longitudinal databases in balt city - abell policy award paper 030510 (id) v3

8/2/2019 Longitudinal Databases in Balt City - Abell Policy Award Paper 030510 (ID) v3

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UNIVERSITY OF MARYLAND SCHOOL OF LAW

2010

Improving Educational

Outcomes in Baltimore

City with Integrated

Data SystemsLeveraging Contemporary Education

Reform Efforts to Build Robust Student-

Level Data SystemsBill Ferguson

2 0 1 0 A B E L L A W A R D I N U R B A N P O L I C Y R E F O R M


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IMPROVING EDUCATIONAL OUTCOMES IN BALTIMORE CITY WITH INTEGRATED DATA SYSTEMS 2010

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I. Statement of the Policy Problem: Baltimore City Public School

Infrastructure

After the 2008-

reported that the -wide high school

graduation rate was 62.69%.1

Accountability Officer, Ben Feldman, explained during a one-on-one interview that the City

Scho

reported rate.2 The difference is not inconsequential; in fact, the discrepancy equals roughly

200-300 students. On this most fundamental education statistic one that officials tie heavily to

public education funding and reform success the two key agencies responsible for City

office could produce a graduation class cohort analysis basing the statistic on the percent of

students who entered high school four years prior to the 2009 graduation, as compared to actual

graduates four years later Feldman responded that such a report, if possible, would take as

long as three weeks to complete.3

In discussing education innovation or reform policies, the fundamentals are key. For

being

able to make fully informed data-driven decisions about what is best for students are lacking,

significantly.

Since Congressional 4

momentum in public education reform has centered on student achievement outcomes. NCLB

assessment outcomes. As a result, federal accountability has heightened state

priorities, many education agencies at all levels of government have attempted to refine and

enhance student-level longitudinal data systems.a,5

a-

maintained databases that allow users to collect, process, track, maintain, and/or analyze student-level

datasets.


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-level databases may seem

exceedingly tangential to the heart of public education reform. Many public education

advocates focus greater attention on more traditional transformational measures, such as

diversifying classroom experiences,6 providing better teachers,7 attracting more capable

administrators,8 providing more financial resources to school districts,9 and/or offering better

curricula.10

While each of these independent reform efforts certainly may affect positive student

gains, each depends on accurate and reliable student data to determine whether the reform

effort actually works. Without effective data systems, states and local school districts rely on

potentially flawed decision points. Further, quality data systems allow districts to effectively

define an educational problem, develop a theory of action, design an intervention strategy, and,

11

collect, maintain, and analyze student data effectively is critical to a

sustainable education reform agenda. Unfortunately, student-level longitudinal database

infrastructures across the country, particularly those data systems in Maryland and Baltimore

City, often are substandard and disorganized at best, completely unavailable at worst. 12

This paper focuses on longitudinal data warehouse issues specific to the City Schools.

The analysis pays particular attention to the City Sch

Schools has made impressive student achievement gains over the past two years, the local

key idea throughout the paper. These system or warehouse datasets may include individualized student

information, such as educational history and testing outcomes, and may include more robustcharacteristics, such as post-secondary studies or workforce participation data. T

-than-one-year, information about a

student. States and researchers generally prefer longitudinal databases over static databases because

longitudinal database reports offer dynamic, year-by-year growth outcomes. Less desirable static, or

non-longitudinal, databases only have the capability of providing detailed reports about students given a

single point in time. Though dynamic, longitudinal databases produce higher quality reporting

measures, states implementing dynamic data warehouses must dedicate significantly greater resources to

create, maintain, and provide training for operations.


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b falters from a severely deficient statewide longitudinal data

warehouse. Even though external organizations like the Baltimore Education Research

c have attempted to provide timely, relevant data to school officials, the

City Schools requires its own integrated student-level database. This database must leverage

cooperation from statewide initiatives through MSDE, as MSDE serves as the most capable

institution to coordinate integration of state agency juvenile data.13

While efficient data systems may serve as a useful tool for state and educational officials,

data warehousing efforts have not garnered universal approval. Those opposed to robust

student-level data warehousing express concerns related to breaches of juvenile privacy rights,

unlawful data disclosures, and data integrity inconsistencies. The paper attempts to present

strategies for alleviating some of these concerns. Admittedly, though, more focused research is

needed around each concern to ensure full appreciation for the myriad of roadblocks that may

hamper data warehouse development.

At the outset, the paper progresses by providing background information about data

warehouses in general, Maryland state efforts at creating a data warehouse, and the City

Schools need for a unified and robust data system. The paper follows by examining the state of

affairs of legal, political, and policy concerns that may arehouse

development. The paper concludes that timely attention to creating a robust juvenile data

warehouse in Baltimore City is strongly warranted. Most importantly, the paper surmises that

b

City Public Schools. Typically, LEAs operate independently from state educational agencies, such as

MSDE, but LEAs traditionally depend on state funding for large-scale reform projects.c BERC operates as a partner to the City Schools, and brings together City Schools central office staff with

third-

communityc education in Baltimore City (Mission, BaltimoreEducation Research Consortium, accessed at baltimore-berc.org/mission/index.shtml on November 25,

2009). BERC organized and first began research in 2007. Currently, the organization is providing City

-level students on

track to educational success . . . and decreasing the dropout rate (Baltimore Education Research

Consortium (2008). On Track and On Time: Baltimore Education Research Consortium Core Analytic Projects

July 2008July 2011. Accessed at baltimore-berc.org/pdfs/On_Track_and_On_Time.pdf on November 28,

2009BERC Strategic Plan 2009-2014, 2. Baltimore, MD:

Baltimore Education Research Consortium).


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yearly views, but they fail to offer longitudinal student-level reports and most often do not

include juvenile data from non-educational state agencies. Thus, state officials are unable to use

data in these reports to determine how individual students are progressing over time, and are

unable to disaggregate student information for non-education characteristics (i.e. students

having had interaction with juvenile services, foster care students, etc.).21

More comprehensive, yet strictly educational, data systems expand on the levels and

years of data agencies maintain. Regulars in the field generally refer to these databases -

16/P-22 P-16/P-20 databases maintain student-specific information starting from

the pre-school level into the postsecondary years, potentially including college-level records.

The majority of P-16/P-wide

student links to a unique number or coding. More advanced systems in this category have the

capability of adding longitudinal reports about individual students. Officials can then highlight

one unique identification number over several years to perform dynamic cohort analyses.23 The

longitudinal aspects of these databases make derivative reports more attractive, but P-20

databases focus strictly on educational data and often do not include juvenile data from non-

education agencies. Currently, Maryland is in the process of moving from at PK-12 database to

a more expansive and longitudinal P-20 database.d,24,25

The most useful longitudinal databases incorporate the P-20 framework but match and

combine juvenile data from public, non-education agencies. These robust systems match

student-specific data from juvenile services, social services, foster care, child welfare,

employment, and/or workforce development among others.26 The most successful models of

agency level in San Diego, CA.27

In Florida, generally seen as the leading state in the juvenile data warehousing

movement, a distinct state department houses and maintains longitudinal data for nearly every

state agency. Such an infrastructure allows Florida officials to create and act upon reports in

expansive areas as: workforce estimations, follow-up program evaluations, social costs of

d However, MSDE is not placing emphasis on inter-agency database development at this time.


