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FACTORS RELATED TO THE SCHOOL PERFORMANCE
OF SECOND GRADE CHILDREN BORN TO LOW-INCOME
ADOLESCENT MOTHERS

presented by
Kunlakam Lekskul

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Ph.D degree in Family and Child Ecolon

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05/06/03

 

 

 

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FACTORS RELATED TO THE SCHOOL PERFORMANCE OF SECOND
GRADE CHILDREN BORN TO LOW-INCOME ADOLESCENT MOTHERS

By

Kunlakam Lekskul

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Department of Family and Child Ecology

2003

ABSTRACT

FACTORS RELATED TO THE SCHOOL PERFORMANCE OF SECOND GRADE
CHILDREN BORN TO LOW-INCOME ADOLESCENT MOTHERS

By
Kunlakam Lekskul

The purpose of this study was to investigate factors which contribute to individual
differences in the school performance of second grade children born to adolescent
mothers. The sample for this study was 90 low-income adolescent mothers and their
children who participated in the Family TIES (Trust, Information, Encouragement,
Support) family support program in Flint, Michigan. Data were collected for the 5 years
that the adolescent mothers and their children were in the program. In addition, follow-
up data were collected when the children were in the first and second grade.

The children’s school performance in second grade relative to their peers was
rated by their teachers at the end of the year in 3 different areas: academic performance,
academic motivation, and social adjustment. Academic performance, including reading,
math, and overall academic performance, was rated using 5-point rating scales. '
Academic motivation was rated by using the Pupil Behavior Inventory (PBI) motivation
scale. Social adjustment was measured with the Social Skills Rating Scale-Teacher
(SSRS-T).

The preliminary analysis explored correlations between second grade school
performance and other factors. Children who performed well in one aspect of school
tended to do well in other areas at the end of second grade. Children who lived in a
relatively supportive home environment and had mothers with high parenting skills in

their early lives tended to have high scores on school performance in the second grade.

In general, children who had high competencies prior to school entry, including high
scores on the Peabody Picture Vocabulary Test-Revised (PPVT-R) and the Vineland
Adaptive Behaviors Scales, tended to have high scores on the Peabody Individual
Achievement Test-Revised (PIAT-R) in first grade. Their teachers also rated them high
on school performance at the end of first grade in all areas. They also did well in second
grade on the various indicators of school performance.

Path analysis was used to analyze the relationships among early home
environment/parenting skills, children’s competencies during the preschool years, and
children’s school performance in second grade. Home environment and parenting skills
during the first five years of children’s lives predicted children’s academic performance
at the end of second grade through the PPVT-R at 54 months, and the PIAT-R and
academic performance in first grade. Similar results were obtained when social
adjustment and academic motivation were the outcome of interest. Surprisingly,
maternal support for academic success in first grade did not predict school outcomes in
second grade when earlier measures of home environment and parenting were controlled.

A structural equation model (SEM) was used to assess the relationships among five
latent variables, including one exogenous latent variable, parenting, and four endogenous
latent variables, children’s competencies prior to school entry, maternal support for
academic success in first grade, and school performance in first grade and second grade.
As expected, children who lived in a more supportive home environment during the
preschool years were more competent prior to school entry, which in turn, predicted

school performance in first and second grade.

To my beloved and wonderful parents, Veerasak and Somsong Lekskul,

for their unconditional love, support, and devotion to my educational endeavors.

iv

ACKNOWLEDGEMENTS

I would like to express my gratitude and appreciation to the many people who
have contributed to this work. Without them, it would not have been possible.

I would like to express my deepest love and acknowledgment to my parents,
Veerasak and Somsong Lekskul, and my wonderful brother, Atikun Lekskul, who are the
most important people in my life for their wisdom and inspiration to pursue higher
education. I really appreciate their encouragement and support that I need for being a
better person in this world. My successes could never repay their unconditional loves
and dedication.

I would like to express a tremendous appreciation to Dr. Tom Luster, who is my
chair of doctoral committee and mentor, for his intelligence, guidance, and devotion from
the time before I was a Family and Child Ecology student until the completion of this
dissertation. I also thank him for sharing data, from his work on the Family TIES project,
to contribute to my dissertation. His continuous insightful and valuable feedbacks have
motivated me to keep track and produce quality work.

I would like to show my gratitude to professors who shared their valuable time
served as my committee. Dr. Robert Boger has accepted me to become an F CE student,
which has given me the doctoral student life. He has believed in my academic and
research abilities, which encouraged me to pursue my doctoral studies. Thanks are also
due to Dr. June Youatt for her academic and emotional support. She is one of my

favorite professors and teachers, who I will continually value in my future professional

career. I would also like to thank Dr. Evelyn Oka for her thoughtful comments, which
guided me in conducting a better quality of work.

I would like to thank the young mothers, the children, teachers, and the family
advocates who participated in this study for sharing their information, as well as, Marcia
Vandenbelt and Laura Bates for their hard work in collecting those data. In addition, I
would like to acknowledge Dr. Alexander von Eye and Laurie Van Egeren for their
valuable comments.

I also appreciate my colleagues in department of Home Economics for allowing me
to temporarily leave my responsibilities to pursue a higher degree and also Sukhothai-
Thammatirat University for providing initial financial assistance. I would also like to
express my grateful to Dr. Deborah Johnson and Dr. Lillian Phenice for their financial
support. They allowed me to work on their research projects and assist in their teachings.
These valuable experiences are important and serve as a solid foundation for my
professional career.

I also would like to express my appreciation to the special person, Polarit
Apiwattanalunggam, who guided and assisted me through many years of studying in the
United States in both happy and difficult times. His encouragement, support, and love
influence me to continue ahead.

Finally, I thank many of my friends at Michigan State University, such as, Kara
Gregory, Nary Shin, So-Jung Seo, and A-ran Chong for their academic and emotional
support and also my old friends from Kasetsart University for their emotional support

through long distance calls.

vi

TABLE OF CONTENTS

LIST OF TABLES
LIST OF FIGURES

CHAPTER l-INTRODUCTION
Purpose of the Study
Statement of the Problems
Research Questions
Conceptual Framework
Conceptual and Operational Definitions

CHAPTER 2- REVIEW OF THE LITERATURE
Adolescent Mothers Parenting
School Performance of Children Born to Adolescent Mothers
Effect of Adolescent Parenting on Children’s School Performance
Child Factors Related to Children’s School Performance
Summary

CHAPTER 3- METHODS
Research Design and Procedure
Core Study
Data Collection
Research Instruments
Conceptual Model and Hypotheses
Data Analyses

CHAPTER 4- RESULTS

Demographic Characteristics of the Sample
Descriptive Statistics

Correlations Among Measures

Path Analyses

Structural Equation Modeling

CHAPTER 5— DISCUSSION AND CONCLUSION
Summary of the Findings and Discussions
Limitations
Future Research
Conclusions

APPENDIX A

LIST OF REFERENCES

vii

102

TABLES

LIST OF TABLES

. The Effects of Attrition: A Comparison of Participants and

Nonparticipants in the Second-grade Follow-up (School
Performance) on Data Collected at Enrollment (Means and
Standard Deviations)

Correlation among Parenting and Home Environment Measures
and Children’s Outcomes

Predictors of Social Adjustment Scores: Partial Regression
Analysis to Generate Path Coefficients and Disturbance Variances

Predictors of Academic Performance Scores: Partial Regression
Analysis to Generate Path Coefficients and Disturbance Variances

Predictors of Academic Motivation Scores: Partial Regression
Analysis to Generate Path Coefficients and Disturbance Variances

Covariance Matrix for the Estimate Data

Goodness of Fit Summary

viii

PAGE

36

58

64

67

71

75

86

FIGURES

8.

9.

LIST OF FIGURES

. Diagrammatic Representation of Bronfenbrenner’s Ecology

of Human Development Model (1979)

Conceptual Model: Micro- and Mesosystem Influences on the
School Performance of Second Grade Children Born to
Adolescent Mothers

Conceptual Model (Hybrid Model)

Measurement Model

. Model of Factors Predictive of Social Adjustment in Second Grade

with Standardized Estimates

Model of Factors Predictive of Academic Performance in Second
Grade with Standardized Estimates

Model of Factors Predictive of Academic Motivation in Second
Grade with Standardized Estimates

Hypothesized Model

Five-F actor Measurement Model

10. Four-Factor Measurement Model

11. Four-Factor Measurement Model Adding Correlations among

Residuals

12. Hybrid Model

13. Hybrid Model of Factors Predicting Social Adjustment in Second

Grade with Standardized Estimates

14. Hybrid Model of Factors Predicting Academic Performance in

Second Grade with Standardized Estimates

15. Hybrid Model of Factors Predicting Academic Motivation in

Second Grade with Standardized Estimates

ix

PAGE

51

63

66

70

73

78

81

83

85

99

100

101

CHAPTER ONE
INTRODUCTION

Although the pregnancy and fertility rates of adolescents have generally declined
since the early 1990s, the absolute number of children born to adolescents remains high.
In 2000, there were almost 480,000 children born to females, under the age of 20. The
majority of births to adolescents (almost 80% in 1999) occur outside of marriage (Child
Trends, 2001). Adolescent pregnancy and childbearing is associated with adverse health
and social consequences for the young women and their children. Many adolescent
mothers and/or their children are at risk for a variety of developmental problems.

Adolescent mothers also tend to have less optimal parenting practices than adult
parents. They are likely to have less knowledge of child development, have less
appropriate interactions with their children, and show less sensitivity and be less
responsive to their children than adult mothers (Sommer, Whitman, Borkowski,
Schellenbach, Maxwell, & Keogh, 1993; Barratt & Roach, 1995). Children of adolescent
parents are at greater risk of living in a disadvantaged environment than children of adult
parents. For example, the children of adolescent parents tend to live in low-income
families or be on welfare, live in crowded conditions, and live in unsafe neighborhoods
(Luster & Brophy-Herb, 2000). As a result, children born to adolescent mothers are at
greater risk for problems in development than their peers who were born to adult
mothers. The slow development of children born to adolescent mothers could be detected
as early as age three (Whitman, Borkowski, Keogh, & Weed, 2001) and continues
through adolescence (Moore, Morrison, & Greene, 1997; Furstenberg, Brooks-Gunn, and

Morgan 1987). Behavior problems of children born to adolescent mothers are detected

from the preschool years (Wadsworth, Osborn, & Butler, 1984) through adolescence
(Furstenberg et al., 1987).

However, not all children born to adolescent mothers perform poorly in school.
Some of them perform at average or above average levels compared with their peers
(Vandenbelt, Luster, & Bates, 2001; Whitman et al., 2001). There is very little literature
on why these children of adolescent mothers, who are considered at risk of school failure,
perform as well as or better than their peers. More studies need to be conducted looking

at what factors contribute to these children’s school performance.

Purpose of the Study

The purpose of this study is to investigate factors which contribute to individual
differences in school performance of second grade children born to adolescent mothers.
This study focused on four sets of predictor variables: 1) the parenting practices of
adolescent mothers during the first five years of the children’s lives, 2) children’s
competencies during the preschool years, 3) children’s school performance in first grade,

and 4) maternal support for academic success in first grade.

Statement of the Problems

Recently, studies examined factors relating to the performance of children born to
adolescent mothers and discovered that supportive home environments and the caregiving
that adolescent mothers provided for their children in the first five years of life are

important predictors of later development (Luster, Bates, Fitzgerald, Vandenbelt, & Key,

2000; Vandenbelt et al., 2001). However, investigators usually focused on only one
developmental outcome in most earlier research. For example, children’s school
performance usually was separately assessed in different areas such as academic
achievement, social competence, or academic motivation. However, these factors could
be considered all together, with each component viewed as important for school
performance over the long term. In addition, the previous studies usually used one
measurement to represent an independent variable of interest; in order to make the
variable more valid and to correct for measurement errors, multiple measurements of
each key construct are suggested (Byme, 2001 ).

