top-rated free essay

article

By trixienagpala Oct 10, 2013 8554 Words
Journal of Research in Rural Education, 2006, 21(3)

School Adjustment and the Academic Success of
Rural African American Early Adolescents in the Deep South
Thomas W. Farmer, Matthew J. Irvin, Jana H. Thompson,
Bryan C. Hutchins, and Man-Chi Leung
University of North Carolina at Chapel Hill

Citation: Farmer, T. W., Irvin, M. J., Thompson, J. H., Hutchins, B. C., & Leung, M.-C. (2006, April 5). School adjustment and the academic success of rural African American early adolescents in the Deep South. Journal of Research in Rural Education, 21(3). Retrieved [date] from http://jrre.psu.edu/articles /21-3.pdf

This study examined the relationship between end-of-year grades and the academic, behavioral, and social characteristics of rural African American youth. Participants included 392 7th and 8th grade students from 2 rural middle schools in the south. Participants were African American and were from 2 communities that have child poverty rates exceeding 50% for public school students. Girls were more likely to have positive characteristics than boys. Academic, behavioral, and social difficulties were linked to low end-of-year grades, and positive characteristics were linked to high grades. Implications for supporting low-achieving African American students from low-resource communities are discussed.

Educational difficulties are often pronounced in rural
school districts that serve high proportions of minority youth from impoverished backgrounds (Johnson & Strange, 2005;
Khattri, Riley, & Kane, 1997; Save the Children, 2002). In
response to the special needs of low-income rural districts, the U.S. Department of Education established the Rural and
Low-Income School Program (RLISP). To qualify for this
program a district must be designated locale code 6, 7, or 8, and at least 20% of the school-age population must be from
families living below the federal poverty level. The RLISP
serves more than 2.5 million students, over 80% of RLISP
eligible schools are located in the south, and about 500,000 students in the RLISP are African American youth who live
in southern states (Farmer et al., 2006). Although they make up a substantial portion of the RLISP student population,
few studies have focused on the academic performance and
related school adjustment factors of rural African American
youth from low-resource communities. The extant data suggest that there is a significant need for more research with this population.
This study was supported by grants U81CCU416369 and
R49CCR419824 from the Centers for Disease Control and Prevention to Thomas W. Farmer (Principal Investigator) and in part by Institute of Education Sciences grant R305A04056. The views expressed in this article do not represent the granting agencies. Correspondence concerning this article should be addressed to Thomas W. Farmer, National Research Center on Rural Education Support, C.B. #8115, University of North Carolina, Chapel Hill, NC 27599-8115. (tfarmer@email.unc.edu)

In a randomly selected sample of RLISP schools, 30%
failed to make adequate yearly progress on No Child Left
Behind (NCLB) criteria (Farmer et al., 2006). In over 40%
of the failing schools, African American and impoverished
youth did not pass end-of-grade standardized tests. These
findings are consistent with other studies that suggest impoverished rural African American youth may be at risk for achievement problems, school failure, school dropout, and
low educational and occupational attainment (Farmer et al.,
2004; Jeffries, 1993; Kao, & Tienda, 1998; Khattri et al.,
1997; Kim, Brody, & Murry, 2003; McLoyd, 1990, 1998;
Smith, Beaulieu, & Israel, 1992; Valdez, 2000). While this
work indicates that rural African American youth from impoverished communities are at increased risk for academic difficulties, very little is known about school adjustment
variables that distinguish between low- and high-achieving
students from such backgrounds. Information along these
lines may help clarify factors that promote academic success in this population and may support the development of interventions that enhance the school adjustment and academic achievement of rural low-income African American students. Accordingly, the purpose of this study was to explore school adjustments factors that differentiate low- and highachieving rural African American students from two lowincome communities in a southern state. Building from a developmental science perspective

of competence and risk, we were interested in examining
whether teacher, peer, and parent assessments of rural African American students’ academic, behavioral, and social adjustment in school were related to their end-of-year school

2

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

grades. According to the developmental science framework,
youth develop as an integrated whole rather than as discrete components (i.e., physical, cognitive, behavioral, social).
This means that rather than having a singular influence,
various developmental factors (e.g., academic, behavioral,
social) operate together as a correlated system and impact
each other as they contribute to patterns of adjustment
(Cairns, 2000; Magnusson & Cairns, 1996; Roeser, Eccles,
& Sameroff, 2000). Consistent with this view, adolescents
who go on to experience poor adult outcomes tend to have
adjustment difficulties across multiple domains (Bergman
& Magnusson, 1997; Cicchetti & Rogosch, 2002), and adolescents from disadvantaged backgrounds who have positive adult outcomes tend to demonstrate multiple competencies
(Luthar, Cicchetti, & Becker, 2000; Masten & Coatsworth,
1998; Roeser & Peck, 2003).
For example, youth who are viewed by teachers as
academically competent are more likely to get along well
with peers, engage in prosocial behavior and productive
classroom activities, and associate with peers who support
academic achievement (Cairns & Cairns, 1994; Wentzel,
Barry, & Caldwell, 2004). In contrast, youth who have
academic difficulties are more likely to be aggressive and
disruptive, to be unengaged in class, and to experience a
range of social difficulties (Farmer et al., 2004; Khattri et al., 1997; Kindermann, 1993). Further, poor educational
outcomes such as school failure, school dropout, and reduced rates of postsecondary education have been linked to correlated packages of academic, behavioral, and social risks in early adolescence (Cairns, Cairns, & Neckerman, 1989;

Farmer et al., 2003). Collectively, such findings suggest that behavioral and social competence may support students’ academic achievement, while behavioral and social difficulties may contribute to poor academic performance.

Relatively little research has examined the relationships
among academic, behavioral, and social factors in rural
African American youth from impoverished backgrounds.
Such work is especially needed during early adolescence
because this is a period when the development of youth is
highly malleable and sensitive to both positive and negative influences (Eccles, 1998; Huber & Garten, 1993). Also, boys and girls tend to have different patterns of adjustment during adolescence (Rojewski, Wicklein, & Schell, 1995). There is

a need to examine whether there are gender differences in
the relationship between school adjustment and academic
performance in rural African American youth. If this is the
case, it would suggest a need for gender-specific interventions to support the academic engagement and achievement of this population.
Because individuals are viewed as developing as an
integrated whole, the developmental science perspective
implies the use of person-centered analyses to identify
subsets of individuals who are similar to each other on key
developmental dimensions (Bergman, 2000; Cairns & Rod-

kin, 1998; Magnusson, 2003). Such analyses are necessary
because there may be nonlinear relationships between subtypes of individuals and developmental constructs of interest that are masked by traditional variable-oriented approaches
(Cairns, 1986; Magnusson, 1988). To address this issue, the
present study categorizes participants into high-, moderate-, and low-achieving subsets for both boys and girls.
During the current climate of NCLB, standardized
tests have become a primary construct for assessing student
achievement. While standardized scores may provide a good
index of student achievement for the purposes of accountability (Hanushek & Raymond, 2005; Smith, 2005), other measures of achievement may be more directly linked to
students’ academic development and their subsequent educational outcomes (Becker & Luthar, 2002). For example, school grades and ratings of academic competence by
teachers and peers tend to differentiate between successful
educational outcomes (e.g., school attendance, participating in advanced courses, completing high school, and attending and completing postsecondary training and educational programs) and low educational attainment (e.g., not passing

