This article was downloaded by: [Portland State University], [Carrie Furrer]On: 07 August 2012, At: 09:06Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Education for Students Placedat Risk (JESPAR)Publication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/hjsp20

Getting Them There, Keeping ThemThere: Benefits of an Extended SchoolDay Program for High School StudentsCarrie J. Furrer a , Linda Magnuson b & Joseph W. Suggs ca Portland State Universityb Multnomah County Department of Human Servicesc Portland Public School District

Version of record first published: 06 Aug 2012

To cite this article: Carrie J. Furrer, Linda Magnuson & Joseph W. Suggs (2012): Getting Them There,Keeping Them There: Benefits of an Extended School Day Program for High School Students, Journalof Education for Students Placed at Risk (JESPAR), 17:3, 149-164

To link to this article: http://dx.doi.org/10.1080/10824669.2012.695920

PLEASE SCROLL DOWN FOR ARTICLE

Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden.

The publisher does not give any warranty express or implied or make any representationthat the contents will be complete or accurate or up to date. The accuracy of anyinstructions, formulae, and drug doses should be independently verified with primarysources. The publisher shall not be liable for any loss, actions, claims, proceedings,demand, or costs or damages whatsoever or howsoever caused arising directly orindirectly in connection with or arising out of the use of this material.

Getting Them There, Keeping Them There: Benefitsof an Extended School Day Program

for High School Students

Carrie J. Furrer

Portland State University

Linda Magnuson

Multnomah County Department of Human Services

Joseph W. Suggs

Portland Public School District

Over a decade of research has demonstrated the positive effects of extended school day programs on

various elementary and middle school student outcomes, both in the short and long term. The

efficacy of extended school day programs in promoting academic outcomes among high school

students is less well understood. This study contributes to the existing literature by examining school

attendance, credit attainment, and standardized reading and math scores in a group of students at risk

of academic failure who participated in extended school day programming. The study compared their

outcomes to those of a group of demographically similar students who did not participate in the

program. The extended school day program is provided within a full-service Schools Uniting

Neighborhoods (SUN) Community School (CS) in the Portland, Oregon metropolitan area. Results

suggest an advantage for SUN students in terms of better school attendance and earning credits

toward graduation, but not in terms of standardized test scores. Implications for future research

and extended school day policy are discussed.

The hours immediately after school are a time of both risk and opportunity for unsupervised

adolescents. In terms of risk, many youths are without adult supervision during the hours after

school. Nationally, in 59% of two-parent families, both parents work full time, and in 70% of

single-parent families, the parent works full time (Bureau of Labor Statistics, 2011). Lack of

supervision increases the likelihood that youths will engage in bullying, substance use, fighting,

and carrying a weapon (e.g., Gage, Overpeck, Nansel, & Kogan, 2005), and therefore the poten-

tial for involvement with the juvenile justice system. Not surprisingly, violent crimes by

juveniles occur most often between the hours of 3 pm and 6 pm (OJJDP, 2010).

In terms of opportunity, there is evidence that students who attend structured activities and

have access to positive adult role models during out-of-school-time (OST) show more positive

Correspondence should be addressed to Linda Magnuson, Department of County Human Services, SUN Service

System and Community Services, 421 SW Oak Street, Portland, OR 97204. E-mail: linda.magnuson@multco.us

Journal of Education for Students Placed at Risk, 17: 149–164, 2012

Copyright # Taylor & Francis Group, LLC

ISSN: 1082-4669 print=1532-7671 online

DOI: 10.1080/10824669.2012.695920

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

adjustment in a variety of life domains (Bartko & Eccles, 2003; Chung, 2000; Fredericks &

Eccles, 2006; Gottfredson, Gerstenblith, Soule, Womer, & Lu, 2004; Jordan & Nettles, 2000;

Mahoney, 2000; National Research Council and the Institute of Medicine, 2002). Structured

extended school day programs may serve as positive developmental contexts for youths—set-

tings in which youths have the potential to build academic, social, and emotion regulation skills

(Junge, Manglallan, & Raskauskas, 2003; Lerner, 2005; Roth & Brooks-Gunn, 2003; Vandell,

Pierce, & Dadisman, 2005). Increasing supports and positive opportunities for youths has been

linked to improved developmental outcomes at the end of high school and long-term adult out-

comes including economic self-sufficiency (Gambone, Klem, & Connell, 2002).

Structured extended school day activities (e.g., organized sports, arts activities, youth organi-

zations, positive youth development programs, and tutoring) vary a great deal. Some activities

are single service (e.g., athletics) and others address multiple life domains. Recently, youth

development advocates have argued that coordinated, community-based OST services can better

serve students and their families by providing a more integrated network of support (Connell,

Gambone, & Smith, 2000; Wimer, Post, & Little, 2004). In the case of community schools, pub-

lic schools can act as a hub for integrating academics and community supports and services,

thereby serving students, families, and the community as a whole. Extended school day

programs within community schools may benefit from the partnerships and support networks

created by the community schools model (Blank, Melaville, & Shah, 2003).

Of particular interest for this study are community schools. The Coalition for Community

Schools Web site defines community schools as:

Both a place and a set of partnerships between the school and other community resources. Its

integrated focus on academics, health and social services, youth and community development and

community engagement leads to improved student learning, stronger families and healthier com-

munities. Schools become centers of the community and are open to everyone—all day, every

day, evenings and weekends. (Coalition for Community Schools, 2012)

Over a decade of research has shown that well-implemented community schools offer

students engaging opportunities for social and academic development in a safe and supportive

environment during before- and after-school hours. For example, in several meta-analytic

reviews of experimental and quasi-experimental studies of extended school day programs, stu-

dents have been shown to achieve better academic and social outcomes than their peers who

were not exposed to such programming (Afterschool Alliance, 2011a; Lauer, Akiba, Wilkerson,

Apthorp, Snow, & Martin-Glenn, 2004; Lauer, Akiba, Wilkerson, Apthorp, Snow, &

Martin-Green, 2006; Redd, Cochran, Hair, & Moore, 2002; Zief, Lauver, & Maynard, 2006).