This study attempted to answer the primary research question: why do some
children born to low-income adolescent mothers perform well in school? This
longitudinal study allowed us to understand what experiences in the early childhood
period (e.g., adolescent mothers’ parenting and home environments) contributed to their
performance in school at the end of second grade. How do these factors relate to the
development of children prior to and after entering school? And finally, how do their
experiences after entering school affect later school experience? This study investigated
different aspects of the development of the children that are likely to influences school

performance over time: academic performance, academic motivation, and social

adjustment.

Research Questions

The main research question is: What factors are related to the school performance
of second grade children born to adolescent mothers? This study addressed two specific
questions:

1. How do parenting practices during the first five years relate to maternal support
for academic success in first grade, and to children’s school performance in
second grade?

2. How do children’s competencies (receptive vocabulary, performance of daily

activities, and social skills) prior to school relate to their school performance in

first and second grade?

Conceptual Framework

This study is based on Bronfenbrenner’s (1979) ecology of human development
model. The development of the individual is influenced by relationships between a
developing person and the changing immediate environment in which he or she lives.
The environment could be an immediate setting as well as the larger social context in
which the setting is embedded. The developing person is defined as a growing dynamic
entity, who is progressively moving into and restructuring the milieu in which he or she
resides.

Bronfenbenner describes four dimensions of an individual’s overall ecological

system, which are useful for understanding behavior and development. The multiple

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interacting environmental systems include the micro-, meso-, exo-, and macrosystem
(Figure 1). This study examined selected variables that represent aspects of individual
micro and mesosystems of the individual, which were expected to influence the school
performance of children born to adolescent mothers.

A microsystem is a pattern of activities, roles, and interrelationships between a
developing individual in a setting, which contains that person. A setting is defined as a
place with particular physical features in which the participants engage in particular
activities in particular roles (Bronfenbrenner, 1979, p. 22). The home is one example
which is viewed as an important microsystem for children. There are other microsystems
for children such as the school, neighborhood, and peer group. However, the home is not
defined solely by the physical setting, but by the transactions which occurs in the setting.
One microsystem of the child in this study is the home of the adolescent mother and the
parenting practice and home environment that adolescent mother provided for the child.

A mesosystem is an interrelationship between two or more microsystems which
contain the developing individuals and is an extension of the microsystem; it is the
interactions among settings containing the developing person. According to
Bronfenbrenner, the child’s development is facilitated by linkages between settings. For
example, an adolescent mother’s involvement in school activities, which is a link
between two microsystems, home and school, could affect the teacher’s perception of the
child’s academic competence, which in turn relates to the child’s academic achievement.
Therefore, adolescent mothers’ support for school success and involvement in school are

viewed as potentially important factors influencing the school performance of their

children.

An exosystem refers to a microsystem that do not involve the developing person
as an active participant but events in that context which can influence the developing
person. In the current study, no selected variable directly represents an exosystem. An
example of an exosystem is the environment of a school that the adolescent mother
attends; teachers’ expectations for the adolescent mother, may affect the adolescent
mothers’ school performance, which in turn affects the attitude of the mothers towards
school and their support for children’s academic success. Thus, the mother’s school
environment has an indirect effect on their children’s school performance.

A macrosystem refers to the consistencies of the form and content of the lower-
order systems (micro, meso, and exosystem), which exist or may exist at the level of
subculture or culture, along with the belief systems that underlies such consistencies.
Macrosystems are always changing. The macrosystem in one generation is different
from that of the next generation. Most macrosystems are informal and are maintained
through ‘custom and practice in everyday life.

The effect of macrosystem dynamics on the school performance of the children
was not examined in this study because relevant data were unavailable. However, an
example of a macrosystem variable is cultural beliefs about the value of education, which
could affect parenting behavior and the home environments they provide for their
children. Thus, beliefs regarding the value of education may be indirectly related to their
children’s school performance.

Based on Bronfenbrenner’s theory of human development and the findings from

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exogenous and endogenous variables are: l) Home/parenting, 2) Maternal support for
academic success, 3) Children’s competencies prior to school entry, and 4) Children’s
school performance in first grade. Home/parenting was assessed by observing the quality
of home environment at 24 and 36 months and the mothers’ parenting skills at 54 months.
Maternal support for academic success in first grade was assessed by reading activities,
maternal involvement in school activities, and expectations regarding the child’s
academic achievement. The children’s competencies prior to school entry was assessed
by the Peabody Picture Vocabulary Test-Revised (PPVT-R), the Social Skills Rating
Scales- Parent Form (SSRS-P), and the Vineland Adaptive Behavior Scale (VABS).
Children’s school performance in first grade was measured by the Peabody Individual
Academic Test-Revised (PIAT-R), and teachers’ evaluations of academic performance,
academic motivation, and social adjustment. The children’s school performance in
second grade, which was assessed by teachers’ ratings of academic performance,

academic motivation, and social adjustment.
Conceptual and Operational Definitions

The following section provides the conceptual and operational definitions for the
variables in this study.
Home/parenting
Conceptual: Parenting refers to the caregivers’ parenting skills and characteristics of the

home environment that support the development of children.

Operational: Parenting was assessed by the Nursing Child Assessment Training (N CAT)
HOME when the children were 24 months old, by the Home Observation for
Measurement of the Environment (HOME) when the children were 36 months old, and
by family advocates’ ratings of maternal caregiving when the children were 54 months
old.

Maternal support for academic success

Conceptual: This refers to the extent to which adolescent mothers involved themselves in
school related activities, such as reading to the child, participating in school activities,
and mothers’ expectations for their children’s academic achievement.

Operational: When their children were in first grade, the adolescent mothers were
interviewed about reading activities (e. g., frequency of reading to the child and frequency
of selecting books from the library), involvement in school activities (e.g., attending a
school open house, serving on a parent-teacher council or advisory group), and maternal
expectations for academic success, such as the grades they expect their children to obtain
in school.

Children’s competencies prior to school entrv

Conceptual: Children’s competencies refers to their ability to understand the meaning of
spoken words, performance on age-appropriate adaptive behaviors (e.g., dressing
themselves), and social skills when interacting with adults and peers.

Operational: Three instruments were used to assess children’s performance prior to
school entry when the children were 54 months old: the Peabody Picture Vocabulary
Test-Revised (PPVT-R) (Dunn & Dunn, 1981), the Vineland Adaptive Behavioral Scales

(VABS) (Sparrow, Balla, & Cicchetti, 1984), and an adapted version of the Social Skills

10

Rating System-Parent Form (SSRS-P) (Gresham & Elliott, 1990). The PPVT—R was
assessed by experienced researchers. The VABS and the SSRS-P were completed by the
adolescent mothers; typically the items were read to the young mothers by members of
the research team.

Children’s school performance in first and secondggafi

Conceptual: This refers to children’s ability to know and interpret their environment,
their ability to recall, reason, problem solve, think and learn, and their ability to adjust
their behaviors in a school setting. The children’s performance in school included
academic performance, academic motivation, and social adjustment.

Operational: School performance in first grade was assessed by four instruments: the
Peabody Individual Achievement Test-Revised (PIAT-R) (Markwardt, 1989), teachers’
ratings of academic performance, the Pupil Behavior Index (PBI) (Vinter, Sarri,
Vorwaller, & Shafer, 1966), and the Social Skills Rating System-Teacher Forrrr (SSRS-T)
(Gresham & Elliott, 1990).

The PIAT—R was administered in the fall semester of first grade. Teachers’ ratings of
academic performance, the P81, and the SSRS-T were completed by the teachers at the
end of first grade.

Children’s school performance in second grade was assessed by teachers’ ratings of
academic performance, the Pupil Behavior Index (PBI), and the Social Skills Rating

System-Teacher Form (SSRS-T) at the end of second grade.

11

CHAPTER TWO
REVIEW OF THE LITERATURE
The review of literature is divided into four main parts. The first part presents an
overview of parenting differences between adolescent and adult mothers. The second
part is an overview of the school performance of children born to adolescent mothers,
compared to the school performance of children born to adult mothers. The third part
summarizes research on the relationship between adolescent mothers’ parenting and
children’s school performance. The last part reviews what is known about the
relationships between child factors (e. g. language ability) and children’s school

performance.

Adolescent Mothers Parenting

The transition into parenting can be a stressful time for all parents, regardless of
age and background. For adolescent mothers, this stress may be compounded by the
likelihood that they have come from unfavorable backgrounds, as well as by the
normative developments that occur during adolescence. The research on adolescent
parental behaviors has focused on three main areas: knowledge about child development,
attitudes toward the parenting role, and appropriate parenting practices (Sommer et al.,
1993). Generally, adolescent mothers had lower levels of child development knowledge,
less supportive parenting attitudes and less optimal parenting styles than adult mothers,
both prenatally and postnatally (Sommer et al., 1993). Osofsky, Harm, and Peebles
(1993) concluded from their review of research that adolescent mothers had a lack of

knowledge of developmental milestones or imprecise knowledge concerning child

12

development, expected their children to reach developmental milestones earlier, had more
punitive child-rearing attitudes, and perceived their infant’s temperament as more
difficult than it actually was. As a result, Whitman, Borkowski, Schellenbach, and Nath
(1987) concluded that children of adolescent mothers were diagnosed as mentally
retarded prior to adolescence more than children of adult mothers. Luster and Brophy-
Herb (2000) reviewed literature and found that adolescent parents were less likely to
indicate that they would intervene in harmful situations than would adult parents. As a
result, children of adolescent mothers suffer from more accidents than children of adult
parents.

Adolescent mothers scored significantly higher in authoritarian attitudes than
adult mothers (Camp, 1995). They also had negatives attitudes about parenting; for
example, they were harsh in their response when faced with perceived or real
inappropriate child behaviors (Whitman et al., 2001).

On average, teenage mothers demonstrated less favorable parenting practices than
adult mothers. Adolescent mothers demonstrated less appropriate or less nurturing
interactions than adult mothers. Adolescent mothers showed quiet interaction, smiled
less, and were less positive in handling irritating infant behaviors (Barratt & Roach,
1995; Osofsky et al., 1993). The language of teenage mothers was less positive; they
tended to give more commands and provided less reinforcement for their children’s
vocalization than adult mothers (Corcoran, 1998; Barratt & Roach, 1995). Adolescent
mothers also provided less appropriate environments than adult mothers. Moore,
Morrison, and Greene (1997) found that children born to younger adolescent mothers

lived in substantially disadvantaged home environments compared to children born to

13

older mothers. For example, adolescent mothers tended to be less responsive; they
provided fewer and less frequent cognitive activities in their home, such as offering or
showing toys (Barratt & Roach, 1995). Adolescent parents had scores significantly lower
than adult mothers on measures of parenting behavior, such as flexibility, verbal
exchanges, and positiveness (Sommer et al., 1993). Adolescent mothers tended to have a
higher rate of child abuse than adult mothers. Children of younger adolescent parents
(age 17 and younger) are more than twice as likely to be referred for abuse and neglect
than the children of mothers who delayed childbirth until age 20 or 21 (George & Lee,

1997).

School Performance of Children Born to Adolescent Mothers

Luster and Brophy-Herb (2000) reviewed the literature and concluded that the
children of adolescent mothers tend to score below their peers on a variety of measures,
including measures of cognitive competence and academic achievement. The cognitive
development problems could be detected at an early age. The children of adolescent
mothers had significantly lower scores on vocabulary tests measured with the English
Picture Vocabulary Test (EPVT) at age 5 than children born to older mothers, after
controlling for other risk factors (Wadsworth, Taylor, Osborn, & Butler, 1984). In one
study, nearly half of the children of adolescent mothers at age 6 had general concepts
scores, measured with the Bracket Basic Concept Scale, that were more than one standard
deviation below the normative mean (Spieker, Larson, Lewis, White, & Gilchrist, 1997).

