student assignment policy

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In This Article Expand or collapse the "in this article" section Student Assignment Policy

Introduction, general overviews.

• Key Court Cases
• Student Body Composition and Outcomes
• Teacher Quality
• Methods of Assignment—School Choice
• Desegregation
• Resegregation

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Student Assignment Policy by Eric A. Houck LAST REVIEWED: 15 December 2011 LAST MODIFIED: 15 December 2011 DOI: 10.1093/obo/9780199756810-0043

Student assignment is a topic of study in educational policy that focuses on the processes by which students are allocated into schools and classrooms. In this subfield of educational policy studies, scholars also study the results from such decisions. Student assignment polices have been influenced historically by federal litigation but remain local decisions in American public school governance. As a result, student assignment policies are highly localized in scope and sensitive to broader district contexts. Historically, student assignment policies have been made with regard to geography and transportation efficiency: students attended schools that were closest to their residences. This changed in 1954 with Brown v. Board of Education , when the US Supreme Court ruled that willful assignment of African American students into separate and inferior schools was unconstitutional. From that time forward, student assignment policies in many districts in the American South have been made with regard to student body racial composition. Beginning in the mid-1990s numerous districts began petitioning for a designation of unitary status, indicating that any student segregation was not related to prior discriminatory practices of the past, or confronting legal challenges on the use of race as a factor in determining a child’s school assignment. These district-led initiatives were given even more importance by the US Supreme Court’s ruling that race could not be used as a primary criterion in student assignment decisions, effectively reversing critical aspects of the Brown ruling. As a result of these developments, districts have begun to look at criteria other than student racial composition to create student body diversity within schools. Some of these approaches have included widening school attendance zones in order to draw from a more diverse population of students, using student socioeconomic status or level of academic performance in assignment policies to create diversity within schools along academic and economic dimensions, or leveraging alternate school types, such as magnet schools, to draw wealthier parents from suburbs into majority-minority urban schools. One important topic seeks to understand the politics of creating student assignment polices. Another topic focuses on primary outcomes, such as academic performance, socialization, and future economic earnings. A third topic examines secondary outcomes, such as teacher and leader quality associated with the student body composition of a school, that are assumed to be correlated with increased student-level academic productivity.

Unlike other well-defined policy arenas in education, such as curriculum, finance, supervision, and law, student assignment policies draw from a variety of approaches and disciplines. In fact it may be safe to assert that there is no well-defined and codified canon of scholarship around the policy issue of student assignment. Further, the fact that student assignment policies are created locally yet are subject to adjudication in state and federal courts requires educators and policymakers seeking to understand student assignment policies to approach the topic with a foundation in educational politics and policymaking. Therefore this section reviews important works in the fields of politics of education and educational policy studies. Wirt and Kirst 2005 provides a cogent review of the role of politics and political players in local, state, and federal educational policymaking. Ravitch 1985 provides an overview of the failure of many school reform policies during the decades leading up to the gestation of the current standards-based reform agenda. The new direction in education and education reform is charted in Clune 1994 , noting a shift from equity-oriented policies to outcome-oriented policies in school finance, but the piece speaks clearly to the broad expanse of educational reform. This perspective is articulated in Fuhrman and Elmore 2004 , which confronts one of the key challenges of the outcome-oriented standards-based reform movement. The larger context for these trends is provided in Cooper, et al. 2004 , which reviews key theories and trends in educational policymaking, and in Guthrie and Schuermann 2009 , which reviews trends and issues in educational leadership. Roza 2010 provides details of the resource allocation inequities at the school level with some discussion of the manner in which student assignment policies impact school-level resource allocation. Two historical pieces provide context for consideration of the links between the desegregation movements of the 1970s and current student assignment policies. Formisano 2004 and Cecelski 1994 provide interesting perspectives on resistance to desegregation as practiced in the 1970s by white blue-collar Bostonians and rural African American southerners, respectively.