a grade level, not completing high school, not attending or
completing postsecondary programs) (Cairns & Cairns,
1994; Feldhusen & Jarwan, 1995; Luthar & Ansary, 2005;
Ripple & Luthar, 2000; Roeser & Peck, 2003; Smokowski,
Mann, Reynolds, & Fraser, 2004; Zheng, Saunders, Shelley,
& Whalen, 2002). In fact, recent studies suggest that school grades may yield a more complete picture of academic
performance for racial and ethnic minorities (Hoffman &
Lowitzki, 2005; Kao & Thompson, 2003). For the present
study, we used end-of-year school grades to classify students as low, moderate, and high on academic achievement and
we used teacher, peer, and parent assessments as indicators
of students’ academic competence.
By examining the relationship between end-of-year
grades and other indices of school adjustment or competence
(i.e., academic, behavioral, and social factors), we may
be able to clarify factors that support or impede academic
achievement. This is especially relevant for rural school districts that serve high percentages of low-achieving students and students from low-income backgrounds (Cadwallader
et al., 2002). The goal of this investigation was to identify factors associated with academic success in rural African
American middle school students from two high-poverty
rural communities in a southern state. While such an analysis cannot indicate causality, it can provide insight into whether particular factors may be part of a constellation of variables that contribute to students’ adjustment. Such information

is necessary groundwork for longitudinal and experimental-control investigations that can more directly assess the impact of specific factors. Accordingly, the current study
was exploratory and was guided by two general aims. The
first aim was to explore possible gender differences in the relationship between school grades and school adjustment.

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS
The second aim was to explore the degree to which high,
moderate, and low end-of-year grades distinguish among
rural African American students on measures of school
adjustment. Information generated from this study may
help to establish school-based interventions to support the
academic achievement of rural African American youth from
impoverished communities.
Method
As part of an ongoing longitudinal study of the developmental pathways of rural African American youth, this study involved a multimethod survey design. Teacher, peer, and
parent reports were used to assess participants’ adjustment within the academic, behavioral, and social domains. School
record data were used to assess academic achievement.
Participants
This investigation took place in two rural counties in
a southern state in the Deep South. Throughout the South,
there are large pockets of rural communities that serve high concentrations of African American youth from impoverished backgrounds (Johnson & Strange, 2005; Murry & Brody, 1999; Save the Children, 2002). Traditionally, this

has been an understudied population (Brody, Murry, Kim,
& Brown, 2002; Cadwallader et al., 2002). Further, rural
schools that serve high concentrations of impoverished and
African American youth are less likely to make adequate
yearly progress on NCLB criteria (Farmer et al., 2006).
Accordingly, a primary goal of this study was to expand
the knowledge base regarding the factors associated with
the educational adjustment of youth from rural schools that
serve very high concentrations of impoverished African
American youth. The two participating communities in this
study were selected as research sites because they reflect the challenges experienced by many rural school districts in the South. Over half of the public school students in these communities live in households below the national poverty level, and over 99% of public school students are African American

(even though 30% of the population in these communities is
European American). The two communities are identified as
locale code 7 by the U.S. Census, and each has a population
density of less than 17 persons per square mile.
Participants were recruited from all seventh- and
eighth-grade classrooms in two middle schools. Parental
consent and participant assent were obtained from 80% of
the students in these schools. The sample comprised 392
students (250 girls and 142 boys), all of whom were African
American. Ninety-six percent of participants received free or reduced-price lunch. This sample reflected the public school attendance of the two counties and the general population
in each of the participating schools.

3

Procedures
Data were collected in the spring when teachers and
peers had had ample time to become familiar with the characteristics of participants. Students completed peer-report measures during the group administration of the student survey. Before the administration of this survey, participants were

assured their answers would be kept confidential, and they
were asked to cover their responses. In addition, students
were told they could stop participating at any time. During
the survey, an administrator read the instructions and questions aloud while scanning the room for potential problems. Additional administrators provided mobile monitoring and
assisted students as needed. During this time, teachers completed rating forms on participants. Students were given a school supply item for their participation, and teachers were paid for completing the rating forms. Grades were collected

from school records at the end of the school year.
Teacher-Report Measures
Interpersonal Competence Scale-Teacher (ICS-T).
Teachers completed the ICS-T for each participant in their
class. The ICS-T is an 18-item questionnaire consisting of
7-point Likert scales (Cairns, Leung, Gest, & Cairns, 1995). The ICS-T yields composite scores on several subscales,
and the following were used in the current investigation:
aggression (α = .82; composed of “always argues,” “gets in trouble,” and “always fights”), popularity (α = .86; composed of “popular with boys,” “popular with girls,” and “lots of friends”), academic (α = .71; composed of “good at math” and “good at spelling”), affiliative (α = .73; composed of “always smiles” and “always friendly”), and internalizing (α = .68; composed of “always sad,” “always worry,” and “very shy”). Three-week test-retest reliability coefficients are moderately high (i.e., .80-.92), and median test-retest

reliability across the factors is .81 for girls and .87 for boys. One-year coefficients are moderately strong (i.e., .40-.50) (Cairns, Leung, Gest, et al., 1995). The ICS-T has convergent validity with direct observation, student records (i.e., grades, discipline reports), and peer nomination measures (Cairns

& Cairns, 1994; Cairns, Leung, Buchanan, & Cairns, 1995;
Rodkin, Farmer, Pearl, & Van Acker, 2000). Composite factor scores are the unweighted average rating across items forming each subscale. Items are positively coded so that a
higher score reflects increased levels of the measured construct. For example, a high score on the popularity factor indicates a high level of popularity while a low score on the aggressive factor indicates a low level of aggression.

Classroom-adjustment scale. This measure focused
on students’ classroom adaptation (Farmer, Estell, Bishop, O’Neal, & Cairns, 2003). Using a 7-point Likert scale similar to the ICS-T, teachers rated students on the following items: “lots of problems paying attention,” “very hyperactive,”

4

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

“bullies peers, “manipulates friendships,” and “is a class leader.” As with the ICS-T, these ratings were positively
coded such that a higher score on a classroom-adjustment
item indicates a higher level on the designated attribute.
Teacher ratings of “very hyperactive” and “lots of problems paying attention” were strongly correlated (r = .50, p < .001). The average teacher rating of these items was
used as an index of teacher-reported instructional engagement (α = .67). Proactive and reactive aggression. Both proactive and
reactive aggression were the average of 3 items on a Likert
scale that ranged from 1 (applies often) to 3 (never applies) and were adapted from Dodge and Coie (1987). Proactive
aggression included the following items: “uses (or threatens to use) physical force in order to dominate other children,” “threatens or bullies others in order to get his/her way,” and “gets other children to gang up on a peer he/she does not

like.” Reactive aggression was comprised of the following
items: “when this child has been teased or threatened, he/she gets angry easily and strikes back,” “when a peer accidentally hurts this child (such as bumping into him/her), this child assumes that the peer meant to do it and then overreacts with anger and fighting,” and “this child always claims that other children are to blame in a fight and feels they started the whole trouble.” Ratings were reversed coded so that a

higher score reflected more of each type of aggression.