Consistently, Whitman et al. (2001) found that the children of adolescent mothers

14

displayed receptive language delays at 3 and 5 years, when assessed with the Peabody
Picture Vocabulary Test-Revised (PPVT-R). Around 60% of the children at age 3 and 5
had PPVT-R scores below the 10th percentile. Consistently, another study found that
children from 4 to 11 whose mothers were 17 or younger at their births scored lower in
mathematics, reading recognition, and reading comprehension measured with the
Peabody Individual Achievement Tests (PIAT) than children born to older mothers (18-
21 years old) (Moore et al., 1997).

The children of adolescent mothers performed at a lower level than children born
to adult mothers not only on standardized tests but also on school performance and
academic achievement. Youth born to adolescent mothers (age 17 or younger) are 70
percent less likely to be rated one of the best students in the class by their teachers at ages
12 to 16 after controlling for mother’s background characteristics (Moore et al., 1997).
They experienced pervasive school failure at the high school level. Among almost 300
adolescents who were born to teenage mothers in Baltimore area, 53% repeated at least
one grade and 49% were suspended or expelled. When the children of adolescent
mothers grew older, their educational goals were less clear than those of their peers who
were born to adult mothers. Less than one third of students born to adolescent mothers
were planning to attend college (Furstenberg et al., 1987).

Children of adolescent mothers are also at risk of intellectual decline relative to
other children over time. Whitman et al. (2001) found that although the majority of
infants of adolescent mothers fell within the normal range on the Bayley Scales of Infant
Development in Mental and Motor skills at age 6 months and 1 year, they showed

increasing evidence of intellectual delays at age 3 and 5 years, measured with the

15

Stanford-Binet Intelligence Scale. Almost half of the children (45%) at age 3 and 25% of
children at age 5 had Stanford-Binet IQ scores at the clinical borderline category or
lower.

Children of adolescent mothers are not only at risk of academic problems, but also
behavioral problems. Luster and Brophy-Herb (2000) concluded that children of
adolescent mothers exhibited greater emotional disturbances such as hostility and poor
relationships with peers. Sommer, Whitman, Borkowski, and Gondoli (2000) studied
121 low-income adolescent mothers and their children from Indiana and South Carolina.
They found that almost 30% of children born to adolescent mothers at age 3 displayed
serious behavior problems measured with the Child Behavior Checklist (CBCL).
Another study compared 1,031 children of adolescent mothers and 950 children of adult
mothers born in the UK. in 1970; the researchers found that children of adolescent
mothers had more behavior problems rated by their mothers than the children of older
mothers at age 5 (Wadsworth et al., 1984). Spieker, Larsen, Lewis, Killer and Gilchrist
(1999) studied 183 children of low-income adolescent mothers whose mothers were
recruited from prenatal clinics and service agencies in the Seattle area. They found that
children of adolescent mothers had higher levels of disruptive behavior measured with
the Child Behavior Checklist (CBCL) compared to the normative sample. More than
twice as many children as expected exceeded the borderline clinical cutoff based on the
normative sample.

When the children of adolescent mothers became youths, they showed
“misbehavior,” such as school disciplinary problems, running away from home, and

being stopped by the police (Furstenberg et al., 1987). Consistently, Moore et al. (1997)

16

found that among 1,150 children of adolescent mothers age 4 to 14, children of the
youngest teen mothers had significantly more behavior problems with and without
controls for the mothers’ background than children whose mothers were older.

The lower school performance of the children born to adolescent mothers did not
depend on a single factor but on multiple factors. Children of adolescent mothers who
experienced multiple stressors may be at the greatest risk for low achievement and
behavioral problems. Studies found that children exposed to several risk factors (e. g.,
were much more likely to perform poorly academically and behaviorally than children

exposed to no risk factors (Dubow & Luster, 1990).

Effect of Adolescent Parenting on Children’s School Performance

As mentioned earlier, children born to adolescent mothers are at greater risk for
problems in cognitive development than their peers. However, not all of the children
born to adolescent mothers perform poorly in school. Approximately 28% of 121
children born to adolescent mothers showed normal cognitive development, emotional
functioning, and adaptive behavior at three years of age, as assessed using the Stanford-
Binet, the Achenbach Child Behavior Checklist (CBCL) and The Vineland Adaptive
Behavior Scales (VABS) (Sommer et al., 2000). Almost 40% of children had average or
above average intelligence, which was assessed with the Stanford-Binet Intellectual
Scales, and almost 10% of the children scored above the 50‘h percentile on the PPVT-R at
5 years (Whitman et al., 2001). Studies found that earlier caregiving, quality of home

environment (Luster et al., 2000), and maternal support for academic achievement

17

(Vandenbelt et al., 2001) are important factors related to the school success of the
children.
Home environment

Quality of home environment could be measured with several instruments such as
The Home Observation for Measurement of the Environment (HOME), which was
developed by Caldwell and Bradley (1984). Early home environment is related to
children’s early and later academic performance. Bradley, Caldwell, and Rock (1988)
found that parental responsivity, availability of stimulating play materials, and parental
involvement assessed when the children were 2 years of age were strongly related to
children’s cognitive development at age 10, controlling for HOME scores at 6 months
and 10 years.

Home environment is an important factor in predicting the academic achievement
of children born to adolescent mothers. Dubow and Luster (1990) found that the positive
home environment that adolescent mothers provided for their children, both in emotional
support and cognitive stimulation, was associated with fewer academic problems for the
children. In addition, Baydar, Brooks-Gunn, and F urstenberg (1993) found that the
physical and emotional quality of the home environment in early childhood is a
significant predictor of later literacy.

Among younger children of adolescent mothers, home environment measured in
early childhood was associated with later academic achievement. Vandenbelt et a1.
(2001) found that the home environments that adolescent mothers provided for their
children at 24 months, measured with the Nursing Child Assessment Training (NCAT)

HOME, were significantly related to their children’s academic achievement measured

18

with the Peabody Individual Achievement Test-Revised (PIAT-R) in the fall of the first
grade. Home environment measured at 36 months was related to the PIAT-R and teacher
rated reading and mathematics at the end of first grade. Moore and Snyder (1991) also
found that adolescent mothers’ HOME scores exhibited a strongly positive and robust
influence on child’s cognitive scores measured with the Peabody Picture Vocabulary Test
(PPVT) at age three to seven.

Among older children, Baharudin and Luster (1998) found that children age 6-9
years who experienced supportive home environments as assessed by the HOME-SF had
higher scores on achievement tests. Consistently, Wheeler (1997) found that those
children of adolescent mothers between 13 and 17 years-old, with the highest HOME
scores measured 4 years ago, were most likely to be in the highest achieving group, and
those with the lowest HOME scores were most likely to be in the lowest achieving
groups.

Home environment is related not only to children’s academic achievement, but
also to social competence. Children’s behavioral problems may occur because the
children are exposed to environmental factors that increase mental health risks. African
American children who had many behavioral problems, assessed with the Behavioral
Problems Index (BPI) at age six to nine, tended to have mothers who had low home
environment scores (Luster & McAdoo, 1994). Studies have also found relationships
between adolescent mothers’ well-being and their children’s behavioral problems.
Adolescent mothers are more likely to be depressed than adult mothers. As a result,
children of adolescent mothers are at higher risk of being exposed to depression and

aggression (Osofsky et al., 1993). Consistently, Dubow and Luster (1990) found that the

19

emotional support subscale measured with the HOME, but not the cognitive stimulation
subscale, was associated with reductions in behavior problems of eight to fifteen-year-old '
children of adolescent mothers.

Maternal caregiving and parenting skills

Quality of parenting is associated with the cognitive development of children.
Cognitive readiness for parenting, which includes knowledge of infant and child
development and parenting attitudes, is also related to children’s academic achievement.
Adolescent mothers who were less cognitively ready for parenting during the prenatal
period had children who obtained lower levels of intelligence and language skills at 3
years of age (Miller, Miceli, Whitman, & Borkowski, 1996).

Quality of parent-child interaction, such as parental warmth or sensitivity to
children’s requests and feelings, has been significantly associated with academic
achievement and cognitive growth (Christian, Bachnan, & Morrison, 2001). Estrada,
Arsenic, Hess, and Holloway (1987) found relationships between quality of mother-child
interactions and children’s cognitive competence including school readiness skills at ages
5 and 6, IQ scores at age 6, and vocabulary and mathematics performance at age 12. The
association between affective relationships and cognitive performance increased from
nonsignificant (age-5-6 school readiness), to marginally significant (age-6 IQ), to clearly
significant (age-12 school achievement).

Consistent with children of adult mothers, adolescent mothers who provided more
supportive caregiving when their children were young tended to have children with
higher academic performance later on. Children whose adolescent mothers initiated

positive interactions with them averaged higher literacy scores than children whose

20

mothers had fewer interactions (Baydar et al., 1993). Harm, Osofsky, and Culp (1996)
measured mother-child interaction in infancy, positive and negative hedonic tone,
maternal positive and negative affect, dyadic verbal reciprocity and rated degree of infant
engagement, maternal sensitivity, and dyadic interactive fit. They found that interactions
between adolescent mothers and their children at 13 and 20 months were predictive of the
receptive vocabulary scores at age 44 months.

In another study, mother-child interaction measured with the Maternal Interaction
Scale when the children were a year old was the best predictor of the child’s IQ, PPVT,
and PIAT math and reading at age S (Whitman et al., 2001). In the study by Vandenbelt
et a1. (2001), the quality of care that an adolescent mother provided for her child, such as
warmth, setting limits for her child, and engaging in activities which enhance the child’s
intellectual development, was measured by family advocates when the child was 54
months. The researchers found that the quality of care that the adolescent mothers
provided for their children was the most consistent predictor of PIAT—R scores in the fall
and teachers’ composite ratings of reading and math in the spring of the child’s first
grade year.

Effective parenting skills are also a protective factor for enhancing prosocial
behavior among at-risk children (Huffman, Mehlinger, & Kerivan, 2000). Parent-child
interactions have tremendous effects on children’s behavior. Among London children
age 9-12, mother-child and father-child relationships were viewed as strong protective
factors against children’s behavioral and emotional problems in at-risk children whose
parents had marital problems (Jenkins & Smith, 1990). Consistently, among children

from urban areas, parenting quality, including warmth and closeness, and high

21

'_.___-

expectation for child’s achievement and prosocial behavior, was predictive of
competencies in childhood and adolescence, even afler cognitive functioning and
socioeconomic status were controlled (Masten, Hubard, Gest, Tellegen, Garrnezy, &
Ramirez, 1999).

Prenatal cognitive readiness of the parents is not only related to children’s
academic performance but also to behavioral outcomes. Miller et a1. (1996) found that
adolescent mothers who were less cognitively prepared for parenting reported that their
children displayed more internalizing behaviors (e.g., depression and anxiety) and
externalizing behaviors (e.g., aggression) at 3 years of age. Poor parenting techniques
increased the risks of poor social development in children. Poor parenting and parent-
child relationships during infancy and toddlerhood may lead to nonoptimal development
later. Wakschlag and Hans (2000) concluded that among adolescent mothers, lack of
dyadic engagement was related to insecure infant attachment. Conflict between young
mothers and their toddlers was also related to behavior problems during the preschool
years. Mothers’ and grandmothers’ competent parenting were negatively associated with
children’s externalizing and internalizing problems during preschool.

Brier (1995) found that parents who are harsh, disengaged, provide inconsistent
guidelines, and are unable to monitor their children’s behavior are more likely to have
children with a higher risk for antisocial behavior. Egeland, Pianta, and O’Brien (1993)
found that intrusive parenting observed during mother-child feeding and play interactions
at 6 months predicted problems with emotional health and peer acceptance in first and
second grade. Consistently, Spieker, Larson, Lewis, Keller, and Gilchrist (1999) found

that children whose adolescent mothers reported the use of negative control strategies,

22

such as yelled, threw, smashed or kicked something, when the children were 5 '/2 and 6
years, had significantly higher disruptive behavior problem scores at age 6. In addition,
the increasing use of negative control practices of the adolescent mothers increased the
children’s disruptive behavior problems. In another study, adolescent mothers who had a
high potential for child abuse, measured with the Child Abuse Potential Inventory-Short
Form (CAPl-SF), had children who had more internalizing problems at ages 3 and 5 and
had externalizing problems at age 5 (Dukewich, Borkowski, & Whitman, 1999).
m1 involvement in education

Several studies found that maternal involvement in children’s education when the
children are young has benefits for academic achievement at an early age as well as later
on. Griffin and Morrison (1997) found that the home literacy environment, such as
frequency of using the library, number of child and adult magazine subscriptions, how
often someone read to the child, and the number of books the child owned, uniquely
predicted kindergarten scores in receptive vocabulary, reading recognition, and general
knowledge and second grade scores in general knowledge and reading recognition. Hess
et a1. (1984) found that maternal behavior which was associated with children’s aptitude
for school-relevant tasks at ages 5 and 6, including teaching behavior, expectations,
beliefs, and disciplinary strategies, was also related to children’s school readiness and
academic achievement scores at age 12.