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student drop out, post-secondary educational access, high school feedback, P-20 accountability,

P-20 pipelines, teacher pipelines, teacher effectiveness, and externally sponsored research.28

matters related to national efforts to develop robust longitudinal data systems in all states. The

Bill & Melinda Gates Foundation established the institution in 2005 to

and use of high- 29 The institution has created the

-level data systems. An ideal state database

includes all 10 of the following characteristics:

(1) Statewide Student Identifier; (2) Student-Level Enrollment Data; (3) Student-

Level Test Data; (4) Information on Untested Students; (5) Statewide Teacher

Identifier with a Teacher-Student Match; (6) Student-Level Course Completion

(Transcript) Data; (7) Student-Level SAT, ACT, and Advanced Level PlacementExam Data; (8) Student-Level Graduation and Dropout Data; (9) Ability to Match

Student-Level P-12 and Higher Education Data; [and] (10) A State Data Audit

System.30

Additionally, the institution evaluates whether the state officials link a statewide student

identifier to student information from non-education agencies

departments, human services, child protective services, foster care, court systems, corrections,

and 31

Within any data warehouse structure, many intricacies exist for the means and purpose

of maintaining data integrity.32 Fordham Law School professors Joel Reidenberg and Jamela

student information through data warehouse infrastructures. In doing so, the professors

offered an intricate analysis of the various internal processes and systems that state officials use

across the country to maintain student-level data.

In general, the authors found that most states did not develop systems with sufficientprotective barriers in place to avoid unlawful data disclosures.33 Specifically, the authors

concluded that: (1) states collected unnecessary data about students in excess to state and

federal education reporting requirements; (2) databases offered weak security processes; and (3)

many states lacked a coherent and systemic plan for protecting the privacy of student records.34


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The most pertinent database findings to Maryland and Baltimore City officials revolve around

in data warehouse

development. The paper explains these internal database procedures further below in the

context of potential concerns around student-level data warehouse development.

B. Importance of Longitudinal Data Systems

s maintenance of a robust longitudinal data system has immense

benefits for a collection of stakeholders, including students & parents; classroom teachers;

school leaders; district leaders; state policymakers & education agencies; federal agencies; and

community, business, & industry leaders.35 National education reform think tanks, such as

Learning Point Associates and the DQC, have produced an array of reports that demonstrate

the positive links between robust data systems and diverse stakeholder benefits.

Focusing on academic achievement reform purposes, Learning Point Associates has

reported that longitudinal student data allows for teachers and administrators to more

effectively test and evaluate school and instructional effectiveness, tying student performance to

individual schools and teachers.36 Robust data reporting also benefits policymakers who may

academic achievement goals. Such a determination leads to state school officials more equitably

funding support initiatives for districts most in need and for local districts to target support to

the most at-risk students.37 A link between student data, funding, and accountability is

foundational to improving student performance over the long-term. Evidence from the

38

When data systems link student-level information and characteristics across education

and non-education agencies, the public benefits are even greater. The DQC has found that

public schools face a growing need to grasp a more comprehensive understanding of an at-risk

non-

deficiencies.39 For non-education agencies, the ability to link social service and juvenile

delinquency data with education data opens the possibilities for state officials to provide


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tailored and targeted intervention services.e,40 Further, interoperability between public sectors

to the kind of organizational improvements . . . that many private-sector businesses undertook a

41 When schools and other public agencies are able to access and analyze

accurate data about individual students, the public benefits.

The negative symptoms of Maryland and Baltimore

-income student population. The lack of a robust longitudinal and inter-agency

database causes the City Schools to potentially forego millions of federal grant dollars

earmarked for low-income students.f,42 The City Schools receives a block federal supplemental

grant for all impoverished students in the district. City Schools distributes these dollars on the

basis of FARMs distribution statistics. To create an accurate FARMs federal submission list,

each year at the end of summer the City Schools receives an Excel file from the Maryland

tes of

directly certified FARMS students. Direct certification refers to those students that do not have

to complete a FARMS application to receive benefits, as previous service provisions through

DSS qualify them automatically. The file, though, includes incorrectly identified information,

does not match City Schools student records, and remains static from the date DSS sends the file

to the City Schools in the early summer.43 Lacking integration of data between agencies creates

a situation where the City Schools is unable to directly FARMS certify upwards of several

thousands of students who likely should have qualified. The result: An inefficient misallocation

of resources that school officials must dedicate to tracking down each low-income student

e Smith, S. (2009) highlights that

educational needs serves as a prime example of the potential benefits resulting from robust, integratedlongitudinal data systems. By accurately reviewing longitudinal data about foster care students in the

Services Department indentified common trends among children who

aged out of foster care programs. These officials identified individuals within the at-risk cohort,

determined the most common negative outcomes, and created targeted interventions and preventative

programs, such as job referral and educational job training. This efficient allocation of state resources

-agency, student-level longitudinal data systems.f Generally, qualifying for Free and Red

collection point to classify students of lesser economic means.


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individually.g,44 Such a misallocation of resources perpetuates educational inequality in high-

risk school districts.

While the theoretical benefits of integrated data systems may be vast, student-level data

ivacy rights. When state or local agencies

design insecure systems or too easily release protected student information, individual privacy

rights may fall victim to harmful unforeseen consequences of well-intentioned public initiatives.

Fordham Law School professors Reidenberg and Debelak explained these concerns in detail. h45

linked data systems when proper protections and procedures exist within a state or local

ag46

C. Contemporary Landscape of Education Reform

country,47-level data systems lag significantly behind other U.S.

states.48 According to the DQC, Maryland is one of two states with educational data systems

that rank as the least comprehensive and least effective in the nation.49

ranking, in a state with clear income and educational disparities, should raise public concern.

Recent MSDE efforts indicate that state education officials recognize the deficiency.

These State officials have taken steps to improve current student-data warehouse.50

In fact, a DQC November 2009 report noted that during the 2008 2009 school year, Maryland

made the greatest strides among all states in improving its statewide data systems.51

districts that could be leveraging an existing system to improve instruction, provide more

g Furthermore, the City Schools student population is highly transient. Tracking down each student

individually to complete a boilerplate form consumes immense resources that otherwise officials could

allocate towards student achievement.h The Reidenberg, J. (2009) report highlights five of the most common causes of insecure data warehouses:

(1) ill-defined user access roles; (2) unclear purposes behind collection of certain sensitive data fields; (3)

lacking confidentiality agreements between agencies; (4) non-existent data retention and purge policies;

and (5) public availability of student and family rights under federal and state privacy laws.


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targeted interventions to at-risk youth, and more effectively evaluate the teaching and learning

that occurs in classrooms every day.

Baltimore City Schools officials also have indicated a desire to upgrade and improve

data systems at a local level. In October 2009, the City Schools issued a Request for Proposal

52 While much of the

proposal focuses on integrating already-existing databases, the recent effort demonstrates the

tackle the problems resulting from non-linked student and employee

data.

Dr. Andrs Alonso, City Schools students have demonstrated significant academic

indicators.53 In comparing Baltimore City to the State as a whole, however, the City Schools has

much room for improvement.

Illustrative of the increased need for intervention, Baltimore City historically has

-based

academic achievement gap.i,54 ance national report comparing

graduation rates between Baltimore City students and peers attending schools in the six

countywide districts surrounding Baltimore City all of which being significantly wealthier

and majority white55 (see Tables 1 & 2 below) -suburban

graduation gap was nearly the most disparate in the country. 56 Specifically, the Baltimore City

graduation rate fell below averages of all six surrounding countywide school districts by at least

35%.57

i The Swanson, C. (2009)

The Baltimore

City rate on average was 35% below that of all six surrounding countywide school districts.


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Even worse, when Baltimore City students are academically successful in their K-12

educations, a Stanford University study found that disconnected data systems, like the systems

bility to succeed in

college.58 Thus, in a school district where low-income, minority students face significant

barriers to reaching high school graduation, lacking data systems may further hamper even the

highest achievers. The occasion to address this critical infrastructure deficiency, though, has

never been more ideal.

