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2011 Comprehensive Facility Assessment Report

DeKalb County School System

June 2011


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2011 Comprehensive Facility Assessment Report for DeKalb County School System

Table of Contents

FOREWORD ................................................................................................................... 2

1.0 INTRODUCTION ....................................................................................................... 3

2.0 EXECUTIVE SUMMARY .......................................................................................... 4

2.1 Facility Condition Assessment ............................................................................................................ 4

2.2 Educational Adequacy Assessment .................................................................................................... 5

2.3 Technology Readiness Assessment ................................................................................................... 5

2.4 Capacity and Utilization Assessment .................................................................................................. 5

2.5 Combined Scores for Schools: Condition, Educational Adequacy, and Technology Readiness

Assessments ............................................................................................................................................. 6

2.6 Cost of Improvement ........................................................................................................................... 7

2.7 Conclusion ........................................................................................................................................... 8

3.0 ASSESSMENT METHODOLOGY AND APPROACH .............................................. 9

3.1 Facility Condition Assessment (FCA) Methodology .......................................................................... 10

3.2 Educational Adequacy and Technology Readiness Assessments Methodology ............................. 12

3.3 Demographics, Capacity and Utilization Assessment Methodology ................................................. 14

3.4 Energy Conservation Analyses Methodology ................................................................................... 23

4.0 FINDINGS ............................................................................................................... 24

4.1 Facility Condition Assessment (FCA) Findings ................................................................................. 25

4.2 Educational Adequacy and Technology Readiness Assessment Findings ...................................... 47

4.3 Demographics, Capacity and Utilization Assessment Findings ........................................................ 65

4.4 Energy Conservation Analysis Findings ........................................................................................... 81

4.5 Combined Condition, Educational Adequacy, and Technology Readiness Findings ....................... 86

APPENDICES

Appendix A Scope of Work

Appendix B Terms and Definitions

Appendix C Facility Assessment Reports

Appendix D Educational Adequacy and Technology Readiness Guidelines

Appendix E Educational Adequacy and Technology Readiness Scoring Criteria

Appendix F Costing Method Development


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ForewordThe following report was prepared by Parsons Commercial Technology Group (Parsons) and MGT of

America, Inc. (MGT) for the DeKalb County Board of Education, presiding over the DeKalb County

School District, but commonly referred to as the DeKalb County School System or DCSS. The goal and

purpose of this report is to provide DCSS with a summary of the results and findings of the

Comprehensive Facility Assessment Project, including deferred maintenance and capital renewal needs,

educational adequacy, and technology readiness of each facility, as well as a calculated capacity of each

facility. The overall conditions of the facilities are ever-changing due to many variables, including newly

occurring deficiencies, new building construction, repairs, renovations, and updated cost estimates. Thefindings and figures contained within this report are estimates and based on data collected at the sites as

of March 2011.

Members of the DeKalb County Board Of Education

District 1 Ms. Nancy T. JesterDistrict 2 Mr. Donald E. McChesneyDistrict 3 Ms. Sarah Copelin-WoodDistrict 4 Mr. H. Paul Womack Jr., Vice ChairDistrict 5 Mr. Jesse "Jay" Cunningham Jr.District 6 Mr. Thomas E. Bowen, ChairDistrict 7 Ms. Donna G. EdlerDistrict 8 Dr. Pamela A. SpeaksDistrict 9 Dr. Eugene P. Walker

Key Staff of the DeKalb County School District

Mrs. Ramona Tyson, Interim Superintendent

Mr. Robert Moseley, Deputy Chief Superintendent School OperationsMs. Barbara Colman, Interim CIP Operations OfficerMr. Steve Donahue, Executive Director of Plant ServicesMr. Michael Worthington, Director of FacilitiesMr. Daniel Drake, Director of Planning and ForecastingMr. Carlton Parker, CIP Program DirectorMr. Joshua Williams, Project Manager

Administrative and Instructional Complex


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1.0 Introduction

As part of its mission to provide the highest quality facilities, effective maintenance, continuousimprovement, and plan for the future, DeKalb County School System (DCSS) contracted with Parsons to

conduct a comprehensive facility condition assessment (FCA) and master planning project. Parsons

selected MGT, a nationally recognized firm in the field of K-12 educational adequacy, capacity and

utilization, and technology planning, as a team member to conduct the necessary assessments and develop

the 10-year facilities master plan. The work included:

Conducting a comprehensive assessment of each DCSS facility to identify needs for immediate

repairs, deferred maintenance, and capital renewal of major building or site systems;

Evaluating the educational adequacy and technology readiness of each instructional facility; and

Gathering and analysis of facility capacity and utilization data to define current and future student

space needs.

The goal of this work is to identify what short term (2011-2012) and longer term (2013-2022)

improvements are needed in these areas for each school or non-school facility; and to utilize this

information, along with other district input, to produce a District Facility Master Plan.

This report outlines the assessment data gathered by Parsons and MGT during the period of September

2010 March 2011 and includes both on-site physical inspections and evaluations and detailed interviews

of DCSS principals, teachers, administrators, and maintenance personnel. The specific scope of work and

associated project objectives are detailed in this report.

Due to the complex nature of the work, the physical condition assessment of the buildings and grounds

was performed separately from the educational adequacy assessment. Both assessments required the use

of specially-trained personnel and two separate and distinctive methods and approaches to the work. Thisreport addresses each assessment separately and also combines the data using a statistical methodology

that will allow us to develop priorities in the next phase of the project.

Parsons personnel conducted the physical condition assessment of the buildings and grounds and prepared

the overall findings in this report. In addition, Parsons utilized the local knowledge and expertise of the

maintenance and operations departments at DeKalb County School System and Parsons DeKalb-based

Program Management Team to assist in development of the individual facility assessment reports and the

findings in this document. MGT personnel conducted the educational adequacy and technology readiness

evaluations, and prepared the findings and reports associated with these parts of the work.

The project included the assessment of all 151 school, non-school, P-12, and vacant/closed sites, totaling

14,396,754 gross square feet throughout DeKalb County. Included in most of these assessments were the

permanent educational/teaching buildings, site and ground features, athletic fields, athletic facilities, and

other permanent administrative, maintenance, warehouse or other ancillary buildings, such as storage or

equipment buildings. No assessment of temporary or portable buildings was made.

The findings in this report are based on Parsons and MGTs standard approaches, methods, and

techniques, and nationally recognized standards used to evaluate and assess the physical condition of

school facilities, as well as the educational adequacy and technology readiness needs of public school

facilities.

Individual assessment reports for each school and non-school facility are located in Appendix C,

including Facility Condition Assessment Reports, Educational Adequacy Reports, and Technology

Readiness Reports


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2.0 Executive SummaryThis report contains the results of the facility condition assessment, educational adequacy assessment,

technology readiness assessment, and capacity and utilization assessment for the buildings and grounds at

DeKalb County Schools. The report is intended to be a planning tool and it is meant for use as a technical

document to assist the DeKalb County Board of Education in making decisions needed to achieve their

short and long term facility goals. The report contains data and exhibits meant to objectively describe the

findings and summarize the results of this study against known K-12 engineering and educational

standards.

The results and findings are strictly a measure of the data and information obtained during the course ofthe field work processes and the application of that information into a standard format used to present the

results. Below is a summary of the findings:

2.1 Facili ty Condition Assessment

Theschoolfacilities and their associated buildings and grounds received an overall score that

shows them as being in overall Fair physical condition. These findings are remarkable for a

public school system with an overall average age of 41 years and indicative of the DeKalbCounty School System commitment to providing safe and quality facilities for their students,

staff, and programs. According to the National Center for Educational Statistics (NCES), DeKalb

County School schools are 1 year younger than the national average of 42 years and four years

older than the US Southeast regional average of 37 years.

Thenon-schoolfacilities, which are the athletic stadiums and other facilities used as

administrative, special purpose, transportation, maintenance, support, or warehouses, and their

associated buildings and grounds, are in overall Poor condition. These findings are primarilyattributed to overall average age of 45 years for these facilities.

Of the 151 school, non-school, P-12, and vacant/closed DCSS facilities assessed, 24 percent of

the facilities are in Good condition, 21 percent are in Fair condition, 32 percent are in Poor

condition, and 23 percent are in Unsatisfactory condition.

The overall Facility Condition Index (FCI) of 24.19 and rating of Fair condition is indicative that

overall general maintenance and repair of the facilities is good for a facility inventory with the

average age of 41 years.

Improvements to the middle and high school facilities over the last five to ten years have

extended the useful life of many buildings systems. However, the assessment data identified

significant needs in HVAC, pluming, interior finish, roofing, exterior window, and parking and

pedestrian paving systems for most facility types.