Cecelski, D. S. 1994. Along freedom road: Hyde County, North Carolina, and the fate of black schools in the South . Chapel Hill: Univ. of North Carolina Press.

DOI: 10.5149/uncp/9780807844373

Traces efforts of the African American community of a rural North Carolina county to resist efforts to desegregate their community school.

Clune, W. H. 1994. The shift from equity to adequacy in school finance. Educational Policy 8.4: 376–394.

DOI: 10.1177/0895904894008004002

An analytic essay charting the broad movement in educational policymaking from a focus on inputs and equity to a focus on outcomes and adequacy of systems.

Cooper, B. S., L. D. Fusarelli, and E. V. Randall. 2004. Better policies, better schools: Theories and applications . Boston: Allyn and Bacon.

A text used to introduce key concepts in the policymaking process and their role in educational policymaking specifically.

Formisano, R. P. 2004. Boston against busing: Race, class, and ethnicity in the 1960s and 1970s . Chapel Hill: Univ. of North Carolina Press.

Historical book that traces white resistance to school integration in Boston in the early 1970s.

Fuhrman, Susan H., and Richard F. Elmore, eds. 2004. Redesigning accountability systems for education . New York: Teachers College Press.

A series of essays addressing the manner in which accountability policies and structures can be reconfigured to meet the challenges of standards-based reform.

Guthrie, J. W., and P. J. Schuermann. 2009. Successful school leadership: Planning, politics, performance, and power . Boston: Allyn and Bacon.

A textbook outlining challenges and strategies for modern educational leaders.

Ravitch, D. 1985. The troubled crusade: American education, 1945–1980 . New York: Basic Books.

Historical piece outlining perceived failures of educational policy to sustain excellence in a period of equity.

Roza, M. 2010. Educational economics: Where do school funds go? Washington, DC: Urban Institute.

A consideration of how federal and state policies interact with the unintended consequence of systematically underfunding high-needs students.

Wirt, F., and M. Kirst. 2005. Political dynamics of American education . 3d ed. Richmond, CA: McCutchan.

Provides an overview of political interest groups and the use of power in educational policymaking at the local, state, and national levels.

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Student Assignment Policy

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The assignment of students to electives, selectives, training sites, clinical teams, or supervision by a given faculty member should be made in a manner that is equitable, allows each student to complete all requirements of the experience, and work in an environment that ensures fair assessment and appropriate supervision: 

• Students are to be allowed to express their preference for assignments prior to the schedules being created and clerkship/elective directors should take these preferences into account. All other assignments are to be made randomly.
• Student assignments must abide by the  Conflict of Interest Policy
• Students may request a trade of clinical assignments within their clerkship with their peers subject to the approval of the clerkship/rotation director. Requests for trades must be agreed upon by both students and submitted in writing and to the department’s educational coordinator no later than 7 days after receipt of the clerkship schedule/assignment.
• Students may request an alternate assignment after being notified of their schedule per the  Requesting Alternate Assignment Policy
• When applicable, the assignment of students in Phase 2 clerkships has priority over those in Phase 3 electives
• COM students have primacy over visiting students in assignment to electives, selectives, and clinical teams. 

Clerkship/elective directors are responsible for verifying that the above process is used and give final approval for all student assignments. Students may appeal their assignment to the Phase Director, followed by the Associate Dean for Medical Education. The latter's decision is final.

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Each student in the Cumberland County Schools System is assigned to the school of his/her grade level serving the attendance area in which the student’s parent or court-appointed custodian resides. The Student Assignment Office has the responsibility of ensuring all students are attending the appropriate schools. Our guidelines and procedures are developed based on the following:

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• Provide choices to explore a variety of educational opportunities toward meeting the diverse needs of our students.

In addition to school assignments, the Student Assignment Office also helps parents, students, and schools with issues involving custody, residency, family hardships involving school assignments and Choice Program application procedures. All students residing in Cumberland County are eligible to apply to the Choice Program during the application period. For more information on the Choice Program, please visit the  Cumberland County Schools Choice Program Website .