When high-risk students succeed in school, their parents are likely to have
influenced their academic achievement. High achieving students from economically
disadvantaged homes in urban schools tended to have parents who were more likely to

emphasize and encourage their academic learning (Wang, Haertel, & Walberg, 1994).

23

Children age 3-11, whose parents read or told stories to them or offered printed resources
such as books, had average or above scores on measures of academic performance
(Ebener, Lara-Alecio, & Irby, 1997). Luster and McAdoo (1996) found that maternal
involvement in kindergarten, rated by teachers, was a significant predictor of the
children’s intelligence in kindergarten, measured with the Stanford-Binet. Maternal
involvement in kindergarten was a consistent predictor of academic achievement in first
grade and eighth grade, measured with the California Achievement Test (CAT), and
educational attainment at age 27. Reynolds (1991) found that parent involvement in
school activities, rated by teachers at the end of the first year, had relatively strong
indirect effects on reading and mathematics achievement at the end of the second year
through reading and mathematics achievement at the end of first year. Among adolescent
mother families, Vandenbelt et a1. (2001) found that maternal support for education, such
as reading activities, expectations for achievement, and maternal involvement in school
activities, was related to PIAT-R scores in first grade.

Parental expectations for children’s school success are related to children’s
academic achievement. Christian et a1. (2001) found that the parents of high achievers
had high educational expectations and fostered children’s active participation in school.
Consistently, adolescent mothers’ high educational aspirations for their children in early
childhood predicted high literacy scores for their offspring in young adulthood (Baydar et

al., 1993).

24

Child Factors Related to Children’s School Performance
Cognitive functioning and ability

One of the most important predictors of academic achievement of children is level
of cognitive ability. Children with lower levels of cognitive ability, especially lower
verbal skills, are more likely to experience school failure. They also may have negative
school attitudes and decreased chances of recognizing the relationship between
achievement in school and later success in life (Huffman et al., 2000). Children’s
cognitive ability could be measured with a variety of measurements such as the Bayley
Mental Development Index for infants and toddlers, and the Stanford-Binet Intelligence
Scale (SBIS) and Peabody Picture Vocabulary Test (PPVT) for preschool and first grade
children.

Among children of adolescent mothers, an average or higher level of verbal skills
measured with the PPVT was viewed as a protective factor, which reduced the risk of
academic problems (Dubow & Luster, 1990). In another study, Whitman et a1. (2001)
found that cognitive ability at an early age predicted the level of later cognitive ability
and academic achievement. Child’s cognitive functioning at l-year, measured with the
Bayley Mental Development Index, was the best predictor of the child’s cognitive
development at age 3 (measured with the SBIS and the PPVT-R) and at age 5 (PIAT).
The Vineland Adaptive behavior (VAB) scale, Stanford-Binet IQ, and language
development (PPVT-R) at age 3 were the best predictors of intelligence scores and
academic readiness (PIAT math and reading) at age 5.

Studies also found relationships between cognitive development and poor school

outcomes in terms of behavioral problems. Children with lower levels of intelligence,

25

especially lower levels of verbal skills, are more likely to exhibit antisocial behaviors
(Huffinan etal., 2000). Among young children, language ability is related to the ability
to recognize and interpret emotions, which in turn are related to self-regulation. Children
who display deficits in language are less likely to remember and follow directions and
more prone to “bump against” rules in situations that contain structure and require
restraint (Brier, 1995). Among adolescents, early intellectual functioning is viewed as a
vulnerability or protective factor for the development of antisocial behavior problems in
high-risk group. Good verbal, learning, or problem solving aptitude could play a role in
assessing threat, accessing resources, and seeking healthier environments or relationships
for development; these qualities may also elicit positive reactions from teachers (Masten,
Hubbard, Gest, Tellegen, Garrnezy, & Ramirez, 1999).
Cognitive madiness Mdemigchievement at the beginning of school

Children who had more cognitive experiences at an early age, such as attending
kindergarten prior to the transition to the first grade, performed better than children who
had less experience in a school setting. Children who were good at letters and sounds
during kindergarten learned to read more easily and performed well in first grade
(Entwisle & Alexander, 1998). Also children who were well prepared before entering
school were less likely to be placed in less advantageous academic tracks. Reynolds
(1989, 1991) found that entering school readiness at kindergarten, in terms of listening,
word analysis, vocabulary, language, and mathematics, measured by the Iowa Tests of
Basic Skills (ITBS), directly affected the reading achievement of African-American

children in first and second grade. Cognitive readiness also had an indirect effect on

26

reading achievement at second grade through reading achievement in kindergarten and
first grade.

Children’s academic skills at the beginning of school are highly predictive of
long-terrn academic success. Stipek (2001) stated that prior skills limit a child’s ability to
learn new skills. Therefore, children with high skills at the beginning are able to take
advantage of the instructional program more than are children with poorer skills. Many
longitudinal studies found that good cognitive skills during the first few years of school
predicted later academic performance (Stipek, 2001). Hess, Holloway, Dickson, and
Price (1984) found that school readiness, such as knowledge of concepts, at age 5 and 6
was predictive of mathematics and vocabulary in Grade 6. In a similar study, Stevenson
and Newman (1986) found that kindergarteners who had high scores on reading
comprehension and mathematics had high scores on reading and math achievement in
Grade 10. Cunningham and Stanovich (1997) concluded that reading achievement in first
grade correlated very highly with reading comprehension, vocabulary, and general
knowledge in the 11th grade when first grade cognitive ability was partialed out.
Academic achievement as early as first grade predicts high school completion; lower
school achievement and academic motivation in sixth grade was associated with a higher
probability of dropping out of high school (Garrrier, Stein, & Jacobs, 1997).

Among a high-risk sample, Luster and McAdoo (1996) found that the behavior of
low-income kindergarteners rated by teachers, including academic motivation and child’s
personal behavior, were predictive of achievement measured by the California
Achievement Test (CAT) in first and eighth grades. Another study found that among

children of adolescent mothers, early childhood cognitive standardized assessments at

27

age 4—6 were highly predictive of literacy skills at age l9-21(Baydar et al., 1993). Earlier
educational problems such as school suspensions or early grade failures are strongly
associated with literacy levels in young adults.

However, some studies found that preschool experiences contributed significantly
only for certain groups of children or depended on other factors, such as family
background. Among the most at-risk children, who had less educated mothers and poorer
home literacy environments, more time in child-care centers was significantly related to
academic performance especially in mathematics scores (Christian, Morrison & Bryant,
1998). For other children in the same study, preschool experience did not play a
significant role in academic performance.

Soc_ial compgterge

Social skills and problem behaviors have been considered less as important
variables related to school success or failure. A few studies have focused on the
relationship between social competence in kindergarten children and academic
achievement. Christian et a1. (2001) found that quality and maintenance of children’s
peer relations affect their schooling experiences. Similarly, kindergarteners’ positive
social skills, assessed with the Social Skills Rating Scale (SSRS) by their teachers, were
related to first grade academic achievement measured with the Stanford Achievement
Test (Agostin & Bain, 1997). On the other hand, negative relationships or conflicts with
peers are viewed as a risk factor for poor school adjustment and decreasing school
involvement. Ladd (1990) concluded that children who had fewer friends and more peer

rejection may have negative perceptions of school, poor school attitudes, and low levels

of achievement.

28

-43!

 

Personal maturity and the behavior of children are also related to children’s
success in school. Pallas, Entwisle, Alexander, and Cadigan (1987) found that personal
maturity of the children in kindergarten, as rated by teachers, significantly predicted
cognitive verbal growth from the fall semester to spring semester of first grade measured
by the California Achievement Test (CAT). On the other hand, children’s psychological
well-being is related to their school performance. Affectively depressed children show
evidence of functional cognitive impairment, with mild declines in verbal performance
over time as the result of difficulties with concentration and less motivation to engage in
learning tasks (Kovacs & Goldston, 1991). Children’s interpersonal skills have also
predicted early academic achievement. Normandeau and Guay (1998) found that
preschool behaviors, such as aggressive, anxious-withdrawn, and prosocial behaviors,
measured with the Preschool Social Behavior Questionnaire by their teachers, influenced
cognitive self-control, which in turn was positively related to school achievement at the
end of first grade measured with the Peabody Picture Vocabulary Test (PPVT).

Arnold (1997) found that there is bidirectional relationship between externalizing
behaviors and academic achievement. Extemalizing behaviors predicted academic skills,
and academic skills predicted externalizing behaviors. Teachers are likely to provide
fewer learning opportunities for children with conduct problems than for children with
fewer conduct problems. Teachers are more likely to spend time on their behavior
problems than instruction in academic tasks. In turn, these children are less likely to have
high academic achievement. Peers are more likely to reject low-achievers; therefore,
these children are more likely to have negative relationships with their classmates, which

in turn could create negative attitudes toward learning and school (Stipek, 2001).

29

Children’s academic motivation

Children who perceive that school activities are interesting will persist in
finishing school tasks; this in turn, increases the likelihood of success in school.
Academic motivation in the early grades had both direct and indirect effects on academic
achievement later on. For children from low income families, academic motivation
before entering school is related to academic achievement in mathematics, after entering
school (Reynolds, 1989). Luster and McAdoo (1996) found that among low-income
Afiican-American children, academic motivation ratings by their kindergarten teachers
with the Pupil Behavior Inventory (PBI) consistently predicted academic achievement in
first and eighth grades. Consistent with Luster and McAdoo’s finding, Reynolds (1991)
found that among low-income children, academic motivation in kindergarten had an
indirect influence on reading achievement in second grade through parent involvement in
school and reading achievement during kindergarten and first grade.

Children’s early performance in school may affect their perceptions of their
academic competence and other motivational variables, which in turn affect their future
performance. Studies found that children’s motivation-related beliefs at the beginning of
school are usually very positive, but the self-perceptions of children who perform poorly
in school decline over the first few years in the elementary grades. Average scores on
motivation measures begin to decline for children who perform poorly after they enter
school. Decline in motivation could decrease effort in academic tasks, in turn, affecting
children’s academic achievement (Stipek, 2001).

Children’s perception of their academic success was also related to their academic

achievement. Pallas et a1. (1987) found that children’s academic self-image such as

30

“learning new things quickly” and “being a good student,” as self rated in the spring of
first grade, significantly related to their verbal grth at the end of first grade.

Recently, researchers have focused on the relationship between social aspects of
academic motivation and academic achievements. Wentzel and Wigfield (1998)
reviewed studies and found that among school-age children, social aspects of academic
motivation, such as displaying socially appropriate classroom behavior and focusing on
academic activities, is strongly associated with academic achievement.

Among young children, teachers’ ratings of first graders’ learning-related

 

behaviors, such as very enthusiastic, interested in a lot of different things, creative or
imaginative, correlated significantly with children’s report card marks and the California
Achievement Test scores (CAT). In addition, the learning-related behaviors in first grade
had a stronger effect on standardized test scores in later years, in second and fourth grade,
than teachers’ report card marks (Alexander, Entwisle, & Dauber, 1993). Researchers
also found that children’s work-related skills, such as listening to instruction and
directions, and compliance with teacher demands at the beginning of kindergarten,
predicted reading and mathematics at the end of second grade, after the influence of
kindergarten reading and mathematics skills had been controlled. Children with low
work-related skills performed significantly worse than the overall sample on a number of
early literacy measures (receptive vocabulary, reading recognition, general information,
and mathematics) at the beginning of kindergarten and at the end of second grade

(McClelland, Morrison, & Holmes, 2000).