O

Arne Duncan on January 20, 2009,59 a philosophical shift in education reform priorities began

-level data usage. Those priorities leveraged

grant dollars for school districts willing to improve their ability to effectively accumulate,

analyze, and make decisions based upon student-level data. Access to the historic federal

education grants, though, has required states and local education agencies to demonstrate

strong investment in innovative and data-driven education reform efforts or initiatives.60 The

table below details of the three most promising federal USDOE grants that may bolster

TABLE 3:KEY FEDERAL GRANT OPPORTUNITIES FOR EDUCATION REFORM INITIATIVES &

MARYLAND STATE &LOCAL DATA WAREHOUSING EFFORTS

Common

Grant Name

Funds

AvailableExplanation Potential Applicant

Race to the

Top

$5 billion

in total

The Race the Top grant has effectively

heightened the importance of student-level data

MSDE in consultation

with the City Schools

88.9

40.0

22.7 20.9 19.9

7.6

49.9

67.158.6

73.2

0

25

50

75

100

Baltimore

City

Baltimore

County

Anne

Arundel

County

Howard

County

Harford

County

Table 1: School Dist. Student Population by

Race

% African American % White

53720

18614

4295 1207 3077

0

20,000

40,000

60,000

Baltimore

City

Baltimore

County

Anne

Arundel

County

Howard

County

Harford

County

Table 2: School Dist. Population by Low-

Income Status

No. of Low-Income Students


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Competitive

Grant as part

of the

American

Recovery and

ReinvestmentAct of 200961,62

for all

applicants

management for educational agencies across the

country. Grant dollars will flow to state-

applicants that are able to demonstrate a sincere

commitment to educational reform. Successful

state-applicants are required to revise state

education laws to facilitate certain educationreform priorities. Additionally, states must

develop comprehensive reform plans with their

local education agencies that utilize progressive

initiatives to bolster student achievement. The

USDOE has set forth an application scoring

rubric that places nearly 20% of review points on

student-level longitudinal data systems.63

Additionally, the grant application rubric

extends additional points for states that link

teacher evaluations to student growth data.64

and other Maryland

LEAs. MSDE has

indicated that the

agency intends to delay

application to June2010, allowing time for

inclusion of

creation of a robust

data warehouse.65

Investing in

Innovation

Fundi

$650

million to

successful

applicants

An additional $650 million exists under ARRA

for the USDOE Secretary to distribute to school

districts and non-

implementation of, and investment in,

innovative and evidence-66

A key priority of the grant will be to fund

67 in

districts with large populations of high-poverty,

at-risk students. Successful i3 grant applications

very likely must include development and/or

expansion of longitudinal data systems.

City Schools in

partnership with

relevant and interested

non-profits.

The Recovery

Program for

Statewide

Longitudinal

Data Systems

$65

million to

successful

applicants

USDOE has dedicated another $65 million under

educational agencies to design, develop, and

implement statewide, longitudinal data systems

to efficiently and accurately manage, analyze,

disaggregate and use individual student d68

MSDE in consultation

with local education

agencies and non-

education state agencies

handling juvenile data.

Although Maryland and Baltimore City school officials may find themselves faced with

deficient data systems at the moment, the USDOE under the Obama Administration has offered

reform agenda around data-driven outcomes, and these heightened monetary incentives should

around the importance of developing longitudinal data

warehouses.

III. Analysis


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(A) Privacy Law Issues

Both actual and perceived beliefs about the complex array of laws governing juvenile

privacy rights often contribute to public agency stand-still when state and local officials

consider developing robust student databases.69 A generalized fear of violati

often causes many education and non-education agency officials to embargo juvenile data by

default.70

In Maryland, such apprehension and standstill are no different.71 To examine the

separate analysis of relevant federal and Maryland state governing provisions.

(1) Relevant Federal Laws

Family Educational Rights and Privacy Act of 1974, 20 U.S.C.S 1232 (2006)

the Federal Educational Rights and Privacy Act of 197472 Many

scholarly and informational resources exist that fully distinguish the extensive intricacies of

. The paper, though, highlights the critical FERPA provisions and recent

regulatory revisions that may most directly affect Baltimore City o

robust data warehouse.j Additionally, the table available as Appendix I provides a

comprehensive overview of scenarios that Baltimore City officials may confront in the

development and implementation of a robust data warehouse.

involving the collection, storage, disclosure, and analysis of student-level data.73 Any

educational institution that receives federal funds in the form of grant, cooperative agreement,

74 An

USDOE investigation that ultimately may result in the discontinuation of federal funds.75

j

more City student-

level data, thereby highlighting K-12 applicability.


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educational agencies with more tangible means of ensuring agency compliance. The USDOE

regularly revises a result of continual changes in

technology and the growing importance of maintaining student-level data.76

Two notions

building blocks. An education record77s that are: (1) [d]irectly related

to a student; and [m]aintained by an educational agency or institution or by a party acting for

78 E

cards, surveys and assessments, health unit records, special education records, and

79 Any information

that an educational agency creates or receives about a student that the agency includes in the

-based cumulative file likely qualifies as an education record under FERPA.80

Most LEA legal departments set a bright-line rule: once a file or document formally or

informallydistrict treats it as an education

record.81 Further, public agency juvenile data, including non-education data, that enters an

and links to an individual student also may

education record. Once a part of the education record, FERPA would apply.

appropriate use of

education records. A disclosure occurs when an education agency in any way releases

personally identifiable student information to any party.82,83 While some FERPA disclosures

require notification to parents and the student before release, other disclosures are permissible

without such recordation and notice. Generally, parental notice hinges on the type of

information released and the extent to which the information is personally identifiable. Release

of unidentified information or cumulative statistics about a cohort of non-identifiable students

would not qualify as a disclosure, as disclosures imply observable links between records and

student identities.

Overall, two types of disclosures exist lawful disclosures and unlawful disclosures.

Lawful disclosures abide by FERPA provisions and are the framework for legal student data


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warehouses and broad data-sharing initiatives. Unlawful disclosures or redisclosuresk define

whether an education agency may be in violation of FERPA.

Within the concepts of education records and disclosures, FERPA places a great deal of

de-identified

information. Directory information includes standard, personally identifiable information, such

as student name, address, telephone number, and birth date.84 When a data release includes

directory information and clearly links the data to the student, FERPA places a heightened

responsibility on education agencies to prevent breaches

data disclosures.85 The USDOE emphasizes

l,86

In any use or disclosure of education records, education agencies ultimately seek to

avoid liability under FERPA. Private rights of action under FERPA, though, are unavailable.87

to investigate and enforce violations. The USDO

regulations permitted the FPCO to open investigation on an alleged violation through reports

provided by students, parents, media publications, or any other third party. 88,89 Also, reports of

an agenc violation no longer must demonstrate a policy of habitual violation, and single

instances of unlawful disclosure may permit FPCO to open an investigatory case.90

As a remedy for violating FERPA, the USDOE may cut off all federal education funding

assistance to an education agency that the FPCO finds to have a practice of consistently

k

education agency has disclosed that information or related education record information to a third party.

receiving party provides to another institution or to the public.l Generally, education agencies have greater leeway in disclosing directory information among students

in the education setting (i.e. class lists). To protect sensitive privacy information, the USDOE clarified the

ban on SSN disclosures without prior student consent. Along these lines, the USDOE permitted the use

of student ID numbers in directory information disclosures. The USDOE clarified, however, that


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violating disclosure rules.91 Prior to such an extreme consequence, an FPCO finding of fault

nece

agreement.92 The USDOE will not immediately withhold funding until the FPCO finds that the

agency under consent agreement fails to meet the voluntary rehabilitation conditions.

No Child Left Behind

FERPA functions as the most germane privacy protection tool for student education

records, but the more recent congressional passage of the NCLB93 often enters into

consideration in efforts to build robust student-level databases. The law created a means for

categories of anonymous data to the U.S. Department 94 However, the law itself

does not set forth specific criteria or policies by which states should abide in their processing or

collecting such data.95 Rather, NCLB only specifically prohibits states from creating a

96 and sets forth specific student-

level data sharing provisions for states seeking additional funding for migratory students. 97

NCLB has effectively pushed states towards collecting greater amounts of information

about s-defined procedures for protecting data do not offer much

guidance in database development.98 Thus, creating a robust student-level data warehouse at

regulations, as

FERPA sets the predominant standard for student record protection.

