of the school facility, or other controlled factors.
Discussion
There possibly may be several explanations of why more modernized computers per
student are found in schools with greater stakeholder participation in this study. Perhaps most
significantly is a self-selection bias and the strength of numbers. These are voluntary
stakeholders in a school’s technology planning process. Thus, it is highly likely that the
involved stakeholders are advocates for technology, which is perhaps why they chose to become
involved in the first place. Their reason to advocate such belief is likely based on the
understanding that technology is an influential tool for student achievement (Betts, 1995).
None-the-less, the found relationship between the quantity of stakeholders in the school
technology planning process and the amount of classroom technological resources available at
that school is of the utmost importance. This empirically indicates that the act of getting
multiple parties involved in a planning process, or not, is influential to its outcome. The
implications of this can be quite widespread. Ideally, the inclusion of various stakeholders in a
decision-making process will result in outcomes that best represent the desires of the collective
community. This is not a new concept, as citizen participation in the community planning
process has been advocated for quite some time, and has become a fairly mainstream notion in
the community planning field (Arnstein, 1969; Briggs, 2003). This is likely due to the
appreciation of the stakeholder regarding their involvement, causing greater ―buy in;‖ being seen
as more ―democratic‖ in nature than top-down planning; and the simple fact that the inclusion of
external forces will bring new ideas to the table (Briggs, 2003). However, the empirical
evidence of this notion is not as abundant.
In the end though, intended for the discourse on public K-12 educational facilities, it is
seen that ―newer does not necessarily always equal better,‖ at least not in terms of classroom
technological resources; busting the myth of ―newer equals better‖ assumptions.
References
Agresti, A., & Finlay, B. (1997). Statistical methods for the social sciences (3rd ed.). Upper
Saddle River, NJ: Prentice Hall.
Arnstein, S. R. (1969). A ladder of citizen participation. Journal of American Institute of
Planners, 35(4), 216-224.
Betts, J. R. (1995). Does schools quality matter? Evidence from the National Longitudinal
Survey of Youth. Review of Economics and Statistics, 77, 231-250.
Baum, H. S. (2004). Smart growth and school reform: What if we talked about race and took
community seriously. Journal of the American Planning Association, 70(1), 14-26.
Bowers, J. H., & Burkett, G. W. (1987). Relationship of student achievement and characteristics
in two selected school facility environmental settings. 64th Annual International
conference on the Council of Educational Facility Planners, Edmonton, Alberta, Canada.
2 This is based on post analytic conversations with Florida public elementary school administrators, faculty, and
staff who are involved in the technology planning process at their respective schools.
Gibson
49 Vol. 1, No. 1, 2011
Briggs, X. (2003). Planning together: How (and how not) to engage stakeholders in charting a
course. Cambridge, MA: The Community Problem-Solving Project at MIT.
Briggs, X. (Ed.). (2005). The geography of opportunity: Race and housing choice in
metropolitan community. Washington, DC: Brookings Institution Press.
Bryson, J. (1995). Strategic planning for public and nonprofit organizations. San Francisco:
Jossey Bass.
Cash, C. (1993). Building conditions and student achievement and behavior. (Doctoral
dissertation, Virginia Polytechnic Institute and State University, 1993).
Chan, T. C. (1979). The impact of school building age on pupil achievement. Greenville, SC:
Office of School Facilities Planning, Greenville School District.
Chatterjee, S., & Hadi, A. S. (2006). Regression analysis by example. Hoboken, NJ: John Wiley
and Sons, Inc.
Coleman, J. S. (1966). Equality of educational opportunity (Coleman) study (EEOS). United
States Department of Health, Education, and Welfare, Office of Education / National
Center for Education Statistics, producer. 1999. Washington, DC. Inter-university
Consortium for Political and Social Research, distributor. 2000. Ann Arbor, Michigan.
Florida Department of Education. (2004). School accountably reports. Retrieved from
http://schoolgrades.fldoe.org/default.asp
Florida Department of Education. (2005a). Florida STAR Survey. Retrieved from www.flstar.org
Florida Department of Education. (2005b). School accountably reports. Retrieved from
http://schoolgrades.fldoe.org/default.asp
Florida Department of Education. (2008a). Florida Inventory of School Houses (FISH), Facility
Inventory Reports. Received via email from the Orange County School Board.
Florida Department of Education. (2008b). Florida Inventory of School Houses (FISH), Facility
Inventory Reports. Received via email from the Seminole County School Board.
Gibson, H. J. (2009). Perceived school quality and its effect on monetary housing value: School
facility age and its association with housing sale price. (Doctoral dissertation, Florida
State University, 2009).
Gurwitt, R. (2004, March). Edge-ucation: What compels communities to build schools in the
middle of nowhere? Governing: The Magazine for State and Localities, 22-26.
Harter, E. A. (1999). How education expenditures relate to student achievement: Insights from
Texas elementary schools. Journal of Education Finance, 24(3), 281-302.
Hines, E. (1996). Building condition and student achievement and behavior. (Doctoral
dissertation, Virginia Polytechnic Institute and State University, 1996).
Hoffman, J. P. (2004). Generalized linear models: An applied approach. Boston, MA: Pearson
Education Inc.