31

Summary

It is evident that children born to adolescent mothers are at risk for school failure.
Both academic and behavioral problems are based on multiple factors, especially
unfavorable parenting by adolescent mothers. On the other hand, the literature suggests
that various factors may influence children’s school success. These factors are viewed as
important for child’s school performance. Within the microsystem in which a child
develops, maternal behaviors especially during the first five years of the child’s life
contributed to school performance both early and later on. Studies (Hess et al., 1984 and
Estrada et al. 1987) suggest that a major impact on later performance in school comes
from early school performance, which is affected by the mothers’ parenting skills. The
current study provided additional information regarding the effects of home
environment/parenting and child competencies prior to school entry, which related to the

school performance of children born to adolescent mothers.

32

 

CHAPTER THREE
METHODS
The purpose of this study was to investigate factors which contribute to individual
differences in school performance of second grade students born to adolescent mothers.
This chapter describes the methodology of the study in detail.
This study addresses two specific questions:

1. How do parenting practices during the early childhood period relate to maternal
support for academic success in first grade and to children’s school performance
in second grade?

2. How do children’s competencies (e.g., vocabulary and social skills) prior to

school relate to their school performance in first and second grade?
Research Design and Procedure

This study is a secondary analysis of a longitudinal data set. The units of analyses

were the adolescent mother and her child. The core data set consisted of one hundred and
forty two pregnant adolescents who were enrolled in the Family TIES (Trust,
Information, Encouragement and Support) family support program in 1991.
Qualification for the program required that these females be expecting their first child,
come from low income families (150% of the poverty line or less), have not completed
high school, and be planning to live in the Flint area until 1996.

At enrollment the adolescent females ranged in age from 13 to 19 years, with a

mean of 16 years. Over half of them were African American (58%) and one third were

33

 

Caucasian (33%). Many of the adolescents were considered “at risk,” based on their
background. More than half of them (56%) had been retained in grade, 42% of them
were abused (physically, sexually, or through domestic violence), and 57% had mothers
who had also been teenage mothers.

The follow-up study was conducted when the children of the adolescent mothers
were in the first and second grade. In the second-grade follow up study, data were
collected on 90 second graders at the end of the school year from their teachers from 47
elementary schools.

Anglos

In the second grade follow-up study, second grade teachers rated children’s
school performance at the end of the school year, including academic performance,
academic motivation, and social adjustment. The families of children who were assessed
in second grade were compared to the families of children who did not participate in the
second grade follow-up study on data collected during the prenatal period. T-tests were
used to compare the two groups on thirteen enrollment variables: age, race, educational
aspirations, educational expectations, childrearing beliefs, education level of their
mothers and of their fathers, age at first birth of their mothers, locus of control, self-
esteem, self-reported grade point average (GPA), self-report of grade retention, and
whether or not she was living with her mother. The results are presented in Table l. The
pregnant adolescents who participated in the follow-up study had higher self-reported
grade point averages (GPA) than adolescents who did not participate in the follow-up
study. There was a marginally significant difference in the child-rearing beliefs scores of

the adolescents who participated and those who did not participate in the second grade

34

 

follow-up study. The pregnant adolescents who participated in the follow-up study had
child-rearing beliefs scores less than adolescents who did not participate in the follow-up
study. No other differences were found between participants and non-participants.
Therefore, the follow-up participants were considered to be fairly representative of the

original participants in the Family TIES program.

35

 

Table l. The Effects of Attrition: A Comparison of Participants and Nonparticipants
in the Second-Grade F ollow-Up (School Performance) on Data Collected at
Enrollment (Means and Standard Deviations).

36

 

Variable Participants Nonparticipants t value
(n=90) (n=52)
Age of teens 16.01 16.06 -.18
(1.46) (1.38)
Educational 4.14 3 .87 1.1 1 17-.
aspirations (1.40) (l .51)
Educational 3.58 3.35 .86
expectations (1.53) (1.58) ;
Self-reported 2.54 2.11 3.11* =3
GPA (0.76) (0.83) r' __
Adult Adolescent 104.92 1 10.11 -178“ r "
Parenting (16.27) (18.34)
Inventory Total
Score
(childrearing
beliefs)
Self-esteem 30.88 30.07 1.08
(4.16) (4.54)
Locus ofcontrol 8.86 9.15 -1.16
orientation (1.38) (1.47)
Mother’s l 1.69 l 1.80 -.40
education (1.62) (1 .60)
Father’s 11.42 11.39 .06
education (2.14) (1 .84)
Teen’s mother’s 19.43 18.47 1.55
age at first birth (3.59) (2.86)
African American 0.60 0.53 .71
(0.49) (0.50)
Repeated a grade 0.56 0.54 .20
in school (0.50) (0.50)
Living with 0.63 0.65 -.24
mother (0.48) (0.48)
7p < .10; * p<.05

Data collection

The first three years

Data were collected from the adolescent mothers and their first-bom children
every 6 months during the first three years after the children were born. The home
environments that the mothers provided for their children were assessed in the family
home by interviewers who all had experience working with young mothers when the
children were 24 and 36 months.
At 54 months

At the end of the program, data were collected by interviewing the mothers.
Children’s receptive vocabulary was also assessed with the PPVT-R. In addition, family
advocates who provided services to the families completed rating scales on maternal
characteristics and caregiving practices.
In the first grade

The adolescent mothers were interviewed when the children were in the fall
semester of first grade. Children’s academic achievement was also assessed with the
PIAT-R during the fall semester. The children were assessed by their teachers at the end
of first grade. The teachers’ questionnaires were mailed to teachers and were collected by
members of the research team when they were completed. Teachers had an opportunity
to discuss any question they had regarding the questions with the member of the research
team (i.e., research manager or graduate assistant).
In the second grade

Children’s teachers assessed the children at the end of the second grade.

37

 

Research Instruments

Exogenous variables

Home/parenting:

Parenting skills: The family advocates rated the young mothers’ parenting skills
at 54-months old by using a series of a 5-point rating scales. The parenting skills
included a) maternal warmth; b) the mother’s ability to set and enforce limits for the
child; c) how frequently the mother engaged in activities to enhance the child’s cognitive
development; (1) how often the mother praised and said positive things to the child; e) the
mother’s skills in communicating with the child about household rules and expectations;
0 how child centered the mother was; and g) the overall quality of care the mother
provided for the child. The mean total rating score was 3.40 with a standard deviation of
.88 (range 1-5).

Home environment: The researchers assessed the home environments which the
adolescent mothers provided for their children at 24-months by using the Nursing Child
Assessment Training (NCAT) HOME (Barnard, 1978) and at 36-months by using the
Home Observation for Measurement of the Environment (HOME)(Caldwell & Bradley,
1984). This instrument assessed various aspects of the home enviromnent which were
related to the cognitive competence of children. Each item is scored “yes” or “no”
(indicating the presence or absence of a positive aspect of the enviromnent); a total score
was computed by counting the number of items scored “yes.” For this sample, the mean
(NCAT) HOME at 24 months was 33.19 (SD = 7.67) and the mean HOME score at 36

month was 33.84 SD= 8.96).

38

Endogenous va_ri_2_1bles

Maternal support for ac_ademic success:

Maternal support for child school success was assessed in the fall semester in first
grade in three areas: reading activities, maternal involvement in school activities, and
maternal expectations for child academic success.

Reading activities: Reading activities were evaluated by asking four questions:
“In typical weeks, how often do you read to your child?” “How often does someone else
in your home read to your child?” “How often does your child read to you or to another
adult?” “In the past 6 months, how often have you assisted your child in selecting books
from a library?” Scores on the first three items ranged from S-everyday to l-hardly ever.
Scores on the library use scale range from S-more than once per month to l-not at all.
Scores on the five scales were summed to obtain a total reading score. The reliability
coefficient for the reading scale was .53. The mean score for this sample was 10.24 (_S_D
= 2.84)

Maternal involvement in school activities: There was a list of 15 possible school
activities that adolescent mothers could be involved in which ranged from attending a
school open house to serving on a parent-teacher council or advisory group. Mothers
were asked about their participation in school-related activities during the child’s
kindergarten year. Positive responses were summed to obtain a subscale score for
maternal involvement in school activities (M =7.68; S_D = 2.40). The reliability
coefficient for these items was .65.

Expectations for academic achievement: Adolescent mothers were asked two

questions related to their expectations for their children’s academic achievement. The

39

first question was “Which of the following best describes what grades you expect your
child to get in school?” Scores ranged from 5--excellent, more A’s than B’s to l--below
average, mostly D’s or below. The second question was “How far do you think your
child will go in school?” Scores ranged from 6--take further training after college to l--
leave school before entering high school. Scores from these two questions were summed
to obtain a total subscale score for the expectations for academic achievement scale. The
reliability coefficient for these two items was .46. The mean was 8.84 (S_D_ = 1.44).

Children’s competencies prior to school entry:

Receptive Vocabulary: The Peabody Picture Vocabulary Tests-Revised (PPVT-R)
(Dunn & Dunn, 1981) was used to assess the receptive vocabulary of the children at 54-
months. The examiner read each word aloud and the child was asked to choose which of
four pictures best illustrates the word. The PPVT-R correlated strongly with other
measures of intellectual functioning such as achievement test scores, and therefore, was
viewed as a useful indicator of school readiness. Raw scores were converted to standard
scores. The mean score for this sample was 76.71(§12= 17.04).

Performance of daily activities: The Vineland Adaptive Behavior Scales
(Sparrow et al., 1984) were used to assess the skills and adaptive behavior of the children
at 54 months. This measure was completed by the adolescent mothers. In this study,
four subscales were used: communication, daily living skills, socialization, and motor
skills. The possible ratings ranged from: 2 (yes or usually) to 0 (no or never). The
standard scores were converted from raw scores. Standard scores for the four subtests
were summed and converted to a total standard score. The mean score for this sample

was 100.23 (S_D:15.05).

40

Social skills: The children’s social skills were assessed with an adaptation of the
Social Skills Rating System-Parent Form (Gresham & Elliott, 1990). The measured was
completed by the adolescent mothers when their children were 54 months old. There are
16 questions on positive socials skills such as “my child follows my rules” and “my child
makes friends easily.” Cronbach’s alpha for the social skills scale was .76. There are 11
questions on behavior problems such as “my child has temper tantrums” and “my child is
mean to other children.” The possible ratings were: 2-usually, l-sometimes, and O-never.
Cronbach’s Alpha for behavior problems was .69.

Children’s school performance in first and second grafl

Children academic achievement: The academic achievement of the children was
assessed by using the Peabody Individual Achievement Test- Revised (PIAT-R)
(Markwardt, 1989) in the fall semester of first grade and the teachers’ ratings of academic
performance at the end of first and second grade. In this study, four subscales of the
PIAT-R were used: general information, reading recognition, reading comprehension,
and mathematics. Grade level standard scores for the four subtests were averaged to
obtain a total achievement test score for each child. The mean score for this sample was
90.17 SD=11.00) which is below the average score for the children this age in the
population (i.e., 100). The range of scores was 61-11975.

The teachers were asked to assess children’s academic performance on children’s
reading, math, and overall academic performance relative to other children in the same
grade at the end of first and second grade. Each rating was made on a 5-point rating

scale. The possible ratings ranged from: 5-superior (highest 20%) to 1- much below

average (lowest 20%).