Health Insurance Portability and Accountability Act of 1996

rights, many education agencies reference the Health Insurance Portability and Accountability

Act of 199699 law that may affect development of a federally compliant

s

for the purposes of creating a more efficient national health care system. HIPAA provides

similar data usage standards for health care institutions as FERPA does for education agencies.

The HIPAA Privacy Rule, though, focuses on electronic data exchange of health records

100 A covered entity includes

ealth plans, health care clearinghouses, and health care providers that transmit health


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information in electronic form in connection with covered transactions.101 Covered

transactions are routine course of business electronic data exchanges between health care

providers and health plan administrators.102

There are almost no occasions when a K-12 education agency would qualify as a covered

entity under HIPAA. HIPAA does not consider schools as covered entities, even if schools

maintain student health records electronically (i.e. immunization records).103 Additionally,

HIPAA regulations include an express exception that defers to FERPA in cases where

under HIPAA Privacy Rule protections.104,105

in medically-related education records extends so far as to apply FERPA regulations to health

care providers that service juveniles in school settings, so long as those providers are operating

106

ouse

development discussions demonstrates the type of confusion that may have led to Maryland

During an interview with MSDE

Deputy Superintendent Leslie Wilson, the high-ranking state education official referenced the

HIPAA compliance burdens as justifying inaction in integrating -

level longitudinal databases across agencies.107 Similarly, public health officials who may be

familiar with HIPAA regulations, yet unversed in FERPA protocols, may allow regulatory

misperceptions to persuade them into operating within public silos.

A 2008 DQC report (Smith, S., 2008) illustrates the legal misperception phenomenon that

hampers inter-agency collaboration. The education

record coverage often discourages non-education agencies from entering into agreements with

egulations thus causes non-education agencies to

view FERPA as merely an education-based regulation too complicated to navigate. Further,

legal misperceptions may cause default reactions where agencies, including education

stricting access to education records, even in cases in which child

welfare or other social service agencies are entitled to access [records] under and authorized

disclosure under the law.108


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By examining each of the most pertinent federal laws in the context of agency

integration, a well-designed robust data warehouse with clear operational protocols and data

disclosure systems should operate with few legal roadblocks so long as FERPA serves as the

overarching legal guidepost.

(2) Maryland State Laws

themselves with state and local guidelines related to student data privacy.

Mar

109 the Maryland State Board of Education incorporates

Maryland

Student Records System Manual 2008

management. The MD Manual expressly requires local education agencies to reference FERPA

to comply with student record confidentiality rules.110

Creating a robust inter-agency data warehouse, though, would require state and local

officials to collect and link juvenile data that resides in non-

integrated data warehouse then would have to comply with state laws that govern disclosure of

non-education juvenile data. The chart available as Appendix II outlines the most pertinent and

relevant state laws that Maryland and Baltimore City policymakers would have to consider in

developing an integrated database.

As the appendix indicates, most agencies have specific statutory prohibitions on sharing

individualized information about children. Specifically, the Maryland Department of Juvenile

Services, the Department of Social Services, the Department of Public Safety, and the Maryland

Courts must comply with expressed laws related to juvenile data maintenance. While this

could pose a barrier for a wholesale release of information, agencies are permitted to enter into

agency-to-agency data-sharing agreements for the purposes of serving children many do so

already with the City Schools in an informal fashion, such as through the FARMS certification

process.111,112 Thus, to comply with Maryland privacy law protections, Maryland state and City

Schools officials must either follow one of two paths: (1) enter into individualized sharing


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agreements with each public agency, or (2) support state legislation that would eliminate

barriers to data-sharing at the state and local levels for data warehouse development purposes.

(B) Political Considerations

for his implementation of the CitiStat program in 2001. 113 The concepts behind CitiStat (now

implemented on the state level through StateStat) strongly correlate with the effective usage of a

robust student-level longitudinal data warehouse to improve student outcomes. CitiStat relied

on the foundational theory of action that by collecting comprehensive data about public

decisions.114 A successful inter-agency student-level data warehouse would operate under the

same premise, focusing -added effect on

student achievement.

With a sympathetic Maryland governor in office and an education reform atmosphere

tied to the use of student data, creating a robust, integrated educational data warehouse in

Maryland could appear as an easily obtainable goal. When dealing with juvenile data,

however, clear political paths to database development may quickly become impasses.

-sharing suggest that publ

maintenance, usage, and disclosure of juvenile data likely could face harsh political opposition.

While all potential opponents likely would not become clear until educational data

warehousing were already underway, two groups likely would stand at the forefront of the

-

TeachersUnions

On the national sc

if data warehousing

has the capacity to link student-level growth data to teacher evaluation and performance, such

linking may undermine successful long-term education reform. Politico recently reported on


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the gulf growing between Secretary Duncan and national teacher union leaders over USDOE

115 Randi Weingarten, national

The Politico

report also pointed to the National Educators Associati letter in opposition to

proposed requirements of the Race to the Top grant competition: [Priorities encouraging

student-level database development are]

In Maryland, the national perspective influences local politics. Superintendent Leslie

potentially played a past a statewide data

warehouse that could link teacher performance to student outcomes.116 Teacher union

opponents generally view student growth measurement as an inaccurate measure of teacher

effectiveness. Further, these organizations argue that comprehensive student databases could

misalign district priorities for reform and reduce creativity in classrooms in Maryland.117

Another anecdotal example of potential Maryland teacher union opposition occurred

during the 2009 General Assembly session. State House Delegate Anne Kaiser introduced

legislation on behalf of MSDE that would enable the State to create teacher identification

numbers for inclusion in the student-level longitudinal data warehouse. Although H.B. 587

passed, teacher union negotiations with MSD

language that prevented local agencies from tying student performance through the teacher

identification number to teacher evaluations.118

Recent education coverage of the collective bargaining negotiations in New Haven, CT,

willing to support a considered data warehousing effort if education officials include union

input early in the decision-making process. The local New Haven AFT-affiliated teachers union

and the New Haven Public Schools came to agreement on progressive contract terms that

included expanded use of data; teacher performance pay based on student achievement growth;

greater emphasis on testing; and school-based operational freedom.119 Union support largely


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implementation details.120 By investing the union at the front-end of policy development, New

Haven teachers and administrators may have presented an ideal framework for Maryland and

advocates soon seek to improve the City and

Sta

Privacy Advocacy Groups

Privacy watch groups likely would raise sound and reasoned concern over some aspects

of robust inter-agency data warehouse development. Collecting and centralizing juvenile data

from agencies across the public spectrum could place a wealth of information at the hands of

government officials. Further, through illegal or negligent actions, an insecure database could

expose sensitive information about students to non-government or ill-intentioned entities.

While the ACLU-MD has praised Baltimore City efforts to address root causes of at-risk City

likely would only go so far should the data warehouse fail to include proper safeguards.

Take, for example, media coverage in Anne Arudel County, Maryland, where police and

school officials are entering the data integration discussion on the basis of identifying gang

activity.121 collection of juvenile data allows for immense reporting

capabilities. But, advocacy groups may suggest that positive intentions in data warehouse

creation could result in harmful outcomes, such as socioeconomic-based law enforcement

c schools.122

Similarly, the ACLU-MD could point to the July 2008 Baltimore Sun series that exposed a

Maryland State Police undercover investigation of peace activists and anti-death penalty

groups.123 In the State Police spying controversy, misinterpretation of available data about

Maryland peace advocacy groups led to a highly secretive and intrusive covert police operation.