Ikpa, V. W. (1992). The Norfolk decision: The effects of converting from a unitary educational
system to a dual educational system upon academic achievement. Norfolk, VA: Norfolk
City Schools.
McGuffey, C. W., & Brown, C. L. (1978). The impact of school building age on school
achievement in Georgia. CEFPI Journal, 16, 6-9.
Morgan, L. (2001). Facility conditions and student test performance in the Milwaukee schools.
Scottsdale, AR: Council of Educational Facilities Planners International.
Plumley, J. P. (1978). The impact of school building age on the academic achievements of
selected fourth grade pupils in the State of Georgia. Athens, GA: University of Georgia.
School Facility Age and Classroom Technology
August 2011 / ACEF 50
Summers, A. A., & Wolfe, B. L. (1977). Do schools make a difference? The American Economic
Review, 67(4), 639-652.
U.S. Department of Education. (2008). Title I - Improving the academic achievement of the
disadvantaged. Retrieved from www.ed.gov/policy/elsec/leg/esea02/pg1.html
U.S. Department of Education. (2009). Title I - Improving the academic achievement of the
disadvantaged. Retrieved from www.ed.gov/policy/elsec/leg/esea02/pg1.html
Huston John Gibson has a Ph.D. in Urban and Regional Planning and is an Assistant Professor in
the Department of Landscape Architecture/Regional and Community Planning in the College of
Architecture, Planning & Design at Kansas State University. To complete his doctoral studies,
Gibson’s dissertation (2009) investigated perceived school quality and its effect on monetary
housing value via school facility age and its association with housing sale price; this is an extension
from that work.
Martin Eugene Sheets THE ACEF JOURNAL
Vol. 1, No. 1, 2011, pp. 51-65
51
The Relationship between the Conditions of Rural High School Facilities and Certain
Educational Outcomes
Abstract
In the era of high stakes accountability, educational leaders must explore all factors that affect
student achievement. If the condition of facilities in some schools is such that the schools cannot
provide a quality education for its students equal to that of other schools, then equal educational
opportunity may not be available for all children. The purpose of this study is to examine the
relationship between the condition of rural public high school facilities in Texas and the
educational outcomes of student achievement, student attendance, and teacher turnover, while
considering the effects of the demographic variables of student wealth level (percentage of
economically disadvantage students), school district wealth level (property value per student),
and percentage of minority students. The measures for the condition of facilities variables used
in this study were obtained from the 2006 Texas Comptroller’s Facility Survey of the 1,037
public school districts in Texas.
The participants for this study were all from the 73 rural public high schools that responded to
the survey. The measures for the demographic variables and educational outcome variables
used in this study were obtained from the 2006 Academic Excellence Indicator System (AEIS)
report from the Texas Education Agency. Multiple regression analyses were utilized to examine
which selected condition of facility variables and demographic variables best predicted certain
educational outcomes. This study found that the condition of school facilities does affect student
achievement, teacher turnover, and student attendance, particularly when found in schools made
up of primarily low-income students. A large percentage of portable classrooms lowers student
achievement and leads to higher teacher turnover. Overcrowded schools lead to lower student
achievement and lower student attendance rates. A large amount of deferred maintenance leads
to lower student achievement. Excellent facilities for children who need them the least and
inadequate facilities for the ones who need them the most violates the principal of equal
educational opportunity for all. Equitable public education is the civil rights issue of the 21st
century. Policy makers and educational leaders have a responsibility for providing a quality
education system for all children.
Introduction and Problem Statement
he mission of public education in Texas is to ―ensure that all Texas children have
access to a quality education that enables them to achieve their potential and fully participate
now and in the future in the social, economic, and educational opportunities of our state and
nation‖ (Texas Education Code, Chapter 4.001). Quality school facilities for the privileged and
inadequate school facilities for the disadvantaged undermine the mission of the Texas Education
Code.
The vision of the original Common School Movement stressed the need for a public
school system that ―generates the informed citizenry needed for democratic government,
embraces the welfare of all children in the nation, upholds the ideal of equal opportunity, and
T
The Relationship
August 2011 / ACEF 52
stresses the belief that public education can and should provide a level playing field‖ (Biddle &
Berliner, 2002, p. 58).
Statement of the Problem
Many people believe that education and learning can happen anywhere. Place does not
matter. A good teacher can teach students no matter what the setting. Although there is some
validity to these statements, researchers are beginning to find that place does matter. An
extensive review of literature suggests that the school environment may have as much effect on
student achievement as the influences of family background, socio-economic status, school
attendance, and behavior combined (Lyons, 2001). One study noted that the school is a
―physical representation of a public message about the value of education‖ (Cash, 1993, p. 83).
This study adds to the body of research literature by exploring the possible relationship between
the condition of school facilities and certain educational outcomes, particularly in rural high
schools.
Significance of the Study
This study is important, because there have been very few studies done in Texas on the
relationship between the condition of school facilities and certain educational outcomes. This
study is the first of its kind to use data collected in a survey of all of the school districts in the
entire state of Texas conducted by an official state agency, the Texas Comptroller of Public
Accounts.
Educational leaders are constantly trying to find ways to increase the academic
achievement of their students. Earthman (1998) found that there is an educational disadvantage
of 5 to 17 percentile points on standardized tests for students housed in poor quality facilities
compared to high quality facilities. School officials do not have much control over some factors
that may impact student achievement. However, the condition of school facilities can be
controlled by school officials. Improving the condition of school facilities is one way that
educational leaders can have a positive impact on student learning and academic performance.