Most of the work done investigating the academic benefits of extended school day programs,

especially in a community school setting, has focused on elementary and middle school students.

The high school youth population is notoriously more difficult to engage in OST programming,

especially if those students are at risk of academic failure (Afterschool Alliance, 2009b; Kauh,

2010). Moreover, older youth are less often targeted for OST programming because there is less

need for child care, and because of the perception that such programming is not appropriate for

an older age group (Afterschool Alliance, 2009a). Even less is known about the efficacy of

extended school day programs in promoting a graduation trajectory for high school students

(Barr, Birmingham, Fornal, Klein, & Piha, 2006). The purpose of this study was to evaluate

150 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

academic outcomes for a group of academically at-risk high school students who participated

in an extended school day program compared to a demographically similar group of

non-participating students.

THREE BASIC REQUIREMENTS FOR ACADEMIC SUCCESS

Existing research on high school programs, for the most part, has focused on students’ fulfill-

ment of three basic requirements for academic success: show up for school, make progress in

class, and master grade-level content. This study thus focuses on three key academic outcomes:

attendance, credits earned, and standardized achievement test scores.

Attendance

Extended school day programs promote school engagement by affording students the

opportunity to form positive relationships with other students and adults in a safe, structured

environment focused on both academic improvement and creative and fun activities

(Anderson-Butcher, 2010; National Research Council, 2002). One indicator of school engage-

ment is attendance, or willingness to come to school each day (Sinclair, Christenson, Lehr, &

Anderson, 2003). Some researchers have found that participation in extended high school day

services contributes to more frequent attendance at school even after accounting for demo-

graphics and previous attendance rates (Goerge, Cusick, Wasserman, & Gladden, 2007; Reisner,

White, Russell, & Birmingham, 2004). Among high school students, participation in after-school

programming has been linked to less decline in attendance than that of students who were unsu-

pervised after school (Birmingham & White, 2005). However, the studies’ results are inconsist-

ent. For example, the Department of Youth and Community Development Out-of-School-Time

Initiative reported no differences in attendance between participants and a matched comparison

group of high school youth (Russell, Mielke, & Reisner, 2009). Thus, the extent to which

extended school day programs promote school attendance, and the program features responsible

for more favorable attendance, remain open questions.

Credits Earned

If students attend school, they are exposed to instruction and therefore have a better chance of

learning material and passing their classes, a necessary condition for graduation. Moreover,

some extended school day programs specifically offer credit recovery services beyond seat time

in a classroom setting (e.g., summer classes, evening classes, online instruction), which offer

flexible options for struggling students and perhaps promote school engagement among youth

via a more personalized learning opportunity (Afterschool Alliance, 2007). Some evidence indi-

cates that extended school day participants earn more credits (and are less likely to fail classes),

even after accounting for demographic and previous academic performance variables (Goerge

et al., 2007; Reisner et al., 2004). However, not all studies have shown this result. For example,

Myers and Schirm (1997) found that participation in Upward Bound had a positive effect on

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 151

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

credits earned for high-risk students but not low-risk students, and the program had no effect on

grade point average.

Standardized Achievement Test Scores

Benchmarks for standardized reading and math tests vary from state to state, but generally mea-

sure grade-level academic achievement. Some research suggests that the OST learning context

can give students, especially those who feel marginalized or otherwise find it difficult to engage

in a regular school day (e.g., students at risk of academic failure), opportunities to interact with

learning materials and teachers in a different way (Fusco, 2008). At least one study has shown

that participation in expanded high school day services contributes to higher scores in reading

and on math tests (Reisner et al., 2004), but other studies have reported that OST programs have

little effect on achievement (e.g., Myers & Schirm, 1997).

Taken as a whole, there is a paucity of research on the efficacy of extended high school day

programs in promoting academic outcomes. The research that has been done has produced

mixed results in terms of attendance, credits earned, and standardized achievement scores. This

study contributes to the existing literature by examining these academic outcomes in a group of

students at risk of academic failure who participated in an extended high school day program and

comparing their outcomes to a group of demographically similar youth who did not participate in

the program.

SCHOOLS UNITING NEIGHBORHOODS (SUN) COMMUNITY SCHOOLS

The structured extended school day programming in this study is a component of SUN Com-

munity Schools (CS). SUN CS System has been operating throughout the Portland, Oregon

metropolitan area since 1999 and currently oversees 64 different SUN Community elementary,

middle, and high school sites. In fiscal year 2009–2010, four nonprofit agencies acted as lead

agencies and provided on-site services at four different SUN sites. Service providers work clo-

sely with school principals and teaching staff to meet the unique needs of each group of students

within a set of standards regarding who is to be served and what types of services are to be

provided.

SUN CS targets students at academic risk. For example, a high number of students (80% to

82%) at the four high schools included in this study were eligible for free and reduced-price

meals (an indicator of poverty and a criterion for how schools are selected to become community

schools). Students living in poverty are at risk of dropping out and other types of academic dif-

ficulties (Cataldi, Laird, & Ramani, 2009). In addition, although providers can serve a broad

range of students and families both from the school site and surrounding community, they are

expected to recruit students struggling with academic performance and who are not on track

to graduate with their peers, and to tailor interventions to their individual needs.

In terms of the type of services provided, the SUN service standards are based on best prac-

tices found in high-quality OST programs: (a) alignment with the school day, (b) goal setting

and intentional programming, (c) family and community connections, (d) positive youth

development, and (e) program evaluation (Afterschool Alliance, 2011b).

152 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

Alignment with the School Day

SUN CS at area high schools collaborate extensively with school personnel, including principals

and teachers, who are also involved in the hiring of site coordinators. They also manage

extended-day services ensuring that one-third of the activities offered for students are academi-

cally focused; at the high schools, these include homework help and credit recovery services.