Thus, whenever government officials have access to sensitive personal information, groups

such as ACLU-MD may have good reason for advocating against a robust student-level

database if proper protections are not in place.


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124 Groups such as Legal Aid and ACLU-MD

often track FERPA compliance vigilantly, and these groups regularly communicate with state

and local education officials to ensure data protection.125 Evidence of this active oversight is

evident in communications from ACLU-

It would be important [for ACLU-MD] to consult with privacy technology

officers who can provide the detailed planning assistance based on the

technology the school is going to use and the goals of the programthe issues

arise because of poor implementation of principles as much as with not thinking

through the broad policy itself.126

During a phone interview, Cindy Boersma, ACLU-

national office has taken interest in state and local efforts to build such databases. 127

Some of these foreseeable threats include: (1) the potential consequences of centralizing

information in one place so as to localize all sensitive information for interested parties;

(2) the effect data warehousing has on degrading the

release of personal data; (3) the difficulty around minimization only collecting necessary

data when more data may be available; (4) avoiding technology creep collecting data

from various sources unnecessarily because the technology allows officials to do so; (5)

data-sharing creep the difficulty in preventing release of information to other public

agencies once another agency has already collected the information; (6) data accuracy

and data-purging insufficiencies; (7) problems in disclosures that fail to de-identify

data when roles of authority are unclear.128

Successfully navigating

In 2006, the Maryland General Assembly overrode then-

Records 129 HB 900 revised

relating to the privacy of juvenile records,

other than those records maintained by the public schools. Specifically, the bill permitted the

BCHD personal data tied to at-risk juveniles.


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develop programs to reduce youth

violence in Baltimore. BCHD gained regulated access to

protected juvenile data at unprecedented levels.130 Thus, developing innovative and

progressive ways to integrate juvenile data is not unprecedented, and crafting state legislation

to initiatives aimed at helping at-risk youth may be successful.

Ultimately, overcoming data warehouse opposition will come through education

development and planning stages of the warehousing process. By including potential

adversaries at the front-end of development, Maryland and Baltimore City officials may be able

These advocates must continually return to basic principles and motivations behind the data

warehousing effort to ensure that the final infrastructure achieves educational goals while

avoiding unnecessary data collection and disclosure.131

IV. Recommendations & Conclusions

Maryland and Baltimore City

resources efficiently. Unavailable robust student data reports also may deny the City Schools

the ability to link teacher performance to student growth, and may contribute to a prevalence of

reform and federal funding under USDOE Secretary Duncan, however, sets the stage for

To take advantage of the distinctive chance at acquiring unprecedented federal

education dollars, Maryland and Baltimore City policymakers must consider important legal,

political, and policy implications. These spheres of influence will govern whether successful

data infrastructure revitalization will be possible.

To frame the discussion, policymakers must recognize that robust student-level data

systems necessitate government collection of massive amounts of potentially sensitive and

personal information about students. City and State policymakers, therefore, must navigate


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Second, accessing and utilizing student data has the potential to raise serious concerns amongst

therefore, must maneuver delicately through hesitations derived from potential political and

budgetary landmines.m The following summary recommendations attempt to provide a

generalized guide for data warehouse proponents to move forward:

Development. Rather

than immediately looking towards creating a statewide data warehouse, Baltimore City officials

should use the current RFP data management system process to integrate data from non-

education public agencies working with juveniles. Ultimately, MSDE officials do not need the

more sensitive information about students to comply with most reporting tasks. Officials

working at the local level are most able to affect student achievement, and data warehousing at

the local level should be the focus point for integrated data-sharing efforts.132

Recommendation 2: Convene a Stakeholder Workgroup of State and Local Officials

and Advocacy Groups. The Baltimore City Council or the Maryland General Assembly should

pass legislation to provide the opportu

stakeholders to convene for the purposes of discussing juvenile data integration amongst the

The workgroup should consist of representatives from MSDE, the City Schools

(and additional school

advocacy groups, technology specialists, state and local politicians, parent associations, and

representatives from the legal community. With this initial gathering, the workgroup should

determine all other potential stakeholders that may have an interest in the data warehouse

development to ensure broad front-end investment. Secondary invitations should follow the

gathering of the most obvious constituents. Ultimately, the workgroup would be charged with

m Given this ollowing section focuses heavily on legal and policy issues. Full

consideration of technological integration issues related to a student database will be critical for

ta warehouse.

However, the paper recognizes that further, specialized studies will be necessary to fully encompass all

factors that may influence effective database programming.


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determining the tiered need for improving data infrastructures based on the priorities outlined

by the DQC.

Recommendation 3: Provide the Workgroup with Specific Expected Outcomes.

Relevant legislation should charge the workgroup with making recommendations about the

following areas of inter-agency, data-sharing decision points. (a) Prioritized outcomes that the

successful City or State robust longitudinal databases would offer to facilitate backward

planning of the development process; (b) design plans for operational structures; (c) an

law provisions; (d) a series of plans that address issues of initial and continual training on the

collection, storage, and use of juvenile data; (e) a list of agencies or groups that would

contribute data and information to the warehouse; (f) a list of agencies and organizations that

would have an interest in obtaining reports or raw data from the robust student-level data

system; (g) data protection and encryption plans that would become standardized across

participating agencies; and (h) a tiered, estimated cost-out of initial development plans for

recommended work moving forward.n,133

Recommendation 4: Develop Standardized Inter-Agency Data-Sharing

Confidentiality Agreements. Presuming the workgroup ultimately advocates a need to

-agency data infrastructures, the workgroup should

outline and sponsor enabling data-sharing legislation at the state level and/or develop

. These agreements must permit

broader juvenile data-sharing while maintaining privacy protections at all levels and within all

participating agencies. Given the strict privacy laws in Maryland around juvenile data, the

workgroup should look towards the efforts of the BCHD to determine if such an expansive

data-sharing legislative effort would be feasible. Additionally, the workgroup should look

towards other state or local data-sharing agencies outside of Maryland, and specialized think

nA critical component of creating a robust data system is establishing buy-in from needed

data or is responsible for reporting out data for necessary reports.


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tanks that may be able to offer best-practice agreements or statutory language that effectively

facilitates data integration.134


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-APPENDICES -


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Appendix I: FERPA Detailed Overview Table by Disclosure Examples

Type of

Information

Release

Type of

DisclosureExplanation Authority

Relevance to State/Local Data

Warehousing

LEA release of

aggregated,

unidentified

student data to

third party or

public

Not a

Disclosure

Although the data includes information

about students, and likely aggregates

no disclosure occurs because third

parties are unable to link data to

individual students.

34 C.F.R.

99.3 (2009)

Unidentified data reports about

schools and school districts are

permissible.135 This allowable

action permits states to publish

yearly report cards about student

performance, and may allow

dynamic databases to produce

more comprehensive aggregated

reports.

LEA release of

education

records toteacher or school

officials within

local district

LawfulDisclosure

Local districts may freely share

within the same district, so long as

20 U.S.C.

1232g(b)(1)

(A)

20 U.S.C.

6311(b)(3)(C)

(xii)

Under FERPA, locally maintained

data systems are less subject to

violations. Thus, creating a local

liability exposure.

LEA release of

education

records to state

agency for

evaluation or

audit of local

programs, or for

accountability

purposes

Lawful

Disclosure

FERPA expressly permits disclosure of

education agencies for evaluative

purposes. However, the state agency

may not redisclose the personally

identifiable education records, and

must destroy the records after

evaluation is complete.

20 U.S.C.

1232g(b)(1)

(C), (b)(3),

(b)(5) (West

2009)

FERPA recognizes the

organizational relationships

between state and local education

agencies. As new FERPA

regulations indicate, such data-

sharing is expected and advised.136

LEA release of

assessment,

enrollment, and

graduation data

for purposes of

NCLB

Lawful

Disclosure

NCLB requires local districts to provide

individual student data for

accountability purposes. While states

and federal agencies must protect this

personally identifiable data about

students, the disclosure is lawful.