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Student Assignment Department 2465 Gillespie Street Fayetteville, NC 28306 Phone: 910-678-2616

Dr. Melody Chalmers McClain, Associate Superintendent, Student Support Services Saundra McNeill, Student Assignment Manager

How do I find out what school my child is assigned to?

Every child in the Cumberland County School system is assigned to a school district by their address. Click on the following link, type in your street address, and the school that your child is assigned to will appear in the display box on the right-hand side of the screen: Find My School .

My family is new the area. How do I enroll my child into school?

Enrollment takes place at the school by contacting the school's data manager or registrar. Click on the link for more information:  Enrollment for CCS Students

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Board Members

GOALS AND GUIDING PRINCIPLES FOR STUDENT ASSIGNMENT

The Board’s Mission and Vision, shall be the guiding premise for this and every Board Bylaw, Policy, and Exhibit.

Student assignment is the responsibility of the Charlotte-Mecklenburg Board of Education. The Student Assignment Goals represent the Board's priorities for assigning students to schools, while the Guiding Principles provide our superintendent and staff the blueprint for developing the Student Assignment Plan.

Student Assignment Goals

The Board believes that a student assignment plan that promotes the vision and the mission of the Board will, to the extent possible:

A. Provide choice and promote equitable access to varied and viable programmatic options for all children;

B. Maximize efficiency in the use of school facilities, transportation and other capital and operational resources to reduce overcrowding;

C. Reduce the number of schools with high concentrations of poor and high-needs children;

D. Provide school assignment options to students assigned to schools that are not meeting performance standards established by the state; and

E. Preserve and expand schools and programs in which students are successfully achieving the mission and vision of the Board.

Guiding Principles for Student Assignment

Many factors related to student assignment are within the Board's influence and authority, including responding to the valuable input and feedback from our families and broader community. Still, there are many factors driving student assignment that are outside the Board's control. These include but are not limited to housing patterns, public transportation and the local economy. The Board calls on all of our community, especially elected officials in Mecklenburg County, business owners, civic organizations, faith houses and philanthropists, to prioritize our children when making decisions that impact schools. If we are to maximize academic achievement for every child, it must be a community effort.

The Student Assignment Plan will be built on a foundation of equitable access to high-quality schools including home schools, magnet schools and additional types of school options. All schools, regardless of type, should consistently demonstrate high student achievement and must eliminate achievement gaps. The district's portfolio of schools should include a range of theme-based programs as well as instructional models that respond to the various learning styles and preferences of its student body.

The Board will intentionally expand and replicate successful programs and schools throughout the county in ways that increase equitable access to high-demand themes and instructional models.

In order to create and maintain a plan that is sustainable over time, the Board will consider several factors when determining and adjusting assignment patterns. These include but are not limited to current and future population growth and potential demographic shifts, overcrowding and underutilization of facilities. Additionally, the Board will consider undertaking a comprehensive district-wide review of the Student Assignment Plan every six years, while recognizing it may be necessary to make more frequent localized changes to the assignment plan based on the aforementioned factors.

The Student Assignment Goals and Guiding Principles will drive all related student assignment decisions.

I. Types of Schools

A. Home Schools

Home schools are schools with fixed, contiguous attendance boundaries. Every student will be assigned to a designated home school within proximity to where he/she lives.

1. To the extent possible when establishing home-school attendance boundaries and determining proximity, the Board will consider:

a. Facility capacity (based on classroom standards for each school);

b. Travel distance from the home to school;

c. Keeping entire neighborhoods assigned to the same school (staff shall use discretion in considering commonly accepted neighborhood boundaries, zoning decisions, covenant agreements, homeowners associations [HOAs], municipal jurisdictions, etc.);

d. Population density within neighborhoods and school attendance areas; and

e. Keeping whole elementary attendance areas intact as part of middle and high school feeder patterns.