Combined, the building exterior closure systems (windows and doors), roof coverings, plumbing

systems, HVAC systems, electrical systems, interior systems (doors, floors, ceilings, and wall

finishes), fixed furnishings (cabinets and counter tops), and fittings (toilet partitions andaccessories, lockers, white boards) represent a majority (70 percent) of the total backlog of

current deferred maintenance needs. This is primarily attributed to the relatively short life cycle

and the typical wear and tear placed on these high demand systems.


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2.2 Educational Adequacy Assessment

The educational adequacy assessments were based on the educational guidelines developed by

DeKalb County Schools and MGT through discussions with district staff and a review of

educational programs in place throughout the District.

The assessments show that many facilities do an excellent job of meeting the educational needs of

the programs housed at the site. In other facilities, spaces are either missing, do not meet the size

guidelines, do not have appropriate adjacencies, or are missing storage or fixed equipment.

Of the facilities assessed, 8 percent were rated Excellent, 24 percent were rated Good, 28

percent were Fair, 32 percent were Poor, and 8 percent were rated Unsatisfactory in termsof their adequacy to support the educational program.

2.3 Technology Readiness Assessment

The technology readiness assessments were based on the infrastructure guidelines developed by

DeKalb County Schools.

The assessments show that most schools have technology infrastructure to support the needs of

the program.

Of the facilities assessed for technology readiness, 16 percent were rated Excellent, 22 percent

were rated Good, 49 percent were rated Fair, 8 percent were rated Poor, and 5 percent of

were rated Unsatisfactory.

2.4 Capacity and Utilization Assessment

The Capacity and Utilization analysis shows that there is excess capacity district wide; however,the rate of utilization varies a great deal with some areas having a high percentage of excess

capacity while other areas having a high degree of over utilized schools. Decisions will need to

be made based on different conditions around the District.


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2.5 Combined Scores for Schools: Condition, Educational

Adequacy, and Technology Readiness AssessmentsThe assessment data, information, and findings detailed in this report are derived from standard processes

of collecting, recording, and reporting. For this report, an additional statistical analysis was used to

combine all the assessments and create one score which may be more readily understood by individuals

who are not as familiar with the assessment process.

The table below shows a weighted average score for each school type. To derive the Combined Score,

the Condition Score was weighted 50 percent, the Educational Adequacy Score was weighted 40 percent,

and the Technology Readiness Score was weighted 10 percent to create the Combined Score which totals100. Similar to a score that a teacher would use with a student, a high Combined Score is indicative of

better overall findings.

Using this scoring approach, the average district-wide combined score for all DeKalb County Schools is

70 which mean the facilities have an overall Fair rating. Some schools have physical condition,

educational, and/or technology needs that require improvements to meet the needs of children and to

maintain and improve the current facilities.

Facility Type

Number

By

Type

Facility

Condition

Score

(50%)

Educational

Adequacy

Score

(40%)

Technology

Readiness

Score

(10%)

Combined

Score

DeKalb County School System 151 75.81 69.23 75.59 70.14

Elementary Schools 84 67.64 69.48 77.54 67.87

Middle Schools 21 84.22 78.33 78.69 80.65

High Schools 24 83.38 65.45 75.98 74.54

Non-Schools 8 61.66 N/A N/A N/A

P-12 Facilities 4 49.07 60.24 62.70 54.49

Vacant / Closed Facilities 10 43.76 56.98 44.59 51.97

Source: Parsons and MGT of America, Inc., 2011


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2.6 Cost of Improvement

The cost of improvement includes current deficiencies1

and budget estimates that include condition,2

deferred maintenance3needs, educational adequacy and technology readiness 4needs, and forecasted

capital renewal5needs for all assessed facilities6at each school or non-school facility. The assessment

information and findings in this report addresses the facility needs for two time periods, the Current

Period (2011 2012)and theForecast Period (2013 2022). The Current Periodincludes facility

needs identified for the years 2011 2012 and includes the repair, replacement or modifications to the

current physical condition, educational adequacy, and technology readiness needs of the assessed

facilities. TheForecast Periodincludes the 10 years following, 20132022, and includes forecast capital

renewal facility needs based on the chronological expiration of the useful life of the systems for eachassessed school. The following table summarizes the district-wide budget estimates for facility needs.

Finding Budget Estimate

Condition Deferred Maintenance Needs (2011 - 2012) $768,574,380

Educational Adequacy Needs (2011 - 2012) $356,946,000

Technology Infrastructure Readiness Needs (2011 - 2012) $15,334,000

Total Current Facility Needs (2011 - 2012) $1,140,854,380

Capital Renewal Needs (2013 - 2017) $394,590,651

Capital Renewal Needs (2018 - 2022) $563,196,625

Total Forecast Capital Renewal Facility Needs (2013 - 2022) $957,787,276

Grand Total Current and Forecast Facility Needs (2011 - 2022) $2,098,641,656

As can be seen in the preceding table, the budget cost estimates to resolve and remedy the Current Period(2011 - 2012)deficiencies associated with deferred maintenance, educational adequacy, and technology

readiness needs is $1,140,845,380. AdditionalForecast Period (2013 2017 and 2018 - 2022)capital

renewal needs are estimated at $957,787,276. The estimated grand total for the period 2011 2022 is

$2,098,641,656.

Special Note regarding the Current Needs Budget Estimates for 2011 2012

During the course of the facility condition assessment, the assessment teams discovered and

observed damage to some foundation and exterior wall systems where further study and testing isneeded to determine the best repair or remediation solution. In such cases, the assessment teams

have provided budget estimates to conduct the additional study and testing. An estimated cost to

perform the best repair or remediation solution has not been included in the budget estimates.

1A deficiency is the physical state of being damaged, missing, inadequate or insufficient for an intended purpose.

2Condition refers to the state of physical fitness or readiness of a facility, system or system element for its intended use.

3Deferred maintenance refers to the Current Period (2011 - 2012) work associated with remedy of deficiencies for systems that have expired orwork has been postponed until funds are available. This figure includes building code compliance and energy conservation opportunities. Thisfigure excludes Function Adequacy & Technology Needs.4Educational Adequacy and Technology indicate how well a facility supports the programs that it houses as described in this report for

determining needs for academic spaces, administrative and support spaces, sports fields and play areas, learning environment, site circulationpatterns, and technology infrastructure.5Capital Renewal is the forecast period (2013 2022) replacement of building systems as those elements become obsolete or beyond their useful

life that are not normally included in an annual operating budget. Functional Adequacy & Technology needs are excluded.6

A facility is a building or part of a building site grounds or athletic feature which exists at a school and is maintained by DCSS


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The following table provides a summary of the deferred maintenance, educational adequacy and

technology readiness needs by thefacility typesassessed

2.7 Conclusion

DCSS has 151 school, non-school, and vacant/closed facilities. In order to determine the needs of these

facilities, the district conducted a comprehensive facility assessment during the period September 2010 June 2011. The assessment included physical condition, educational adequacy, technology readiness,

capacity and utilization of the facilities, as well as identification of energy conservation opportunities.

This report presents not only the summarized findings, but also the individual building data. The data

enables the district to measure needs based on the condition of the buildings and educational adequacy

issues. In the next phase of the project, DCSS will use the data to develop short- and long-range plans to

address the identified needs. It is strongly recommened that DCSS implement a 20% annual

reassessment of the facilities portfolio beginning in 2013. Through this 20% annual reassessment, DCSS

will be able to reevaluate the aging building systems and provide annual updates to this report.

Kelly Lake Elementary School

Facility Type

Number

By

Type

Gross

Square

Footage

Site

Acres

2011 - 2012

Deferred

Maintenance

Estimated

Budget Cost

2011 - 2012

Educational

Adequacy

Estimated

Budget Cost

2011 - 2012

Technology

Readiness

Estimated

Budget Cost

Current

Replacement

Value

Average

Replacement

Cost by GSF

DeKalb County School System 151 14,396,754 2,919 $768,574,380 $356,946,000 $15,334,000 $3,177,777,708 $220.73

Elementary Schools 84 5,816,857 1,051 $420,306,027 $143,491,000 $5,844,000 $1,299,034,215 $223.32

Middle Schools 21 3,156,031 718 $101,148,284 $49,481,000 $2,791,000 $641,038,900 $203.12

High Schools 24 4,394,887 835 $182,943,871 $140,173,000 $5,231,000 $1,100,455,178 $250.39 Non-Schools 8 337,055 126 $24,348,979 $0 $0 $63,500,884 $188.40

P-12 Facilities 4 151,382 50 $15,824,124 $5,384,000 $270,000 $31,072,421 $205.26

Vacant / Closed Facilities 10 540,542 139 $24,003,095 $18,417,000 $1,198,000 $42,676,110 $78.95

Note 1 - Deferred Maintenance Cost reflect cost for demolition only and no FCI or Condition Scores were produced.


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3.0 Assessment Methodology and ApproachThis Comprehensive Facility Assessment Report includes four critical parts, each with a distinctivemethodology and process. Data and information from each part were used to produce the facility

assessment findings and needs for DeKalb County Schools for the period of 2011 2022.