No Child Left

Behind Act of

2001, 20

U.S.C. 6311

(b)(3)(B)

Greater amounts of federal

funding for local education

agencies increases the likelihood

that federal offices will hold local

school districts accountable for

reform efforts. Statewide, or

robust local data warehouses,

provide such an infrastructure for

federal reporting.

LEA release of

individual

education

records to a

contractor that

maintains a

database on an

Lawful

Disclosure

FERPA recognizes the resource and

technological restraints that many LEAs

face. Thus, the law permits districts to

contract out database services when the

terms of the data-sharing are expressly

outlined. The LEA or state agency must

operations. Contractors must exercise

the same heightened security around

cation records as the

disclosing LEA would have.

34 C.F.R.

99.31(a)(1)(i)

(B) (West

2009)

34 C.F.R.

99.33(a) (West

2009)

34 C.F.R.

99.35 (West

clarified this type of disclosure

between public agencies andcontractors. The clearer language

likely permits a third party

contractor the ability to maintain

warehouse, so long as the LEA

clearly defines the scope of the

sharing agreements.


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Type of

Information

Release

Type of

DisclosureExplanation Authority


Warehousing

Contractors also may not use the data

for purposes other than those outlined

in initial disclosure agreement.

Importantly, disclosing education

FERPA violation.

2009)

LEA release of

education

records to

police, parents,

or other parties

to prevent

generalized

threat to

students

Unlawful

Disclosure

LEAs may only release education

records to such parties for health and

safety reasons when the data release is

significant and articulable threat to

137

or another party. USDOE violation

investigators will review a data release

under these conditions by a totality of

the circumstances standard.

34 C.F.R.

99.36(a) (West

2009)

While a robust longitudinal

student database may maintain

inter-agency juvenile data, release

of this data is impermissible unless

a clear emergency exists.

LEA or state

release of

education

records for

purpose of a

longitudinal

data system

Lawful

Disclosure

2008 revised FERPA regulations

expressly permit release of education

records for maintenance within a

statewide data system.

34 C.F.R.

99.35(b) (West

2009)

With this recent revision, the

USDOE expressed a clear

commitment to providing

incentives for states to expand

educational databases.138

Third party

breaches LEAs

records to obtain

education

records

Likely

Unlawful

Disclosure

The revised FERPA guidelines set

standards that education agencies must

factor when establishing technological

safeguarding protocols. If an education

encryption guidelines, the agency may

be liable for an unlawful disclosure.

34 C.F.R.

99.62, .64, .65,

.66 (West

2009)

In establishing a robust student

data warehouse, state or local

officials must exercise great care in

establishing technological

infrastructures.

LEA release to

non-public or

research

agencies that

conduct

educational

studies

Likely

Lawful

Disclosure

2008 revised FERPA guidelines

included language within the

regulation to clarify the role that

outside parties may play in obtaining

education records for research

purposes. The regulations highlight the

need to de-identify information prior to

release, and provide methods for

permissible de-identification (i.e.

stripping potentially identifiable

information about a student fromlinked educational statistics). The

revised regulations also provide factors

that LEAs or state education agencies

should consider in determining what

education record data to provide, and

in what means agencies should about

providing it.139

34 C.F.R.

99.31(a)(6)

(West 2009)

With the creation of a robust

educational data warehouse, a

local or state agency likely will

find researchers who desire access

to student data files for research

purposes. Even though

regulations include a potential 5

year access ban for organizations

that violate the use of disclosed

research data, LEAs and states

should craft clearly articulated

agreements when permitting third

parties to use education record

data for purposes not directly

related to the LEA or state.


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Appendix II: Maryland Laws Related to State/Local Inter-Agency Data-Sharing

Maryland

Agency

Governing

AuthorityExplanation


Warehousing

Dept. of

Juvenile

Services

MD.CODE

ANN.,CTS.&

JUD.PROC.

3-8A-27

(2009)

The law prohibits the Department from distributing ajuvenile police record to any party, except in select

including notice of arrests, generally requires a judicial

order for disclosure. Two significant exceptions exist: (1)

access juvenile records in connection to treatment or to

develop anti-violence programming in Baltimore City,

and (2) law enforcement authorities may release specific

criminal offense information to Maryland school

superintendents and principals (see below, MD.CODE

ANN.,EDUC. 7-303).

Adding juvenile arrest records to

any comprehensive student-level

database would be highly

problematic. Unless clear

guidance existed in the data-

sharing agreement, pursuing

education agency data integration

on an individual student-level

with DJS seems unlikely.

DJS

MD.CODE

ANN.,HUM.

SERV. 9-219

(2009)

While DJS may produce studies and research reports

related to juveniles under its authority, the law prohibits

The law allows for publication of aggregated statistics and

information, so long as data does not link to individual

juveniles. The law permits the BCHD to access individual

anti-violence programming in Baltimore City.

The Human Services article

provides an avenue for juvenile

data integration. If DJS data flows

to a statewide education database

in an aggregated form, collection

of data may be possible.

Multi-

Agency

Cooperation

(DJS)

MD.CODE

ANN.,HUM.

SERV. 9-219

(2009)

Law requires DJS to work cooperatively with MSDE,

Dept. of General Service, Dept. of Health & Mental

ces, Dept. of

Public Safety and Correctional Services.

The express mandate for DJS to

work cooperatively with other

state departments provides a ripe

framework for discussions around

developing a robust student-level

data warehouse.

Maryland

Education

Agencies

MD.CODE

ANN.,EDUC.

7-303 (2009)

When law enforcement officers arrest a juvenile in

connection to a gang-related crime, the law enforcement

l or

district superintendent of the offense.140 However, the

law expressly prohibits including this notice in the

This section breaches the gap of

including juvenile delinquency

data in an education database.

The express denial of inclusion of

the offense in an education record,

though, further solidifies the

difficulty of integrating such data.

Dept. of

Hum. Res.

MD.ANN.

CODE art. 88A

(2009)

Prohibits all disclosure of juvenile records related to child

abuse or neglect. DHR

upon request of the local education agency. There is no

for the purpose of providing treatment or anti-violence

programming in Baltimore City.

The law allows local education

agencies to access sensitive

juvenile data on an individual

basis. Such information may be

inclusive in a statewide or localrobust data warehouse.

Maryland

Courts

MD.CODE

ANN.,CTS.&

JUD.PROC.

3-827 (2009)

Section prohibits disclosure of juvenile court records

without court order. However, law permits the BCHD to

providing treatment or anti-violence programming in

Baltimore City.

Like other Maryland juvenile

privacy laws, the stringent

prohibition includes a narrow

exception for BCHD.

Dept. of Pub. MD.CODE Requires the Dept. of Pub. Safety to produce reports The section permits BCHD to


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Maryland

Agency

Governing

AuthorityExplanation


Warehousing

Safety ANN.,PUB.

SAFETY 2-

307 (2009)

about statewide incidences of crime. Orders the

Department to publish certain reports. The law permits

the BCHD to access individual juvenile victim data for the

purpose of providing treatment or anti-violence

programming in Baltimore City.

collect juvenile crime victim data.


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1. Maryland State Department of Education (MSDE) (2009). Maryland Report Card, Graduation: BaltimoreCity, obtained from MSDE Report Card website at mdreportcard.org on November 25, 2009.

2. Feldman, Benjamin (2009). Personal interview with Benjamin Feldman, Chief Achievement &Accountability Officer, Baltimore City Public Schools, October 25, 2009.

3. Ibid.4. No Child Left Behind Act of 2001 (NCLB) (2002), Pub. L. 107-110, 115 Stat. 1425 (codified as amended in

scattered sections of 20 U.S.C.).

