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

Chan

Dishman

7 Vol. 1, No. 1, 2011

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,

Chan

Dishman

9 Vol. 1, No. 1, 2011

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

Chan

Dishman

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.

References

Berry, M. A. (2002). Healthy school environment and enhanced educational performance. The

case of Charles Young Elementary School, Washington, DC. Retrieved from

http://carpet-rug.com/pdf_word_docs/020112_Charles_Young.pdf

Castaldi, B. (1994). Educational facilities: Planning, modernization, and management (4th

ed.).

Boston, MA: Allyn and Bacon.

Chan, T. C. (2002). Working with agencies. In T. J. Kowalski (Eds.), Planning and managing

school facilities (pp. 191-202). Westport, CT: Bergin & Garvey.

Chan, T. C., & Richardson, M. D. (2005). Ins and outs of school facility management. Lanham,

MD: Scarecrow Education.

Chan, T. C., Richardson, M. D., & Jording, C. (2001). Carpet in schools: Myth and reality.

School Business Affairs, 67(6), 19-22.

Choremiotis, P. (1993). A study of indoor air quality and health effects in regular and portable

classrooms in a local primary school. (Unpublished doctoral dissertation) Queen’s

University, Kingston, Canada.

Cooze, J. (1995). Curbing the cost of school vandalism: Theoretical causes and preventive

measures. Education Canada, 35(3), 38-41.

Crisler, A., & Chan, T. C. (2007). Ensuring safe schools for safe learning. School Business

Affairs, 73(5), 24-26.

Dunklee, D. R., & Silberman, R. M. (1991). Healthy buildings keep employees out of bed and

employers out of court. School Buiness Affairs, 57(12), 19-22.

Earthman, G. I. (2009). Planning educational facilities (3rd

ed.). Lanham, MD: Rowman &

Littlefield Education.

Fahey, J. A. (2000). Water, water, everywhere. Educational Leadership, 57(6), 60-61.

Folks, K. H., & Hirth, M. A. (2009). Getting a fresh perspective on school safety audits. School

Business Affairs, 75(6), 8-11.

Georgia Department of Education. (1996). Square footage requirements for use in developing the

local facilities plans. Atlanta, GA: Author.

Government Accounting Office. (1996). School facilities: America’s schools report differing

conditions (GAO Report No. HEH-96-103).

Grebow, P. M., Greene, B. Z., Harvey, J., & Head, C. J. (2000) Shaping health policies.

Educational Leadership, 57(6), 63-67.

Johnson, R. L. (2007). Creating high-performing schools with high-performance HVAC. School

Business Affairs, 73(5), 20-23.

Kelly, M. (2010). School violence: How prevalent is it? Retrieved from

http://712educators.about.com/cs/schoolviolence/a/schoolviolence.htm

Kerr, M. M. (2009). School crisis prevention and intervention. Upper Saddle River, NJ: Pearson.

Kingsley, P. (2000). On school safety. A presentation delivered at the College of Education,

University of Oregon, February 9, 2000.

Maintaining a Safe and Healthy School

August 2011 / ACEF 12

Marx, E., & Northrop, D. (2000). Partnerships to keep students healthy. Educational Leadership,

57(6), 22-24.

Marx, E., & Wooley , S. F. (Eds.) (1998). Health is academic: A guide to coordinated school

health programs. New York: Teachers College Press. Retrieved from

http://www2.edc.org/MakingHealthAcademic/Concept/actions_environment.asp

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50, 370-396.

McPhee, N. (2005). Addressing asthma and indoor air quality. School Business Affairs, 71(5),

28-31.

National Policy Board for Educational Administration. (2002). Standards for advanced

programs in educational leadership. Reston, VA: Author.

Ornstein, S. W., Moreira, N. S., Ono, R., Franca, A. J. G. L., & Nogueira, R. A. M. F. (2009).

Improving the quality of school facilities through building performance assessment.

Journal of Educational Administration, 47, 350-367.

Responsible Industry for a Sound Environment. (1999). A bug’s life. American School and

University, February, 39-41.

Roberts, L. W. (2009). Measuring school facility conditions: An illustration of the importance of

purpose. Journal of Educational Administration, 47(3), 368-380.

Schiffbauer, P. (2000). A checklist for safe schools. Educational Leadership, 57(6), 72-74.

Schmidt, E. A. (1994). Bugs in your rugs? Carpet maintenance and indoor air quality. School

Business Affairs, 60(6), 39-43.

Schneider, T., Walker, H., & Sprague, J. (2000). Safe school design. Eugene, OR: University of

Oregon.