Section 3.1includes an assessment of thephysical conditionof each school facility, building, or

site system, such as foundations, roofing coverings, exterior walls, windows, doors, roadways,

and parking lots, as well as mechanical, plumbing, and electrical equipment. Also included in the

condition assessment process are the verification of building code compliance issues and energy

conservation opportunities.

Section 3.2includes aneducational adequacy and technology readinessassessment and analysis

of each schools ability to meet the current educational and technological needs. This assessment

was not conducted on storage, ancillary, athletic, or administrative buildings.

Section 3.3 includes acapacity and utilizationassessment to define current and future student

space needs. This capacity data will be combined with the assessment data in order to develop a

facility master plan for DeKalb County Schools.

Section 3.4includes the evaluation of the educational buildings and selected administrative and

support buildings to identify possible energy conservation opportunities. This evaluation was

not conducted on storage, ancillary, or athletic buildings.


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3.1 Facility Condition Assessment (FCA) Methodology

To start the condition assessment, the Parsons team met with DCSS facilities and maintenance personnelin a kick-off meeting in November 2010 to gain a mutual understanding of the project goals and

objectives to achieve a successful assessment. During this meeting, several key actions were taken that

set the course on how the work would progress. These actions included:

Establishing the schools and the facilities that would be assessed.

Describing the various phases of the work and types of assessments involved.

Prioritizing the order of the schools assessed. Identifying existing information that was available for each school.

Selecting and scheduling the schools for the pilot assessment.

Establishing the lines of communication.

Identifying access needs and procedures.

Preparing the Integrated Master Schedule and Weekly Assessment Schedules.

Parsons then conducted a pilot condition assessment on three school facilities and produced preliminary

reports for review. After review of the pilot condition assessment reports, some adjustments were made

to data collection, cost estimating, and reporting methods and information. Once mutual agreement on

the information adjustments was achieved, Parsons staff was assigned to perform the condition

assessment on the remaining sites.

During the field data collection and individual facility report preparation phase, between November 2010

and April 2011, a total of six separate draft report review sessions were held. The results of those

separate facility reports and this summary report are compiled from and supported by Parsons Condition

Management Estimation Technology (COMET) software, which stores and produces the assessment

information for each school and non-school facility.

The process used by Parsons to perform the condition assessment on the facilities was as follows:

Assemble and map a list of the overall facilities to be assessed. From this list, Parsons produced

the weekly assessment and reporting schedules for review and approval by DeKalb County

Schools.

Gather existing information about each facility from school records and drawings as to the

location, type of school, age, size, construction, additions, renovations, and major repairs or

replacement of facility systems.

Develop school, facility, and building system cost models for each facility type using the RS

Means cost estimating guides which are integral to Parsons COMET software to estimate facility

Current Replacement Values (CRV).

Review and update the cost models with historical construction costs paid by DeKalb CountySchools.


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Interview school administration, facilities management, maintenance, and operations personnel to

learn what the people maintaining the schools know about the facilities, such as the original

construction date, additions and upgrades done since construction, planned or on-going projects,and any known problems with the various facility systems, such as the foundation, structure, the

mechanical, electrical, and plumbing systems, and the floor, wall, and ceiling finishes.

Review documents furnished by the DeKalb County Schools to learn more about special

problems and needs, such as completed work orders, outstanding work orders, roof reports, and

other studies. This includes information from the Special-Purpose Local-Option Sales Tax

(SPLOST) data compiled by the district and any items for construction or improvement already

identified by the district. Visually assess and photograph the facilities to independently determine the overall physical

condition of the existing components and systems, and prepare deficiency reports and cost

estimates.

Enter the collected data into Parsons COMET proprietary software and database tool, gaining

access to approved cost models that are designed for facilities assessment, cost estimating,

reporting, and planning.

Identify energy conservation opportunities for each school or non-school main building.

Analyze the condition assessment data for completeness and produce individual facility

assessment reports.

Henderson Middle School


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3.2 Educational Adequacy and Technology Readiness

Assessments MethodologyMGT of America, Inc. conducted assessments of educational adequacy and technology readiness for

DeKalb County Schools (DCSS) from October through December 2010. In preparation for the site visits,

MGT staff met with the districts curriculum and technology specialists to ensure that the MGT data

collection software, Building Assessment System (BASYS) was calibrated to measure the DCSS schools

against the districts current educational guidelines. This software has been used to evaluate educational

adequacy and technology readiness for thousands of school buildings across the country. BASYS

provides a consistent assessment of a districts existing facilities.MGT conducted two separate assessments: educational adequacy and technology readiness. The

educational adequacy assessment evaluates how well the facility supports the educational program that it

houses. This assessment looks at both the inside and the outside of the school. For the outside of the

school, there are assessments regarding parking, traffic safety, play and athletic facilities, and signage.

For the inside of the school, there are three issues relative to each kind of space: size, adjacency, and

storage/fixed equipment.

Size of spaces For example, are the classrooms large enough for the assigned enrollment; is thecafeteria large enough to seat an appropriate percent of the student body.

Adjacency of spaces For example, is the library adjacent to the classrooms for easy access to

information and support; is the music space near other noisy spaces.

Storage and fixed equipment in spaces For example, do the science rooms have fire

extinguishers and other safety equipment; is there space in the classrooms for teacher and student

materials to be stored.

The technology readiness assessment measures the capability of the existing infrastructure to support

information technology and associated equipment. This assessment does not include the number of

computers or other devices. Instead, it reviews the capacity of the infrastructure to support current and

planned technology.

These assessments measure the educational and programmatic needs required to promote safe and

effective learning environments. A school-by-school assessment of educational adequacy and technology

readiness is essential since all of these factors impact the learning environment

The district asked that all schools/school types be visited and have an on-site assessment. MGT assessed

144 schools through site visits. Each site visit began with a meeting between the site administrator

(typically the principal or assistant principal) and the evaluator to discuss the educational program for the

school. The principal then conducted a tour that included both the inside of the building(s) and the

outside of the site, including play/athletic fields, parking lots, and circulation areas. The evaluator noted

the appropriateness of approximately 50 items, the number of items varying depending on the grade level

of the school. SeeAppendix D and E for the DCSS space guidelines and the assessment scoring criteria

used for this assessment. The recorded data was entered into BASYS and a draft report was generatedand reviewed with the site administrator. Community members and staff were included on each building

tour.


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3.3 Demographics, Capacity and Util ization AssessmentMethodology

3.3.1 Demographics Methodology

To be effective, a facility master plan must be responsive to the current and future number of students the

district serves. Determining the future enrollment of the district requires the examination of a variety of

demographic factors such as historic trends, live births, the number of housing units, local events, etc. It

is important that all factors that could potentially impact student enrollment be considered and the correct

methods employed when projecting future enrollment.

MGT used a multi-faceted approach to project enrollment for DeKalb County Schools. To begin, MGT

collected two forms of data: quantitative (statistical data) and qualitative (demographic trends based on

interviews). Quantitative data sources were obtained from the district, the county, and the U.S. Census

Bureau (Census) in the form of historical and forecasted population (total population and total population

broken down into age brackets), live births, housing units, and historical enrollment. Qualitative data was

gathered from conversations with district officials familiar with enrollment trends and county planners.

Both forms of data were critical to the preparation of enrollment projections for the districts ten year

facility master plan.

Next, MGT examined the district from three perspectives: the district as a whole, the super cluster

system, and magnet/charter school trends. Examining the district as a whole was to provide context.

However, in a district as large as DeKalb County Schools, analyzing trends solely at the district level can

be misleading--there are areas within the district trend differently from the district as a whole. It was

necessary to be aware of those area trends in order for the analysis to be effective. Accordingly, the

second perspective divided the district into five super clusters based on high school attendance areas that

resemble one another in historical experience and geographic location. The following Exhibit 3-1identifies the five super clusters.


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Exhibit 3-1Super Cluster Configuration

Source: DeKalb County School System


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These five super clusters are based on geographic areas. Two additional super clusters allow for analysis

of trends at the magnet schools and the charter schools. Because the magnet schools and the charter

schools draw enrollment from across the district, the analysis seeks to understand the enrollment trends atthese schools separate and apart from the attendance area enrollment-based schools. This third

perspective translates down to the individual school level, taking a look at trends within the magnet

schools and the charter schools across the district.

Finally, MGT developed enrollment projections for the ten-year planning period, using the weighted

average of four baseenrollment projection models to determine future enrollment patterns for the district.

Enrollment was projected for each super cluster and the projected enrollment for the district was the sum

of the super cluster enrollment projections.

3.3.2 Data Examined

Historical Enrollment

Historical enrollment provides the basis for all enrollment projections. Enrollment trends from past years

can, in the absence of significant events, be reasonably expected to continue for the foreseeable future.

Examining historical enrollment also provides insight into why trends do what they do.