Seeks help. This person is always looking for help,
asks for help even before trying very hard.

Peer-Report Measures

Popular. Some kids are very popular with their
peers. That is, many classmates like to play with
them or do things with them.

Peer interpersonal assessments. Peer interpersonal assessments were used to determine classmates’ perceptions of peers’ social and behavioral characteristics. Students were asked to nominate, from free recall, up to three peers who

best fit descriptors for 16 items. They were told that they may nominate themselves and that they may nominate the
same persons for more than 1 item. The items were:
Cooperative. Here is someone who is really good
to have as part of your group, because this person
is agreeable and cooperates—pitches in, shares,
and gives everyone a turn.
Disruptive. This person has a way of upsetting everything when he or she gets into a group—doesn’t share and tries to get everyone to do things their
way.
Acts shy. This person acts very shy with other kids.
It’s hard to get to know this person.
Starts fights. This person starts fights. This person
says mean things to other kids or pushes them, or
hits them.

Leader. This person gets chosen by the others as
the leader. Other people like to have this person
in charge.
Athletic. This person is very good at many outdoor
games and sports.
Gets in trouble. This person doesn’t follow the
rules, doesn’t pay attention, and talks back to the
teacher.
Good student. This person makes good grades,
usually knows the right answer, and works hard
in class.
Cool. This person is really cool. Just about everybody in school knows this person. Sad. This person often seems sad.
Starts rumors. This person gossips and says things
about others. This person is good at causing people
to get mad at each other.

Picked on. This person is picked on by others.
Friendly. This person is usually friendly to others.
Bully. This person is always hurting or picking
on others.
Three-week test-retest reliability with individual items
ranged from .72-.93. These items are identical with, or similar to, peer assessments used by other investigators (e.g., Cantrell & Prinz, 1985; Coie, Dodge, & Coppotelli, 1982;
Masten, Morison, & Pellegrini, 1985). The total number of
nominations participants received on each peer-assessment
item was divided by the total number of possible nominators
(i.e., all participants in the school). Because the denominator was the total number of participants in each school, the resulting proportions were small. In order to make mean
differences clearer, these proportions were multiplied by
1000. A factor analysis of these 16 items yielded a four-factor solution consisting of aggression (α = .90; consists of “disruptive,” “starts fights,” “gets in trouble,” “starts rumors,” and “bully”), prosocial (α = .81; consists of “cooperative,”

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS
“good student,” and “friendly”), social prominence (α = .83; consists of “leader,” “athletic,” “cool,” and “popular”), and internalizing (α = .63; consists of “acts shy,” “seeks help,” “sad,” and “picked on”).

Social-network centrality. The Social Cognitive Mapping (SCM) procedure has been used extensively in research on school social networks and was employed in the current
study to obtain a measure of social-network centrality (e.g., Cairns & Cairns, 1994; Kinderman, 1993; Xie, Cairns, &
Cairns, 1999). For this measure, students were asked “Are
there some kids in your classroom who hang around together
a lot? Who are they?” Following the procedures developed
by Cairns and colleagues (e.g., Cairns, Leung, Buchanan,
et al., 1995), students were then instructed to list as many groups as they could think of in their grade. To ensure
reliability and validity, a 50% participation rate has been
established as the standard (Cairns, Leung, Buchanan, et al.). The participation rate for this study was consistent with
these guidelines. For the current study, the total number of times an individual student was named by peers was used
an indicator of an individual’s prominence or centrality in the social network.
Parent-Report Measures
Behavioral Emotional Rating Scale (BERS). The BERS
(Epstein & Sharma, 1998) is a parent report strength-based
assessment that includes a focus on students’ school functioning. This measure was completed via phone interviews with participants’ parent or guardian. The BERS consists
of 52 items on a 4-point scale that ranged from 0 (not at all like the child) to 3 (very much like the child). For the current investigation, only the school-functioning subscale (α = .86) was used. This scale consists of 9 items: “completes a task on first request,” “completes school tasks on time,” “completes homework regularly,” “pays attention in class,” “computes math problems at or above grade level,” “reads at or above grade level,” “studies for tests,” “attends school regularly,” and “uses note-taking and listening skills in school.”

End-of-Year Grades
Students’ end-of-year grades were obtained from school
records. Grades from English, math, science, social studies, and reading classes were used for the current study. Grades
were in the form of a percentage averaged across five classes. Some students (n = 40, 10.2%) were missing a grade in one
of the five classes. For these participants, the scores of the remaining four classes were used to obtain an average.
Data Reduction Procedures
A strength of this study was that it assessed school
adjustment with multiple measures and informants. While

5

redundant information on similar constructs can enhance
confidence in the findings, it can also lead to confusion. To facilitate clarity in interpretation, three distinct domains (academic, behavioral, social) were established to group
constructs in the analysis and presentation of the results.
Academic domain. Measures of the academic domain
were gathered from teachers, peers, and parents or guardians. Factors within these measures were identified as described
above in the description of the measures. These factors were further grouped into an academic competence and academic
orientation subcategory. Academic competence consisted of
the academic factor of the ICS-T and the peer-assessment
item of “good student.” Academic orientation was composed of the instructional engagement factor (“very hyperactive” and “lots of problems paying attention”) of the teacher assessment of classroom adjustment and parent reports of the school-functioning subscale of the BERS.

Behavioral domain. Measures of students’ behavior
were gathered from teachers, students, and peers. Assessments in this domain were grouped into the following subcategories: aggression, internalizing, and prosocial. Aggression. Teachers completed several measures

about aggressive behavior. These included the aggression
subscale of the ICS-T, the “bullies peers” and “manipulates friendships” items of the classroom-adjustment scale, and
the proactive and reactive aggression factors. Bivariate
correlations indicated that these teacher-reported indices
of aggressive behavior were highly related (rs = .37 to .80, p < .001). A principal components analysis indicated that all measures loaded on a single factor. Consequently, each variable was standardized, and the unweighted average across these measures was obtained. This factor, teacher-reported

aggression, was used in subsequent analyses. The aggression factor from peer assessments was used as an additional index of aggressive behavior.
Internalizing. The internalizing subscale on the ICS-T
provided a teacher report of this behavior. Likewise, the internalizing peer-assessment factor comprised a peer measure of this construct.
Prosocial. Prosocial behavior was assessed with both
teacher and peer reports. The affiliative subscale of the ICS-T was used to assess teachers’ perceptions of students’ prosocial behavior, and the prosocial factor of the peer-behavioral assessments was used to measure peers’ perceptions of their classmates prosocial behavior.

Social domain. Several measures of participants’ social
adjustment were available from various sources. These were
grouped into indices of perceived popularity and social position within the school social network. Perceived popularity. The popularity subscale from
the ICS-T was considered as a teacher-report measure
of this subcategory. The peer interpersonal assessment
social-prominence factor was also included as a peer-report
measure of perceived popularity.