Theoretical Framework
A theoretical model showing a relationship between the condition of school facilities and
student outcomes was first designed by Cash (1993). The theoretical model in this study utilizes
a simplified version of Cash’s basic model, but adds the variable Teacher Turnover as one of the
educational outcomes (Figure 1).
Purpose of the Study
The purpose of this study is to examine the relationship between the condition of rural
public high school facilities in Texas and the educational outcomes of student achievement,
student attendance, and teacher turnover, while considering the effects of the demographic
variables of student wealth level (percentage of economically disadvantage students), school
district wealth level (property value per student), and percentage of minority students.
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53 Vol. 1, No. 1, 2011
Figure 1
Theoretical Model Used in This Study
Research Question
What is the relationship between the condition of school facilities and certain educational
outcomes, particularly in rural Texas public high schools?
Review of the Literature
Condition of School Facilities
The condition of school facilities nationwide is one of deterioration and obsolescence.
President Bill Clinton, in his 1997 State of the Union Address, stated that ―we cannot expect our
children to raise themselves up in schools that are literally falling down. With the student
population at an all-time high, and record numbers of school buildings falling into disrepair, this
has now become a serious national concern‖ (Clinton, 1997, para. 39).
The National Center of Education Statistics (1999) reported the average age of public
school buildings in the United States in 1998 was 42 years old. School buildings begin rapid
deterioration when the buildings are over 40 years old, and most schools are abandoned after 60
years (Ornstein, 1994).
In 1995, the General Accounting Office conducted a survey of the facilities needs of
school districts in the United States. The study documented widespread physical deficiencies in
many school facilities across the country. One of the most disturbing findings was that the most
likely students to attend the most inadequate facilities were the academically neediest students—
minorities and low-income students (General Accounting Office, 1995).
Older school facilities are more prevalent in schools with a higher percentage of low-
income children than those with a higher percentage of high-income children. A higher
proportion of children in poverty enroll in the oldest school buildings in the United States.
Twenty percent of schools with high-income students were built before 1950. However, 33% of
Demographic Characteristics
Leadership
Condition of School Facilities
Student Achievement
Teacher Turnover
Student Attendance
Financial Ability
The Relationship
August 2011 / ACEF 54
schools with low-income students were built before 1950 (National Center for Educational
Statistics, 1999).
Overcrowded Facilities
The National Center for Educational Statistics (2000) reported that one in four public
schools are overcrowded. Earthman (2002) found that overcrowded school facilities have a
negative influence on student performance of low-income and minority students.
In a survey of teachers in overcrowded New York City public schools, teachers said that
overcrowding and lack of space was a higher priority to address than sanitation, maintenance,
violence, and other issues. Seventy percent of the teachers also said that overcrowding was
leading to staff burnout (Rivera-Batiz & Marti, 1995).
General Condition
As the condition of school facilities improve, so do the average student achievement
scores. A study of public schools in the District of Columbia in 1991 found that as a school
facility improved its general condition from poor to excellent, the average achievement score
increased 10.9 points (Earthman, 2004).
A study of rural high schools in Virginia compared the ITBS scores of students with the
condition of school facilities. The condition category of the facilities were substandard,
standard, and above standard. The study found that test scores of student in school facilities
rated as above standard were as many as five percentage points above the scores of students in
school facilities rated as poor (Cash, 1993).
Portable Classrooms
Chan (2005) studied the use of portable classrooms in 11 Georgia elementary schools and
found the physical conditions of portable classrooms were inferior to that of permanent
classrooms. Most of the portable classrooms in the study were poorly configured, lacked internet
access, and were overcrowded.
The use of portable classrooms to address overcrowded conditions in schools affects
property-poor school districts to a greater degree than property-wealthy school districts. In a
study of Nebraska school facilities, Pool (1993) reported that school districts with low property
value per student had more portable facilities than school districts with high property value per
student.
Age of School Facilities
More students in rural areas attend schools with school facilities over 50 years old than
do students in suburban areas. In addition, schools with an enrollment of over 50% low-income
students generally have older facilities than do schools with an enrollment of less than 50% low-
income students (National Center for Education Statistics, 1999).
Bowers and Burkett (1988) studied the relationship of school facility age and student
achievement using two elementary school facilities from the same school district in rural
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55 Vol. 1, No. 1, 2011
Tennessee. Bowers and Burkett (1988) concluded that a relationship did exist between the
physical environment and student achievement, health, attendance, and behavior.
Number of Years since Last Renovation
One of the most reliable indicators of the true age of school facilities is the number of
years since its last major renovation. The age of school facilities is usually an accurate indicator
of the condition of the facilities. Older school facilities do not usually have the building features
of newer school facilities such as adequate classroom spaces, new technology infrastructure, and
energy efficient environmental systems. However, major renovation of older school facilities
can transform obsolete facilities into school facilities that are comparable to the newest facilities.
The lack of major renovation of older school facilities greatly restricts the school’s ability to
meet the current needs of students.