Homework help can involve one-on-one tutoring or adult monitored study halls. Credit recovery

classes are most often offered online so that students can work at their own pace, focusing on

what they need to learn. These online classes are monitored by certified instructors who offer

one-on-one help when needed. During the summer, some of the high schools offer full classes

for credit taught by certified instructors. Consistency between school day and OST personnel

and curriculum aligned with the school day have been shown to promote academic achievement

(Afterschool Alliance, 2011b; Chung, 2000).

Goal Setting and Intentional Programming

Another best practice supported by research involves goal setting and intentional programming

(Afterschool Alliance, 2011b; Chung, 2000; Little, Wimer, & Weiss, 2008). SUN site coordina-

tors are required to create an annual plan based on their individual schools’ needs. Plans describe

the steps that each school and partner organization will take to strengthen: (a) student achieve-

ment, (b) family involvement, (c) community and business involvement, and (d) collaboration

among the partners. Annual plans also describe how coordinators intend to reach target goals

set across the SUN CS System, which include sustained participation (the number of students

who attend at least 30 days of SUN annually), the amount of weekly programming, student

academic achievement scores, and student attendance rates.

Family and Community Connections

A strong family and community connection is an important component of high quality extended

school day programs (Afterschool Alliance, 2011b; Chung, 2000; Hall & Gruber, 2007; Little

et al., 2008). In line with this best practice, SUN site coordinators actively engage family mem-

bers in community events (at least 3 events annually), classes, and advisory committees, and refer

families to antipoverty services aligned with SUN CS. Examples of community events include

culturally-specific events such as Latino Parent Night and Somali Family Gathering. They also

may focus on skills and activities such as a Summer Survival Kit Party, Pumpkin Carving,

and a Gift-Making Party. Adult classes are typically English as a second language, but also

include art, cooking, recreation, tax preparation, supporting student learning, and computers.

Positive Youth Development

Another attribute of high-quality extended school day programs is that they provide safe,

interesting, and engaging learning opportunities using principles from positive youth develop-

ment (Afterschool Alliance, 2011b; Chung, 2000; Hall & Gruber, 2007). SUN students are

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 153

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

encouraged to participate in advisory committees and other leadership activities. For example,

one of the SUN CS high schools uses a local organization to teach Latino students leadership

skills. When students achieve proficiency, they get an opportunity to mentor elementary students

at nearby schools. In addition, each high school offers students a time to socialize during a

nutritionally balanced dinner served at the end of the extended school day.

Program Evaluation

Finally, high-quality extended school day programs have ongoing program evaluation efforts

(Afterschool Alliance, 2011b; Chung, 2000; Hall & Gruber, 2007). Each SUN site receives

an annual program evaluation report from Multnomah County SUN Service System. For

SUN community high schools, the report includes information tracked by each school district,

including Oregon Department of Education achievement test scores, school attendance rates,

credits earned, and demographic and risk factor information collected by program staff. Site

coordinators, in consultation with their supervisors, principals, and the site advisory committee,

are encouraged to use the data to improve the quality of services. The information is used to

critically evaluate services provided during the school year and develop an annual plan for

the following year.

HYPOTHESES

Research suggests that a high-quality extended school day program (i.e., one that adheres to best

practices) that provides a sufficient amount of service should support academic attainment for its

participants. The purpose of this study is to examine the academic benefits of the SUN CS

extended school day programming for high school students. We hypothesize that, compared

to a demographically similar group of high school students, SUN students who participated in

30 or more days of programming would have better attendance, would have earned more credits

over the course of a school year, and would have received better test scores in both reading and

math.

METHODS

Participant Selection

Selection criteria for SUN students included (a) enrollment in 9th to 12th grade as of October 1,

2008, (b) attending one of 12 high schools or high school academies, and (c) participation in

SUN school services on at least 30 days during the school year1 (M¼ 48 days, SD¼ 20.3,

ranged from 30 to 139 days). The final sample included 441 SUN participants across four

SUN sites.

1For all 21st Century Community Learning Center-funded programs, such as SUN, the US Department of Education

defines a regular attendee as having attended 30 or more days of programming (Ozuna, Clara, & Larsen, 2011). This

guideline was used for the purposes of identifying regular attendees for the SUN program.

154 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

Propensity score matching (see Rosenbaum & Rubin, 1983) was employed to select a demo-

graphically similar comparison group of students from the larger pool (n¼ 3,774) of 9th through

12th grade students attending the same schools in the district. The probability that a student did

or did not participate in SUN was estimated using a logistic regression equation including the

following characteristics: (a) gender, (b) grade, (c) school attended, (d) English language learner

status (yes=no), (e) free or reduced-price meal status (yes=no), (f) special education status (yes=no), (g) race=ethnicity, and (h) achievement (8th grade Oregon Assessment of Knowledge and

Skills reading score2). The estimated probability is the propensity score, or likelihood that a

student would participate in SUN given the characteristics just listed.

After calculating propensity scores for each student, a stratification matching approach, which

has been shown to remove 90% of selection bias due to the covariates included in the model

(Rosenbaum & Rubin, 1984), was used to select a comparison sample. Propensity scores were

split into quintiles and each student was assigned to one of five quintile bins. Comparison stu-

dents were randomly selected within each bin, without replacement, to exceed by 10–15% the

number of SUN students within each bin. The number of comparison students exceeded the

number of SUN students to ensure that the comparison group was proportional to the SUN group

across all 12 schools included in the study. Selecting a comparison group without replacement

within each quintile bin allowed for each SUN student to be matched only with the control

students with a propensity score within the quintile range, as opposed to nearest neighbor match-

ing, which can result in larger differences in propensity scores (Becker & Ichino, 2002).