5. Palaich, Robert M., Gixie G. Good, and Arie van der Ploeg (2004). State Education Data Systems ThatIncrease Learning and Improve AccountabilityPolicy Issues (June), p. 1. Naperville, IL: Learning Point

Associates.

6. Bifulco, Robert, Helen F. Ladd, and Stephen Ross Public School Choice: Evidence from Durham,North Carolina,Working Paper, Vol. 14 (February) 3-4. Washington, D.C.: Urban Institute.

7. Weisberg, Daniel, et al. The Widget Effect, 2-3. New York, NY: The NewTeacher Project. Accessed at widgeteffect.org/downloads/TheWidgetEffect_execsummary.pdf on

November 10, 2009.

8. Mazzeo, Christopher Improving Teaching and Learning by Improving School Leadership,IssueBrief(September), 1, 6-7. Washington, D.C.: National Governors Association, Center for Best Practices.

Accessed at www.nga.org/cda/files/091203LEADERSHIP.pdf on September 10, 2009.

9. Keltner, Brent R. Funding Comprehensive School Reform,Issue Paper, 5. Santa Monica, CA:Rand Corporation. Accessed at http://www.rand.org/pubs/issue_papers/IP175/index2.html on

September 10, 2009.

10. Edutopia (2009). Big Ideas for Better Schools: Ten Ways to Improve Education. Accessed atwww.edutopia.org/big-ideas on November 25, 2009.

11. Childress, Stacey, and Geoff Marietta (2008).A Problem-Solving Approach to Designing and Implementing aStrategy to Improve Performance, 1, 2-5. Boston, MA: Public Education Leadership Project, Harvard

University.

12. Center for American Progress (2009). Leaders and Laggards: A State-by-State Report Card on EducationalInnovation, 12, 15. Accessed at www.americanprogress.org/issues/2009/11/leaders_laggards/report.html

on November 15, 2009.

13. Plank, Stephen (2009). Telephone interview with Stephen Plank, Co-Director, Baltimore EducationResearch Consortium on October 15, 2009.


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14. Anderson, Nick (2009). Black-White Achievement Gap Smaller in Va. Than Md.,Washington Post, July14, 2009.

15. Dougherty, Chrys (2002). ,Issue Brief(September), 2. Denver, CO: Education Commission of the States.

16. Smith, Nancy J., and Jane Armstrong (2006). Data Quality Campaign, Creating Longitudinal Data Systems Lessons Learned by Leading States. Washington, D.C.: Data Quality Campaign.

17. Goldsboro, David (2009). Telephone interview with David Goldsboro, Manager IT Support Systems,Baltimore City Public Schools on October 14, 2009.

18. Collins, Laurie, Michael Sessa, and Elizabeth Laird (2007). The Right Data to the Right People at the Right , 6. Washington, D.C.: Data Quality Campaign.

19. Maryland Department of Education (2009). 2009 Maryland Report Card. Accessed atwww.mdreportcard.org/index.aspx on October 15, 2009.

20. Palaich, R., op.cit.21. Appendix Table 1.22. Western Interstate Commission for Higher Education (WICHE) (2009). State Policy Inventory Database

Online. Accessed at www.wiche.edu/spido/policy_issues_definitions on October 15, 2009.

23. Data Quality Campaign (DQC) (2009). 10 Essential Elements of a State Longitudinal Data System. Accessed atwww.dataqualitycampaign.org/survey/elements on October 16, 2009.

24. Wilson, Leslie (2009). Telephone interview with Leslie Wilson, Assistant Superintendent, Maryland StateDepartment of Education on October 15, 2009.

25. Maryland State Department of Education (MSDE) (2009).MSDE Wins $6.5 Million Federal Grant to UpgradeData System, Press Release onMarch 31, 2009. Accessed at

www.marylandpublicschools.org/NR/exeres/24A0CA71-5A99-4E41-B311-

4598E272EE29,frameless.htm?Year=2009&Month=3%%3E on October 15, 2009.

26. Smith, Susan, Deborah Staub, Mary Myslewicz, and Elizabeth Laird (2007). Linking Education and SocialServices Data to Improve Child Welfare, 8. Washington, D.C.: Data Quality Campaign.

27.

Ibid., p. 8, 10-11, 13.

28. Ibid., p. 9.29. Data Quality Campaign (DQC) (2009).About DQC. Accessed at www.dataqualitycampaign.org/about on

October 10, 2009).

30. DQC (2009), 10 Essential Elements, op.cit.


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31. Data Quality Campaign (DQC) (2009).Maryland (3 of 10 Essential Elements)Using Data Systems. Accessedat www.dataqualitycampaign.org/survey/states/MD/actions on October 17, 2009.

32. Reidenberg, Joel R., and Jamela Debelak (2009). . New York, NY:Center for Law and Policy, Fordham Law School.

33. Ibid., p. 2.34. Ibid.35. Palaich, R., op.cit., p. 2-3.36. Ibid., p. 1-2.37. Ibid., p. 6.38. Ibid., p. 8.39. Smith, S., op.cit., p. 1-2.40. Ibid., p. 5.41. Collins, L., op.cit., p. 14.42. Goldsboro, D., op.cit.43. Ibid.44. Ibid.45. Reidenberg, J., op.cit., p. 37-52.46. Ibid., p. 57.47. Maryland State Department of Education (MSDE) (2009).

One Overall, Press Release on January 7, 2009. Accessed at

www.marylandpublicschools.org/MSDE/pressrelease_details/2009_01_07.htm on October 17, 2009.

48. Data Quality Campaign (DQC) (2008). 2008 Survey Results by State: Maryland. Accessed atwww.dataqualitycampaign.org/survey/states/MD on October 10, 2009.

49. Data Quality Campaign (DQC) (2008). 2008 Survey Results by State. Accessed atwww.dataqualitycampaign.org on October 10, 2009.

50. MSDE (2009), Press Release, op.cit.51. Bowie, Liz ,The Baltimore Sun,

November 28, 2009.


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52. Baltimore City Public Schools (2009). Request for Proposal Data Management System, RFP-10035 (on file withauthor).

53. Baltimore City Public Schools (2009). City Schools Momentum Builds: MSA Gains Continue Across All Grades,, Press Release on July 21, 2009. Accessed at

www.bcps.k12.md.us/News/PDF/MSA08_09PressReleaseFINAL.pdf on October 15, 2009.

54. Swanson, Christopher B. (2009). Cities in Crisis 2009: Closing the Graduation Gap, 16. New York, NY:Education .

55. Maryland State Department of Education (MSDE) (2008). 2007-2008 Fact Book, 1. Accessed atwww.msde.maryland.gov/NR/rdonlyres/FCB60C1D-6CC2-4270-BDAA-

153D67247324/18996/FACT_BOOK_20072008_12309.pdf on October 25, 2009.

56. Ibid.57. Ibid.58. Venezia, Andrea, Michael W. Kirst, and Anthony L. Antonio (2003). Betraying the College Dream: How

Disconnected K-12 and Postsecondary Education Systems Undermine Student Aspirations. Stanford, CA: Bridge

Project, Stanford University.

59. United States Department of Education (USDOE) (2009).Arne Duncan, U.S. Secretary of Education Biography. Accessed at www.ed.gov/news/staff/bios/duncan.html on October 15, 2009.

60. United States Department of Education (USDOE) (2009). U.S. Secretary of Education Announces NationalCompetition to Invest in Innovation, Press Release on October 6, 2009. Accessed at

www.ed.gov/news/pressreleases/2009/10/10062009a.html on October 15, 2009.

61. Pub. L. 111-5, 14005-06, 123 Stat. 282-3 (2009).62. United States Department of Education (USDOE) (2009). Race to the Top Fund: Purpose. Accessed at

www.ed.gov/programs/racetothetop/index.html on November 25, 2009.