Schools that have not renovated older facilities in recent years will face difficulty in
improving their educational programs. The National Center for Education Statistics (1999)
reported statistics on the year that schools underwent their last major renovation. About three-
fourths of public schools in America have undergone at least one major renovation. Seventeen
percent of schools reported last undergoing a major renovation prior to 1980; 17% reported the
last major renovation between 1980 and 1989; and 39% reported the last major renovation
between 1990 and 1995. The study reported that the year since the last major renovation is not
significantly related to student enrollment, locale, or region.
The date of the last major renovation is important for policymakers to consider when
evaluating whether or not school facilities are equipped to meet world class standards. Older
school facilities must be renovated to allow for new technology infrastructure, adequate space for
new instructional techniques, and energy efficient environmental systems.
Deferred Maintenance
Many school districts facing aging facilities simply put off performing critical facility
maintenance and upgrades due to a lack of funding. Deferred maintenance will result in higher
facility construction costs over time and, ultimately, will result in inadequate educational
facilities for children (Rees, 2004).
Deferred maintenance is a concern, especially for rural school districts. Rural school
districts are constructing new school buildings and upgrading old ones at a slower rate than non-
rural districts. From January 1994 to June 1998, about ―21 percent of districts in urban areas
constructed at least one new school compared to only nine percent of districts outside of urban
areas‖ (Dewees & Earthman, 2000, p. 12).
Rural school districts have little capacity to support bonds that fund facilities upgrades.
Rural districts are in communities with small population, inadequate tax bases, and regulatory
limits to their debt. These factors ―restrict their ability to generate the revenues required to build
school facilities‖ (Dewees & Earthman, 2000, p. 11). A declining enrollment translates into
fewer taxpaying citizens. Fewer taxpayers mean less revenue capacity available for supporting
bonds to update facilities.
In Texas, state statutes prohibit some small, rural school districts from incurring debt
sufficient to replace existing facilities. Long-term debt for school districts that receive state
The Relationship
August 2011 / ACEF 56
assistance from the Instructional Facilities Allotment is limited by the greater of $100,000 per
year or $250 per student in average daily attendance per year (Texas Education Agency, 1997).
Some small school districts may not have the capacity to incur the debt they need because
of the lack of student population. Small schools that receive state assistance by participating in
the Existing Debt Allotment program are limited to a debt tax rate that may not exceed $.29 per
$100 of valuation (Texas Education Agency, 1999).
Policy makers must address the difficulty rural schools face with regard to facilities, or
these school districts will continue to put off critical facility upgrades. Many rural schools have
facilities that are in great need of repair or replacement; yet, some school districts lack the
capacity to raise the necessary funds to solve these facilities’ needs. This lack of capacity
contributes to the inequities in school facilities funding (Texas Education Agency, 1997).
Demographic Characteristics of Schools
School district wealth level. The quality of school facilities should not depend on the
wealth of the local community. However, public schools in Texas receive more than half of their
funding from local property taxes. High-wealth school districts have more capacity to finance
major facility renovations and new facilities than low-wealth school districts. When school
facilities funding is based on local property wealth, there will be inequities in the condition of the
school facilities. Low-wealth school districts tend to have relatively high tax rates and low
education expenditures, while high-wealth school districts tend to have low tax rates and high
education expenditures.
Low-wealth school districts face a greater challenge of updating school facilities than
schools in more affluent districts. A survey of school principals in New Jersey revealed
significant disparities in the overall condition and overall educational adequacy in low-wealth
school districts when compared to other school districts (Schneider, 2002).
Minority students. Pastor and Reed (2005) examined school facilities in California and
found that there are three times more minority students enrolled in critically overcrowded
schools than white students. Overcrowding is an important condition of school facilities,
because Earthman (2002) found that overcrowded school facilities have a negative effect on
student performance of minority students.
Texas must allocate the educational resources necessary to provide equal educational
opportunity to minority children. It is very difficult to say that all children have equal
educational opportunities when resources are distributed inequitably for minority children.
Earthman (2002) found that old, inadequate, and overcrowded school facilities have a
negative influence on student performance of low-income students. Poor conditions of school
facilities constitute major barriers in education that directly affect opportunities for low-income
students to learn and achieve at levels equal to those of other students.
Rural school facilities. Texas has the ―largest number of rural students attending the
largest number of rural schools‖ (Stern, 1994, p. 15). One of the critical building features that
rural schools lack is the infrastructure necessary for modern technology. Nearly half of rural
schools have six or more unsatisfactory technology elements (Dewees & Earthman, 2000).
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57 Vol. 1, No. 1, 2011
Educational Outcomes
Student achievement. Several studies have shown that there is a relationship between
the condition of school facilities and student achievement. A study of the Houston ISD reported
that schools with roofs in ruin, schools that rely on temporary buildings instead of permanent
structures, and schools with understaffed custodial services provide an environment where
students are less likely to attend school and more likely to drop out (Branham, 2004).
Teacher turnover. The quality of a school’s infrastructure may have a significant
impact on teacher retention and teacher turnover. Buckley, Schneider, and Shang (2004) found
that the impact of facility improvement on teacher retention is equal to or greater than the impact
of pay increases for teachers. Studies of teacher satisfaction in developing nations also show that
improvement in the quality of facilities was found to offset low wages. School districts with
inadequate facilities are less likely to attract and retain teachers (Schneider, 2004).