The final step was to evaluate the quality of the stratification match. Once the number of SUN

and comparison students was proportional across bins, each characteristic was examined for dif-

ferences between the two conditions (using contingency tables and adjusted standardized resi-

duals or t-test). None of these tests was statistically significant. To ensure that propensity

scores were evenly distributed for both conditions (SUN and comparison) at different levels

of the matching variables, each characteristic was examined according to condition and bin

(2� 5 interaction using logistic regression or analysis of variance [ANOVA]). Only two of

31 tests were statistically significant, which is no more than you would expect to see by chance

(approximately 5%). Thus, the resulting sample of 499 comparison students was deemed rela-

tively balanced across all eight characteristics and therefore adequately matched to the SUN

sample. Table 1 shows the distribution of characteristics for SUN and comparison students.

Measures

The school district provided data from its student information system for the following

outcomes.

Attendance. Attendance data were available in both 2007–2008 and 2008–2009 school

years for 419 (95%) SUN students and 482 (97%) comparison-group students. Attendance rates

for each school year were calculated by dividing the total number of days present (summed across

2Eighth-grade Oregon Assessment of Knowledge and Skills (OAKS) math scores were not used in the propensity

matching process because they were strongly correlated with OAKS reading scores, r¼ .62, and did not predict a sig-

nificant amount of variation in SUN program participation over and above reading scores.

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 155

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

all students) by the total number of days enrolled (number of days present plus the number of days

absent summed across all students). This calculation method weights individual student attend-

ance rates by the number of days they were enrolled (i.e., students enrolled fewer days have a

smaller effect on the overall attendance rate than students enrolled for a full school year).

Credits. The credits outcome was a count of the total number of high school credits earned

between September 1, 2007 and August 31, 2008 (2007–2008 school year) and September 1,

2008 and August 31, 2009 (2008–2009 school year). High school credit hours for both the

2007–2008 and the 2008–2009 school years were available from 432 (98%) SUN students

and 471 (94%) comparison-group students.

Standardized test scores. The Oregon Assessment of Knowledge and Skills (OAKS) was

used to assess reading and literature and math skills. The OAKS online testing system assesses

students’ mastery of Oregon content standards for 3rd through 8th and 10th grade students.

Grade-level achievement standards include cut scores to determine which students have not

met, met, or exceeded standards in each subject. Scores were available for 128 (97%)

tenth-grade SUN students and 134 (84%) tenth-grade comparison group students, and did not

include those who took different achievement tests for nonnative-English speakers or special

education students taking alternate assessments. All of these students also had OAKS scores

in math and reading and literature from their 8th-grade year, which were used as a covariate

in certain analyses. OAKS scores are reported on a Rasch Unit (RIT) scale. RIT scores are based

on one-parameter item response theory and are equal interval scores between 150 and 300

points.

TABLE 1

Demographic Characteristics of Schools Uniting Neighborhoods (SUN) Versus Comparison-Group Youth

SUN Program Youth Comparison Group

Characteristic % n % n

Gender

Male 48 211 46 231

Female 52 230 54 268

Race=Ethnicity

American Indian=Alaskan Native 2 10 2 10

Asian=Pacific Islander 10 44 10 49

African American=Black 43 191 42 208

Hispanic=Latino 18 77 18 91

White 27 117 28 138

Unknown 1 2 1 3

Grade

9th 45 198 40 198

10th 30 133 32 160

11th 15 65 20 99

12th 10 45 8 42

English language learner 19 85 17 84

Special education (IEP) 20 87 18 90

Eligible for free=reduced-price lunch 82 361 79 396

Total 441 499

156 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

RESULTS

Baseline Descriptive Statistics

At baseline (2007–2008), SUN students had significantly higher weighted average attendance

than comparison students (92.8% vs. 88.8%, respectively), t(900)¼ 6.24, p< .001. SUN and

comparison students had earned a similar number of credits at baseline (average for both groups

was 5.7 credits), t(914)¼�0.09, ns, and they also did not differ significantly on 8th-grade

OAKS math and reading scores (average math scores were 229.4 and 230.1 and average reading

scores were 227.7 and 228.4, respectively). To adjust outcome estimates for potential baseline

differences, these values were used as control variables in their respective analyses.

Attendance Rates

It was hypothesized that youth participating in SUN programming would have better attendance

rates in 2008–2009 than a group of demographically similar comparison youth. Percentages as a

dependent variable posed three analytical challenges. First, the distribution within each group

was nonnormal and bound by 0 and 1, thereby violating an assumption of analytical techniques

typically used to analyze mean differences (e.g., t-test, ANOVA). Tobit analysis adjusts for

‘‘ceiling effects’’ when dependent variables are heavily clustered in the tails of the distribution

(i.e., attendance is clustered toward 1.0 or 100%) by calculating model parameters based on the

assumption that predicted values cannot exceed the upper (or lower) bound of the distribution

(Wang, Zhang, McArdle, & Salthouse, 2008).

Second, there were inconsistent standard errors within groups, thereby violating the assump-

tion of homoskedasticity. Accordingly, the model employed a MLR estimator, or a robust

maximum likelihood estimation that produces valid standard error estimates even when variables

have non-normal distributions (Muthen & Muthen, 2004).

Third, attendance percentages were calculated using number of enrolled days as the denomi-

nator. A student present for 18 of 20 days would have the same attendance percentage as a stu-

dent present for 153 of 170 days (the length of the school year). To address this issue, the model

was weighted by total number of enrolled days to increase the influence of students who were

enrolled for a larger proportion of the school year.

A Tobit model was constructed in Mplus 4.0 to test for differences in the average percent of

enrolled days that students were present at school. The model also included previous attendance

(percent of enrolled days present in 2007–2008) as a control variable (see Table 2 for results).

SUN students had a significantly higher average attendance rate than that of the comparison stu-

dents (89.8% and 85.6%, respectively). The effect size (r2) was small, with SUN participation

predicting 2.6% of the variation in 2008–09 attendance. A difference of 4.2 percentage points

corresponds to approximately an additional 2.4 days spent in school.