Shaw, R. (2000). Clean and safe. American School and University, September, 42-43.

Shelton, D. R. (2003). Perceptions of key informants toward the use of portable facilities for

educational purposes. (Unpublished doctoral dissertation) Oklahoma State University,

Oklahoma City, OK.

Shideler, L. (2001). A clean school is a healthy school. American School and University, 79(3),

52-56.

Shoop, M. A. (2004). Design and construction database linked to photographic documentation:

Technology, facilities management. In D. A. Ritchey (Eds.), Innovative ideas for school

business officials (pp. 51-54). Lanham, MD: Scarecrow Education and Association of

School Business Officials International.

Spencer, R. D. (1998). When poor indoor air causes a crisis. School business Affairs, 64(7),

21-26.

Tanner, C. K., & Lackney, J. A. (2006). Educational facilities planning. Boston, MA: Allyn and

Bacon.

U.S. Department of Education. (2010, March). Elementary and secondary education act

reauthorization: A blueprint for reform. Retrieved from

http://www2.ed.gov/policy/elsec/leg/blueprint/index.html

U.S. Department of Education. (2010). Successful, safe and healthy students. Washington, DC:

U.S. Department of Education. Retrieved from

http://www2.ed.gov/policy/elsec/leg/blueprint/successful-safe-healthy.pdf U.S. Environmental Protection Agency. (2000, January 6). IAQ tools for schools—Frequently

asked questions. Received from http://www.epa.gov/iaq/schools/scfaqs.html

U.S. Environmental Protection Agency Indoor Environments Division. (2004). Does the indoor

air quality in schools impact student performance? School Business Affairs, 70(4), 18-20.

Chan

Dishman

13 Vol. 1, No. 1, 2011

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).

PARTNERSHIPS

INNOVATION

TRADITION

VALUE

DIVERSITY

REPUTATION

RELATIONSHIPS

DEVELOPING PROFESSIONALS

INVESTING IN AMERICA’S

FUTURE

Tarleton State

University

College of Education

EXCEL

EXTEND

EXPAND

ENCOURAGE

Tarleton State University College of Education

CONNECTIONS NEWSLETTER

For a Degree of Difference

PHONE 254-968-9089 / FAX 254-968-9525

BOX T-0120, STEPHENVILLE, TX 76402

LOLLAR@TARLETON.EDU

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

Lemasters

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

Lemasters

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.

Lemasters

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

References

Bailey, J. A. (2009). A synthesis of studies pertaining to school building condiiton, student

achievement, student behavior, and student attitude (Unpublished doctoral dissertation).

Virginia Polytechnic Institute and State University, Blacksburg, VA.

Bishop, M. E. (2009). A case study on facility design: The impact of new high school facilities in

Virginia on student achievement and staff attitudes and behaviors (Unpublished doctoral

dissertation). The George Washington University, Washington, DC.

Bowers, J. H., & Burkett, C. W. (1987, October). Relationship of student achievement and

characteristics in two selected school facility environmental settings. Paper presented at

the 64th

Council of Educational Facility Planners, International Conference in Edmonton,

Alberta, Canada.

Brannon, W. L. (2000). A study of the relationship between school leadership and the condition

of school buildings (Unpublished doctoral dissertation). Virginia Polytechnic Institute

and State University, Blacksburg, VA.

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. Retrieved from http://www.edfacilities.org

Bullock, C. (2007). The relationship between building condition and student achievement in

Virginia middle schools (Unpublished doctoral dissertation). Virginia Polytechnic

Institute and State University, Blacksburg, VA.

Cash, C. S. (1993). A study of the relationship between school building condition and student

achievement and behavior (Unpublished doctoral dissertation). Virginia Polytechnic

Institute and State University, Blacksburg, VA.

Chan, T. C. (1980). The impact of school building age on pupil achievement. CEFPI Journal,

18(2), 13-14.

Crook, J. F. (2006). A study of school building conditions and student achievement in the high

schools of Virginia (Unpublished doctoral dissertation). Virginia Polytechnic Institute

and State University, Blacksburg, VA.

Dawson, C. G., & Parker, D. R. (1998). A descriptive analysis of the perspectives of Neville High

School teachers regarding the school’s renovation. Paper presented at the annual meeting

of the Mid-South Educational Research Association, New Orleans, LA. (ED427506)

Retrieved from http://www.eric.ed.gov/PDFS/ED427506.pdf

Earthman, G. I. (2004). Prioritization of 31 criteria for school building adequacy. Baltimore,

MD: American Civil Liberties Union Foundation of Maryland.