2. In establishing home schools, the Board will consider:

a. Configuring schools with varying grade levels;

b. Constructing attendance boundaries, especially for newly established schools, that contribute to a socioeconomically diverse student population; and

c. Collaborating with other local governmental bodies to inform those policy decisions (e.g., housing, transportation) that directly impact student assignment.

B. School Options

1. Non-Magnet School Options

Non-magnet school options do not have fixed attendance boundaries. Access is within a transportation zone or a choice zone (a geographic area that may or may not correspond with a transportation zone). Broader than magnet schools and not governed by the Board's magnet policies, non-magnet school options include but are not limited to middle and early colleges, innovative small schools and e-Learning academies. Students may apply to attend a non-magnet school option using the district's school options lottery. As provided in Exhibit  S-ASGP/E1 , sibling guarantees and proximity priorities do not apply for admission to non-magnet school options, nor do non-magnet school options have continuation schools.

2. Full and Partial Magnet Schools

Magnet schools do not have fixed attendance boundaries, and access is within a transportation zone or a choice zone (a geographic area that may or may not correspond with a transportation zone). Admission is governed by the Board's magnet policies. Students may apply to attend a magnet school using the district's school options lottery. Magnet schools may be full or partial school programs. Partial magnets are schools where part of the seats are assigned to students residing within a fixed home school attendance area (the "home school guarantee") and the remaining seats are assigned to students who apply via the school options lottery. At full magnet schools, all of the seats are assigned via the school options lottery.

C. In preserving, expanding, replicating and establishing new school options, the Board will consider:

1. Responding to demand as demonstrated by lottery applications and parent and community feedback;

2. Strategically locating school options throughout the county; and

3. Establishing a variety of choice and/or transportation zones.

D. In assuring equitable access to school options, the Board will consider:

1. Establishing priorities in the school options lottery based on socioeconomic status;

2. Streamlining criteria for enrollment and continuation based on programmatic requirements; and

3. Providing varied transportation options.

II. Ensuring Equitable Access to High-Quality Schools

To increase each student's opportunity to access high-quality schools, the Board will:

A. Establish a priority in the school options lottery and the transfer process for students attending a school that has been designated by the state as low performing for three consecutive years; and/or

B. Implement partial magnet, targeted turnaround programs and specialized academic options in low-performing schools to improve outcomes for all students.

III. Operational Efficiency

The Student Assignment Plan must be cost effective and make efficient use of our facilities, transportation and other capital and operational resources. To that end, the Board will strive to:

A. Prioritize ensuring every home school is a high quality and viable school choice;

B. Increase utilization of schools operating under capacity by expanding partial magnet schools and school options;

C. Consider alternative instructional delivery models that maximize student achievement while reducing facility and transportation costs; and

D. Consider modifications to transportation zones and feeder patterns that are designed to provide operational efficiency and equitable access to quality educational programs.

STUDENT ASSIGNMENT PLAN POLICY

As provided by North Carolina law, all students under the age of 21 years who are domiciled in Mecklenburg County and who have not been removed from school for cause or have not yet obtained a high school diploma are entitled to be enrolled in public school. Students shall be assigned to a particular school by the Board of Education in accordance with the student's place of residence and a student assignment plan adopted by the Board.

I. School Attendance Areas

A. The Board of Education shall establish geographic boundaries for home schools, transportation zones and other zones of choice, locations for school options, and feeder patterns for home schools and school options.

1. Attendance areas shall be determined based on the Goals and Guiding Principles set forth at the beginning of this policy.

2. Any such action shall be taken only after the Board has held a public hearing on the initial proposal.

3. With the exception of situations that constitute an emergency threat to the safety of staff or students, the Board will notify students and parents of potential changes to the Student Assignment Plan by the first Board meeting in November prior to the school year in which the changes are scheduled to go into effect.

B. Notwithstanding the above, the superintendent is authorized to make minor changes within a school year to school attendance boundaries in response to the construction of new roads or new subdivisions.