Course Credits

SUN students were expected to have earned more credits during the 2008–09 school year than

comparison students. To test this hypothesis, a generalized linear model was constructed in

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 157

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

SPSS 19.0 using a robust estimator (to address heteroskedasticity, as previously described) and

two covariates, grade and previous achievement (eighth-grade OAKS reading score). As

expected, SUN students earned an average of 6.5 credits, compared to the 5.3 credits earned

by comparison students (see Table 2 for results). The effect size, a difference of 1.2 credits,

was medium as measured by Cohen’s d, calculated using estimated means and the pooled, unad-

justed standard deviation, d¼ .57. Moreover, students are expected to earn six credits per year

(for a total of 24 credits to graduate), suggesting that SUN students, on average, were on track

with their credits, whereas comparison students were not.

Math and Reading Achievement

With the additional academic support that SUN students received, it was expected that they

would have higher math and reading achievement scores than comparison students. This hypoth-

esis was tested for 10th graders (the only group with OAKS scores in 2008–2009) using an

ANCOVA in SPSS 19.0. The model controlled for eighth-grade achievement scores in the same

subject. SUN students did not score statistically different than comparison students in math and

reading. Average test scores differed by less than two points for SUN and comparison students

(see Table 2).

DISCUSSION

Results from this study suggest that SUN students had somewhat higher attendance rates than

students not participating in SUN, after controlling for the previous year’s attendance. In

addition, SUN students earned more credits toward graduation. These positive outcomes,

however, did not include higher standardized test scores. This research provides additional evi-

dence that staying in and progressing in school is associated with attending an extended school

day program for high school students.

TABLE 2

Outcome Estimates for Schools Uniting Neighborhoods Versus Comparison Youth

SUN Program Comparison Group

Outcome M n M n Difference Significance Test

Attendance 2008–2009 89.8% 419 85.6% 482 4.2% t¼ 5.38��

Credits earned 6.5 432 5.3 471 1.2 credits Wald X2¼ 75.59���

10th grade OAKS reading score 232.9 108 233.5 134 �0.6 points F¼ 0.48

10th grade OAKS math score 231.3 109 229.9 133 1.4 points F¼ 2.63

Notes. OAKS¼Oregon Assessment of Knowledge and Skills. Estimates for attendance were weighted by number of

days enrolled and were adjusted for attendance from the previous year. Estimates for credits earned were adjusted for

grade and previous achievement as measured by 8th grade OAKS reading scores. Estimates for OAKS math and reading

scores were adjusted for 8th grade achievement in that particular subject.�p< .05. ��p< .01. ���p< .001.

158 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

SUN students averaged 16 more days of school (absent 6 less days and enrolled 10 more

days) than comparison students. In addition, SUN students had higher attendance rates, miss-

ing an average of 10% of enrolled days compared to a 15% rate for comparison students.

These findings are consistent with other research suggesting that extended school day pro-

grams have a positive effect on school attendance (e.g., Birmingham & White, 2005; Goerge

et al., 2007).

The longer enrollment of SUN students than comparison students suggests that SUN students

experienced fewer disruptions in enrollment than comparison students. Reasons for disruptions

in enrollment include unexcused absences for 10 or more days in a row, family crises, and mov-

ing to a different school district. It should be noted that SUN students also had significantly

higher baseline attendance than comparison students. Mobility could be a fundamental differ-

ence between the SUN and comparison students driving the difference in attendance rather than

program participation, but it is also plausible that participation in SUN motivates students to

come to school and avoid enrollment disruptions.

Despite these encouraging findings for attendance, note that the average SUN student was

chronically absent, missing at least 10% of school days (see Allensworth & Easton, 2007, for

the impact of chronic absence on academic performance). Thus, a great deal of work remains

to engage high school students (especially those at risk of academic failure), not only for

extended school day programs, but for districts, schools, and teachers.

In terms of academic outcomes, the biggest difference between the SUN and comparison stu-

dents was the number of credits earned over the course of the 2008–2009 school year. Annual

credit gain is imperative to ensure timely graduation (Allensworth & Easton, 2005). The average

SUN student was on track to graduate, having earned 6.5 credits, whereas the average compari-

son student was not, having earned less than 6 credits. This finding is consistent with other

research on high school students who participated in extended school day programs (e.g.,

Goerge et al., 2007; Porowski & Passa, 2011; Reisner et al., 2004).

Credit recovery is part of SUN programming and perhaps gives students an advantage

over nonprogram students through flexible options for learning. The degree to which SUN

students participated in specific credit recovery services is, however, unknown. Credit recov-

ery services may be at least in part responsible for the higher number of credits earned by

SUN students. Alternatively, SUN academic programming may have promoted school

engagement, encouraged homework completion, and therefore led to more credits earned.

Indeed, Allensworth and Easton (2007) found that passing courses is largely determined

by attendance.

This study showed no statistically significant difference between SUN and comparison stu-

dents on OAKS math and reading tests, suggesting that the program did not promote improve-

ment in performance on standardized tests. SUN programming ensures that one-third of the

activities offered for students are academically focused, although the nature of these activities

differs from site to site (e.g., homework, one-on-one tutoring, and monitored study halls). If

standardized test scores are to improve, SUN academic activities may need to be focused on

teaching the content standards and test-taking skills necessary to reach OAKS grade-level

benchmarks.

Although the SUN students, on average, were on track in terms of credit attainment, they did

not demonstrate mastery of the content in which the credit was earned (based on standardized

test scores). One explanation for this finding is that the Portland Public School District awards

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 159

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

credit for D grades, which means that credits can be earned in the absence of mastery. Another

possible explanation is that the extent to which state learning standards are being taught differs

from school to school and teacher to teacher, especially in high school. If SUN academic activi-

ties focus on homework completion and the material being covered in class is not consistently

linked to state learning standards, it is understandable that participation in the program will not

have a strong effect on standardized test scores. SUN may also have helped to retain students

who had fallen behind on grade level content, which could account for the lack of improvement

on test scores from 8th to 10th grade.