The analysis begins with total enrollment. Then, the total enrollment is broken down by grade band,

either elementary school (grades K-5), middle school (grades 6-8), or high school (grades 9-12).

Frequently, one particular grade band will drive the trend seen in the total enrollment. For example, if

total enrollment is increasing, it is instructional to know that elementary school enrollment is also

increasing, while middle school and high school enrollment is holding steady. In such as situation, a

planner will know that enrollment at the elementary schools will eventually lead to an increase in

enrollment at the higher grades and will need to strategize accordingly.

Delving deeper into the data, the grade bands are organized into their respective grade levels (e.g.,

elementary school grade band into grades K, 1, 2, 3, 4, and 5). To continue the example from above, if

elementary school enrollment is increasing, it is helpful to know that kindergarten enrollment was the

initial impetus for the increase, and that continued increases in kindergarten enrollment has continued to

push elementary school enrollment higher. Armed with this knowledge, a planner will know that

elementary school enrollment will also be increasing in the short term.

Once the data has been fully pulled apart, it is also helpful to look at the increase or decrease in grade

level enrollment over the historical study period. Trend anomalies such as a significant increase/decreaseat a particular grade level require additional analysis. For example, a disproportionate increase in 9th

grade enrollment could be caused by a number of factors. Possible reasons could be:

Students migrating from a non-public school after 8th grade and entering public school,

A large number of students retained in 9th grade due to poor academic performance, or

A significant number of students transferring from another part of the district to attend 9th grade

in a particular super cluster.The final perspective on historical enrollment is that of the average cohort survival rates. Cohort survival

rates calculate the percentage of students who move from one grade level to the next from year to year.

For example, if there are 100 students in grade 1 in 2008 and there are 110 students in grade 2 in 2009,

the cohort survival rate is 110 percent. Similar to the analysis of the increase or decrease in enrollment

over the study period, analyzing the average cohort survival rate over the historical enrollment study


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period allows a planner to identify additional areas of inquiry as a full understanding of historical

enrollment trends is developed.

Intra-District Transfers

An analysis of intra-district transfers provides an expanded understanding of historical enrollment trends

and the potential effect on anticipated enrollment within a super cluster. For example, if a super cluster

has experienced a dramatic increase in enrollment due to a high number of transfer students coming into

that super cluster, the effect on enrollment projection methodology differs from the situation in which an

increase in enrollment is driven by an increase in live births. Transfers are more volatile and program-

based. The relocation of a program could lead to the relocation of that enrollment as well, leaving that

super cluster with a much different enrollment picture in the future. Transfer data is critical to

understanding historical enrollment trends and formulating a basis for weighting enrollment projection

models.

Grade-Level Retention

Additional understanding of historical enrollment trends comes from analyzing grade-level retention

trends. A bubblein enrollment may be due to an unexpected influx of students, or it could be due to,

among other possibilities, a significant number of students not progressing to the next grade level. Ratherthan assume that a bubble is due to an influx of students, a planner needs to evaluate retention data to

determine whether that bubble is due to students being retained due to poor academic performance.

Live Births and Kindergarten Enrollment

Another key component to analyzing potential future enrollment is to examine live-birth trends in the

district and the live-births-to-kindergarten capture rate. A steady or increasing birth rate in the district

could lead to additional students in the district, which would also push future enrollment higher.

When examining the ratio of live-births-to-kindergarten enrollment, live-birth data is collected for the

past fifteen years and kindergarten enrollment for the past ten years. For example, a child born in 1990

would enroll in kindergarten in 1995 at the age of five. Therefore, in this analysis, we are looking at how

many children are enrolled in kindergarten as compared to the number of children born in the city five

years prior to a particular school year.

Two statistics are critical to understanding the relationship between live births and kindergarten

enrollment in the district: correlation coefficient and capture rate. The correlation coefficient calculatesthe relationship between two series of data. A correlation coefficient of 1indicates a strong relationship;

a correlation coefficient of 0indicates a weak relationship. The capture rate measures the percentage of

live births that resulted in kindergarten enrollment five years later.

Future births provide a potential indication of future kindergarten enrollment. Therefore, projecting

future live births is essential to understanding what future enrollment could be. This analysis employs

two methods for estimating future live births. The first is a simple linear regression analysis, which finds

the line of best fit within the historical data and then uses the slope of that line as the future live birthsprojection.

The second method is more complicated and requires an examination of birth rates among females of

child-bearing age groups. Child bearing age is generally between ages 15 and 45. By comparing

historical live births by female age groupings (e.g., 10-19, 20-24, 25-34, etc.) with the number of females

in each age grouping, a natality rate is generated for each grouping. For this analysis, this comparison is

d f th 2000 U S C A ti t d t lit t f h i i l l t d f 2010


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Then, the 2010 natality rate is combined with the 2015 estimated female population at each age grouping

to generate an estimated number of live births at each age grouping in 2015. Finally, for the years

between 2010 and 2015, data is interpolated to plug in a number of live births in the interim years. Thoselive birth estimates will lead to estimated kindergarten enrollment between 2016 and 2020.

Planners need to examine future live births from both perspectives to validate an understanding of

possible future live births and their impact on future kindergarten enrollments.

Housing Units

Housing trends in a district are a good indication of where future students will be located. Significant

housing increases in a particular area can generally be expected to result in additional students.Conversely, if an area is transitioning from multi-family to single-family housing, fewer students should

be expected to be the result.

The key statistic is the student generation factor. In other words, how many students at each grade level

do the three types of housing (single family, multi-family, mobile home) tend to produce? The total

number of housing units is pulled apart into the three housing types, and the resulting trends are

evaluated. Then, a gross student generation rate is calculated by dividing the number of students in a

given year by the number of housing units in that same year. Next, each housing unit type is compared tothe total number of housing units in that year to determine the proportion of the total each type comprises.

That proportion is then multiplied by the gross student generation rate for each grade level. The resulting

generation rate provides the planner with an opportunity to examine which type of housing generates

more students and apply that understanding to the enrollment projection models.

Population Trends

Trends in the population of the district as a whole can help a planner determine whether more students are

moving into the district and what the likelihood of future students might be. Population trends analysis

looks at the total population size and the age structure of the district. Of particular interest is the shape of

the age structure. A pyramid-shaped age structure indicates a growing population. An age structure that

is rectangular in shape indicates a stable population, i.e., a population that is neither growing nor

shrinking, while an inverted pyramid-shaped age structure suggests an aging or declining population.

Furthermore, a projected increase in school-age population suggests that the district will have more

students in the future. Planners need to have a sense of the shape of the districts population age structure

to gain insights into possible future enrollment.

Racial Composition

Though not a driving component of enrollment projection development, it is important to understand the

racial composition of the district as a part of the context for each of the super clusters.

Non-Public School and Charter School Enrollment

It is helpful to study the trends in enrollment experienced by other education providers in the area and to

identify where common or complimentary trends are occuring. For example, if a decline in district

enrollment ocurred over the same period that non-public school enrollment increased, a logical conclusion

would be that district students have left to attend non-public schools. On the other hand, if both district

and non-public enrollment is declining, the inquiry will lead to additional analysis of population trends to

determine whether, for example, fewer children are being born in the district or, perhaps, children are


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leaving the district before reaching school age. Whatever the case may be, comparing district enrollment

with non-public school enrollment can help to explain historical district enrollment trends.

Socio-Economic Status

Like racial composition, socio-economic status is not a significant factor in developing enrollment

projections. However, socio-economic status does provide important context for the analysis of historical

data and the development of enrollment projections.

3.3.3 Enrollment Projection Methodology

It is critical to understand that enrollment projections are merely an estimateof future activity based onthe historical data and information provided. As demonstrated by the district calculations over the past

ten years, there can be constant variations in growth. These numbers can be highly accurate, but it must

be remembered that the numbers are still a projection or estimate. During the implementation of any of

the recommendations provided, it is critical that the district reassess these numbers on a regular basis and

adjust plans accordingly.

To identify trends and prepare for adequate spaces, teaching staff and materials and supplies, educational

leaders use several methods of projecting enrollment. Among the most commonly used models are

Average Percentage Annual Increase, Cohort Survival, Linear Regression, and Student-per-Housing Unit

models. Because no one model is foolproof, MGT generates a weighted average of these four base

models to arrive at its enrollment projection.

A rule of thumb when forecasting enrollment is that the models should use as many years of historical

data as there are years in the projection period. In other words, if the model is projecting enrollment for

five years from now, then five years of historical data is used. If the model is projecting enrollment for

ten years from now, then ten years of historical data is used. Each of the following base models draw data

in this manner for their calculations.

Average Percentage Annual Increase Model

This model calculates future school enrollment growth based on the historical average growth from year

to year for each grade level. This simple model multiplies the historical average percentage increase (or

decrease) by the prior years enrollment to project future enrollment estimates. For example, if

enrollment in first grade decrease five percent from 2000 to 2001 and decreased seven percent from 2001

to 2002, then the average percentage increase/decrease would be six percent, and six percent would be thefactor used to project future enrollment in this base model.