II. Determination of Student Residence

A. Except as set forth below, the residence of a student is defined as the domicile of the student's parent. A student's domicile may be changed only in the event the parent has abandoned the parent's former domicile with no intention of returning to it, established actual residence in another location, and evidenced an intention to remain in the new location permanently or indefinitely. A minor may not select, acquire, or change his/her domicile to a domicile other than that of the minor's parent.

B. Notwithstanding the domicile of a student's parent:

1. The residence of a married student shall be the domicile of the student rather than the domicile of the student's parent.

2. The residence of a student who is an emancipated minor shall be the domicile of the emancipated student.

3. The residence of a student who is residing in a group home, foster home, or pre-adoptive home shall be the group home, foster home, or pre-adoptive home. A pre-adoptive home is one in which a child is placed by a county Department of Social Services or licensed child-placing agency.

III. School Options Lottery

A. Effective with assignments for the 2017-18 school year, assignments for the following categories of schools will be made through the School Options Lottery:

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The opportunities and risks of K-12 student placement algorithms

Subscribe to the center for technology innovation newsletter, matt kasman and matt kasman assistant research director - center on social dynamics and policy jon valant jon valant director - brown center on education policy , senior fellow - governance studies.

February 28, 2019

• 16 min read

This report is part of “ A Blueprint for the Future of AI ,” a series from the Brookings Institution that analyzes the new challenges and potential policy solutions introduced by artificial intelligence and other emerging technologies.

How students are assigned to schools is changing, especially in urban areas. After decades of using students’ home addresses to determine school assignments, many U.S. cities are now turning to placement algorithms—alongside school choice policies—to determine which students can attend which particular schools. These algorithms, built on the Nobel Prize-winning theory of market design, elicit families’ ranked preferences for schools and use those preferences, along with schools’ priorities, to match students and schools.

In this paper, we examine the unified enrollment (UE) systems that use placement algorithms to make student assignments. After describing these systems, we explore their considerable promise and peril. We argue that UE systems can markedly improve the equity and efficiency of urban education systems. However, they must navigate difficult political terrain—with strong forces pushing against equity—and are vulnerable to misunderstandings by system users and designers. In other words, for all of their technical elegance, these systems’ ultimate success will depend on how people interact with them.

Background on student placement algorithms

A defining feature of the U.S. public education system is the strong link between where children live and which schools they attend. This is problematic in a country with severe levels of racial and socioeconomic segregation and inequality. School choice reforms, like charter schools and open enrollment policies, offer one approach to weaken this link, as they provide families with additional tuition-free options. Yet these reforms often bring obstacles along with them. As a result, many cities’ school choice policies—especially as they relate to student placement—have evolved over time. What began as highly decentralized systems turned to common applications and now UE systems that use placement algorithms.

“A defining feature of the U.S. public education system is the strong link between where children live and which schools they attend. This is problematic in a country with severe levels of racial and socioeconomic segregation and inequality.”

Consider, first, a decentralized school choice environment in which families can apply to various charter schools that operate alongside a traditional district, with each school managing its own enrollment process. In this environment, parents find themselves with a host of logistical challenges—navigating multiple schools’ deadlines, requirements, and informational materials—while school leaders find themselves handling a burdensome process.

In response, some cities created a common application that lets families apply to multiple schools at once. In New Orleans, for instance, the Recovery School District instituted a common application in 2008 for its direct-run schools . This simplified the application process by reducing paperwork and standardizing deadlines and procedures—but problems remained. School leaders still had to manage their own enrollment process and paperwork, raising concerns about transparency and inefficiency. They struggled to project how many students would enroll—and how many teachers they should hire—since a student could hold a seat in multiple schools while deciding which one to attend. Moreover, with enrollment processes left to individual schools, there was no mechanism to match students and schools that incorporated families’ preferences for some schools to which they applied over others.