Standardized test performance is not a proximal outcome given the type of intervention

received. Kane (2004) argued that change, especially after 1 year of intervention, may be more

likely for proximal outcomes such as homework completion and teacher perceptions of student

engagement. Both of these outcomes are markers of academic performance and, themselves,

could be mediators of improved standardized test scores in the longer term.

Limitations

The findings reported in this study must be understood in light of several methodological limitations.

First, the study included students from four different SUN sites. Although each site is expected to

adhere to basic service requirements (e.g., one-third of the activities offered for students are academi-

cally focused), the programming is not necessarily consistent at each site, nor is there consistency in

the combination of services received by each participant. The lack of consistent programming likely

introduced variation in the observed outcomes for which the study did not methodologically account,

largely due to having only four sites. Having a larger number of sites (which becomes the unit of

analysis) enables researchers to employ more sophisticated analytical techniques (e.g., hierarchical

linear modeling) to evaluate directly the variation accounted for by site.

Relatedly, students selected for this study had participated in SUN services for 30 or more

days, but it is impossible to know how students spent their time during the extended day and

at which time of year they participated in certain activities. Some students may have spent all

of their academically-focused time in homework club, whereas other students may have spent

all of their academic time receiving one-on-one tutoring. Moreover, students may have partici-

pated in SUN intensively at the end of the school year (i.e., after the standardized testing window

was closed) and therefore would not have received the full benefit of the program when academ-

ic outcomes were tested. Indeed, type, extent, and timing of participation in extended school

day academic activities have been linked to gains on standardized tests, credit attainment, and

attendance (Prenovost, 2001).

Another related service issue is that comparison group students may have participated in other

types of extended school day programming or educational options offered through the school

district. Comparison group students may also have been SUN participants during elementary

or middle school. Compared to a group of students who received no other type of intervention

or support, one would expect to see even larger positive effects for SUN programming on attend-

ance, credit attainment, and possibly even standardized test scores.

A second limitation of this study is a lack of program quality measures. To date, SUN does

not have a comprehensive quality assessment system for its various sites to assess, for example,

staff practices, program climate, and activity characteristics. Staff practices, such as effective

160 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

group management and positive adult support, are related to program engagement, learning, and

retention at least among elementary and middle school students (Grossman, Campbell & Raley,

2007). Program quality and fidelity to program models are likely key mediators of the relation-

ship between program participation and academic outcomes, an area ripe for future research.

Third, other systematic differences between SUN and comparison students may not have

been captured during the matching process. Propensity score matching is only as good as the

extent to which variables included in the model predict participation in a program. If students

participated in SUN for ‘‘unmeasured’’ reasons (e.g., greater motivation to access credit recov-

ery opportunities), these variables were not taken into account during analysis and, therefore,

may be at least partially responsible for the outcomes reported.

Implications for Practice and Policy

Perhaps the most important policy implication of this research is the importance of making avail-

able credit recovery opportunities, especially for ninth and 10th grade students. Credit attainment

is key for timely graduation (Allensworth & Easton, 2005). Extended school day offerings, such

as alternative learning formats (e.g., online courses), summer credit recovery opportunities, and

evening classes, could provide students options that support graduation.

In addition to providing alternative learning options for students outside of the school day,

extended school day programs may work to promote students’ engagement with and connection

to school (Anderson-Butcher, 2010; National Research Council, 2002), thereby providing a

potentially important intervention lever for students at risk of poor attendance and drop-out.

Indeed, school attendance is a necessary (albeit not sufficient) condition for credit attainment

and eventually graduation.

In 2008–2009, failing to pass the OAKS tests did not have serious consequences for students.

Starting with the class of 2012, students who do not pass OAKS tests (or another equivalent

approved standardized test) will not receive a standard diploma. With increasing attention placed

on standardized test performance, extended school day programs may offer alternative learning

opportunities that some students need to create new pathways for graduation. However, many

extended school day programs have not shown improvements in their students’ standardized test

scores, especially among high school students, suggesting that programs need to focus on aligning

curricula with the school day (especially programs that enhance rather than duplicate school day

curricula) and providing instruction and support around standardized test-taking. Moreover, if high

school curricula are not clearly linked to the grade-level standards being tested, it is hard to imagine

that participation in extended-day programs would have a direct effect on standardized test scores.

Finally, how well students fare in high school has been linked to their functioning as young

adults (Gambone et al., 2002). Extended school day programming that facilitates positive change

in high school performance has long-term positive community effects, which is possibly the

most compelling reason for promoting and expanding such programs.

REFERENCES

Afterschool Alliance. (2007). New England After 3 PM: Spotlight on New Hampshire. Washington, DC: Nellie Mae

Education Foundation. Retrieved from http://www.afterschoolalliance.org/documents/NH_Spotlight_Report.pdf

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 161

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

Afterschool Alliance. (2009a). Afterschool innovations in brief: Focusing on older youth (Afterschool Alert Issue Brief,

No. 36, December 2009). Retrieved from http://www.afterschoolalliance.org/documents/Afterschool_In_Brief_09_

FINAL.pdf

Afterschool Alliance. (2009b). Afterschool: The challenges of recruiting and retaining older youth (Afterschool Alert

Issue Brief, No. 37, April 2009). Retrieved from http://www.afterschoolalliance.org/issue_briefs/Recruitmentan-

dRetention%20Brief%2037%20FINAL.pdf

Afterschool Alliance. (2011a). Evaluations backgrounder: A summary of formal evaluations of afterschool programs’

impact on academics, behavior, safety and family life (Afterschool Research Report, May 2011). Retrieved from

http://www.afterschoolalliance.org/documents/evaluationsBackgrounder2011.pdf

Afterschool Alliance. (2011b). Quality afterschool: Helping programs achieve it and strengthening policies to support it

(Afterschool Alert Issue Brief, No. 47, March 2011). Retrieved from http://www.afterschoolalliance.org/issue_

briefs/issue_quality_47.pdf

Allensworth, E. M., & Easton, J. Q. (2007). What matters for staying on-track and graduating in Chicago public high

schools: A Close look at course grades, failures, and attendance in the freshman year. Chicago, IL: University of

Chicago, Consortium of Chicago School Research. Retrieved from http://www.eric.ed.gov/PDFS/ED498350.pdf

Allensworth, E. M., & Easton, J. Q. (2005). The ontrack indicator as a predictor of high school graduation. Chicago, IL:University of Chicago, Consortium of Chicago School Research. Retrieved from http://ccsr.uchicago.edu/sites/

default/files/publications/p78.pdf

Anderson-Butcher, D. (2010). The promise of afterschool programs for promoting school connectedness. PreventionResearcher, 17, 11–14.