41

 

Social competence and behavior problems: The children were assessed on social
competence and behavior problems with the Social Skills Ratings System-Teacher Form
(SSRS-T) (Gresham & Elliott, 1990). The measure was completed by teachers at the end
of first and second grade. There are 30 items of positive social behaviors such as
“attends to your instructions” and “controls temper in conflict situations with peers.”
There is a 3-point rating scale. The possible ratings were: 2-very often, l-sometimes, and
O-never. Cronbach’s alphas for social skills for this sample were .92 for both the first and

second grade assessments. There are 18 behavior problems such as “fights with others”

 

FF’LWJ

and “threatens or bullies others.” The teachers rated these behaviors by using the same
rating scales used to rate positive social behaviors. Cronbach’s alphas for behavior
problem were .91 for both the first and second grade assessments.

Children ’s academic motivation: The teachers rated children’s academic
motivation by using the Pupil Behavior Inventory (PBI) (Vinter et al., 1966) at the end of
first grade. This measure consists of nine items measuring academic motivation such as
“is motivated toward academic performance” and “positive concern for own education.”
Items are scored on a 5-point rating scale. The possible ratings ranged from 5- very
fi'equently to l-very infrequently. Cronbach’s alpha for this sample in first grade and

second grade were .93 and .94 respectively.

42

Conceptual Model and Hypotheses

Conceptual model

The conceptual model is presented in Figure 3 (p. 44). It shows the hypothesized
relationships among the variables. In this study, parenting, children’s competencies prior
to school entry, maternal support for academic success, and children’s school
performance in first grade were expected to predict children’s school performance in
second grade.

Hypotheses

In this study, six hypotheses were tested to answer the question stated earlier
regarding what factors relate to the school performance of the second grade children born
to adolescent mothers.

Hypothesis 1: Adolescent mothers’ supportive parenting during early childhood has a
positive direct effect on their children’s competencies prior to school
entry.

Hypothesis 2: Adolescent mothers’ supportive parenting during early childhood is
predictive of maternal support for academic success in first grade.

Hypothesis 3: Children’s competence prior to school entry has a positive direct effect on
children’s school performance in first grade.

Hypothesis 4: Maternal support for academic success has a positive direct effect on
children’s school performance in first grade.

Hypothesis 5: Children’s school performance in first grade has a positive direct effect on

children’s school performance in second grade.

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Hypothesis 6: Adolescent mothers’ parenting and maternal support for academic success
have positive indirect effects on children’s school performance in second
grade through children’s competencies prior to school entry and children’s

school performance in first grade.

Data Analyses

Overview of analyses

The analyses involved four main parts: descriptive statistics, correlations between
the exogenous and endogenous variables, path analyses, and a structural equation model.
The first step was to compute descriptive statistics (i.e., means and standard deviation)
which were used to determine the distributional characteristics of each variable. The
second part is an examination of the relationships among variables. Zero-order
correlations were calculated to determine the extent of associations among the exogenous
and endogenous variables. The third part is path analyses. A path analysis was used to
analyze the relationships among variables and to determine which of the predictor
variables had a direct or an indirect effect on the second grade outcome measure: social
adj ustment, academic performance, and academic motivation.

The last part is the structural equation model. The structural equation model
specifies the direct and indirect relationships among the latent variables and is used to
describe the amount of explained and unexplained variance (Schumacker & Lornax,
1996, p. 49-50). In general, structural equation models can be decomposed into two

submodels: a measurement model and a structural model. The measurement model

45

defines relations between the observed and unobserved variables. In other word, it
provides the link between scores on a measuring instrument (i.e., the observed indicator
variables) and the underlying constructs they are designed to measure (i.e., the
unobserved latent variables). In the case that a researcher has some knowledge of the

theory and/or empirical research of the underlying latent variable structure, the

E"
measurement model could draw relations between the observed measures and the
underlying factors a priori and then test this hypothesized structure statistically, which is ,
categorized as confirmatory factor analysis (CFA) (Byme, 2001). The structural model g

 

defines “relations among the latent variables. It specifies the manner by which particular
latent variables directly or indirectly influence changes in the values of certain other
latent variables in the model” (Byme, 2001, p. 12). The Hybrid model combines
measurement and structural models: multiple exogenous and endogenous variables that
can be either latent or observed (Kline, 1998, p.64).

In general, there are two steps of testing a structural equation model
(measurement model and structural model): model assessment and model respecification.

1. Model assessment: After developing a hypothesized model, then the next logical

step is to assesses how well the model adequately describe the sample data.

Ideally, evaluation of model fit should be based on several criteria that can assess

model fit from a diversity of perspectives. In particular, one should focus on the

adequacy of (a) the parameter estimates and (b) the model as a whole.

(a) The pagarneter estimatas;

The fit of individual parameters in the model involves three aspects of concern:

46

The feasibility of the parameter estimates: “The fit of individual
parameters in a model is to determine the viability of their estimated
values. Parameter estimates should exhibit the correct sign and size, and
be consistent with the underlying theory” (Byme, 2001, p.75). Examples
of parameters exhibiting unreasonable estimates are correlations > 1.00 or
signs which show the opposite direction that it should be.

The appropriateness of the standard errors: Poor model fit shows standard

 

errors that are excessively large or small. For example, if a standard error
approaches zero, the test statistic for its related parameter cannot be
defined. Likewise, standard errors that are extremely large indicate
parameters that cannot be determined. However, because standard errors
are influenced by the units of measurement in observed and/or latent
variables, as well as the magnitude of the parameter estimate itself, no
definitive criterion of “small” and “large” has been established (Byme,
2001)

The statistical significance of the parameter estimates: The test statistic
here is the critical ratio (on), which represents the parameter estimate
divided by its standard error; as such it operates as a z-statistic in testing
that the estimate is statistically different from zero. “Based on a level of
.05, the test statistic needs to be >i1.96 before the hypothesis (that the
estimate equals 0.0) can be rejected. Nonsignificant parameters can be

considered unimportant to the model” (Byme, 2001, p.76). However,

47

nonsignificant parameters can also be indicative of a sample size that is

too small.

(b) Model aaa whole:

The important aspects of fitting hypothesized models are the goodness-of-fit

statistics. There are a variety of measures which provide indicators of model fit.

However, the suggested measures are CMIN (x2), GFI, CF I, IFI, and RMSEA.

Minimum discrepancy (CMIN), most commonly expressed as a chi-square
statistic ()6), “represents the likelihood ratio test statistic or represents the
discrepancy between the unrestricted sample covariance matrix S and the
restricted covariance matrix 2(0). The probability value associated with x2
represents the likelihood of obtaining a x2 value that exceeds the x2 values
when H0 is true.” (Byme, 2001, p.79). The null hypothesis being tested is that
the postulated model holds in the population or specification of the factor
loading, factor variance/covariances, and error variances for the model under
study are valid [Ho: Z= 21(0)]. Thus, “the higher the probability associated
with x”, the closer is the fit between the hypothesized model (under Ho) and
the perfect fit” (Byme, 2001, p.79). If a probability is less than .05, it
suggests that the fit of the data to the hypothesized model is not entirely
adequate. The present data summarized in the model represents an unlikely
event (occurring less than five time in a hundred under the null hypothesis)
and should be rejected (Byme, 2001).

However, the x2 is very sensitive to sample size; that is if the sample size is

large, the index may be interpreted as a significant test. Therefore, some

48

researchers divided )6 values by degrees of freedom (ledf), which results in a
lower value. Although there is no clear-cut guideline about what value is

minimally acceptable, a frequent suggestion is less than 3 (Kline, 1998,

 

p.128).

The goodness-of-fit index (GFI) is a measure of the relative amount of IT
variance and covariance in S that is jointly explained by 2. “The index ranges
from zero tol .00, with values close to 1.00 being indicative of good fit. A ;
cutoff value of .95 was considered representative of a well-fitting model” rm

(Byme, 2001, p. 82).

The comparative fit index (CFI): The CFI has shown a tendency to
underestimate fit in small samples which take sample size into account. “The
value of CFI range from zero to 1.00. A cutoff value close to .95 was
considered representative of a well-fitting model” (Byme, 2001, p. 83).

The incremental index of fit (IFI) was developed to address the issues of
parsimony and sample size which were known to be associated with the
normed fit index (NF I). Its computation is basically the same as the NFI,
except that degrees of freedom are taken into account. “Consistent with the
CPI, it yields values ranging from zero to 1.00, with values close to .95 being
indicative of good fit” (Byme, 2001, p.83).

The root mean square error of approximation (RMSEA) takes into account the
error of approximation in the population and asks the question, “How well
would the model, with unknown but optimally chosen parameter values, fit

the population covariance matrix if it were available?” (p.83). This

49

discrepancy, as measured by the RMSEA, is expressed per degree of freedom,
thus making the index sensitive to the number of estimated parameters in the
model (i.e., the complexity of the model); “values less than .05 indicate good
fit, and values as high as .08 represent reasonable errors of approximation in
the population. Value greater than .10 indicate poor fit” (Byme, 2001, p.85).
. Model respecification: If given findings indicate an inadequate goodness of fit,
the next logical step is to detect the source or areas of misfit in the model. There
are two types of information that can be helpful in detecting model
misspecification: the standardized residuals and the modification indices. After
analyses of the information from modification indices, the researcher can decide
whether or not to respecify the model.

In summary, the data analyses in this study were as follows.

. Descriptive statistics (i.e., means, standard deviation) were calculated for each of
the measures of the variables to determine the distributional characteristics of

each variable.

. Zero-order correlations were calculated to determine the extent of associations

among the exogenous and endogenous variables.

. Path analyses were used to examine the relationship between exogenous and
endogenous variables.

. The measurement model (CFA) of this study is depicted in Figure 4. The
measurement model represents five one-factor models. The details of each model

are as follows.

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51

The first one-factor model is parenting which was measured by three ‘
observed variables: parenting skills at 54 months and quality of home
environment at 24 and 36 months.

The second one-factor model is children’s competence prior to school
entry, which was measured by the PPVT, the VABS, and social skills
rated by the young mothers. F

i

The third one-factor m4odel is maternal support for school success, which I

was measured by reading activities, maternal involvement in school

 

activities, and expectations for academic achievement.

The fourth one-factor model is children’s school performance in first
grade, which was measured by the PIAT, teachers’ ratings of academic
performance, the PBI, and the SSRS-T. Children’s school performance in
second grade is defined by teachers’ ratings of acaderrric performance, the
PBI, and the SSRS-T.

The fifth one-factor model is children’s school success in second grade
which was measured by teachers’ ratings of academic performance, the

FBI, and the SSRS-T.

The measurement model was analyzed based on the parameter estimates; if one of

five models does not fit, then the modification of a particular part of the model is needed.

After the measurement model is operating adequately, then the hypothesized structural

model is assessed. The structural model in this study was comprised of parenting,

children’s competencies prior to school entry, maternal support for school success, and

children’s school performance in first grade as predictive and intervening latent variables.

52

The design of the hybrid model is depicted in Figure 3. After the measurement model
has been approved, the evaluation of a hybrid model is processed. However, after the
findings of the goodness of fit indexes identified that the structural models was not

adequate, the next logical step was to detect the source or areas of misfit in the model.

Then the process of respecification of the model was undertaken.

53

CHAPTER 4
RESULTS
This chapter is divided into 5 parts. The first part describes demographic

characteristics of the sample. The second part presents descriptive statistics for each
variable. The third part shows the correlations among the key variables used in the
analysis. The fourth part presents a path analysis for each aspect of children’s school
performance assessed in this study, which includes academic achievement, academic
motivation, and social adjustment. The last part is a structural equation model of multiple

aspects of children’s school performance.

Demographic Characteristics of the Sample

Demographic characteristics of the sample included child’s age and gender;
mother’s age, education, and marital status; and family size. The total number of
children in second grade whose school performance was rated by their teachers was 90.
Fifty-nine percent were male and 41% were female. Sixty percent were African-
American, 31% were Caucasian, 3% were Hispanic, and 6% were bi-racial. Age of
children ranged from 88 months (7 years) to 107 months (8 years) with a mean age of 97
months.