Earthman, G. I. (2006). My Classroom Appraisal Protocol©. Survey instrument. Blacksburg,

VA: Virginia Polytechnic Institute and State University.

Earthman, G. I. (2007). Student School Building Attitude Scale©. Survey instrument.

Blacksburg, VA: Virginia Polytechnic Institute and State University.

Earthman, G. I. (2008). The relationship between the attitudes students have about their school

building and their achievement. Scottsdale, AZ: Council of Educational Facility Planners,

International.

Earthman, G. I., Cash, C. S., & Van Berkum, D. (1996, June). Student achievement and

behavior and school building condition. Journal of School Business Management, 8(3),

26-37.

Lemasters

35 Vol. 1, No. 1, 2011

Earthman, G. I., & Lemasters, L. K. (2004). School maintenance & renovation: Administrator

policies, practices, & economics. Lancaster, PA.: Proactive Publications.

Earthman, G. I., & Lemasters, L. K. (2009). Teacher attitudes about classroom conditions.

Journal of Educational Administration, 47(3), 323-335.

Edwards, M. M. (1991, May). Building conditions, parental involvement and student

achievement in the D. C. public school system (Unpublished master’s thesis).

Georgetown University, Washington, DC. (ED 264 285)

Elementary and Secondary Education Act of 1965 20 U.S.C. 6301 et seq. (1965).

Harrison, E. K. (2009). Principals’ perceptions of the impact of building conditions on student

achievement (Unpublished doctoral dissertation). The George Washington University,

Washington, DC.

Hatch, M. S., & Cunliffe, A. L. (2006). Organizational theory: Modern, symbolic, and

postmodern perspectives. Oxford, England: Oxford University Press.

Hines. E. M. (1996). Building condition and student achievement and behavior (Unpublished

doctoral dissertation). Virginia Polytechnic Institute and State University, Blacksburg,

VA.

Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago, IL: The University Press of

Chicago.

Lanham, III, J. W. (1999). Relating building and classroom conditions to student achievement in

Virginia’s elementary schools (Unpublished doctoral dissertation). Virginia Polytechnic

Institute and State University, Blacksburg, VA.

Lemasters, L. K. (1997). A synthesis of studies pertaining to facilities, student achievement, and

student behavior (Unpublished doctoral dissertation). Retrieved from Dissertation

Abstracts International. (UMI No. 9722616)

Lemasters, L. K., & Earthman, G. I. (2003). A study of the relationship between air-conditioned

classrooms and student achievement. Scottsdale, AZ: Council of Educational Facility

Planners, International.

McGuffey, C. W. (1982). Facilities, Chapter 10. In W. Herbert (Ed.), Improving educational

standards and productivity (pp. 237-288). Berkley, CA: McCutchan Publishing.

Maxwell , L. (1999). School building renovation and student performance: One district’s

experience. Scottsdale, AZ: Council of Educational Facility Planners, International.

No Child Left Behind Act of 2001. (2001). Pub. L. No. 107-110 § 115, Stat. 1425.

Oakes, J. (2002). Education inadequacy, inequity, and failed state policy: A synthesis of expert

reports prepared for Williams v. State of California. Williams Watch Series:

Investigating the Claims of Williams v. State of California. (Document wws-rr016-1002)

Los Angeles, CA: UCLA Institute for Democracy, Education, & Access. Retrieved from

http://escholarship.org/uc/item/8727d11z

O’Neill, D. J. (2000). The impact of school facilities on student achievement, behavior,

attendance, and teacher turnover at selected Texas middle schools in Region XIII ESC

(Unpublished doctoral dissertation). Texas A&M University, College Station, TX.

O’Sullivan, S. (2006). A study of the relationship between building condition and student

academic achievement in Pennsylvania’s high schools (Unpublished doctoral

dissertation). Virginia Polytechnic Institute and State University, Blacksburg, VA.

Phillips, R. W. (1997). Educational facility age and the academic achievement and attendance of

upper elementary school students (Unpublished doctoral dissertation). University of

Georgia, Athens, GA.

The Influence of School Building Conditions

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.

FREE FACILITIES SUPPORT

855-610-ACEF

ACEF Serves

Public early childhood schools, K-12 schools, and

institutions of higher education.

ACEF Provides

• Information to connect

professionals to resources via an

online clearinghouse at

www.acefacilities.org

• Training to guide, advise, and

support public school officials

with facilities management.

• Free facilities support via live

chat, email, and phone.