Barr, S., Birmingham, J., Fornal, J., Klein, R., & Piha, S. (2006). Three high school after-school initiatives: Lessons

learned. New Directions for Youth Development, 111, 67–79. doi: 10.1002=yd.183

Bartko, W. T., & Eccles, J. S. (2003). Adolescent participation in structured and unstructured activities: A

person-oriented analysis. Journal of Youth and Adolescence, 32, 233–241. doi: 10.1023=A:1023056425648

Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2,

358–377.

Birmingham, J., & White, R. N. (2005). Promoting positive youth development for high school students after school:Services and outcomes for high school youth in TASC programs. Washington, DC: Policy Studies Associates.

Retrieved from http://www.tascorp.org/content/document/detail/1447

Blank, M. J., Melaville, A., & Shah, B. P. (2003). Making the difference: Research and practice in community schools.Washington, DC: Coalition for Community Schools. Retrieved from http://www.communityschools.org/assets/1/

Page/CCSFullReport.pdf

Bureau of Labor Statistics U.S. Department of Labor. (2011). News release. March 24, 2011. USDL-11–0396. Retrieved

from http://www.bls.gov/news.release/archives/famee_03242011.pdf

Cataldi, E. F., Laird, J., & Ramani, A. K. (2009). High school dropout and completion rates in the United States: 2007.

Washington, DC: Institute of Education Sciences’ National Center for Education Statistics. Retrieved from http://

nces.ed.gov/pubs2009/2009064.pdf

Chung, A.-M. (2000). Working for children and families: Safe and smart after-school programs. Washington, DC: US

Department of Education. Retrieved from http://www.eric.ed.gov/PDFS/ED441579.pdf

Coalition for Community Schools. (2012). What is a community school? Retrieved from http://www.communityschools.

org/aboutschools/what_is_a_community_school.aspx

Connell, J. P., Gambone, M. A., & Smith, T. J. (2000). Youth development in community settings: Challenges to our fieldand our approach. Philadelphia, PA: Public=Private Ventures. Retrieved from http://www.ydsi.org/ydsi/pdf/

publication_01.pdf

Fredericks, J. A., & Eccles, J. S. (2006). Is extracurricular participation associated with beneficial outcomes? Concurrent

and longitudinal relations. Developmental Psychology, 42, 698–713. doi: 10.1037=0012–1649.42.4.698

Fusco, D. (2008). School vs. afterschool: A study of equity in supporting children’s development. Journal of Research in

Childhood Education, 22, 391–403.

Gage, J. C., Overpeck, M. D., Nansel, T. R., & Kogan, M. D. (2005). Peer activity in the evenings and participation

in aggressive and problem behaviors. Journal of Adolescent Health, 37, 517–521. doi: 10.1016=jadohealth.2004.12.012

Gambone, M. A., Klem, A. M., & Connell, J. P. (2002). Finding out what matters for youth: Testing key links in a com-

munity action framework for youth development. Philadelphia, PA: Youth Development Strategies, Inc., & Institute

for Research and Reform in Education. Retrieved from http://www.ydsi.org/ydsi/pdf/WhatMatters.pdf

162 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

Goerge, R., Cusick, G. R., Wasserman, M., & Gladden, R. M. (2007). After-school programs and academic impact: Astudy of Chicago’s after school matters (Chapin Hall Center for Children: Brief #112). Retrieved from http://

www.chapinhall.org/sites/default/files/publications/ChapinHallDocument(2)_0.pdf

Gottfredson, D. C., Gerstenblith, S. A., Soule, D. A., Womer, S. C., & Lu, S. (2004). Do after school programs reduce

delinquency? Prevention Science, 5, 253–266. doi: 10.1023=B:PREV.0000045359.41696.02Grossman, J., Campbell, M., & Raley, B. (2007). Quality time after school: What instructors can do to enhance learning.

Philadelphia, PA: Public=Private Ventures. Retrieved from http://www.ppv.org/ppv/publications/assets/213_

publication.pdf

Hall, G., & Gruber, D. (2007). Making the case: Quality afterschool programs matter (The Massachusetts Special Com-

mission on After School and Out of School Time, Issue Brief Fall 2007). Retrieved from http://www.niost.org/pdf/

MSC_brief_Hall_Gruber.pdf

Jordan, W. J., & Nettles, S. M. (2000). How students invest their time outside of school: Effects on school-related

outcomes. Social Psychology of Education, 3, 217–243. doi: 10.1023=A:1009655611694

Junge, S. K., Manglallan, S., & Raskauskas, J. (2003). Building life schools through afterschool participation in experi-

ential and cooperative learning. Child Study Journal, 33, 165–174.

