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Example Problem Statements Draft: Deliberative and Predecisional
Youth Homelessness (Department of Education)
Problem: Homelessness affects a growing number of students nationwide.
The number of homeless students nationwide has nearly doubled from about 680 thousand homeless
children and youths enrolled in public schools in 2006-07, to m
ore than 1.3 million during the 2013-14
school year.Over the same period, the number of unaccompanied homeless youths (not in the
physical custody of a parent or guardian) has more than doubled to nearly 100,000 students.Young
children constitute a substantial proportion of children experiencing sheltered homelessness in
families (about 250,000 in total) – in FY 2015, about half of all such children were under age 6.
Homelessness can significantly affect students’ success in school: homeless students are much less
likely to graduate. Homeless students experience greater mobili
ty between schools as well as chronic
absenteeism, which can interrupt their education and are associated with lower school achievement
and a higher risk of dropping out. Leaders at all levels can benefit from better understanding this
challenge and how we serve such students.
Use Case: National, state, and local policymakers, educators, and service agencies could benefit from
better understanding where our homeless preK-12 students are en
rolled and how well we are serving
them.
Areas of need for digital resources include:
● Supporting communities addressing youth homelessness as they consider educational needs.
For example, the HUD Youth Homelessness Demonstration Program i
s providing $33 million in
funding to 10 communities committed to ending youth homelessness. The Program requires
communities to commit to collaborate with a broad array of partners, develop a coordinated
community plan to prevent and end youth homelessness, and participate in a program
evaluation.
o This tool could help communities perform needs assessments and plan for success
with an emphasis on education. For example, the tool could focu
s on specific
educational needs, including data such as age and grade breakdown and
unaccompanied status.
● Mapping data related to homeless student enrollment, contributing factors, and
federally-funded programs/resources. Geographic representation
of where homeless students
are enrolled by school district; for instance, to understand where services might be most
needed.
o The tool could also include national data on fair market rents (which illustrate housing
costs for geographic areas), as well as local data regarding ev
ictions and foreclosure
rates to understand potential factors contributing to student homelessness.
o The tool could also include location and program type data for federally-funded
programs and resources that serve vulnerable students. For exam
ple, the tool might
include publicly available grant award data for HUD Continuum of Care (CoC) funded
programs, HHS Runaway and Homeless Youth funded programs, and DOL funded
programs such as YouthBuild and Job Corps. Capturing publicly available contact
information for local CoC planning bodies, which are required by HUD to address
homelessness within their geography, and local school districts—relationships
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Example Problem Statements Draft: Deliberative and Predecisional
between education liaisons and CoCs vary significantly in strength across
communities– could help these stakeholders build relationships and common
understanding.
● Comparing relationships between funding and need. The tool could help local leaders to
understand how funding for homeless-related programs compares geographically and by
number/percent of homeless students served.
● Comparing outcomes. Help users better understand the relationship between outcomes and
homelessness at varying levels. Service providers, for instance, could learn examples of best
practices.
o Comparing the academic outcomes of homeless students to those of their
non-homeless peers, potentially identifying schools with best practices for serving
homeless students.
o Comparing characteristics and outcomes of schools/LEAs with high homeless
populations to those with low homeless populations.