63. United States Department of Education (USDOE) (2009). Race to the Top Fund, Final Rule, 74 Fed. Reg. 221,59813, November 18, 2009 (to be codified at 34 C.F.R. subtitle B, chapter II).

64. Ibid.65. The Baltimore Sun, December 11, 2009. Accessed

at www.baltimoresun.com/news/education/bal-md.schools11dec11,0,4143916.story on December 20,

2009.

66. United States Department of Education (USDOE) (2009). Investing in Innovation Fund. Accessed atwww.ed.gov/programs/innovation/factsheet.html on November 25, 2009.


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67. United States Department of Education (USDOE) (2009). Investing in Education, 74 Fed. Reg. 195, 52218,October 9, 2009.

68. United States Department of Education (USDOE) (2009). Grant Program for Statewide Longitudinal DataSystems, 74 Fed. Reg. 144, 37873, July 29, 2009 (to be codified in 34 C.F.R. parts 77, 80, 81, 84, 85, 97, 98,and 99).

69. Smith, S., op.cit., p. 1.70. Ibid.71. Wilson, L., op.cit.72. Family Educational Rights and Privacy Act of 1974 (FERPA) (2009). 20 U.S.C.S 1232g, 34 C.F.R. part 99.73. United States Department of Education (USDOE) (1997). Sharing Information: A Guide to the Family

Educational Rights and Privacy Act and Participation in Juvenile Justice Programs, 3. Accessed athttp://www.eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/43/95/3c.pdf on

October 15, 2009.

74. Family Educational Rights and Privacy, 34 C.F.R. 99.1(c) (2009).75. 20 U.S.C.A. 1232g(B) (West 2009).76. USDOE (1997), op.cit., p. 11.77. 20 U.S.C. 1232g(a)(4) (2006).78. FERPA, op.cit., 34 C.F.R. 99.3(a).79. Ibid.80. USDOE (1997), op.cit., p. 3.81. Robinson, Sally (2009). Telephone interview with Sally Robinson, Deputy Counsel, Office of Legal

Affairs, Baltimore City Public Schools on October 5, 2009.

82. 20 U.S.C. 1232g(a)(2) (2009).83. FERPA, op.cit., 34 C.F.R. 99.3.84. Ibid.85. United States Department of Education (USDOE) (2008). Family Educational Rights & Privacy Act (FERPA)

Final Rule 34 CFR Part 99, Section-by-Section Analysis, 1-2. Accessed at

www.ed.gov/policy/gen/guid/fpco/pdf/ht12-17-08-att.pdf on October 10, 2009.

86. Ibid.


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87. Gonzaga v. Doe, 536 U.S. 273 (2002).88. FERPA (2009), op.cit., 34 C.F.R. 99.62.89. USDOE (2008), op.cit., p. 14.90. Ibid.91. 20 U.S.C. 1232g(a) (2009).92. 20 U.S.C. 1232g(f) (2009).93. 20 U.S.C. 6301-7916 (2002).94. Reidenberg, J., op.cit., p. 11.95. Ibid., p. 12.96. 20 U.S.C. 7911 (2009).97. Reidenberg, J., op.cit., p. 14.98. Ibid., p. 13-15.99. P.L. 104-191, 110 Stat. 1936.100.United States Department of Health and Human Services (DHHS) (2009). Standards for Privacy of

Individually Identifiable Health Information, Final Rule: 45 C.F.R. 160.163.

101.Ibid.102.United States Department of Health and Human Services (DHHS), and United States Department of

Education (USDOE) (2008).Joint Guidance on the Application of the Family Educational Rights Privacy Act

(FERPA) and the Health Insurance Portability and Accountability Act of 1996 (HIPAA) to Student Health

Records, 2. Accessed at www.ed.gov/policy/gen/guid/fpco/doc/ferpa-hipaa-guidance.pdf on October 15,

2009.

103.Ibid., p. 1, 3.104.45 C.F.R. 160.103 (2009).105.DHHS & USDOE (2008), op.cit., p. 4.106.Ibid.107.Wilson, L., op.cit.108.Smith, S., op.cit., p. 6.


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109.Code of Maryland Annotated Regulations (2009). MD.CODE.REGS. 13A.08.02.01.110.Maryland State Department of Education (MSDE) (2008).Maryland Student Records System Manual 2008,

A-2. Baltimore, MD: Maryland State Department of Education.

111.Plank, S., op.cit.112.Brice, Jonathan (2009). Interview with Jonathan Brice, Executive Director, Office of Student Support,

Baltimore City Public Schools on November 15, 2009.

113.Office of the Maryland State Governor (2009). The Origins of StateStat. Accessed atwww.statestat.maryland.gov/history.asp on November 29, 2009.

114.Ibid.115.Henderson, Nia-Malika (2009). ,Politico, October 17, 2009.

Accessed at www.politico.com/news/stories/1009/28409.html on October 17, 2009.

116.Wilson, L., op.cit.117.NEA at Odds with Obama Team Education

Week, Sept. 2, 2009, 6.

118.Md. Code Ann., Educ. 6-115 (2009); H.B. 587, 2009 Leg., 426th Sess. (Md. 2009); Wilson, L., op.cit.119.Orson, Diane (2009).New Haven Teacher Contract Hailed as National ModelWNPRConnecticut

Public Radio, Oct. 27, 2009. Accessed at www.cpbn.org/article/new-haven-teacher-contract-hailed-

national-model on November 15, 2009.

120.Obama Wins a BaWall Street Journal, Oct.17, 2009, A3.

121.What Information Can Police, Schools Share?The Baltimore Sun,November 5,2009. Accessed at www.chicagotribune.com/topic/bal-md.hermann05nov05,0,2421373.story on November

15, 2009.

122.Project, ACLU-MD on December 2, 2009 (on file with author).

123.Spying UncoveredThe Baltimore Sun, July 18, 2008, A1.124.Diibor, Ike (2009). Telephone interview with Ike Diibor, Coordinator, Office of Accountability, Baltimore

City Public Schools on Oct. 10, 2009.

125.Ibid.126.Verdery, B., op.cit.


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127.Boersma, Cindy (2009). Telephone interview with Cindy Boersma, Legislative Director, American CivilLiberties Union Maryland on December 17, 2009.

128.Ibid.129.H.B. 900, 421st Gen. Assem., Reg. Sess. (Md. 2006).130.MD.CODE ANN.,art.83C 2-115 (2009) (Juvenile Services); MD.CODE ANN.,art.88A 2-115 (2009)

(Department of Human Resources); MD.CODE ANN.,CTS.&JUD.PROC 3-827, 3-8A-27 (2009) (Maryland

Juvenile Courts); MD.CODE ANN.,PUB.SAFETY 2-307 (2009) (State & Local Police Authorities).

131.Smith, N., op.cit., p. 5.132.Reidenberg, J., op.cit., p. 54.133.Smith, N., op.cit., p. 4.134.USDOE (1997), op.cit., p. 15, E-1, -2, -4.135.Winnick, Steven, Scott R. Palmer, and Arthur L. Coleman (2006). State Longitudinal Data Systems and

Student Privacy Protections Under the Family Educational Rights and Privacy Act, 11. Washington, D.C.:

Holland & Knight LLP. Accessed at www.educationcounsel.com/files/pub.pdf on November 15, 2009.

136.United States Department of Education (USDOE) (2008). Family Educational Rights and Privacy Act(FERPA) Final Regulations, Dear Colleague Letter. Accessed at

www.ed.gov/policy/gen/guid/fpco/hottopics/ht12-17-08.html on November 15, 2009.

137.Ibid.138.Ibid.139.USDOE (2008), op.cit., p. 7-8.140.Maryland Annotated Code, Education Article 7-303(b) (2009).

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