6

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

Social position. Teacher ratings of “class leader” from
the classroom-adjustment scale and the corresponding peerbehavioral assessment item for “leader” were used as an index of social position. Also, participants’ social-network centrality (i.e., frequency of nominations to a peer group)

from the SCM procedure provided an additional measure
of social position.
Academic success. The aggregate of participants’ school
grades was used as a measure of academic success. Typically, participants were taught in five distinct content areas by five different teachers. The collective grade a participant receives yields a measure of how teachers’ generally view

her or his academic progress. Based on grade averages,
participants were designated as having low, moderate, and
high levels of academic grades. Students in the upper 20%
of the distribution of grade averages were designated as
having high academic grades, and those in the lower 20%
of the distribution were considered to have low academic
grades. Participants between the upper and lower 20% of the
distribution were deemed to have moderate grades. These
classifications were made within gender. Fifty girls were
designated as having low grades, 149 had moderate grades,
and 51 had high grades. Twenty-seven boys were classified
as having low grades, 86 had moderate grades, and 28 were
identified as having high grades.
Results
The results are presented in two sections. The first section examines gender differences in academic grades and on measures of academic, behavioral, and social adjustment. In the second section, the academic grade subgroups (i.e., levels of academic grades) are examined to identify

differences among the groups on measures within the academic, behavioral, and social domains. To address the second aim of this investigation, a
series of ANOVAs by levels of academic grades was conducted on each relevant measure. Significant omnibus F tests (α = .05) were followed by post hoc pairwise comparisons.
For some variables, the Levene statistic for the equality
of group variances was significant. Such violations of the
homogeneity of variance assumption are potentially more
problematic when groups have different sample sizes
(Howell, 1997). Under these circumstances, the more appropriate Welch statistic was examined. In all cases, an overall significant difference of the
Welch statistic reflected those of the F test. Further when the Levene statistic was significant, post hoc pairwise comparisons were completed with the use of the Dunnett’s T3 test that does not assume equal variances. Finally, to control the family-wise Type I error rate, a Bonferonni correction for the post hoc comparisons of the three levels of academic grades

was employed at the .05 level divided by 3. Consequently,

a post hoc comparison was deemed significant when the
p value was equal to or less than .0167.
Gender Differences
Table 1 shows the means of each measure by gender.
Academic grades. Girls had significantly higher academic grades than boys, F(1, 390) = 41.07, p < .001. Academic domain. Girls had significantly higher
academic competence on both teacher-reported and peerassessed measures, F(1, 390) = 26.06, p < .001 and F(1, 390) = 7.43, p = .007, respectively. Girls also were significantly higher on teacher- and parent-reported measures of academic

orientation, F(1, 387) = 12.54, p < .001 and F(1, 280) =
12.11, p = .001, respectively.
Behavioral domain. Boys had significantly higher
scores on teacher-reported and peer-assessed aggression
measures, F(1, 390) = 8.90, p = .003 and F(1, 390) = 9.99,
p = .002, respectively. There were no differences between
boys and girls on teacher-reported and peer-assessed measures of internalizing behavior. There was not a gender difference on teacher-reported prosocial behavior, but girls were, according to their peers, more prosocial than boys,

F(1, 390) = 16.13, p < .001.
Social domain. Teachers rated girls as more popular
than boys, F(1, 390) = 11.20, p = .001, but there was not a
gender difference on peer-assessed popularity. Girls were
higher on all measures of social position. Girls were more
likely to be viewed by teachers and peers as being leaders,
F(1, 390) = 7.81, p = .005 and F(1, 390) = 3.86, p = .05.
Girls also had higher social-network centrality than boys,
F(1, 390) = 18.50, p < .001.
Differences on Domains by Levels of Academic Grades
Tables 2-4 show the means on measures in each domain
by levels of academic grades.
Academic domain. There were differences on both
teacher-reported and peer-assessed measures of academic
competence by girls’ level of academic grades, F(2, 247) = 44.39, p < .001 and F(2, 247) = 32.77, p < .001, respectively. Post hoc tests revealed an identical pattern across these
measures. Girls with high academic grades had significantly higher adjustment on teacher-reported academic and peerassessed “good student” measures than those with low and moderate grades. Girls with moderate grades were higher

on both measures than those with low grades.
For boys, there were also differences on both teacherreported and peer-assessed measures of academic competence by levels of academic grades, F(2, 139) = 10.57, p < .001 and F(2, 139) = 10.22, p < .001, respectively.

Pairwise comparisons indicated that boys with high academic grades were higher on the teacher-reported academic

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS

7

Table 1
Means and Standard Deviations on Measures by Gender
Girls

Boys

M (SD)

M (SD)

Partial η2

77.78 (8.82)

71.93 (8.42)

.10

4.73 (1.66)

3.90 (1.34)

.06

10.08 (20.73)

4.88 (12.47)

.02

5.06 (1.64)

4.43 (1.72)

.03

2.54 (.43)

2.35 (.48)

.04

-.09 (.75)

.16 (.85)

.02

4.38 (7.36)

8.44 (17.84)

.03

2.97 (1.28)

2.98 (1.06)

4.55 (10.12)

4.80 (8.12)

5.43 (1.40)

5.32 (1.28)

9.50 (13.07)

4.70 (7.52)

.04

5.24 (1.41)

4.75 (1.34)

.03

6.08 (10.11)

7.97 (15.58)

4.05 (1.98)

3.49 (1.77)

.02

Peer-assessed leader

7.88 (15.98)

4.93 (10.70)

.01

Social-network centrality

12.32 (8.73)

8.57 (7.44)

.05

Measure
Academic grades
Grades
Academic competence
Teacher-reported academic
Peer-assessed “good student”
Academic orientation
Teacher-reported instructional engagement
Parent-reported school functioning
Aggressive behavior
Teacher-reported aggression
Peer-assessed aggression
Internalizing behavior
Teacher-reported internalizing
Peer-assessed internalizing
Prosocial behavior
Teacher-reported affiliative
Peer-assessed prosocial
Popularity
Teacher-reported popularity
Peer-assessed social prominence
Social position
Teacher-reported class leader

8

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

Table 2
Means and Standard Deviations on Academic Domain Measures by Levels of Academic Grades Levels of Academic Grades
Low

High

M (SD)

Measure

Moderate
M (SD)

M (SD)

Partial η2

Academic competence
Teacher-reported academic

3.41 (1.58)

4.71b (1.45)

6.09b,c (1.20)

.26

Boys

3.22 (1.11)

3.83 (1.25)

4.74b,c (1.40)

.13

Girlsa

1.82 (2.69)

6.57b (11.04)

28.44b,c (36.36)

.21

Boysa

Peer-assessed “good student”

Girls

2.48 (4.23)

2.67 (4.89)

13.66 (24.36)

.13

Academic orientation
Teacher-reported instructional
engagement

4.22 (1.70)

4.98b (1.59)

6.12b,c (1.11)

.14

Boys

3.43 (1.56)

4.54b (1.71)

5.07b (1.52)

.10

Girlsa

2.33 (.55)

2.54 (.37)

2.79b,c (.29)

.13

Boys

Parent-reported school functioning

Girlsa

2.07 (.50)

2.35b (.47)

2.63b,c (.33)

.14

Dunnett’s T3 used for post hoc comparisons. bSignificantly different from Low. cSignificantly different from Moderate.

a

measure than boys with low and moderate grades. However,
none of the pairwise comparisons on peer-assessed “good
student” reached significance.
There were differences for girls on both teacher- and
parent-reported academic orientation by levels of academic
grades, F(2, 245) = 19.73, p < .001 and F(2, 176) = 13.30,
p < .001, respectively. Post hoc tests revealed that girls with high academic grades were significantly higher on teacherreported instructional engagement and parent-reported school-functioning measures than those with low and moderate grades. In addition, girls with moderate grades were higher on teacher ratings of instructional engagement than

those with low grades.
Boys also had differences on teacher- and parentreported academic orientation by levels of academic grades, F(2, 138) = 7.39, p = .001 and F(2, 100) = 8.36, p < .001,
respectively. Post hoc tests revealed that boys with high and moderate academic grades were, according to teachers and
parents, significantly higher on instructional engagement and school functioning than those with low grades. In addition,
parents indicated that boys with high grades were higher on
school functioning than those with moderate grades.