Kane, T. J. (2004, January). The impact of after-school programs: Interpreting the results of four recent evaluations(William T. Grant Foundation Working Paper). New York: William T. Grant Foundation. Retrieved from http://

www.pasesetter.com/reframe/documents/ThomasKane.pdf

Kauh, T. J. (2010). Retaining and recruiting older African American and Hispanic boys in after-school programs.New York, NY: Public=Private Ventures. Retrieved from http://www.ppv.org/ppv/publications/assets/323_

publication.pdf

Lauer, P. A., Akiba, M., Wilkerson, S. B., Apthorp, H. S., Snow, D., & Martin-Glenn, M. (2004). The effectiveness of

out-of-school-time strategies in assisting low-achieving students in reading and mathematics: A research synthesis.Washington, DC: Institute of Education Sciences, Department of Education. Retrieved from http://www.mcrel.org/

pdf/SchoolImprovementReform/5032RR_RSOSTeffectiveness.pdf

Lauer, P. A., Akiba, M., Wilkerson, S. B., Apthorp, H. S., Snow, D., & Martin-Green, M. (2006). Out-of-school-time

programs: A meta-analysis of effects for at-risk students. Review of Educational Research, 76, 275–313. doi:10.3102=00346543076002275

Lerner, R. M. (2005). Promoting positive youth development: Theoretical and empirical bases. White paper prepared for

the Workshop on the Science of Adolescent Health and Development, National Research Council=Institute of

Medicine. Washington, DC: National Academies of Science. Retrieved from http://ase.tufts.edu/iaryd/documents/

pubPromotingPositive.pdf

Little, P., Wimer, C., &Weiss, H. (2008). After school programs in the 21st century: Their potential and what it takes to achieve

it. Cambridge, MA: Harvard Family Research Project. Retrieved from http://www.hfrp.org/ publications-resources=

browse-our-publications=after-school-programs-in-the-21st-century-their-potential-and-what-it-takes-to-achieve-it

Mahoney, J. L. (2000). School extracurricular activity participation as a moderator in the development of antisocial

patterns. Child Development, 71, 502–516. doi: 10.1111=1467-8624.00160

Muthen, L. K., & Muthen, B. O. (2004). Mplus user’s guide. Third edition. Los Angeles, CA: Muthen & Muthen.

Myers, D., & Schirm, A. (1997). The short-term impacts of Upward Bound: An interim report. Washington, DC:

Mathematica Policy Research.

National Research Council and the Institute of Medicine. (2002). Community programs to promote youth development

(report brief). Washington, DC: National Academy Press.

Office of Juvenile Justice and Delinquency Prvention. (2010). Statistical Briefing Book. Retrieved from http://ojjdp.ncjrs.gov/

ojstatbb/offenders/qa03301.asp?qaDate=2008

Ozuna, R., Clara, T., & Larsen, K. (2011). 21st Century community Learning centers database manual. Sunnyside, WA:

RGI Corporation.

Porowski, A., & Passa, A. (2011). The effect of Communities in Schools on high school dropout and graduation rates:

Results from a multiyear, school-level quasi-experimental study. Journal of Education for Students Placed at Risk,

16, 24–37. doi: 10.1080=10824669.2011.545977Prenovost, J. K. E. (2001). A first-year evaluation of after school learning programs in four urban middle schools in the

Santa Ana Unified School District. Irvine, CA: Author.

BENEFITS OF AN EXTENDED SCHOOL DAY PROGRAM 163

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2

Redd, Z., Cochran, S., Hair, E., & Moore, K. (2002). Academic achievement programs and youth development: A syn-thesis. Washington, DC: Child Trends. Retrieved from http://www.childtrends.org/what_works/clarkwww/acadach/

acadachrpt.pdf

Reisner, E. R., White, R. N., Russell, C. A., & Birmingham, J. (2004). Building quality, scale and effectiveness in

after-school programs. Washington, DC: Policy Studies Associates. Retrieved from http://tascorp.org/content/

document/detail/1445/

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal

effects. Biometrika, 70, 41–55. doi: 10.2307=2335942Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the

propensity score. Journal of the American Statistical Association, 79, 516–524. doi:10.2307=2288398

Roth, J. L., & Brooks-Gunn, J. (2003). What exactly is a youth development program? Answers from research and

practice. Applied Developmental Science, 7, 94–111. doi: 10.1177=0272431604273211Russell, C. A., Mielke, M. B., & Reisner, E. R. (2009). Evidence of program quality and youth outcomes in the DYCD

out-of-school-time initiative: Report on the initiative’s first three years. New York, NY: Wallace Foundation.

Retrieved from http://www.wallacefoundation.org/knowledge-center/after-school/coordinating-after-school-

resources/Pages/Evidence-of-Program-Quality-and-Youth-Outcomes.aspx

Sinclair, M. F., Christenson, S. L., Lehr, C. A., & Anderson, A. R. (2003). Facilitating student engagement: Lessons

learned from Check & Connect longitudinal studies. California School Psychologist, 8, 29–41. Retrieved from

http://education.ucsb.edu/school-psychology/CSP-Journal/PDF/CSP2003(volume_8).pdf

Vandell, D. W., Pierce, K. M., & Dadisman, K. (2005). Out-of-school settings as a developmental context for children

and youth. In R. V. Kail (Ed.), Advances in child development and behavior (Vol. 33, pp. 43–77). New York:

Academic.

Wang, L., Zhang, Z., McArdle, J. J., & Salthouse, T. A. (2008). Investigating ceiling effects in longitudinal data analysis.

Multivariate Behavioral Research, 43, 476–496. doi: 10.1080=00273170802285941

Wimer, C., Post, M., & Little, P. (2004). Leveraging resources to promote positive school-CBO relationships. Afterschool

Matters, 3, 15–23. Retrieved from http://www.robertbownefoundation.org/pdf_files/afterschoolmatters_

spring04.pdf

Zief, S. G., Lauver, S., & Maynard, R. (2006). The impacts of after-school programs on student outcomes: A systematic

review for the Campbell Collaboration. Campbell Systematic Reviews 2006:3, 1–51. doi: 10.4073=csr.2006.3

164 FURRER, MAGNUSON, SUGGS

Dow

nloa

ded

by [P

ortla

nd S

tate

Uni

vers

ity],

[Car

rie F

urre

r] a

t 09:

06 0

7 A

ugus

t 201

2