Advances in economics offered potential solutions to these problems. In 1962, mathematicians David Gale and Lloyd Shapley proposed a deferred acceptance (DA) algorithm to address instability in markets. Over the years, the theory has been refined and the applications extended. Alvin Roth, who shared the 2012 Nobel Prize in Economics with Shapley (four years after Gale’s death),  put algorithms to use  in matching kidney replacements to patients, medical residents to hospitals, and, most relevant here, students to schools through UE systems. Other economists, including Atila Abdulkadiroğlu and Tayfun Sönmez, worked on both developing the  theory behind student assignment mechanisms  and their  practical application  in cities such as Boston.

The first step in the UE application process is for families to submit rank-ordered lists of the schools they most want their children to attend. In Camden, New Jersey, for instance, applicants can request up to eight schools. In Denver, they can request up to 12. Critically, the placement algorithm is “strategy-proof” in the sense that applicants cannot game the algorithm by ranking schools out of their true order of preference. Applicants are not punished for ranking a school highly—e.g., as a first-choice school—if the probability of admission is low. (This is not the case for some non-DA types of placement algorithms, like those long used in Boston .)

Along with parents’ requests, the algorithm needs a procedure for determining how to allocate seats when demand for a school’s seats exceed supply. One option is to use only random lottery numbers. In practice, however, most cities give priority to certain groups of students and use lottery numbers to order students within these groups. Priority categories can be school-specific (e.g., sibling priority to a single school) or universal (e.g., priority to any school because one’s current school is closing).

The core algorithm tends to be quite simple. Take, for example, the DA algorithm that places students in New Orleans. First, it attempts to place all applicants in their first-choice school. If a school is oversubscribed, the algorithm tentatively admits students in order of their priority ranking (based on priority categories and lottery numbers) until the school reaches its capacity. Any students who do not make this cut are eliminated from consideration at that school. However, these students then receive full consideration at their second-choice school, even if that means displacing a student who ranked that school first. The algorithm cycles through this process until it has considered all relevant school requests and then finalizes the assignments. No student receives a seat in more than one school.

The use of this type of algorithm is what distinguishes a UE system from a common application. A unified enrollment system includes a common application, but it also asks applicants to rank-order schools and then uses an algorithm to make placements across a large number of schools.

Denver and New Orleans are thought to have launched the country’s first UE systems with DA algorithms in 2012 (although other cities, like San Francisco , had been doing similar work). Since then, many cities have followed suit, including Camden and Newark in New Jersey, Chicago, Indianapolis, New York, and Washington. These UE systems differ from one another on various dimensions. For example, while nearly all New Orleans public schools and some private schools are available through its OneApp system , New York’s system focuses on public high schools . Some cities, like Chicago and Indianapolis, offer a second round of applications for families who lack or dislike a placement after the first round; other cities do not. While Denver’s priority categories consist of only sibling and geographic preference, New Orleans has given priority to students whose schools are closing, and some schools in Washington give priority to children of staff or those who would like to transfer from another school managed by the same organization. Several other cities, including Boston and Detroit, are reportedly now considering unified enrollment .

Opportunities

Relative to less centralized approaches to student enrollment, UE systems can, under certain conditions, create significant benefits for applicants and school leaders alike. In addition, these systems can serve public interests by providing greater transparency and more tools to policymakers to align public education systems with the public’s goals. Next, we describe some of these potential benefits.

UE systems generally simplify the application process for parents and improve the matches between students and schools. Simplification comes from the ability to fill out a single application by a single deadline, and from the tendency for cities to improve and centralize their school information offerings when they adopt UE systems. This could lead to parents considering more schools and making more informed decisions for their children.

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Beyond simplification, DA algorithms can improve the likelihood of a desired placement for their children. A decentralized system in which schools conduct their own lotteries for admission has no mechanism for incorporating applicants’ varied preferences. DA algorithms provide that mechanism.

School leaders

By centralizing application and assignment, UE systems keep school leaders from having to manage burdensome processes. While some school leaders decry the loss of control to centralization, many leaders welcome the opportunity to devote their resources and attention to other matters.