There was no information collected on the adolescent mothers when their children
were in the second grade. The latest information related to the adolescent mothers was
obtained by interviewing them when their children were in the first grade. The age of the

young mothers ranged from 20 to 26 years with a mean age of 23 years. The information

54

showed that most adolescent mothers were not married (74%). Eighty-four percent of
mothers lived in their own home or apartment, 10% lived with their parents, 3% lived
with their grandmothers, and 2% lived with their friends. Information about their
education revealed that 66% of the adolescent mothers had graduated from high school
when their children were in the first grade and 32% of all the mothers were in college or
vocational school. The adolescent mothers had an average of 2 children, and 26% of the

mothers had only one child.
Descriptive Statistics

Ninety children were rated by their teacher at the end of second grade on their
school performance which included academic performance, academic motivation, and
social adj ustrrrent. Academic performance, which included reading and mathematics,
was rated by using a five-point rating scale ranging from lowest 20% (much below
average) to highest 20% (superior). The percentage of children in each category for
reading performance was: 14 (superior), 19 (above average), 26 (average), 28 (below
average), and 13 (much below average). The percentage of children in each category for
mathematics was: 9 (superior), 18 (above average), 28 (average), 32 (below average), and
13 (much below average). An overall teachers’ rating of academic performance was
obtained by summing their reading and mathematics ratings. The range for overall
academic scores was 2-10 with a mean of 6.30 (SD = 2.26).

The second school performance measure was the Pupil Behavior Inventory (PBI),

which assessed academic motivation. The range of possible scores on this 9-item scale

55

was from 5 to 45; the actual scores ranged from 9 to 45 with a mean of 3 1 .70 (SD= 8.34).
Overall academic motivation was also rated by teachers using a five-point rating scale
ranging from lowest 20% (much below average) to highest 20% (superior). The
percentage of children in each category of academic motivation was: 13 (superior), 26
(above average), 34 (average), 20 (below average), and 7 (much below average). The
mean overall academic motivation scores was 3.19 (SD=1.11).

Social adjustment was measured with the Social Skills Ratings System-Teacher
Form (SSRS—T). The total score was a combination of social skills and behavioral
problems scores. The range of possible scores on this 48-item scale was from 0 to 96; the
actual scores ranged from 21-93 with a mean of 63.54 (S_D=l7 .32). Overall children’s
classroom behavior was rated by using a five-point rating scale ranging from lowest 20%
(much below average) to highest 20% (superior). The percentage of children in each
category was: 20 (superior), 22 (above average), 31 (average), 17 (below average), and
10 (much below average). The mean overall classroom behavior score was 3.26

SD=1.24).

Correlations Among Measures

Correlatio&among parenting measures prior to school entry

Parenting and home environment during the first five years of children’s lives
were assessed by using different measures at different periods of time, and the
correlations among these measures are presented in Table 2. Adolescent mothers who

provided a positive home environment at 24 months tended to consistently provide a

56

positive home environment for their children at 36 months. Adolescent mothers who
provided a positive home environment for the children at 24 and 36 months tended to
receive high parenting skills ratings from the family advocates at 54 months.
Correlations among parenting support for ac_ademic success subscales in first 831$

Different aspects of maternal support for academic success during first grade were
measured, including maternal support for reading activities, maternal involvement in
school activities, and maternal expectations for school success. Adolescent mothers who
supported reading tended to have high level of school involvement and high expectations
for their children’s academic success (Table 2).

Adolescent mothers who provided a positive home environment at 36 months and
who had high parenting skills ratings tended to have a high level of involvement in
school and tended to participate more frequently in reading activities with their children
in first grade.

Correlations among children’s competencies prior to school entry and children’s school
performance in first and second grad;

Children’s competencies prior to school entry were assessed when the children
were 54 months old with a variety of measures from different sources, which included the
PPVT-R, the VABS performance in daily activities, and the SSRS-P social adjustment
measure. Children who had high receptive vocabulary scores tended to have high
Vineland Adaptive Behavior scores as rated by their mothers. However, counter to
expectations, children’s social adj ustment rated by their mothers at 54 months did not

relate to either children’s receptive vocabulary or Vineland scores.

57

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Children’s first grade school performance was assessed in the areas of academic
performance, PBI academic motivation, and SSRS-T social adjustment. Academic
performance was assessed by using the Peabody Individual Achievement Test-Revised
(PIAT-R) during the fall semester and teachers’ ratings of academic performance at the
end of the spring semester. Children who started school with high academic achievement
in the first semester, tended to perform well academically at the end of the year. In
addition, they were rated high on academic motivation and were viewed as well adjusted
at the end of the year. Children who had good performance in one area tended to have
good performance in other areas at the end of first grade (included in Table 2).

Consistent with the findings for first grade, children who performed well in one
aspect of school tended to do well in other areas at the end of second grade. For example,
children who had a high level of motivation tended to be rated high in academic
performance and tended to be well adjusted.

In general, children who had high competencies prior to school entry, including
high scores on receptive vocabulary and good performance in daily activities, tended to
have high scores on the PIAT-R in first grade. Their teachers also rated them high on
school performance at the end of first grade in all areas. They also did well in second
grade on the various indicators of school performance.

However, children’s social adjustment prior to school entry was not associated
with first grade school performance. Interestingly, children who had high social
adjustment scores prior to school entry had lower social skills and had higher behavior

problems scores in school at the end of second grade.

59

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Relations between home environment and parenting skills prior to and after school entry
and children’s competencies and school performm

As expected, children who lived in a positive home environment and had mothers
with high parenting skills in their early lives tended to be relatively competent prior to
school entry. This included receptive vocabulary and Vineland Adaptive Behavior scores

at 54 months. They also tended to have high scores on academic performance, academic

a...

motivation, and social adjustment in the first and second grade. The correlations ranged

from .24 to .64. Surprisingly, all aspects of maternal support for academic success were

‘fi'.

 

not related to children’s school performance in first and second grade except for a
relation between maternal expectations for children’s school success and academic

performance at the end of first grade.

Path Analyses

A path analysis was used to analyze the relationship between early home
environment/ parenting skills, children’s competencies at an early age, and children’s
school performance in second grade. In this study, different aspects of school
performance were measured. Each school performance outcome was examined
separately. Home environment at 24 and 36 months and advocates’ ratings of parenting
skills at 54 months were converted from raw scores to z scores and then averaged.
Maternal support for academic success in first grade was a total score combining support
for reading activities, school involvement, and maternal expectation for children’s

academic achievement.

6O

In addition, a structural equation model was used to examine the model similar to
the path analysis which focused on different aspects of school performance. However,
home/parenting was viewed as an exogenous latent variable which included three
observed variables: the quality of home environment that the adolescent mothers
provided for their children at age 24 and 36 months and the parenting skills of adolescent
mothers when the children are 54 months old. An endogenous latent variable was I
children’s competence prior to school entry (54 months), which included two observed
variables: the Peabody Picture Vocabulary Test-Revised (PPVT-R) and the Vineland
Adaptive Behavior Scales (VABS). Three endogenous variables were the Peabody
Individual Achievement Test (PIAT-R), and each aspect of school performance in first
and second grade.

Mum

The first outcome examined was social adjustment in second grade and the results
of the path analysis are presented in Figure 5 and Table 3. As expected, the result
showed that the PPVT-R and the VABS improved by .61 and .40 standard deviations
given a change in the home environment/ parenting skills of one full standard deviation
when other variables in the model were controlled. The PIAT-R improved .58 standard
deviations given a change in the PPVT-R of one full standard deviation. Social
adjustment in first grade improved .33 standard deviations given a change in the PIAT-R
of one full standard deviation. Social adjustment in second grade was directly predicted
to increase .24 and .34 standard deviations given a change of one standard deviation in

social adjustment in first grade and the PIAT-R respectively. Overall, home environment

61

and parenting skills predicted children’s social adjustment at the end of second grade
through the PPVT-R at 54 months, the PIAT-R, and social adjustment in first grade.

Children who experienced a home environment that supported cognitive
development and whose mothers had high parenting skills had higher scores on the
measure of receptive vocabulary at 54 months, had higher social skills and had fewer
behavior problems in first and second grade. Although home environment and maternal
parenting skills had both direct effect and indirect effects on maternal support for
academic success in first grade through the Vineland, maternal support for school success
in first grade did not contribute to children’s social adjustment in first and second grade.
This model explained 16% of the variance in children’s social adjustment in second
grade.

In addition, a structural equation model was used to examine the model similar to
path analysis model, focusing on social adjustment. Overall, the results were similar to
the path analyses except that the PIAT-R had no direct effect on social adjustment in

second grade. The results of these analyses are present in Figure 13 in Appendix A.

62

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Table 3. Predictors of Social Adjustment Scores: Partial Regression Analysis to Generate

Path Coefficients and Disturbance Variances

Criterion

1. Vineland
2. PPVT-R
3. PIAT-R

4. Maternal
support for
academic
success

6. Social
adjustment

1St grade

7. Social
adjustment
2Ind grade

Predictors

HOME/parenting
HOME/parenting
HOME/parenting
Vineland
PPVT-R
HOME/parenting
Vineland
PPVT-R

PIAT-R
HOME/parenting
Vineland
PPVT-R

PIAT-R
Maternal support
for academic
success
HOME/parenting
Vineland
PPVT-R

PIAT—R
Maternal support
for academic
success

Social adjustment

lSt grade

Regression coefficients
Unstandardizeda Standardized Adjus

8.10**(2.25)
13.38**(2.12)

-.18 (1.79)
.O9(.O8)
.39**(09)
.77* (.35)
.05**(02)
-.01(.02)
.01(.02)
2.62(3.25)
.23(.15)
.OO(.18)
.50*(22)
-.95(1.13)

1.24 (3.09)
.19(;15)
—.22 (.16)
.48* (.22)
.22*(12)

-.08 (1.07)

a The value in parentheses are standard errors
+ p<.10; *p<.05; "p<.01

64

.40
.61
-.Ol
.12
.58
.29
.43
--.10
.06
.12
.21
.00
.34
-.12

.06
.18
-.24
.34
.24

-.01

ted (11th
R2
.15** .85
.37** .63
.39** .61
.29** .71
.18** .82
.16** .84

ALademic performa_ng

The results presented in Table 4 and Figure 6 were obtained with academic
performance in second grade as the outcome variable. Academic performance in second
grade was directly predicted by the PIAT-R in the fall of first grade and academic
performance at the end of first grade. The standardized betas were .27 for the PIAT-R
and .38 for academic performance in first grade. This model is similar to the path
analyses model for social adjustment in second grade. Academic performance in second
grade was significantly predicted by home environment and parenting skills during the
preschool years through the PPVT-R, the PIAT-R, and academic performance in first
grade. Maternal support for academic success in first grade did not affect academic
achievement in first and second grade. All variables explained 39% of the variance in
academic achievement in second grade.

In addition, a structural equation model was used to examine the model similar to
path analysis model, focusing on academic performance. Overall, the results were
similar to the path analyses except that the PIAT-R had no direct effect on academic
performance in second grade. The results of these analyses are present in Figure 14 in

Appendix A.