Behavioral domain. There were differences for girls on
teacher-reported and peer-assessed measures of aggression
by levels of academic grades, F(2, 247) = 10.35, p < .001
and F(2, 247) = 7.28, p = .001, respectively. Post hoc tests revealed that on both of these measures girls with high academic grades were significantly less aggressive than those with low and moderate grades.

Boys also had differences on teacher-reported and
peer-assessed measures of aggression by levels of academic
grades, F(2, 139) = 5.69, p = .004 and F(2, 139) = 8.44,
p < .001, respectively. Post hoc tests revealed that on both measures boys with high academic grades were significantly
less aggressive than those with low grades.
Teacher-reported and peer-assessed measures of internalizing behavior differed by levels of academic grades, F(2, 247) = 13.68, p < .001 and F(2, 247) = 5.41, p = .005,
respectively. Post hoc tests revealed that on both of these
measures girls with high academic grades were significantly lower on internalizing behavior than those with moderate
grades. On the teacher-reported measure, girls with high
grades were also lower on internalizing behavior than girls
with low grades. Boys did not evidence any significant dif-

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS

9

Table 3
Means and Standard Deviations on Behavioral Domain Measures by Levels of Academic Grades Levels of Academic Grades
Low

High

M (SD)

Measure

Moderate
M (SD)

M (SD)

Partial η2

Aggressive behavior
Teacher-reported aggression

.14 (.78)

-.03 (.76)

-.48b,c (.53)

.08

Boysa

.62 (1.10)

.09 (.75)

-.07b (.73)

.08

Girlsa

6.95 (9.52)

4.49 (7.36)

1.51b,c (2.39)

.06

Boysa

Peer-assessed aggression

Girlsa

20.29 (28.18)

6.37 (14.49)

3.54b (7.33)

.11

.10

Internalizing behavior
Teacher-reported internalizing

3.28 (1.25)

3.13 (1.18)

2.18b,c (1.28)

Boys

2.91 (1.12)

3.04 (1.11)

2.87 (.85)

Girlsa

8.37 (19.32)

4.11 (6.14)

2.09c (3.29)

Boys

Peer-assessed internalizing

Girls

7.18 (8.62)

4.55 (8.64)

3.33 (5.36)

.04

Prosocial behavior
Teacher-reported affiliative

5.17 (1.54)

5.31 (1.36)

6.05b,c (1.21)

Boys

5.07 (1.33)

5.31 (1.27)

5.55 (1.25)

Girlsa

3.91 (3.77)

8.09b (10.38)

19.09b,c (19.66)

.15

Boysa

Peer-assessed prosocial

Girls

.05

2.65 (3.88)

3.58 (4.41)

9.90b (13.27)

.13

Dunnett’s T3 used for post hoc comparisons. bSignificantly different from Low. cSignificantly different from Moderate.

a

ferences on the measures of internalizing behavior by levels of academic grades.
Teacher-reported and peer-assessed prosocial behavior
also differed by academic grades for girls, F(2, 247) = 6.65, p = .002 and F(2, 247) = 22.52, p < .001, respectively. Post hoc tests indicated that girls with high academic grades
were significantly higher on teacher-reported affiliative
and peer-assessed prosocial factors than those with low and
moderate grades. In addition, girls with moderate grades
were, according to their peers, also more prosocial than
girls with low grades.
For boys, peer-assessed prosocial behavior differed by
academic grades, F(2, 139) = 10.01, p < .001. According

to peers, boys with high grades were more prosocial than
boys with low grades.
Social domain. Differences were apparent on teacherreported popularity by academic grades for girls, F(2, 247) = 8.21, p < .001, but not on the peer-assessed measure. Teachers rated girls with high academic grades as more popular than girls with low and moderate grades. There were not any

significant differences on teacher-reported or peer-assessed popularity by levels of academic grades for boys.
Girls also had differences on teacher-reported and peerassessed measures of social position, F(2, 247) = 24.78, p < .001 and F(2, 247) = 5.61, p = .004, respectively. On
both measures, girls with high and moderate grades were

10

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

Table 4
Means and Standard Deviations on Social Domain Measures by Levels of Academic Grades Levels of Academic Grades
Low

High

M (SD)

Measure

Moderate
M (SD)

M (SD)

Partial η2

.06

Popularity
Teacher-reported popularity

4.72 (1.41)

5.21 (1.40)

5.82b,c (1.24)

Boys

4.59 (1.37)

4.73 (1.33)

4.95 (1.39)

Girls

3.63 (3.26)

6.41 (10.38)

7.54 (13.11)

Boys

Peer-assessed social prominence

Girls

5.79 (4.52)

6.96 (14.10)

13.01 (23.77)

Social position
Teacher-reported class leader

4.01b (1.87)

5.37b,c (1.77)

.17

2.48 (1.70)

3.47b (1.61)

4.52b,c (1.77)

.13

Girlsa

3.91 (4.09)

7.12b (14.43)

13.97b (24.16)

.04

Boysa

3.21 (4.20)

3.49 (7.75)

10.78 (18.27)

.08

Girls

11.32 (9.13)

13.07 (9.32)

11.08 (6.05)

Boys

Social-network centrality

2.84 (1.69)

Boys
Peer-assessed leader

Girls

6.96 (5.14)

8.50 (7.73)

10.28 (8.18)

Dunnett’s T3 used for post hoc comparisons. bSignificantly different from Low. cSignificantly different from Moderate.

a

more likely to be viewed as leaders than were girls with low grades. In addition, teachers also rated girls with high grades as being more of a leader than girls with moderate grades.
Boys had differences on teacher-reported and peerassessed measures of leadership, F(2, 139) = 10.55, p < .001 and F(2, 139) = 5.83, p = .004. Post hoc tests revealed that teachers rated boys with high and moderate grades as more of a leader than boys with low grades. In addition, teachers also rated boys with high grades as being leaders than boys with

moderate grades. However, none of the pairwise comparisons on the peer-assessed measure reached significance. Discussion
The results of this study yield two important findings
for understanding intervention needs in rural schools serving high concentrations of African American early adolescents from low-resource communities. First, there may be

significant gender differences in the school adjustment of
students in such settings. Generally, girls appeared to have more positive characteristics than boys. They tended to have higher academic grades, higher teacher- and peer-reported
academic competence, higher teacher- and parent-reported
academic orientation, higher teacher- and peer-reported
leadership, higher peer-reported prosocial behavior, higher
teacher-reported popularity, and higher peer-reported
social-network centrality. Boys were higher on teacher- and
peer-assessed aggression. Second, the end-of-year grades of
rural African Americans from high-poverty communities
appear to be associated with their academic, behavioral, and social adjustment. Youth who had high end-of-year grades
were more likely to have positive academic, behavioral,
and social characteristics, while students who had low endof-year school grades were more likely to have negative characteristics.