Student attendance. One of the first studies on the relationship between the condition of
school facilities and student attendance concluded that there was a relationship between the
condition of school facilities and student achievement (Bowers & Burkett, 1988).
Branham (2004) also concluded that a school that utilizes at least 5% of its total facilities
as temporary facilities can expect to lose one student per day in student attendance more than a
school of the same size without temporary facilities. Working conditions of employees in
overcrowded school facilities are stressful and unpleasant, resulting in the high rate of
absenteeism (Corcoran, Walker, & White, 1988).
Methodology
Description of Data
Participants in the study. Participants in the Comptroller’s study included small Rural
and Non-Metro: Stable public high schools in Texas, as defined by the Texas Education
Agency. These school districts were selected from the sample of school districts responding to
the 2006 Texas Comptroller’s Facility Survey. The Texas Education Agency defines Rural and
Non-Metro: Stable schools as follows:
Rural is the classification of school districts that either have a growth rate less than 20
percent and the number of students in membership is between 300 and the state median
or the number of students in membership is less than 300.
Non-Metro: Stable is the classification of school districts that are not major urban,
suburban, towns over 25,000 population, or in a fast-growth area, yet have a number of
students in membership that exceeds the state median.
(Texas Education Agency, 2006, para. 1)
The participants in this study included small rural and Non-Metro: Stable public high
schools in Texas (referred to as Rural in this study). These school districts were selected from
the sample of school districts responding to the 2006 Texas Comptroller’s Facility Survey. The
Comptroller’s Survey was sent to all 1,037 public school districts in Texas. There were a total of
309 school districts that responded to the survey. These school districts represent 48.1% of the
state’s student population.
The Relationship
August 2011 / ACEF 58
The Comptroller’s Study utilized several categories as the Primary Use of Facility.
Examples of different Primary Uses include Instruction, Administrative, Warehouse, Extra-
curricular, etc. Only data from facilities under the category of ―Instruction‖ were used in the
data analysis for this research. There were no extra-curricular facilities, warehouses, storage
facilities, etc. used in this study unless they were a part of the high school building.
There are a total of 137 small rural school districts in Texas. Of these 137 school
districts, 64 schools house multi-grade classrooms from Kindergarten through 12th grade in a
single facility. This study eliminated these schools, because student achievement data in these
schools is combined together with other grade levels to make a single campus.
There were 73 districts that house their high schools in separate facilities from other
grade levels. These 73 high schools represent 53% of the small, rural high schools in Texas.
These high schools separate their student achievement data from the rest of their school
campuses. This study used only data from these 73 high schools.
Power Analysis for this study is strengthened by previous research in this area. Carpenter
(1996) suggested that studies involving similar school districts in terms of geographic locations,
student demographics, available funds, and school size might provide a better data fit with a
smaller sampling error than the large sample size studies. Although this is a relatively small
sample size for a research study, 73 high schools are appropriate for this study because these
similar districts will provide a quality sample for determining the relationship between the
condition of school facilities and educational outcomes.
Data collection method. Data used in this study were collected by a survey instrument
developed by the Texas Comptroller of Public Accounts, in collaboration with representatives
from the Texas Association of School Administrators (TASA), Texas Association of School
Boards (TASB), Texas Association of School Business Officials (TASBO), the Texas Education
Agency (TEA), the executive directors of the state’s 20 Regional Educational Service Centers
(RESCs), and individuals with facilities expertise. The 2006 Academic Excellence Indicator
System (AEIS) report from the Texas Education Agency provided the demographic data, teacher
turnover, student attendance, and student achievement for each high school.
The Texas Comptroller of Public Accounts sent a letter to all public school districts and
charter schools in Texas on May 1, 2006, announcing the survey and directing the schools to the
online survey questionnaire.
The facility inventory survey was submitted via e-mail in an Excel spreadsheet format.
The survey was available online on the web site of the Texas Comptroller of Public Accounts
from May 1, 2006 through August 15, 2006. The Comptroller’s staff members called over 500
school districts in late June requesting their participation and offering assistance. Although the
survey was voluntary, there were several attempts by the Comptroller’s staff to encourage school
district personnel to respond to the survey. There were 309 public school districts and charter
schools that responded to the Comptroller’s request. Seven responses included partial responses
and were not included in the results. One school response was a non-taxing entity, and it was not
included in the results.
Data Analysis Methods
The study used multiple regression to explore selected school facilities variables and
demographic variables (General Condition of School Facilities, Percent Portable to Total
Permanent Square Feet per Student; Percent Capacity, Average Age of Facilities, Number of
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59 Vol. 1, No. 1, 2011
Years Since Last Renovation, Percent Deferred Maintenance, Property Value per Student,
Percent Economic Disadvantage Students, and Percent Minority Students), which were
hypothesized to attribute to the variations in the educational outcomes (Student Achievement,
Teacher Turnover, and Student Attendance).
Results
Data Analysis Using Multiple Regression Analyses
The results in the following sections present an evaluation of which condition of facilities
variables and demographic variables best predict Student Achievement, Teacher Turnover, and
Student Attendance.
The selected condition of facilities variables were hypothesized to attribute to the
variations in certain educational outcomes. The predictor variables included: General Condition
of School Facilities; PercentPortable to Permanent Square Feet per Student; Percent Capacity;
Age of Facilities; Number of Years Since Last Renovation; Deferred Maintenance; Property
Value per Student; Percent Economic Disadvantage Students; and Percent Minority Students.