Linear Regression Model

This model uses a statistical approach to estimating an unknown future value of a variable by performing

calculations on known historical values. Once calculated, several future values for different future dates

can then be plotted to provide a regressionor trend line. MGT has chosen a straight-linemodel to

estimate future enrollment values, a model that is the most accommodating based on the historical data.

Cohort Survival Model

This model calculates the growth or decline in a grade level over a period of ten years based on the ratio

of students who attend each of the previous years, or the survival rate. This ratio is then applied to the

incoming class to calculate the trends in that class as it moves or graduates through the school system.

For example if history shows that between the first and second grades the classes for the last ten years


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have grown by an average of 3.5 percent, then the size of incoming classes for the next ten years is

calculated by multiplying them by 103.5 percent. If the history shows a declining trend, the multiplying

factor would be 100 percent minus the declining trend number.

The determination of future kindergarten enrollment estimates is critical, especially for projections

exceeding more than five years. There are two methods of projecting kindergarten enrollment. The first

model is based on the correlation between historical birth rates (natality rates) and historical kindergarten

enrollment. The second model uses a linear regression line based on the historical kindergarten

enrollment data. The correlation model was selected due to the strong correlation between live births and

kindergarten enrollment as discussed above.

Students-Per-Household Model

This last model utilizes the estimated number of households as its base data. Using the housing unit data

and historical enrollment data, MGT created a student generation factor for each projected housing unit.

By taking the total enrollment by grade level and dividing it by the current housing levels, a student

generation factor(SGF) was calculated for each grade level. This factor indicates the number of students

within each grade level that will be generated by each new housing unit.

Weighted Average

Once each of these four base models has been calculated, MGT generates a weighted average of each of

the models. A weighted average allows the analysis to reflect all of the trends observed in the historical

data and the over-arching themes from the qualitative information gathered in this process. The weighted

average also works to maximize the strengths of each of the base models.

Two models, the Average Percentage Annual Increase Model and the Linear Regression Model,

emphasize historical data. These models are quite effective predictors if there is no expectation of

unusual community growth or decline and student population rates have minimal fluctuation.

The Cohort Survival Model also uses historical enrollment numbers, but takes into account student-

mobility patterns and the effects of the natality rates in prior years. The Cohort Survival Model is perhaps

the best-known predictive tool using this type of data. However, like the Annual Percentage Annual

Increase Model and the Linear Regression Model, the Cohort Survival Model loses its predictive

capabilities in communities that experience, or are expecting to experience, more rapid growth.

The Students-Per-Household Model allows the planner to take into account projections for housing

developments and general growth in the county. This model looks forward and is based on the input from

local planners. The planning information is important and the district should continue to monitor this

information.

3.3.4 Capacity Methodology

MGT uses theInstructional Use Modelto calculate a schools capacity. The Instructional Use Model

counts the number of the various types of instructional rooms and multiplies that number by a students-

per-room or loadingfactor to identify the gross capacity for the school. The gross capacity is thenmultiplied by a scheduling factor, which takes into account the realities of how the space is used. For

example, middle and high school students move from room to room and enroll in a variety of courses. As

a result, some rooms will sit empty or will be less than fully occupied at any given time. Teacher

preparation periods will also contribute to rooms not being used for instruction at a particular time.

Therefore, MGT uses a 75 percent scheduling factor to reduce the gross capacity of the building to reflect

th d d t th liti f h hi h h l f ti A l t h l th th


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hand, has students that remain in one room for most of the school day. Therefore, MGT uses a 90 percent

scheduling factor for elementary schools to reflect the fairly consistent, day-long use of elementary

classrooms. The guidelines used for these calculations are listed below.

Exhibit 3-2Instructional Space Model Guidelines

Instructional Space Model Guidelines

Room Type

MGT Students/

Room

Preschool 20

Kindergarten 20

K-5 Early Intervention (EIP) self-contained & pull-out classes 18

1-3 22

4-8 (E/LA, Math, Social Studies) 284-8 (Science) 0

K-3 Fine Arts (Music, Art) 0

6-8 Fine Arts & World Language 28

4-8 (all other subjects) 28

9-12 (E/LA, Math, Social Studies, World Language) 28

9-12 (Science) 28

9-12 (all other subjects) 28

Typing/Keyboarding 24

Vocational Labs 24

Instrumental Music (Band) (Secondary) 40

Choral Music (Secondary) 40

Physical Education (Secondary) 44


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Exhibit 3-2Instructional Space Model Guidelines (cont.)

Instructional Space Model Guidelines

Room TypeMGT Students/

Room

SPED - K-5 Gifted 12

SPED - K-5 Resource 12

SPED - 6-12 Gifted (Resource and Advanced Content) 12

SPED - 6-12 Remedial (REP) 12

Alternative Programs (ask principal) 20

K-3 ESOL 13

4-8 ESOL 16

9-12 ESOL 20

Computer Lab 0

Spec. Ed. - Self Contained 8

Portable (classrooms, not buildings) 0

Scheduling Factors

Elementary Schools 90.0%

Middle Schools 75.0%

High Schools 75.0%

Source: MGT of America, Inc., 2011


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3.4 Energy Conservation Analyses Methodology

Concurrent with the facility condition assessment, the teams also conducted a system level energy

evaluation on the main educational buildings at each school to identify potential energy conservation

opportunities. Prior to commencing this work, Parsons identified eight (8) UNIFORMAT II building

systems that could offer potential energy conservation opportunities. The identified systems included:

Roof Coverings & Insulation

Exterior Windows

Window Treatments

Interior Lighting

Exterior Lighting

Heating, Cooling & Air Conditioning (HVAC)

Plumbing

Building Controls & Automation

The assessment teams subsequently assessed and identified for each school the systems that due to overallaged and condition, and if replaced, could provide potential energy conservation to the school system.

Parsons prepared and provided to DeKalb County Schools the findings and opportunities for energy

conservation for each of the schools. Summary of the findings and potential conservation opportunities

for DeKalb County Schools can be found in the Findings section of this report. A large majority of the

energy conservation opportunities can be achieved through the course of replacing those building systems

that are identified as beyond their service life and are identified as current deferred needs (2010 2012) in

the individual building assessment reports.

Cooling Generating System at Miller Grove Middle School


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4.0 Findings

DCSS has school facilities that are performing well and should continue to meet the school systemsneeds; however, the district must contend with the inevitable aging process of the facilities7, fluctuating

numbers of students, and changing educational programs. Older schools have building and grounds

systems that have already surpassed their service life and need replacing now, while the life cycle of some

newer school systems will expire and need replacing in the next 10 years. Some schools are experiencing

growth due to new student in-flow and, in some schools, student enrollments are decreasing as a result of

demographic migration from one area to another. New technologies and initiatives that envision the

evolving relationship between school facilities and student performance and behavior are profoundly

impacting the school facilities and curricula. Addressing facility condition, educational adequacy,

capacity and utilization, and technology readiness needs is critical to meet the DeKalb County Schools

Master Plan initiatives.

This section of the report includes the findings of the facility assessments and includes four separate parts

which describe the methodology and approach used to conduct the assessments. These four parts allow a

review of the facility assessment findings and needs for DeKalb County Schools for the period of 2011

2022.

Section 4.1includes the results of thephysical conditionassessment of each school facility,

building or site system, such as foundations, roof coverings, exterior walls, windows, doors,

roadways, and parking lots, as well as the mechanical, plumbing, and electrical equipment.

Section 4.2includes the results ofthe educational adequacy and technology readiness

assessments,and analysis of each schools ability to meet the educational and technological

needs into the future.

Section 4.3includes the results of thecapacity and utilizationassessment and defines current andfuture student space needs.

Section 4.4includes the various energy conservation opportunities for the schools.

Miller Grove High School

7A facility refers to site(s), building(s), or building addition(s), or athletic features or combinations thereof that provide a particular service or

support of an educational purpose


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4.1 Facility Condition Assessment (FCA) Findings

Part 1 details the findings on the physical condition of the building and site systems installed at eachschool facility. Information in this section is derived from the methods and approach used by the

assessment team and described earlier to visually assess each school. This section includes the following

information:

Benchmark Indices and Measurements Used to Rate the Current Physical Condition of Each

School

Current Facility Condition Index and Rating for Each School

Facility Condition Index by Facility Type, e.g., Elementary School (ES), Middle School (MS),

High School (HS), P-12 School, and Non-School Site (NSS)

Analysis and Comparison of Facility Age of the DeKalb County Schools

Deferred Maintenance and Capital Renewal Cost Estimates

Deferred Maintenance, Educational Adequacy, and Technology Readiness Needs by Super

Cluster

Deferred Maintenance and Capital Renewal Needs by Gross Square Feet (GSF)

Facility Condition Index (FCI) by GSF

Current Needs by Facility System (Roofs, Windows, Etc.)