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS
By reflecting a person-oriented approach that focuses
on subtypes of individuals rather than relationships among
variables (c.f., Bergman & Magnusson, 1997; Cairns &
Rodkin, 1998; Luthar, Cicchetti, & Becker, 2000; Roeser &
Peck, 2003), the current findings help to clarify factors that distinguish among rural African American early adolescents
from low-resource communities who are successful and
unsuccessful in school. Consistent with a developmental
science framework and the concept of correlated constraints
(Cairns & Cairns, 1994; Farmer, Quinn, Hussey, & Holahan,
2001), the present works suggests that academic, behavioral, and social factors may contribute to students’ end-of-year grades. The term contribute here does not mean cause. In
fact, current views of developmental science suggest that it is not productive to think in terms of causation in the sense that an outcome is produced by a preceding factor. Rather,
multiple factors at multiple levels (e.g., biophysical, cognitive, behavioral, social contextual) operate coactively within a system of bidirectional influence such that each dynamically influences the other as they collectively contribute to human functioning and adaptation (see Bergman, Cairns,

Nilsson, & Nystedt, 2000; Cairns, Bergman, & Kagan, 1998;
Cairns & Cairns, 1994; Cairns, Elder, & Costello, 1996;
Magnusson, 1988; Sameroff, 1983).
Our findings suggest that academic, behavioral, and
social adjustment are all part of a system of factors that are associated with students’ end-of-year grades. Other factors at the individual, family, and community levels are also
likely to contribute. However, academic, behavioral, and
social factors are all within the purview of schools. Thus,
these factors may be most accessible for school-based interventions aimed at enhancing the academic performance of students in rural schools that serve high concentrations
of African American early adolescents from low-resource
communities and backgrounds.
While African American youth from impoverished
rural communities in the South are only a small portion of
students who are served in rural schools, they do make up
a substantial group of students who need academic support
within the Rural Low-Income School Program (Farmer et
al., 2006). Further, throughout the South there are many
schools that serve high concentrations of such youth who
are struggling academically (Johnson & Strange, 2005; Save
the Children, 2002). Although the current sample does not
generalize to the universe of rural school and students, it
does reflect fairly common circumstances in many parts of
the South. Therefore, the present findings may help to serve as a guide for interventionists as they work to establish and evaluate programs to address the academic needs of early
adolescents from rural schools that serve high concentrations of impoverished African American students.
Accordingly, the findings of this study suggest that,
overall, rural African American early adolescent males

11

may be at higher risk of experiencing low end-of-year
school grades and associated school adjustment problems.
Thus, there may be a need for selected interventions that
specifically focus on supporting rural African American
males from low-resource communities. In addition, there is
a need for targeted interventions that focus on youth (both
boys and girls) who experience risks across the academic,
behavioral, and social domains. For youth who have multiple
risks, there is a need for interventions that systematically focus on the interrelations among these various factors and
that support positive change across these domains (Coie et
al., 1993; Farmer & Farmer, 2001). Finally, because of the
general risk of poverty and low resources, there is a need
for universal interventions that are aimed at enhancing
the general competence and academic achievement of all
students in rural schools that serve high concentrations of
impoverished African American youth.
The results of this study suggest that to improve the academic success of low-achieving youth in schools that serve high concentrations of rural African American early adolescents from low-resource backgrounds, there is a need to focus on behavioral and social factors as well as instructional practices. Teachers of struggling students must be prepared

to work with a range of problems that may contribute to poor academic performance in rural youth. This includes attention problems and hyperactivity, aggressive and disruptive behavior, bullying and victimization, and generally lower

rates of academic orientation and engagement. Efforts to
improve student achievement may be enhanced by professional development programs that bring together a focus on behavior management, classroom social dynamics, and the
instructional needs of students with learning difficulties. Because rural communities and schools have highly
diverse needs and populations (Johnson & Strange, 2005;
Sherwood, 2000), it is not appropriate to generalize the
current findings to the broader rural education community.
Nonetheless, the current findings are consistent with general research on developmental pathways and academic adjustment with a range of adolescents from rural, suburban, and urban settings both in the United States and internationally (see Cairns et al., 1998; Roeser & Peck, 2003). There is a

need for additional research that examines factors associated with the academic success of rural youth from settings that
are geographically, economically, ethnically, and culturally different. We expect that there will be findings that are similar to those in the current report. But we also expect there will be differences that reflect characteristics of the communities. Such differences are likely to demonstrate that there is no

one-size-fits-all in rural education research and that there is a need to establish rural intervention programs and policies that are responsive to the context of particular schools and communities. When such information is available, it is likely to enhance efforts for improving the educational outcomes

12

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

and academic achievement of rural youth in ways that are
consistent with their personal goals and aims and the needs
of their respective communities.
That said, this study has several limitations. First, it
focused exclusively on rural African American youth. It is
possible that our findings would not generalize to rural youth from other ethnic or racial backgrounds. Second, the two
communities involved in this study are highly impoverished.
Our results may not be representative of rural areas that have moderate or low rates of poverty. Third, the sample size for boys was relatively small as there was a lower participation rate for boys than girls. It is possible that the lack of significant differences for some findings (e.g., social relations) was due to inadequate statistical power. Fourth, we did not consider key developmental variables such as family structure, social capital, and community values and goals.

In summary, our results demonstrate the need to consider how academic, behavioral, and social factors may come together to contribute to the academic difficulties of lowachieving early adolescents in rural schools that serve high concentrations of impoverished African American youth.

While these findings are informative, more work in this
area is needed. Future investigations should examine factors that contribute to academic achievement in geographically,
ethnically, and economically different rural samples. Also,
there is a need to extend the focus to other factors such
as peer affiliations, parent involvement, school bonding,
social capital, and other community factors. Finally, there
is a need to develop and evaluate professional development
programs that prepare teachers to address the behavioral
and social factors that may contribute to the achievement
problems of students with learning difficulties. Such work
can be conducted within an experimental framework with a
longitudinal design to examine the impact of changing such
variables on the academic outcomes of students. This work
will make it possible to examine pathways of configurations and developmental trajectories and will enhance current
views of developmental contribution and causation.
References
Becker, B. E., & Luthar, S. S. (2002). Social-emotional
factors affecting achievement outcomes among disadvantaged students: Closing the achievement gap. Educational Psychologist, 37, 197-214.
Bergman, L. R. (2000). The application of a person-oriented
approach: Types and clusters. In L. R. Bergman, R. B.
Cairns, L.-G. Nilsson & L. Nystedt (Eds.), Developmental science and the holistic approach (pp. 137-154). Mahwah, NJ: Lawrence Erlbaum Associates.
Bergman, L. R., Cairns, R. B., Nilsson, L.-G., & Nystedt,
L. (2000). Developmental science and the holistic approach. Mahwah, NJ: Lawrence Erlbaum Associates.