The criterion variables included: Student Achievement (Average TAKS Scores), Teacher
Turnover (Average Years Experience of Teachers with District), and Average Student
Attendance.
Student Achievement (Average TAKS Scores)
The first criterion variable examined in this study using multiple regression analysis was
Student Achievement as measured by Average TAKS Scores. Multiple regression results
indicated that the linear combination of one demographic variable and four condition of facilities
measures was significantly related to Average TAKS Scores, F(5,67) = 11.267, p < .05. The
total R Square of .457 for the sum of these predictors indicates that, taken together, the inclusion
in the regression equation of Percent Economic Disadvantage Students, Average Age of
Facilities, Percent Portable to Permanent Square Feet, Percent Capacity, and Percent Deferred
Maintenance contributed 45.7% of the variance in Average TAKS Scores.
Student income level. The demographic variable, Student Income Level, as measured
by Percent Economic Disadvantage Students, accounted for most of the variance in the Average
TAKS Scores. The resulting R Square Change of .284 for the low-wealth students indicates that
approximately 28% of the Average TAKS Scores can be accounted for by the percentage of low-
income students, F(1,71) = 28.096, p < .05.
As the percentage of low-income students increases, the average TAKS scores decrease,
r(73) = -.532, p < .01. Most researchers would agree that it is not surprising that about one-
fourth of the variance in average TAKS scores can be accounted for by the percentage of low-
income students in the high school.
Condition of facilities. Four conditions of facilities measures predicted Average TAKS
Scores significantly over and above the low-income students. The first of these facilities
variables was Average Age of Facilities. The resulting R Square Change of .042 indicates that
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August 2011 / ACEF 60
approximately 4% of the variance in Average TAKS Scores can be accounted for by the Average
Age of Facilities, F(1,70) = 4.407, p < .05.
The second condition of facilities measure that was found to be significant during the
multiple regression analysis was the Percent Portable to Permanent Square Feet per Student. The
resulting R Square Change of .050 indicates that approximately 5% of the variance in Average
TAKS Scores can be accounted for by the percentage of portable space per student, F(1,69) =
5.508, p < .05.
The third condition of facilities measure that was found to be significant during the
multiple regression analysis was the Percent Capacity (overcrowding). The resulting R Square
Change of .038 indicates that approximately 4% of the variance in Average TAKS Scores can be
accounted for by overcrowding, F( 1,68) = 4.442, p < .05.
The fourth condition of facilities measure that was found to be significant during the
multiple regression analysis was the Percent Deferred Maintenance. The resulting R Square
Change of .043 indicates that approximately 4% of the variance in Average TAKS Scores can be
accounted for by the percentage of deferred maintenance, F(1,67) = 5.267, p < .05.
The multiple regression analysis did not find the other predictor variables statistically
significant as predictors for Average TAKS Scores.
Teacher Turnover (Average Years Experience of Teachers with District)
The second criterion variable examined in this study using multiple regression analysis
was Teacher Turnover. Average Years Experience of Teachers with District was used as a proxy
for Teacher Turnover. Teacher Turnover is not reported at the high school level by the Texas
Education Agency (TEA). However, the Average Years Experience of Teachers with District
for each school is reported by TEA. Since there is only one high school in every school district
in this study, Teacher Experience with District can serve as a proxy for Teacher Turnover.
The multiple regression analysis found that the first significant condition of facilities
measure was Percent Portable to Permanent Square Feet per Student. The resulting R Square
Change of .062 indicates that approximately 6% of the variance in teacher turnover can be
accounted for by the percentage of portable to permanent square feet per Student, F(1,70) =
4.728, p < .05.
The second significant condition of facilities measure was Average Age of Facilities.
The resulting R Square Change of .073 indicates that approximately 7% of the variance in
teacher turnover can be accounted for by the average age of facilities, F(1,70) = 5.951, p < .05.
Other predictor variables. The other predictor variables did not show a significant
correlation with teacher turnover.
Student Attendance
The third criterion variable examined in this study using multiple regression analysis was
Average Student Attendance.
Multiple regression results indicated that there was only one measure, Percent Capacity
(Overcrowding), that was significantly related to Average Student Attendance, F(1,71) = 5.382,
p < .05. The resulting R Square Change of .070 indicates that approximately 7% of the variance
in Average Student Attendance can be accounted for by Overcrowding in school facilities.
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61 Vol. 1, No. 1, 2011
Other predictor variables. The other predictor variables did not show a significant
correlation with average student attendance.
Summary, Discussion, and Conclusions
It is sometimes difficult to generalize the findings in a study such as this to other school
districts across the nation. However, because this study used a sample of high schools taken
from the entire population of public small rural high schools in Texas, the findings can
realistically be generalized to other small rural high schools across the United States.
Student Wealth Level
In this study, low-income students accounted for approximately 28% of the variance in
average TAKS scores. Student wealth level is frequently noted as one of the main contributors
to the variance in standardized test scores (Earthman, 2002; Lanham, 1999; Lyons, 2001).
This study confirms previous research that highlights the importance of providing
additional resources to school to help students from impoverished homes. If states do not
provide these additional resources to schools with high percentages of low-wealth students, our
nation’s schools will continue to be segregated by schools with students of privilege and schools
with economically disadvantage students.