• Free on-Site facilities support

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.

Sheets

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

Sheets

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).

Sheets

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

Sheets

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

The Relationship

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.

Sheets

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.

The Relationship

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.

Sheets

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

Biddle, B., & Berliner, D. (2002). Unequal school funding in the United States. Educational

Leadership, 59(8), 49-59.

Bowers, J., & Burkett, C. (1988). Physical environment influences related to student

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.

The Relationship

August 2011 / ACEF 64

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.

Clinton, W. J. (1997). 1997 state of the union address. Retrieved from

http://clinton2.nara.gov/WH/SOU97/

Corcoran, T., Walker, L., & White, J. (1988). Working in urban schools. Washington, DC:

Institute for Educational Leadership. (ED 299 356)

Dewees, S., & Earthman, G. (2000). Trends and issues affecting school facilities in rural

America: Challenges and opportunities for action. In S. Dewees (Ed.), Improving rural

school facilities: Design, construction, finance, and public support. Charleston, WV:

AEL, Inc.

Earthman, G. (1998). The impact of school building condition and student achievement, and

behavior. Paper presented at the European Investment Bank/Organization for Economic

Coordination and Development International Conference, Luxembourg.

Earthman, G. (2002). School facility conditions and student academic achievement. Los Angeles,

CA: UCLA’s Institute for Democracy, Education, and Access (IDEA).

Earthman, G. (2004). Prioritization of 31 criteria for school building adequacy. Retrieved from

http://www.schoolfunding.info/policy/facilities/ACLUfacilities_report1-04.pdf

General Accounting Office. (1995). School facilities: Condition of America’s schools. Report

No. HEHS-95-61. Washington, DC: National Government Publication.

Lanham, J. (1999). Relating building and classroom conditions to student achievement in

Virginia's elementary schools. (Doctoral dissertation, Virginia Polytechnic Institute and

State University, Blacksburg, Virginia).

Lyons, J. (2001). Do school facilities really impact a child’s education? Scottsdale, AZ: Council

of Educational Facility Planners International.

National Center for Education Statistics. (1999). How old are America’s public schools?

Washington, DC: U.S. Department of Education Office of Educational Research and

Improvement.

National Center for Education Statistics. (2000). Condition of America’s public school facilities:

1999. Washington, DC: U.S. Department of Education (NCES 2000-032)

Ornstein, A. (1994). School finance and the condition of schools. Theory into Practice, 33(2),

118-125.

Pastor, M., & Reed, D. (2005). Understanding equitable infrastructure investment for California.

San Francisco, CA: Public Policy Institute of California.

Sheets

65 Vol. 1, No. 1, 2011

Pool, D. (1993). Nebraska school facilities: Educational adequacy of structures and their

funding. Paper presented at the Annual Rural and Small School Conference, Manhattan,

Kansas.

Rees, R. (2004). Circling the drain: Content analysis of cost reduction documents from

financially exigent school districts in the state of Texas. (Doctoral Dissertation, Texas

Tech University, Lubbock, Texas).

Rivera-Batiz, F., & Marti, L. (1995). A school system at risk: A study of the consequences of

overcrowding in New York City public schools. IUME Research Report No. 95-1. New

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.

Stern, J. (1994). Location and characteristics of rural schools and school districts. In J. Stern

(Ed.), The condition of education in rural schools. Washington, DC: Office of

Educational Research and Improvement, U.S. Department of Education.

Texas Constitution of 1876. Article VII, Section 1. Retrieved from

http://tarlton.law.utexas.edu/constitutions/text/IART07.html.

Texas Education Agency. (1997). Instructional facilities allotment (IFA). Retrieved from

http://www.tea.state.tx.us/school.finance/facilities/ifa.html

Texas Education Agency. (1999). Existing debt allotment (EDA). Retrieved from

http://www.tea.state.tx.us/school.finance/facilities/eda.html

Texas Education Agency. (2006). Snapshot 2006 summary tables–community type. Retrieved

from http://www.tea.state.tx.us/perfreport/snapshot/2006/commtype.html

Texas Education Code, Chapter 4.001(a). Texas statutes. Retrieved from http://tlo2.tlc.state.

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).

The Relationship

August 2011 / ACEF 66

American Clearinghouse on Educational Facilities

Box T-0205

Stephenville, TX 76402

Phone (254) 968-9990 / Fax (254) 968-9779

acef@acefacilities.org / 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 ortiz@acefacilities.org; 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).

Sheets

67 Vol. 1, No. 1, 2011

The Relationship

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.