@gardnercenter

Community Research for Youth and Families

Amy Gerstein

Children and Families Policy Symposium

March 4, 2015

@gardnercenter

Agenda

• About The John W. Gardner Center

• Community Research for Youth and Families

• Chronic Absenteeism: Redwood City

• Early Warning Indicators: San Francisco

• Key Takeaways

About the Gardner Center

Our Mission

The Gardner Center

partners with

communities to develop

leadership, conduct

community-driven

research, and effect

positive change in the

lives of youth

RESEARCH

COMMUNITY ENGAGEMENT

CAPACITYBUILDING

CHANGE

The Youth Sector

YOUTH

AFTERSCHOOL PROGRAMS

SUMMER PROGRAMS

HEALTH SERVICES

FAMILIES

RELIGIOUS INSTITUTIONS

NEIGHBORHOODS

SCHOOLS

SOCIAL SERVICES

Our Strategies

• Implementation research

• Integrated longitudinal data analysis

• Community engagement

Community Research for Youth and Families

• Cross-sector collaborations

• Identification of problem area

• Community engaged throughout process

• Iterative discussion of questions, methods, findings, and possible solutions

• Conversations, behaviors, and policies change

Chronic Absenteeism in Redwood City

Redwood City 2020

• Concerned about chronic absence

• Believed that response should be community-wide

• Engaged Gardner Center in collaborative research process

Research Question 1

What is the extent of the problem?

• How many and what percent of students are chronically absent or truant?

• What are the demographic characteristics of these students?

• How has the arc of the problem changed over time?

Research Question 2

In what ways does this affect student outcomes?

• What demographic characteristics and other factors are correlated with students’ absenteeism?

• What are educational outcomes for students with absenteeism issues over time?

Data and Analyses

• Used longitudinal linked data from the elementary and high school districts through the Youth Data Archive

• Conducted descriptive and regression-adjusted analyses

• Examined chronic absence across school years to understand the persistence of the problem

Extent of the ProblemWhat percent of Redwood City students are chronically absent?

K 1 2 3 4 5 6 7 8 9 10 11 120%

10%

20%

30%

12%

9%7% 7% 6% 6% 6% 7%

10% 10% 10% 9%11%

Grade Level

• Being an English Learner

• Having been suspended

• Having a parent who did not graduate from college

• Having made a school or district transition

• Having been tardy 3+ days

PROFILE OF CHRONIC ABSENCE

Chronically absent elementary-school students had higher rates of . . .

• Being an English Learner

• Having been suspended

• Having made a school or district transition

• Being female

PROFILE OF CHRONIC ABSENCE

Chronically absent high-school students had higher rates of . . .

Key IndicatorsStrongest predictors of chronic absence in a school year include . . .

ELEMENTARY SCHOOL

HIGH SCHOOL

Prior year chronic absence X XAccumulated 3+ tardies XSuspension X

Key Effects

Number of days absent had significant negative effect on students’

• California Standards Test (CST) percentiles in Math and ELA in elementary grades

• Grade point average (GPA) in high school grades

Implications for Policy and Practice

• Community-wide interventions

• System-wide response to chronic absence

• School-based focus on chronic absence

What Happened?

• Elementary district hired attendance coordinator

• Police shifted strategies

• Health system re-assessed role

• Community awareness increased

Early Warning Indicators in San Francisco

Project Goals

• Ensure that more students are graduating from high school in a timely manner

• Develop Early Warning Indicators to identify 8th and 9th grade students at risk of not graduating

• Provide extra supports to help move them back on track

• Engage in a collaborative research process

Research ObjectiveDevelop a 3 Part Indicator System that . . .

Identifies 8th grade students

who may benefit from a

summer program that

eases transition to high school

Helps high schools identify

incoming 9th grade students

who might benefit from

added supports

Monitors students during

9th grade to ensure they stay on track

for high school graduation

Data and Analyses

• Regression analysis of SFUSD administrative data

• SFUSD selected two 8th grade indicators or risk factors: (1) GPA below 2.0 (2) Attendance rate below 87.5%

Student Graduation Rate by 8th Grade Risk Factor

Zero Risk Fac-tors (N=2,633)

One Risk Factor (N= 476)

Two Risk Factors (N = 273)

0%

20%

40%

60%

80%

100%

84%

43%

15%

Students Entering 9th Grade with At Least One Risk Factor

All S

tude

nts

Fem

ale

Male

Chine

se

Latin

o

Afric

an A

mer

ican

White

Filip

ino

Other

Asia

n/PI

All O

ther

0%

10%

20%

30%

40%

50%

60%

22% 20%25%

6%

39%

53%

19% 19%14%

19%

Questions for Policy and Practice

• What role can school staff (principals, teachers, counselors) and non-school staff (parents, external partners) play in assisting or monitoring these students?

• Given the differences in school populations across high schools, do schools need to adopt new strategies?

• What resources could help schools effectively assist these students?

What Happened?

• Students are progressing through high school

• Schools, partners & district created interventions

• Confidence that students have services they need

• Families, DCYF, and CBOs are working in partnership

• Now investigating identifying students even earlier

Key Takeaways

Key Takeaways

• Focusing on questions raised by community partners supports solutions that communities can put to work—in policy and practice.

• Regular and iterative exchanges throughout the research process generate actionable knowledge

• Working in deep partnership with communities forges relationships that extend beyond the life of a study

• Much of the work is as good as your data

Thank you for joining us today!

www.gardnercenter.stanford.edu@gardnercenter