The percentage of low-income students did not seem to have much of an effect on teacher
turnover and student attendance. In this study, teacher turnover and student attendance appear to
be less effected by socioeconomic factors than student achievement. This should be encouraging
to policy makers and school leaders, because they have little control over the socio-economic
status of the children in their school. They do, however, have control over the resources
necessary to provide quality school facilities that provide the environment for a quality education
for every child in Texas.
Average Age of Facilities
The average age of facilities did not seem to affect average student attendance. However,
the average age of facilities did affect average TAKS scores and teacher turnover to a small
degree.
Portable Classrooms
This study indicated that the larger the percentage of portable square feet compared to
permanent square feet in a school, the lower the average TAKS scores and the higher the teacher
turnover rate.
A larger teacher turnover rate costs the school district time, energy, and money to recruit
and train new teachers. If a school district does not have the money to build quality, permanent
facilities for its students, how will it provide the increased money necessary to fund the
additional recruiting and training of new teachers that comes from high teacher turnover?
A priority for school leaders should be to decrease the number of portable facilities in the
school to positively affect teacher turnover.
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August 2011 / ACEF 62
Overcrowded Schools
This study found that overcrowded classrooms are a predictor of lower student attendance
rates. Schools that have overcrowded classrooms are setting themselves up for discipline
problems, frustrated teachers, and higher student absenteeism. Student attendance problems
affect student achievement, because students who are not at school have less time in the
classroom to be engaged in learning.
Policy makers and school leaders must make equitable school funding a priority so that
schools are able to provide adequate classroom space for all children in Texas. All children
deserve to have a quality education in a learning environment that is not crowded, noisy, or
distracting.
Deferred Maintenance
Deferred maintenance refers to the amount of maintenance in a school that was needed
but was deferred because of a lack of resources to perform the maintenance. This study found
that the more deferred maintenance problems in a high school, the less success the students
demonstrate through their average TAKS scores. Policy makers and educational leaders must
provide the resources and leadership to adequately maintain school facilities so that all children
can have access to a quality education.
Implications for Practice
The findings in this study show that socioeconomic backgrounds of students in small
rural high schools have the most influence on the variability of educational outcomes. However,
certain conditions of school facilities can have a measurable effect on the educational outcomes
of student achievement, teacher turnover, and student attendance, particularly when combined
with the socioeconomic characteristics of students. The fact that students come to school with
differing socioeconomic backgrounds that are out of the control of educators magnifies the
importance of policy makers and educational leaders to establish priorities and policies in the
areas they do control that will improve educational opportunities for all children.
There are several implications for current best practices that come from this study. An
effective teacher retention strategy is for schools to improve and upgrade their school facilities.
Buckley et al. (2004) found that the impact of facility improvement on teacher retention is equal
to or greater than the impact of pay increases for teachers. One benefit of the strategy of
improving school facilities is that it is actually a more cost-effective teacher retention strategy
than a permanent salary increase for teachers. Salary increases are on-going year after year.
Facilities improvements are likely to be a one-time expense, last for many years, and have
supplemental sources of state or federal funding available. School leaders and policy makers can
have a better impact on teacher retention by spending limited resources on improving school
facilities than even on increased salaries.
The quality of the school facilities in which a child receives his or her education should
not depend on the wealth of the area in which he or she happens to reside. Excellent facilities for
the few and adequate or barely adequate facilities for the many violates the proud heritage of
Texas. Inequitable school funding has resulted in an economic segregation of students that
closely resembles the racial segregation of the early 20th century.
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63 Vol. 1, No. 1, 2011
Equal educational opportunity is fast becoming the new civil rights issue of the 21st
century. Excellent facilities for children who need them the least and inadequate facilities for the
ones who need them the most violates the principal of equal educational opportunity for all.
Policy makers and educational leaders have a responsibility for providing a quality education
system for all children. School leaders must demand equitable school funding for every school
so every child can have access to equal educational opportunity.
John Dewey once said, ―What the best and wisest parent wants for his own child, that
must be what the community wants for all its children‖ (Biddle & Berliner, 2002, p. 58).
Dewey’s ideal can be applied to equity in educational facilities by paraphrasing his words: What
the most affluent community wants in the way of school facilities for its best and brightest
students, that must be what the state of Texas wants for every child in the state.
Public education for all children is necessary for a free, democratic society. Equal
educational opportunity must be provided for all children to level the playing field for everyone.
America must have a public school system that provides an informed citizenry needed for
democratic government, embraces the welfare of all children in the nation, upholds the ideal of
equal educational opportunity, and levels the playing field for all children. Social justice and
equal educational opportunity demand that the quality of school facilities should not be
determined by race or social class.
In 1954, the United States Supreme Court ruled that separate but equal facilities were no
longer sufficient, partly because the school facilities of black schools were actually not equal to
the school facilities of white schools (Brown v. Board of Education, 1954). Today, when school
facilities are found to be unequal, equal educational opportunity still does not exist. Texans must
insist that policy makers not allow inadequate and unequal funding for school facilities that serve
low-income and minority children. Otherwise, many children will still face the reality of
separate but unequal school facilities.