Current Needs by Deficiency Priority

Current Needs by Deficiency Category

Current Needs by Deficiency Distress

Capital Renewal Needs Forecast (2013 2022)

Funding Options to Target Condition Improvement

Benchmark Indices and Measurements

When reading the findings of this report, it is important to understand that an assessment is a snapshot of

conditions found at a facility on the day it is inspected. Facility conditions typically change subtly over

time; however, they can also change very quickly. For example, the day after an inspection is conducted,

a facility system or component may break or be repaired, and that break or repair will not be reflected in

the assessment findings. Schools removed from or added to service after a scheduled field assessment

will not be represented accurately. For this reason, the findings in this report should be viewed as time-

bound although the conditions at the sites are ever-changing.

The Facility Condi tion Index (FCI) Standard

One of the tasks of the assessment is to determine the Facility Condition Index (FCI) for each facility andthe cost variables that are to be used in the FCI determination. The National Association of College and

University Business Officers (NACUBO) established the FCI standard and defined the FCI as a ratio of

the Cost of Repairs (Deferred Maintenance) divided by the Current Replacement Value (CRV) of a

facility. This is typically expressed as a ratio:

FCI = Cost of Repairs (DM) / Current Replacement Value (CRV)


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NACUBO established and published this standard in 1991 as a means to quantitatively measure the

physical condition of a facility or portfolio of facilities. This standard is widely used today. The standard

provides a rating system relative to the FCI to offer a qualitative sense of the Good, Fair, Poor, orUnsatisfactory condition of a facility (or its components, or a group of facilities) against a cost model of

a similar facility as if it was at the beginning of its useful life, or fully renewed to todays standards. As

shown below, the lower the FCI, the better the facility condition.

FCI% Rating

0% - 15%Good: The facility is in overall good physical condition with 15% orless of the value of the building systems needing repair orreplacement.

15.1%- 30%Fair: The facility is in overall fair condition with 15.1% to 30% of the

value of the building systems needing repair or replacement.

30.1% - 50%

Poor: The facility is in overall poor condition with 30.1 to 50% of the

value of the building systems needing repair or replacement. Many

of the building systems have exceeded their expected useful life.

50%

Unsatisfactory: The facility is in unsatisfactory physical condition

with more that 50% of the value of the building systems needingrepair or replacement. Many of the building systems are failing or nolonger meet the needs of the facility.

DeKalb County Schools FCI

Cost Estimates

The cost and budget estimates in this report are order-of-magnitude8repair estimates for full or partial

replacement of expired systems or elements, out-of-cycle repairs, and modifications. In some cases, the

total of these estimates may exceed a facilitys Current Replacement Valuean indicator that it may be

more economical to replace a facility than to repair it. The cost estimates are taken from two sources.

The first source is the2011 RS Means Square Foot Cost for Construction Estimating Guidewhich

provides the square foot unit cost estimate for each of the facility systems. The second source of the cost

estimates is a comparison of the national RS Means unit cost to the actual, local cost of construction being

paid by DeKalb County Schools.

Special Note regarding the Current Needs Budget Estimates for 2011 2012

During the course of the facility condition assessment the assessment teams discovered and

observed damage to some foundation and exterior wall systems where further study and testing is

needed to determine the best repair or remediation solution. In such cases, the assessment teams

have provided budget estimates to conduct the additional study and testing. An estimated cost to

perform the best repair or remediation solution has not been included in the budget estimates.

Addi tional Project Costs

The cost estimates include additional project costs, such as design and management fees, surveys,

permits, materials testing, and contingency.

8Order of Magnitude is a rough approximation, made with a degree of knowledge and confidence that the estimated figure falls within a

reasonable range of cost values


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4.1.1 Condition Finding #1: Facility Condition Index (FCI) and Rating for EachFacility

The table below contains the Current Deferred Maintenance Cost, Current Replacement Value, FacilityCondition Index (FCI), and Rating for each school or non-school in DeKalb County.

Facility NameYear

Built

Gross

Square

Footage

2011 - 2012

Deferred

Maintenance

Estimated

Budget Cost

2011 - 2012

Educational

Adequacy

Estimated

Budget Cost

2011 - 2012

Technology

Readiness

Estimated

Budget Cost

Current

Replacement

Value

FCI %Condition

Rating

DeKalb County School Sys tem 14,396,754 $768,574,380 $356,946,000 $15,334,000 $3,177,777,708 24.19% Fair

Elementary Schools 5 ,816,857 $420,306,027 $143,491,000 $5,844,000 $1,299,034,215 32.36% Poor

Allgood Elementary 1955 63,989 $6,363,842 $1,269,000 $86,000 $13,517,001 47.08% Poor Ashford Park Elementary 1955 49,726 $2,702,772 $1,602,000 $75,000 $10,716,578 25.22% Fair

Atherton Elementary 1964 64,356 $7,246,269 $1,133,000 $72,000 $13,352,153 54.27% Unsat

Austin Elementary 1975 60,581 $4,649,209 $3,517,000 $28,000 $13,219,479 35.17% Poor

Avondale Elementary 1953 71,567 $10,226,565 $1,009,000 $61,000 $19,641,998 52.06% Unsat

Bob Mathis Elementary 1975 69,401 $5,301,507 $1,489,000 $75,000 $23,846,622 22.23% Fair

Briar Vista Elementary 1955 58,418 $7,177,740 $1,587,000 $93,000 $12,196,956 58.85% Unsat

Briarlake Elementary 1957 53,750 $5,529,511 $1,700,000 $52,000 $13,971,344 39.58% Poor

Brockett Elementary 1961 54,794 $6,273,203 $1,301,000 $59,000 $12,521,881 50.10% Unsat

Browns Mill Elementary 1990 75,978 $3,094,130 $2,054,000 $67,000 $16,296,611 18.99% Fair

Canby Lane Elementary 1967 67,806 $6,183,967 $994,000 $81,000 $14,032,927 44.07% Poor

Cary Reynolds Elementary 1961 73,466 $6,195,299 $2,656,000 $77,000 $14,939,838 41.47% Poor

Cedar Grove Elementary 1975 75,901 $5,869,487 $888,000 $117,000 $15,484,984 37.90% Poor

Chapel Hill Elementary 1967 69,150 $8,226,293 $1,785,000 $110,000 $13,922,961 59.08% Unsat

Chesnut Elementary 1969 52,018 $5,007,535 $2,051,000 $50,000 $11,491,572 43.58% Poor

Clifton Elementary 1967 59,801 $4,881,298 $741,000 $35,000 $14,005,379 34.85% Poor

Columbia Elementary 1961 75,793 $6,683,544 $1,893,000 $85,000 $16,227,895 41.19% Poor

Coralwood Diagnostic Center 1967 38,102 $243,680 $2,217,000 $0 $7,938,213 3.07% Good

DeKalb Elementary School of the Arts 1958 68,865 $2,471,777 $599,000 $32,000 $14,560,649 16.98% Fair

Dresden Elementary 1963 69,760 $3,846,896 $1,604,000 $103,000 $13,538,173 28.42% Fair

Dunaire Elementary 1967 67,401 $4,457,723 $2,011,000 $83,000 $14,738,709 30.25% Poor

Dunwoody Elementary 2009 150,020 $16,568 $2,444,000 $23,000 $44,725,846 0.04% Good E.L. Bouie Elementary 1996 91,602 $1,392,505 $1,553,000 $53,000 $19,947,555 6.98% Good

Eldridge Miller Elementary 1981 72,443 $7,759,358 $1,930,000 $76,000 $14,166,371 54.77% Unsat

Evansdale Elementary 1967 53,998 $4,106,363 $2,024,000 $60,000 $11,992,543 34.24% Poor

Fairington Elementary 1975 66,977 $4,395,435 $2,959,000 $132,000 $13,922,678 31.57% Poor

Fernbank Elementary 1958 61,027 $7,041,787 $2,479,000 $52,000 $13,513,156 52.11% Unsat

Flat Rock Elementary 2007 107,937 $667,504 $2,170,000 $67,000 $23,567,685 2.83% Good

Flat Shoals Elementary 1966 63,644 $3,826,857 $1,836,000 $76,000 $14,088,453 27.16% Fair

Glen Haven Elementary 1943 66,827 $2,605,595 $961,000 $46,000 $14,107,116 18.47% Fair

Gresham Park Elementary 1958 55,718 $6,829,751 $1,710,000 $58,000 $12,584,750 54.27% Unsat

Hambrick Elementary 1971 72,384 $6,845,794 $1,085,000 $89,000 $15,697,549 43.61% Poor

Hawthorne Elementary 1961 53,418 $4,801,244 $1,815,000 $68,000 $11,340,681 42.34% Poor Henderson Mill Elementary 1965 55,887 $7,440,767 $2,246,000 $69,000 $16,984,911 43.81% Poor