Bergman, L. R., & Magnusson, D. (1997). A person-oriented
approach in research on developmental psychopathology. Development and Psychopathology, 9, 291-319. Brody, G. H., Murry, V. M., Kim, S., & Brown, A. C. (2002).
Longitudinal pathways to competence and psychological adjustment among African American children living in rural single parent households. Child Development,
73, 1505-1516.
Cadwallader, T. W., Farmer, T. W., Cairns, B. D., Leung, M.C., Clemmer, J. T., Gut, D. M., et al. (2002). The social relations of rural African American early adolescents
and proximal impact of the School Engagement Project.
Journal of School Psychology, 40, 213-237.
Cairns, R. B. (1986). Phenomena lost: Issues in the study
of development. In J. Valsiner (Ed.), The individual
subject and scientific psychology (pp. 97-111). New
York: Plenum Press.
Cairns, R. B. (2000). Developmental science: Three audacious implications. In L. R. Bergman, R. B. Cairns, L.-G. Nilsson, & L. Nystedt (Eds.), Developmental
science and the holistic approach (pp. 49-62). Mahwah,
NJ: Lawrence Erlbaum Associates.
Cairns, R. B., Bergman, L. R., & Kagan, J. (1998). Methods
and models for studying the individual. Thousand Oaks,
CA: Sage Publications, Inc.
Cairns, R. B., & Cairns, B. D. (1994). Lifelines and risks:
Pathways of youth in our time. New York: Harvester
Wheatsheaf.
Cairns, R. B., Cairns, B. D., & Neckerman, H. J. (1989).
Early school dropout: Configurations and determinants.
Child Development, 60, 1437-1452.
Cairns, R. B., Elder, G. H., Jr., & Costello, E. J. (1996).
Developmental science. New York: Cambridge University Press. Cairns, R. B., Leung, M.-C., Buchanan, L., & Cairns, B. D.
(1995). Friendships and social networks in childhood
and adolescence: Fluidity, reliability, and interrelations.
Child Development, 66, 1330-1345.
Cairns, R. B., Leung, M.-C., Gest, S. D., & Cairns, B. D.
(1995). A brief method for assessing social development: Structure, reliability, stability, and developmental validity of the interpersonal competence scale. Behaviour Research and Therapy, 33, 725-736. Cairns, R. B., & Rodkin, P. C. (1998). Phenomena regained:

From configurations to pathways. In R. B. Cairns, L. R.
Bergman, & J. Kagan (Eds.), Methods and models for
studying the individual (pp. 245-265). Thousand Oaks,
CA: Sage Publications, Inc.
Cantrell, V. L., & Prinz, R. J. (1985). Multiple perspectives of rejected, neglected, and accepted children: Relation
between sociometric status and behavioral characteristics. Journal of Consulting and Clinical Psychology, 53, 884-889.

SCHOOL ADJUSTMENT AND ACADEMIC SUCCESS
Cicchetti, D., & Rogosch, F. A. (2002). A developmental
psychopathology perspective on adolescence. Journal
of Consulting & Clinical Psychology, 70, 6-20.
Coie, J. D., Dodge, K. A., & Coppotelli, H. (1982). Dimensions and types of social status: A cross-age perspective. Developmental Psychology, 18, 557-570.
Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markman, H. J., et al. (1993). The science of prevention: A conceptual framework and some directions for a national research program. American Psychologist,

48, 1013-1022.
Dodge, K. A., & Coie, J. D. (1987). Social-informationprocessing factors in reactive and proactive aggression in children’s peer groups. Journal of Personality and
Social Psychology, 53, 1146-1158.
Eccles, J. S. (1998). Perceived control and the development
of academic motivation. Monographs of the Society for
Research in Child Development, 63, 221-231.
Epstein, M. H., & Sharma, J. (1998). Behavioral emotional
rating scale: Strength-based approach to assessment.
Austin, TX: PRO-ED.
Farmer, T. W., Estell, D. B., Bishop, J. L., O’Neal, K. K., & Cairns, B. D. (2003). Rejected bullies or popular leaders? The social relations of aggressive subtypes of rural African American early adolescents. Developmental

Psychology, 39, 992-1004.
Farmer, T. W., Estell, D., Leung, M.-C., Trott, H., Bishop,
J., & Cairns, B. D. (2003). Early adolescent peer affiliations, aggression, and school dropout: Aggressive and popular group types. Journal of School Psychology,
41, 217-232.
Farmer, T. W., & Farmer, E. M. Z. (2001). Developmental
science, systems of care, and prevention of emotional
and behavioral problems in youth. American Journal
of Orthopsychiatry, 71, 171-181.
Farmer, T. W., Leung, M.-C., Banks, J. B., Schaefer, V.,
Andrews, B., & Murray, R. M. (2006). Adequate yearly
progress in small rural schools and rural low-income
schools. Manuscript submitted for publication.
Farmer, T. W., Price, L. N., O’Neal, K. K., Leung, M.-C.,
Goforth, J. B., Cairns, B. D., et al. (2004). Exploring risk in early adolescent African-American youth. America
Journal of Community Psychology, 33, 51-59.
Farmer, T. W., Quinn, M., Hussey, W., & Holahan, T. (2001).
The development of disruptive behavior disorders and
correlated constraints: Implications for intervention.
Behavioral Disorders, 26, 117-130.
Feldhusen, J. F., & Jarwan, F. (1995). Predictors of academic success at state-supported residential schools for mathematics and science: A validity study. Educational
and Psychological Measurement, 55, 505-512.
Hanushek, E. A., & Raymond, M. E. (2005). Does school
accountability lead to improved student performance?

13

Journal of Policy Analysis and Management, 24, 297327.
Hoffman, J. L., & Lowitzki, K. E. (2005). Predicting college success with high school grades and test scores: Limitations for minority students. Review of Higher
Education, 28, 455-474.
Howell, D. C. (1997). Statistical methods for psychology.
Belmont, CA: Duxbury Press.
Huber, J. D., & Garten, T. (1993). Causes, consequences, and reduction of distress and burnout among rural middle
school students. Rural Educator, 14, 11-13.
Jeffries, R. B. (1993). To go or not to go: Rural African
American students’ perspectives about their education.
Journal of Negro Education, 62, 427-32.
Johnson, J., & Strange, M. (2005). Why rural matters 2005:
The facts about rural education in the 50 states. Arlington, VA: Rural School and Community Trust. Kao, G., & Thompson, J. S. (2003). Racial and ethnic stratification in educational achievement and attainment. Annual Review of Sociology, 29, 417-443.

Kao, G., & Tienda, M. (1998). Educational aspirations of
minority youth. American Journal of Education, 106,
349-384.
Khattri, N., Riley, K. W., & Kane, M. B. (1997). Students
at risk in poor, rural areas: A review of the research.
Journal of Research in Rural Education, 13, 79-100.
Kim, S., Brody, G. H., & Murry, V. M. (2003). Longitudinal
links between contextual risks, parenting, and youth
outcomes in rural African American families. Journal
of Black Psychology, 29, 359-377.
Kindermann, T. A. (1993). Natural peer groups as contexts
for individual development: The case of children’s
motivation in school. Developmental Psychology, 29,
970-977.
Luthar, S. S., & Ansary, N. S. (2005). Dimensions of
adolescent rebellion: Risks for academic failure among
high- and low-income youth. Development and Psychopathology, 17, 231-250. Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The construct of resilience: A critical evaluation and guidelines for future work. Child Development, 71, 543-562.