DA algorithms also facilitate planning for school leaders. In decentralized choice systems, a student could hold seats in many schools simultaneously. UE systems enable school leaders to project enrollment more accurately by allowing a student to hold a maximum of one seat at a time.

The general public

UE systems can promote transparency and equity by limiting schools’ opportunities to manipulate admissions and making schools more visible and accessible to parents. They generate data on parents’ preferences and the effects of schools that can inform educational policy and practice. In addition, they provide a method, albeit a controversial one, to grant priority access to desirable schools to the most vulnerable, disadvantaged students—in effect, an opportunity to nudge the system to be more equitable or integrated.

We have described opportunities for UE systems to generate benefits. The extent to which they fulfill their potential depends on the details of their design and execution, and on how well system leaders navigate the related challenges.

The school choice process is difficult, and applicants’ mistakes and misunderstandings can have harmful effects. Some of these issues exist with or without a UE system, like parents being uninformed or misinformed about the schools available. Others are more specific to UE. Applicants might attempt to “game” a strategy-proof DA algorithm—by, for example, ranking higher-probability schools ahead of their true first choices—and undermine their placements. They might underestimate the risks of not requesting enough schools, finding themselves without a placement after the first round (when the most desirable options are typically available). To date, many cities have observed applicants requesting far fewer than the maximum number of schools available.

“Perhaps the greatest threat, however, comes from applicants’ perceptions of UE systems and the broader politics of school choice. As long as some schools are oversubscribed, UE systems will tell some applicants they cannot have the schools they want.”

Perhaps the greatest threat, however, comes from applicants’ perceptions of UE systems and the broader politics of school choice. As long as some schools are oversubscribed, UE systems will tell some applicants they cannot have the schools they want. For example, in Chicago’s first year with unified enrollment, about half of applicants did not receive their first-choice program and 19 percent did not receive a top-three choice. These rejections have consequences. First, they can undermine public satisfaction with UE systems and the systems’ long-term political viability. Second, they can lead residents to apply pressure on policymakers to grant admissions priority to their children. Political influence is not evenly distributed, and relatively wealthy parents have advocated for policies within choice systems—like priority for students who live in a school’s geographic zone—that improve access for the privileged at the expense of the underprivileged.

Policymakers

Similar to challenges arising from UE applicants, challenges arise from the mistakes, misunderstandings, and biases of policymakers. Even if DA algorithms are relatively simple, predicting how student assignment policies will affect enrollment and outcomes is difficult. This policymaking complexity has multiple causes. For one, after settling on a plan—like giving priority to students who live in a school’s geographic zone—policymakers confront questions about how to operationalize it in an algorithm. What happens if the priority applies only to a subset of the seats in a school? What are the consequences of putting it higher or lower in the hierarchy of priorities? These questions are hard to answer without considerable analysis.

Complicating matters further, school-choice behaviors and student-assignment policies are inherently interconnected and dynamic. Families make school requests. Their placements and their peers’ placements depend on how the algorithm is designed, and their enrollment decisions might depend on their peers’ enrollment decisions. These decisions can change schools, which can change applicant behaviors in subsequent years. All of this creates challenges for policymakers to assess a priori how policy decisions will affect students and schools—and creates potential for unintended negative consequences.

Furthermore, UE systems require policymakers to make tradeoffs even across the principles they might prioritize. The most efficient algorithm is not always the most transparent or understandable to parents, as New Orleans policymakers found when they abandoned a “top trading cycle” (TTC) approach in 2012 to 2013. After-market placements also can be difficult. An approach that seems straightforward and benign on paper—like working informally with families and schools to place students who missed the application window—could create opportunities to game the process.

“Furthermore, UE systems require policymakers to make tradeoffs even across the principles they might prioritize. For example, the most efficient algorithm is not always the most transparent or understandable to parents.”

Some challenges arising on the policymaker side are less innocuous. Over the last few years, two chancellors of the District of Columbia Public Schools (DCPS) left their positions amid controversy related to the district’s UE system. In one case , the chancellor was found to have given preference to her close acquaintances; in the other case , to his own child. While UE systems reduce the opportunity for indiscretion at the school level, they can create opportunities for indiscretion at other levels.