Hightower Elementary 1958 54,213 $1,285,043 $1,891,000 $50,000 $11,818,057 10.87% Good

Huntley Hills Elementary 1964 54,012 $6,466,698 $1,580,000 $102,000 $12,296,880 52.59% Unsat

Idlewood Elementary 1967 72,668 $5,348,763 $2,001,000 $87,000 $15,009,110 35.64% Poor

Indian Creek Elementary 1961 80,323 $9,277,965 $2,125,000 $93,000 $17,697,307 52.43% Unsat

Jolly Elementary 1968 71,924 $4,971,698 $1,181,000 $58,000 $15,353,347 32.38% Poor

Kelley Lake Elementary 1963 53,237 $4,189,572 $920,000 $51,000 $11,363,903 36.87% Poor

Kingsley Elementary 1971 60,378 $6,020,584 $1,734,000 $65,000 $12,414,305 48.50% Poor

Kittredge Magnet School at Nancy Creek 1970 57,163 $6,206,535 $1,214,000 $48,000 $12,091,016 51.33% Unsat

Knollwood Elementary 1955 63,342 $3,424,725 $1,361,000 $76,000 $14,240,671 24.05% Fair

Laurel Ridge Elementary 1958 58,384 $6,561,153 $1,358,000 $77,000 $12,379,130 53.00% Unsat

Livsey Elementary 1971 40,414 $4,399,272 $1,139,000 $48,000 $8,756,400 50.24% Unsat


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Facility NameYear

Built

Gross

Square

Footage

2011 - 2012

Deferred

Maintenance

EstimatedBudget Cost

2011 - 2012

Educational

Adequacy


2011 - 2012

Technology

Readiness


Current

Replacement

Value

FCI %Condition

Rating

Marbut Elementary 1994 98,739 $2,767,985 $1,457,000 $49,000 $21,346,709 12.97% Good

McLendon Elementary 1958 58,843 $1,635,565 $1,567,000 $48,000 $12,230,149 13.37% Good

Meadowview Elementary 1961 54,761 $6,061,389 $1,193,000 $70,000 $12,003,317 50.50% Unsat

Medlock Elementary 1951 40,054 $5,447,634 $877,000 $65,000 $9,201,836 59.20% Unsat

Midvale Elementary 1966 60,855 $4,543,503 $1,383,000 $38,000 $13,768,850 33.00% Poor

Midway Elementary 1958 71,318 $5,370,735 $913,000 $69,000 $14,099,186 38.09% Poor

Montclair Elementary 1967 71,711 $5,160,614 $2,789,000 $58,000 $15,085,698 34.21% Poor

Montgomery Elementary 1963 61,857 $6,215,176 $2,006,000 $72,000 $13,184,096 47.14% Poor

Murphey Candler Elementary 1969 73,818 $1,922,993 $2,514,000 $165,000 $13,414,403 14.34% Good

Narvie Harris Elementary 1998 99,190 $414,609 $319,000 $123,000 $22,013,857 1.88% Good

Oak Grove Elementary 1958 55,666 $3,895,055 $1,946,000 $88,000 $14,396,300 27.06% Fair

Oak View Elementary 2004 108,000 $4,271,752 $551,000 $79,000 $37,800,690 11.30% Good

Oakcliff Elementary 1964 72,228 $4,139,194 $1,619,000 $67,000 $16,506,534 25.08% Fair

Panola Way Elementary 1987 86,443 $7,704,227 $1,582,000 $103,000 $17,711,730 43.50% Poor

Peachcrest Elementary 1961 72,194 $6,564,877 $2,616,000 $84,000 $14,632,830 44.86% Poor

Pine Ridge Elementary 1988 87,192 $6,280,886 $3,541,000 $114,000 $18,308,914 34.31% Poor

Pleasantdale Elementary 1968 64,744 $5,386,074 $3,738,000 $135,000 $14,505,285 37.13% Poor

Princeton Elementary 2007 102,000 $83,150 $958,000 $47,000 $22,962,258 0.36% Good

Rainbow Elementary 1970 72,970 $5,382,475 $2,717,000 $59,000 $15,450,935 34.84% Poor

Redan Elementary 1935 82,784 $7,631,840 $1,391,000 $86,000 $17,074,208 44.70% Poor

Robert Shaw Elementary 1955 56,249 $6,198,161 $1,170,000 $54,000 $11,541,847 53.70% Unsat

Rock Chapel Elementary 1969 73,744 $6,605,587 $173,000 $9,000 $14,510,496 45.52% Poor

Rockbridge Elementary 1972 60,708 $8,117,987 $2,190,000 $77,000 $13,039,123 62.26% Unsat

Ronald E. McNair Discovery Learning

Academy 2008 99,000 $21,726 $2,137,000 $23,000 $22,643,747 0.10% Good

Rowland Elementary 1967 64,528 $885,959 $1,003,000 $65,000 $13,766,331 6.44% Good

Sagamore Hills Elementary 1961 54,891 $4,847,786 $2,335,000 $40,000 $15,268,273 31.75% Poor

Shadow Rock Elementary 1991 112,298 $6,319,707 $654,000 $29,000 $24,242,002 26.07% Fair

Sky Haven Elementary 1955 63,875 $7,194,285 $2,492,000 $106,000 $14,216,158 50.61% Unsat

Smoke Rise Elementary 1969 65,694 $8,837,248 $2,053,000 $71,000 $14,047,500 62.91% Unsat

Snapfinger Elementary 1964 87,316 $3,594,463 $2,725,000 $81,000 $19,636,792 18.30% Fair Stone Mill Elementary 1975 70,896 $6,625,808 $637,000 $27,000 $14,284,617 46.38% Poor

Stone Mountain Elementary 1954 65,647 $8,848,976 $2,035,000 $94,000 $13,915,949 63.59% Unsat

Stoneview Elementary 1963 71,293 $6,596,528 $1,675,000 $91,000 $16,341,537 40.37% Poor

Toney Elementary 1953 56,094 $6,813,151 $1,836,000 $65,000 $11,889,661 57.30% Unsat

Vanderlyn Elementary 1973 58,951 $3,090,438 $2,067,000 $14,000 $11,619,629 26.60% Fair

Wadsworth Elementary 1958 54,142 $6,452,795 $1,934,000 $63,000 $11,285,505 57.18% Unsat

Woodridge Elementary 1975 58,418 $5,107,390 $1,553,000 $56,000 $11,808,525 43.25% Poor

Woodward Elementary 1961 74,161 $3,742,750 $3,064,000 $114,000 $19,408,287 19.28% Fair

Wynbrooke Elementary 2001 95,022 $1,011,766 $265,000 $81,000 $19,649,108 5.15% Good

Middle Schools 3,156,031 $101,148,284 $49,481,000 $2,791,000 $641,038,900 15.78% Fair Avondale Middle 2000 156,479 $1,056,345 $620,000 $154,000 $35,041,991 3.01% Good

Cedar Grove Middle 1999 162,926 $4,329,585 $2,175,000 $155,000 $35,005,764 12.37% Good

Chamblee Middle 2006 129,449 $1,645,752 $1,682,000 $27,000 $25,695,716 6.40% Good

Champion Middle 1961 131,176 $13,995,260 $3,055,000 $254,000 $26,994,478 51.84% Unsat

Chapel Hill Middle 1991 154,881 $5,369,698 $2,392,000 $131,000 $31,821,022 16.87% Fair

Columbia Middle 2001 161,263 $357,380 $1,502,000 $68,000 $33,503,309 1.07% Good

Freedom Middle 2000 161,263 $839,038 $779,000 $85,000 $31,476,602 2.67% Good

Henderson Middle 1968 158,140 $6,242,405 $4,381,000 $251,000 $30,311,899 20.59% Fair

International Student Center 1958 47,808 $3,208,395 $2,277,000 $62,000 $8,502,158 37.74% Poor

Lithonia Middle 1955 148,358 $2,548,304 $2,025,000 $120,000 $30,950,668 8.23% Good

Mary McLeod Bethune Middle 2001 161,263 $1,745,345 $1,017,000 $68,000 $31,053,886 5.62% Good

Miller Grove Middle 1985 132,700 $11,019,027 $3,474,000 $98,000 $25,878,444 42.58% Poor

Peachtree Middle 2006 147,300 $186,524 $1,860,000 $114,000 $32,643,840 0.57% Good

Redan Middle 2003 161,263 $1,216,443 $1,159,000 $165,000 $34,563,482 3.52% Good


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Facility NameYear

Built

Gross

Square

Footage

2011 - 2012

Deferred

Maintenance


2011 - 2012

Educational

Adequacy


2011 - 2012

Technology

Readiness


Current

Replacement

Value

FCI %Condition

Rating

Ronald McNair Sr. Middle 1958 173,040 $17,769,168 $4,762,000 $201,000 $34,160,185 52.02% Unsat