Magnusson, D. (1988). Individual development from an
interactional perspective. Mahwah, NJ: Lawrence
Erlbaum Associates.
Magnusson, D. (2003). The person approach: Concepts,
measurement models, and research strategy. New Directions for Child and Adolescent Development, 101, 3-23.
Magnusson, D., & Cairns, R. B. (1996). Developmental
science: Toward a unified framework. In R. B. Cairns,
G. H. Elder, Jr., & E. J. Costello (Eds.), Developmental
science (pp. 7-30). Cambridge, England: Cambridge
University Press.

14

FARMER, IRVIN, THOMPSON, HUTCHINS, AND LEUNG

Masten, A. S., & Coatsworth, J. D. (1998). The development
of competence in favorable and unfavorable environments: Lessons from research on successful children. American Psychologist, 53, 205-220.
Masten, A. S., Morison, P., & Pellegrini, D. S. (1985). A
revised class play method of peer assessment. Developmental Psychology, 21, 523-533. McLoyd, V. C. (1990). The impact of economic hardship
on black families and children: Psychological distress,
parenting, and socioemotional development. Child
Development, 61, 311-346.
McLoyd, V. C. (1998). Socioeconomic disadvantage and
child development. American Psychologist, 53, 185204.
Murry, V. M., & Brody, G. H. (1999). Self-regulation and
self-worth of black children reared in economically
stressed, rural, single mother-headed families: The
contribution of risk and protective factors. Journal of
Family Issues, 20, 458-484.
Ripple, C. H., & Luthar, S. S. (2000). Academic risk among
inner-city adolescents: The role of personal attributes.
Journal of School Psychology, 38, 277-298.
Rodkin, P., Farmer, T. W., Pearl, R., & Van Acker, R. (2000). The heterogeneity of popularity in boys: Antisocial and
prosocial configurations. Developmental Psychology,
36, 14-24.
Roeser, R. W., Eccles, J. S., & Sameroff, A. J. (2000). School as a context of early adolescents’ academic and socialemotional development: A summary of research findings. Elementary School Journal, 100, 443-471. Roeser, R. W., & Peck, S. C. (2003). Patterns and pathways

of educational achievement across adolescence: A holistic-developmental perspective. New Directions for Child and Adolescent Development, 101, 39-62.
Rojewski, J. W., Wicklein, R. C., & Schell, J. W. (1995).
Effects of gender and academic-risk behavior on the
career maturity of rural youth. Journal of Research in
Rural Education, 11, 92-104.

Sameroff, A. J. (1983). Developmental systems: Contexts
and evolution. In P. H. Mussen (Gen. Ed.) & W. Kessen
(Vol. Ed.), Handbook of child psychology: Vol. 1. History, theory, and methods (4th ed., pp. 237-294). New York: Wiley.
Save the Children. (2002). America’s forgotten children:
Child poverty in rural America. Retrieved May 13,
2004, from http://www.savethechildren.org/usa/report_download.asp Sherwood, T. (2000). Where has all the “rural” gone? Rural education research and current federal reform. Journal
of Research in Rural Education, 16, 159-167.
Smith, E. (2005). Raising standards in American schools:
The case of No Child Left Behind. Journal of Education Policy, 20, 507-524. Smith, M. H., Beaulieu, L. J., & Israel, G. D. (1992). Effects of human capital and social capital on dropping out of

high school in the south. Journal of Research in Rural
Education, 8, 75-87.
Smokowski, P. R., Mann, E. A., Reynolds, A. J., & Fraser, M. W. (2004). Childhood risk and protective factors and
late adolescent adjustment in inner city minority youth.
Children and Youth Services Review, 26, 63-91.
Valdez, J. R. (2000). Searching for a path out of poverty: Exploring the achievement idealogy of a rural community college. Adult Education Quarterly, 50, 212-230.
Wentzel, K. R., Barry, C. M., & Caldwell, K. A. (2004).
Friendships in the middle school: Influences on motivation and school adjustment. Journal of Educational Psychology, 96, 195-203.
Xie, H., Cairns, R. B., & Cairns, B. D. (1999). Social network centrality and social competence among innercity children. Journal of Emotional and Behavioral Disorders, 7, 147-155.
Zheng, J. L., Saunders, K. P., Shelley, M. C., II, & Whalen, D. F. (2002). Predictors of academic success for freshmen residence hall students. Journal of College Student Development, 43, 267-283.

Cite This Document

Related Documents

  • Exploration of a Journal Article

    ...Exploration of a Journal Article In Sociology Lanika K. Jones Professor Robert Hammes Introduction to Sociology May 4, 2013 The article I choose was by Amy E. Singer, Ph.D. “A Novel Approach: The Sociology of Literature, Children, Book and Social Inequality. While reading this article I saw that this was a primary review of an ex...

    Read More
  • Journal Article Critique Rubric

    ...AP Biology Scientific Journal Article Critique DIRECTIONS: Select and critique a journal article relating to biology and biological research. The teacher must approve your article choice. An article critique consists of a summary of the key aspects and a critique where you offer your thoughts and opinions. Your critique should be at leas...

    Read More
  • Tips on how to write an article

    ...Tips on how to write an article What is an article? • A piece of writing usually intended for publication in a newspaper, magazine or journal • It is written for a wide audience, so it is essential to attract and retain the readers’ attention • It may include amusing stories, reported speech and descriptions • It can be ...

    Read More
  • Article Review Guideline

    ...EDER 893 Journal Article Review – Reading and Understanding Journals Choose the article that most interests you from among the abstracts listed. Then, acquire read, and evaluate the article as if you were reviewing it for publication. Use the following questions in addition to manuscript review guidelines for journals to direct your evaluation...

    Read More
  • Exploration of a Journal Article in Sociology

    ...Exploration of a Journal Article in Sociology Introduction to Sociology: SOC 100   Exploration of a Journal Article in Sociology In this paper I will be discussing the type of article being explored. What type of research is involved in this article? I will be doing a summary of this article to discover what the main findings are. Explain...

    Read More
  • Article Review Assignment

    ...things that make a paper a good paper…Today I will be discussing three of the most important… Intro paragraph—Purpose—and Conclusions. The opening paragraph…or intro paragraph in any type of writing…whether it is a novel…an essay…newspaper or magazine article or whatever it may be… it is a major part of any type of writing. ...

    Read More
  • English Teaching Material for "Articles"

    ...Class 1 Topic – 2 Articles Introduction An article, sometimes called an article adjective is a little word used before a noun to point to something The words a, an, and the are special adjectives called articles. Types of Articles Definite Article Indefinite Article Definite Article The article “the” points to a definite (pa...

    Read More
  • The Deffine Article

    ...Problem of the Definite Article in the English Language Ludmila Dubenyuk Group 404 Department of Germanic Philology Research Adviser Volkova Kyiv 2011 TABLE OF CONTENTS INTRODUCTION ……………………………………………………………........3 CHAPTER ONE. THE PROBLEM OF THE ARTICLE DEFINITION……..4...

    Read More

Discover the Best Free Essays on StudyMode

Conquer writer's block once and for all.

High Quality Essays

Our library contains thousands of carefully selected free research papers and essays.

Popular Topics

No matter the topic you're researching, chances are we have it covered.