Texas is moving toward a two-tiered school system: one for more affluent, mostly white
students who enjoy the advantages of a quality educational system, and the other, for low-
income, mostly non-white students whose educational environment virtually denies them the
opportunity to learn at a comparable level.
It has always been immoral to shortchange schools that educate the greatest numbers of
students growing up in poverty. As long as students continue to be disadvantaged by being
educated in substandard facilities, advocates for children everywhere must continue to call for
equity in our public educational system.
References
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Leadership, 59(8), 49-59.
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achievement, health, attendance, and behavior. Educational Facility Planner, 26(4), 33-
34.
Branham, D. (2004). The wise man builds his house upon the rock: The effects of inadequate
school building infrastructure on student performance. Social Science Quarterly, 85(5),
1-15.
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Brown v. Board of Education, 347 U.S. 483 (1954). Retrieved from
http://www.nationalcenter.org/brown.html
Buckley, J., Schneider, M., & Shang, Y. (2004). The effects of school facility quality on teacher
retention in urban school districts. Washington, DC: National Clearinghouse for
Educational Facilities.
Carpenter, C. (1996). Development of a structural equation model to identify the relationship
between expenditures and student performance in Texas public high schools. Lubbock,
Texas: Doctoral Dissertation, Texas Tech University.
Cash, C. (1993). A study of the relationship between school building condition and student
achievement and behavior. (Doctoral dissertation, Virginia Polytechnic Institute and
State University, Blacksburg, Virginia).
Chan, T. C. (2005). Portable versus permanent classrooms: Student attitude, behavior, and
achievement. Educational Facility Planner, 40(2), 3-7.
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http://clinton2.nara.gov/WH/SOU97/
Corcoran, T., Walker, L., & White, J. (1988). Working in urban schools. Washington, DC:
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behavior. Paper presented at the European Investment Bank/Organization for Economic
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State University, Blacksburg, Virginia).
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of Educational Facility Planners International.
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Washington, DC: U.S. Department of Education Office of Educational Research and
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Pool, D. (1993). Nebraska school facilities: Educational adequacy of structures and their
funding. Paper presented at the Annual Rural and Small School Conference, Manhattan,
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Tech University, Lubbock, Texas).
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York, NY. Retrieved from http://www.eric.ed.gov/ERICDocs/data/ericdocs2sql/content_
storage-01/0000019b/80/13/a6/68.pdf
Schneider, M. (2002). Do school facilities affect academic outcomes? Washington, DC: National
Clearinghouse for Educational Facilities.
Schneider, M. (2004). The educational adequacy of New Jersey public school facilities: Results
from a survey of principals. Stony Brook, NY: Department of Political Science, State
University of New York at Stony Brook.
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(Ed.), The condition of education in rural schools. Washington, DC: Office of
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http://www.tea.state.tx.us/school.finance/facilities/ifa.html
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tx.us/statutes/docs/ED/content/htm/ed.002.00.000004.00.htm#4.001.00
Dr. Martin Eugene (Gene) Sheets, Superintendent of Muleshoe Independent School District
(Texas), is a graduate of Texas Tech University (2009). He has served as superintendent, since 1996,
in several school districts across Texas, including Hedley ISD and Hamilton ISD. Dr. Sheets has
served as an Adjunct Professor for Texas Tech University, Wayland Baptist University, and West
Texas A&M University. In addition, he has received numerous honors and awards; most recently
he was named Texas Administrator of the Year by the Texas Classroom Teachers Association
(2008-09).
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August 2011 / ACEF 66
American Clearinghouse on Educational Facilities
Box T-0205
Stephenville, TX 76402
Phone (254) 968-9990 / Fax (254) 968-9779
[email protected] / www.acefacilities.org
Call for Papers
Volume 2, Issue 2 (March 2012)
ACEF Journal, the biannual blind-reviewed journal of the American Clearinghouse on Educational Facilities
(ACEF), provides an excellent forum for the publication of current research, theory, and practice related to
educational facilities.
Manuscripts will be accepted related to one or more of the ACEF focus areas outlined below.
The ACEF Journal welcomes original contributions with relevance to educational facilities. It seeks to
publish work that develops, tests, and advances theory, research and practice of educational facilities. The
ACEF Journal considers articles from a wide variety of interest areas, including, but not limited to:
Environmentally Sound Practices
Facility Planning
Facility Design
Facility Construction
Facility Improvement
Facility Operations
Facility Maintenance
Facility Safety
Student Learning
The deadline for submission is
October 31, 2011
Manuscript Submission: Articles submitted to the ACEF Journal should be original contributions and should
not have been published elsewhere. Manuscripts submitted to the ACEF Journal may be submitted
simultaneously to other journals provided ACEF is advised, and the author(s) inform the Journal immediately if
the work is published or accepted for publication elsewhere.
Two copies of the manuscript should be sent as an email attachment to [email protected]; one copy will
have all self-identification information removed to facilitate the ―blind‖ aspect of the review process and the
other copy will be retained by the Journal for additional reference by the Editor.
All manuscript submissions must be submitted in Microsoft Word (or Word-compatible) format (.DOC,
.DOCX).
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67 Vol. 1, No. 1, 2011
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August 2011 / ACEF 68
A Program of The Texas Center for Educational Facilities, the educational
facilities clearinghouse funded by The United States Department of Education.