Salem Middle 1989 138,469 $8,149,267 $1,949,000 $200,000 $25,693,885 31.72% Poor

Sequoyah Middle 1965 162,448 $7,658,186 $4,942,000 $183,000 $32,070,579 23.88% Fair

Shamrock Middle 1967 161,542 $5,914,928 $5,392,000 $154,000 $32,399,030 18.26% Fair

Stephenson Middle 1994 190,323 $7,326,677 $1,142,000 $201,000 $39,625,353 18.49% Fair

Stone Mountain Middle 2006 163,590 $115,438 $1,737,000 $52,000 $33,309,577 0.35% Good

Tucker Middle 2004 152,350 $455,119 $1,159,000 $48,000 $30,337,032 1.50% Good

High Schools 4,394,887 $182,943,871 $140,173,000 $5,231,000 $1,100,455,178 16.62% Fair

Administrative & Instructional Complex 1988 274,075 $111,872 $2,159,000 $35,000 $63,952,238 0.17% Good

Arabia Mountain High 2009 227,670 $0 $5,532,000 $59,000 $56,679,150 0.00% Good

Avondale High/DeKalb School of the Arts 1955 175,429 $11,364,116 $9,503,000 $331,000 $39,119,117 29.05% Fair

Cedar Grove High 1972 207,700 $12,144,498 $8,058,000 $398,000 $51,557,313 23.56% Fair

Chamblee High 1963 193,320 $26,264,173 $12,548,000 $169,000 $46,842,842 56.07% Unsat

Clarkston High 1964 160,454 $13,409,049 $7,177,000 $245,000 $41,567,127 32.26% Poor

Columbia High 1966 187,240 $4,698,546 $5,818,000 $416,000 $60,291,913 7.79% Good

Cross Keys High 1958 175,847 $8,822,394 $5,197,000 $46,000 $37,441,958 23.56% Fair

DeKalb East Campus/Alt School/Alt Night

School1982 117,375 $3,450,653 $4,579,000 $164,000 $25,281,611 13.65% Good

DeKalb HS of Technology South 1977 47,467 $4,253,406 $1,627,000 $76,000 $10,750,113 39.57% Poor

Druid Hills High 1927 170,915 $8,327,400 $5,655,000 $134,000 $44,035,429 18.91% Fair

Dunwoody High 1972 182,604 $8,082,909 $5,428,000 $167,000 $49,827,995 16.22% Fair

Lakeside High 1965 164,666 $3,227,240 $12,348,000 $409,000 $56,757,248 5.69% Good

Lithonia High 2001 188,851 $1,964,875 $2,640,000 $74,000 $48,515,712 4.05% Good

Margaret Harris Comprehensive School 1967 43,766 $1,643,982 $590,000 $34,000 $10,762,933 15.27% Fair

Martin Luther King Jr. High 2001 186,272 $14,822,854 $3,457,000 $284,000 $48,673,677 30.45% Poor

Miller Grove High 2005 240,000 $2,651,183 $1,757,000 $94,000 $59,262,986 4.47% Good

Redan High 1976 180,668 $10,112,972 $10,575,000 $519,000 $41,473,117 24.38% Fair

Ronald McNair Sr. High 1964 222,769 $484,201 $4,197,000 $300,000 $54,647,343 0.89% Good

Southwest DeKalb High 1967 206,179 $15,253,452 $8,849,000 $287,000 $51,626,248 29.55% Fair

Stephenson High 1994 241,181 $15,889,204 $4,361,000 $336,000 $55,299,999 28.73% Fair Stone Mountain High 1976 173,918 $13,391,038 $7,074,000 $234,000 $40,374,609 33.17% Poor

Towers High 1963 178,624 $2,573,854 $6,750,000 $420,000 $43,914,494 5.86% Good

Tucker High 2010 247,897 $0 $4,294,000 $0 $61,800,006 0.00% Good

Non-Schools 337,055 $24,348,979 $0 $0 $63,500,884 38.34% Poor

Adams Stadium 1962 14,048 $2,266,405 N/A N/A $4,463,997 50.77% Unsat

Avondale Stadium 1958 7,935 $2,371,195 N/A N/A $3,868,794 61.29% Unsat

Elks Lodge/East Campus II 1979 11,850 $72,285 N/A N/A $2,004,906 3.61% Good

James R. Hallford Stadium 1968 25,465 $2,988,380 N/A N/A $6,921,409 43.18% Poor

North DeKalb Stadium 1962 14,260 $4,482,143 N/A N/A $10,464,310 42.83% Poor

Panthersville Stadium 1968 24,873 $1,791,146 N/A N/A $7,064,901 25.35% Fair

Sam A. Moss Service Center 1970 197,583 $6,476,590 N/A N/A $20,519,684 31.56% Poor

William Bradley Bryant Center 1963 41,041 $3,900,835 N/A N/A $8,192,883 47.61% Poor

P-12 Facilities 151,382 $15,824,124 $5,384,000 $270,000 $31,072,421 50.93% Unsat

DeKalb Transition Academy 1953 24,964 $2,988,219 $1,496,000 $75,000 $4,485,353 66.62% Unsat

Eagle Woods Academy 1970 44,000 $4,881,056 $1,578,000 $46,000 $8,268,125 59.03% Unsat

Fernbank Science Center 1967 38,740 $1,641,199 $1,506,000 $115,000 $7,881,831 20.82% Fair

Warren Technical School 1963 43,678 $6,313,650 $804,000 $34,000 $10,437,112 60.49% Unsat


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Eagle Woods Academy

Facility NameYear

Built

Gross

Square

Footage

2011 - 2012

Deferred

Maintenance


2011 - 2012

Educational

Adequacy


2011 - 2012

Technology

Readiness


Current

Replacement

Value

FCI %Condition

Rating

Vacant / Closed Facilities 540,542 $24,003,095 $18,417,000 $1,198,000 $42,676,110 56.24% Unsat

District Offices-Building A & B (Closed) 1973 81,000 $7,193,544 N/A N/A $17,079,896 42.12% Poor

Doraville Drivers Ed 1951 5,545 $996,824 $204,000 $15,000 $1,124,350 88.66% Unsat

Forrest Hills ES (Closed) 1954 68,430 $6,711,789 $3,048,000 $274,000 $14,679,575 45.72% Poor

Heritage School (Closed) 1968 35,132 $4,680,088 $1,602,000 $49,000 $8,626,247 54.25% Unsat

Hooper Alexander ES (Closed) 1935 68,906 $896,992 $4,133,000 N/A Note 1 Note 1 Note 1

Misty Waters (Land Only) 1980 0 $34,720 N/A N/A $208,607 16.64% Fair

Old Briarcliff Open Campus (Closed) 1958 154,855 $1,713,764 $7,196,000 $661,000 Note 1 Note 1 Note 1

Old Chamblee MS/Old Shallowford ES 1968 63,792 $732,082 N/A N/A Note 1 Note 1 Note 1

South Campus (Closed) 1977 5,333 $349,309 $104,000 $9,000 $957,435 36.48% Poor

Tilson Elementary (Closed) 1958 57,549 $693,983 $2,130,000 $190,000 Note 1 Note 1 Note 1

Note 1 - De ferred Maintenance Cos t reflect cost for demolition only and no FCI or Condition Scores were produced.


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4.1.2. Condition Finding #2: Facility Condition Index (FCI) by Facility Type

Detailed in the table below are the Facility Condition Index (FCI) scores and ratings by facility type. The

FCI is interpreted as, the lower the score, the better the condition of the facility. As can be seen in thefollowing tables, the overall FCI for DeKalb County School System is rated as Fair. Schoolfacilities,

which are defined as those used as traditional teaching facilities, are in much better condition than the

Non-School,P-12or the Vacant/Closed facilities. Non-School facilities are the athletic stadiums and

other facilities used as administrative, special purpose, transportation, maintenance, support, or

warehouses. P-12 facilities are older non-traditional facilities being used for special purpose or

alternative school programs, and the Vacant/Closed facilities are either older school facilities which are

no longer used for educational purposes.

Tucker Middle School

Facility Type

Number

of

Facilities

Gross

Square

Footage

Site

Acres

2011 - 2012

Deferred

Maintenance

Estimated

Budget Cost

2011 - 2012

Educational

Adequacy

Estimated

Budget Cost

2011 - 2012

Technology

Readiness

Estimated

Budget Cost

Current

Replacement

Value

FCI %Condition

Rating

DeKalb County School System 151 14,396,754 2,919 $768,574,380 $356,946,000 $15,334,000 $3,177,777,708 24.19% Fair

Elementary Schools 84 5,816,857 1,051 $420,306,027 $143,491,000 $5,844,000 $1,299,034,215 32.36% Poor Middle Schools 21 3,156,031 718 $101,148,284 $49,481,000 $2,791,000 $641,038,900 15.78% Fair

High Schools 24 4,394,887 835 $182,943,871 $140,

facility report (2011)

Documents