Recommendations

In response to these challenges, we propose a set of policy recommendations for UE systems:

First, clearly articulate the goals of the UE system. UE systems embody and implement the goals that policymakers have for student assignment. Policymakers should be forthcoming about those goals—e.g., whether to integrate schools or give all families a neighborhood option—and make policy decisions that align with them. Specifically, we suggest creating a statement of values for student assignment. Some of these values might exist in tension with one another, but community members should know how policymakers approach these tensions.

In addition, system leaders should communicate about what UE systems cannot do. UE systems can efficiently allocate the seats that exist. They cannot create good schools by themselves, nor can they ensure that all applicants receive a seat in their first-choice school. Being clear about these limitations could help to direct some community frustrations to the true causes of those frustrations.

Second, actively disseminate information about the UE system, and be transparent. System leaders must actively inform the community about the choice process. The goal is to inform families, not just make information available. That could require different types of outreach for certain subpopulations such as those in poverty, new to the city, or not fluent in English. The costs of information failures can be high. With application deadlines many months before school starts, a parent might get locked out of desirable schools long before it occurs to her to start searching.

System leaders also should be transparent about how the placement algorithm works. Some cities provide animated videos that explain the algorithm in accessible language. Beyond this, the algorithm that the district uses—including its software code—should be publicly available. Many districts have contracts with vendors who write and run code for UE systems. While these vendors have valid concerns about protecting proprietary information, these concerns do not outweigh the public’s right to see how children are assigned to public schools. Making this information public can enhance the perceived legitimacy of the system, make policymakers aware that the public (and researchers) can scrutinize their decisions about algorithm design, and enable more people to assess and comment on the algorithm.

Third, use emerging technologies to improve the information available to policymakers. Understanding the implications of algorithm design decisions sometimes requires one to assess the complex dynamics of applicant behaviors, schools’ responses, subsequent applicant behaviors, and more. While UE system administrators might prefer to avoid doing this work themselves, researchers can use complex adaptive systems models to illuminate the likely consequences of various decisions. One such approach, agent-based modeling (ABM), is especially well suited for this work. A comprehensive description of ABM is beyond the scope of this paper, but ABM offers policymakers a powerful tool to evaluate the potential effects of policies. ABM has already been used in San Francisco to simulate how school applicants behave and schools evolve under prospective policy conditions, and to inform student assignment policy . These models can incorporate heterogeneity in applicants’ attributes and behaviors, along with realistic geographic characteristics. They can thus act as “virtual laboratories” to explore the likely effects of a large array of potential interventions beyond changes in student assignment policies, such as school openings, school closings, or successful information dissemination. This could be a particularly valuable area of collaboration for researchers and practitioners.

“An algorithm cannot solve every problem in student assignment.”

Fourth, determine how the UE system should—and should not—change in response to community feedback, and recognize that an algorithm cannot solve every problem in student assignment. Any UE system will elicit strong reactions from the community. Policymakers must address these concerns without compromising their goals. Some changes go too far, like succumbing to political pressure for strong geographic preferences if the goals prioritize access for disadvantaged populations. Moreover, policymakers should recognize that the best solution to a student assignment problem might not involve tinkering with the algorithm. If the community is frustrated about the scarcity or inaccessibility of high-quality seats, the best approach might involve decisions about school siting, seat capacity , or student transportation , not algorithm design.

In conclusion, residence-based school assignment is part of the foundation of U.S. public schooling. UE systems, coupled with school choice policies, have taken aim at this foundation—and provided solutions to problems with decentralized school enrollment. They have real potential to make public education more equitable and efficient. However, to fulfill this potential, they must survive numerous challenges. While the heart of a UE system is an algorithm, it will be people’s responses that determine how long and successfully these systems operate.

Jacqueline Lantsman contributed to this paper.

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