65

 

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66

Table 4. Predictors of Academic Performance Scores: Partial Regression Analysis to
Generate Path Coefficients and Disturbance Variances

Regression coefficients
Criterion Predictors Unstandardizeda Standardized Adjusted (l-RZ)
R

l. Vineland HOME/parenting 8.10**(2.25) .40 .15“ .85
2. PPVT-R HOME/parenting 13.38**(2.12) .61 .37" .63
3. PIAT-R HOME/parenting -.18 (1.79) -.01 .39“ .61

Vineland .09(.08) .12

PPVT-R .39**(.09) .58
4. Maternal HOME/parenting .77“ (.35) .29 .29" .71
support for Vineland .05**(.01) .43
academic PPVT-R -.01(.02) -.10
success PIAT-R .Ol(.02) .06
5. Academic HOME/parenting -.09(.44) -.O3 .40" .60
performance Vineland .OO(.02) .01
1St grade PPVT-R .02(.02) .14

PIAT-R .14**(.O3) .58

Maternal support -.01(.15) .01

for academic

success
6. Academic HOME/parenting .30(.37) .1 1 .38“ .62
performance Vineland .02(.02) .16
2“d grade PPVT-R —.01(.02) -.04

PIAT-R .05*(.03) .27

Maternal support -.08(. 13) -.08

for academic

success

Academic .31**(.11) .38

performance 1St
grade

3 The value in parentheses are standard errors
i p<.10; ‘p<.05; "p<.01

67

Memic motivation

The results of the path analysis presented in Table 5 and Figure 7 show that
academic motivation of the children in second grade was directly predicted by the PIAT-
R in the fall semester of first grade and academic motivation at the end of first grade.
The standardized betas were .30 for the PIAT-R and .26 for academic motivation in first
grade. Once again, the results for children’s academic motivation were very similar to
the path analyses for children’s academic achievement and social adjustment in second
grade. Children who experienced a supportive home environment and had mothers with
high parenting skills had higher PPVT-R scores before entering school. They also had
high academic achievement scores at the beginning of school. As a result, these children
had higher motivation to learn in first and second grade. In the path analyses models for
social adjustment and academic performance, the VABS did not predict either of the
children’s outcomes. In contrast, the VABS was related to children’s academic
motivation in first grade. The children who had high performance in daily living skills
before entering school had high academic motivation to learn at the beginning of school,
which in turn predicted high academic motivation at the end of second grade. All
variables in this model explained 21% of the variance in motivation scores in second
grade.

In addition, a structural equation model was used to examine the model similar to
the path analysis model, focusing on social adjustment. Overall, the results were similar
to path analyses except the direct effect of PIAT-R on academic motivation in second

grade and direct effect of children’s competencies prior to school entry (VABS) on first

68

grade academic motivation were not found in the SEM model. The results of these

analyses are present in Figure 15 in Appendix A.

69

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Table 5. Predictors of Academic Motivation Scores: Partial Regression Analysis to
Generate Path Coefficients and Disturbance Variances

Regression coefficients

Criterion Predictors Unstandardized’ Standardized Adjusted (1-112)
R
1. Vineland HOME/parenting 8.10**(2.25) .40 .15" .85
2. PPVT-R HOME/parenting 13.38**(2.12) .61 .37" .63
3. PIAT-R HOME/parenting -.18 (1.79) -.01 .39" .61
Vineland .09(.08) .12
PPVT-R .39**(.09) .58
4. Maternal HOME/parenting .77* (.35) .29 .29“ .71
support for Vineland .05**(.02) .43
academic PPVT-R -.Ol(.02) -.10
success PIAT-R .01(.02) .06
5. Academic HOME/parenting .94(1.56) .08 .29" .71
motivation Vineland . 14+(.O7) .25
1st grade PPVT-R -.02(.08) -.04
PIAT-R .36**(.10) .47
Maternal support -.57(.54) -.13
for academic
success
6. Academic HOME/parentin g -.O7(1.47) -.OO .21 * * .79
motivation Vineland .O7(.O7) .14
2“d grade PPVT-R -.Ol(.08) -.03
PIAT-R .20+(.l 1) .30
Maternal support -.20(.52) -.05
for academic
success
Academic .23’(.12) .26

motivation 1st
grade

3 The value in parentheses are standard errors
i p<. 10; ‘p<.05; "p<.01

71

Structural Equation Modeling

A structural equation model (SEM) was used to assess the relationships among
several latent variables. The proposed model (Figure 8) included one exogenous latent
variable, parenting, with three observed variables: the quality of home environment that
the adolescent mothers provided for their children at age 24 and 36 months and the i
parenting skills of the adolescent mothers when the children were 54 months old. The

four endogenous latent variables were: children’s competencies prior to school entry,

 

maternal support for academic success in first grade, and school performance in first and
second grade. Children’s competencies prior to school entry included three observed
variables: the Peabody Picture Vocabulary Test-Revised (PPVT-R), the Vineland
Adaptive Behavior Scales (V ABS), and the social adjustment of children based on ratings
by the mothers. Maternal support for academic success included three observed
variables: reading activities, maternal involvement in school activities, and maternal
expectations for children’s academic success. Children’s school performance in first
grade included teachers’ ratings of academic performance, the Pupil Behavior Inventory
(PBI) which assessed academic motivation, the Social Skills Ratings System (SSRS-T)
which assessed social adjustment and the Peabody Individual Achievement Test-Revised
(PIAT-R). Children’s school performance in second grade included teachers’ ratings of
academic performance, the FBI, and the SSRS-T.

Home environment! parenting skills of the adolescent mothers were expected to
predict children’ s competencies prior to school entry and maternal support for academic

success in first grade. Children’s school performance in first grade was expected to be

72

predicted by children’s competencies prior to school entry and maternal support for
academic success in first grade. Children’s school performance in first grade was

expected to predict children’s school performance in second grade.

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73

Distribution and m_atrix to be analyzed

The sample in this study has missing data as expected in any longitudinal data set.
In order to analyze data by using structural equation model, a complete data set is
required. The estimation maximum (EM) method was employed to estimate missing data
with the SYSTAT program (version 10). This procedure requests the EM algorithm to
estimate covariance matrices. The data estimation was done at 2 separate times. If a
subject was missing data in home/parenting or parent support for academic success
categories, the data point was estimated using values from these two categories. On the
other hand, if a subject was missing data in children’s competencies prior to school entry
or children’s school performances in first grade, the data point was estimated using the
values from these two categories. Missing values were not estimated if a subject was
missing data for school performance in second grade. Table 6. presented a covariance
matrix with standard deviations, means, skeweness, and kurtosis for each variable which
was obtained from data estimation. All variables have univariate normal distributions
based on the standard that an absolute value of univariate skew indexes greater than 3.0
and an absolute value of the kurtosis index greater than 10.0 are serious problems (Kline,
1998). The estimation procedures that are widely used in SEM assume normal
distributions; non-normality can violate the assumption, which may affect the fit of the

model (Schumacker & Lornax, 1996).

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75

Method of estimafion

The-specified model was tested to obtain standardized coefficients by using the
maximum likelihood (ML) method of estimation. The ML allowed analyzing all
parameters at once rather than separately analyzing each endogenous variable (Kline,
1998, p.125). The ML also performs reasonably well under a variety of less-than-optimal
analytic conditions such as a small sample size (Hoyle & Panter, 1995 p. 163).
Mement model

The measurement model was examined to confirm convergent and discriminant
validity. To test the measurement models (Confirmatory Factor Analyses), a structural
equation modeling approach using AMOS 4 (Arbuckle, 1995) was employed.

Model 1 CFA

The hypothesized model (Figure 9) represented the associations among five
factors: home environment/parenting, children’s competencies prior to school entry,
maternal support for academic success, children’s school performance in first grade, and
children’s school performance in second grade. The first model has the following fit
indices: chi-square (94, N=89) = 211.94, p<.001, chi-square/df = 2.25, CFI=.82, IF I=.83,
GFI= .78, RMSEA= .12, indicating poor fit. Although the chi-square is significant, the
chi-square/df ratio is somewhat low (less than 3) which is considered an acceptable fit
(Kline, 1998, p. 128). However, the values of the fit indicies were less than .90,
indicating that the model was a poor fit. The RMSEA was over .10, indicating that this
model is a poor fit (MacCallum, Browne, & Sugawara, 1996). Inspection of the
standardized parameter estimates indicated that two factor loadings were very low; the

loading of mother-rated social adjustment at 54 months on children’s competencies prior

76

to school entry (.23) and the loading of mother-reported expectations for academic
success on maternal support for academic success (.24), which suggested that these
indicators have a high proportion of unique variances. Because each factor represented
different constructs and different times, social adjustment at 54 months and maternal
expectations could not be used as indicators of another factor. Although home
environment/parenting was significantly correlated with maternal support for academic
success in first grade (.73), the correlations between maternal support for academic
success and school performance in first grade and second grade were not significant and
very low (.18 and .14 respectively), which showed that maternal support for academic
success did not relate to school performance in first and second grade.

The standardized residual values showed 4 large residual values, based on the
cutpoint exceeding 2.58 (J oreskog & Sorbom, 1998), which were the covariance between
social adjustment at 54 months and in second grade (—3.84), the covariance between
social adjustment at 54 months and PBI academic motivation in second grade (—2.92), the
PPVT-R and the PIAT-R (2.61), and the PIAT-R and academic performance in second
grade (2.64).

Based on the reasons mentioned above, the measurement model was respecified
by dropping an observed variable, which was social adjustment at 54 months and one

factor, which was maternal support for academic success.

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Model 2 CFA

The respecified measurement model (Figure 10), a four-factor model, was
analyzed with CFA. Its overall fit to the data did not improve. The fit indices were chi-
square (48, N=89) = 133.73, p<.001, chi-square/df = 2.78, CFI=.8S, IFI=.86, GFI= .80,
RMSEA= .14, indicating poor fit. This model needed a respecification.

The inspection showed that all factor loadings were acceptably high and the
correlations between factors were not excessively high or low. The inspection of the
correlations residuals suggested that correlations residuals among variables were very
high. The seven highest covariances among variables ranged from 8.94 to 15.08. The
correlations included two sets of observed variables of first grade school performance:
PBI motivation and social adjustment and FBI academic motivation and the PIAT-R.
These patterns suggested that the measurement errors within the same period of time,
measured by the same person may covary. There were correlations of the similar
measure at different periods of time: social adjustment in first and second grade,
academic performance in first and second grade, the PPVT-R and the PIAT-R, and the
PIAT-R and academic achievement in second grade. Moreover, the measures, which
have a similar pattern but were measured in different periods of time may also covary.
Such measurement error correlations may reflect common method variance.

The measurement errors suggested to correlate the residuals included the VAB
and academic achievement in first grade, the PPVT-R and the PIAT-R, teacher-rated
academic motivation and teacher-rated social adjustment in first grade, the PIAT-R and
academic motivation, the PIAT-R and academic achievement in second grade, academic

achievement in first and second grade, and teacher-rated social adjustment in first and

79

 

second grade. Therefore, the measurement model was respecified by adding the

correlation residuals between the seven pairs of variables as suggested.

80

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Model 3 CFA

The respecified measurement model, a four-factor model adding correlations
among residuals (Figure 11), was analyzed with CFA. Its overall fit to the data seems
satisfactory. The fit indices were chi-square (41, N=89) = 54.56, p>.05, chi-square/df =
1.33, CFI=.98, IFI=.98, GFI= .91, RMSEA= .06, indicating an acceptable fit. In
assessing the extent to which a respecified model exhibits improvements in fit, the two
models (model 2 and model 3) were tested for statistical significance. Results presented
in Table 7 are the chi-square difference test between the two models showing the
comparison of model 2 ()8 [48]=133.73) with model 3 (x? [40]=54.56). Model 3 is
improved significantly from model 2 ( A} [8] = 79.17).

All of the standardized factor loadings were significant and exceeded .45. The
values of the factor correlations were not excessively high and all of the correlations were
significant at .05. Once the measurement model was satisfied, the evaluation of the

structural model could proceed.

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Model testing

Model 4 Hybrid model

Measurement model 3 was respecified as a hybrid model in which
home/parenting is an exogenous variable and the children’s competencies prior to school
entry, and school performance in first and second grade were endogenous variables
(Figure 12). The hybrid model had adequate fit: chi-square (44, N= 89) = 56.28, p>.05,
chi-square/df=1.28, CFI = 0.98, IFI= .98, GFI = 0.91, RMSEA= 0.06. Comparing the
baseline model with model 4, there was no significant difference between the 2 models
( )8 [4] = 1.72). This result indicated that the paths from home/parenting to school
performance in first grade, from home/parenting to school performance in second grade
and from children’s competencies prior to school entry to school performance in second
grade did not differ significantly from zero. Path coefficients that were statistically
significant were the direct effect standardized path coefficients from home/parenting to
children’s competencies prior to school entry (.75), from children competencies prior to
school entry to children’s school performance in first grade (.62), and from school
performance in first grade to second grade (.61). All factor loadings were statistically
significant at .05. This model explained 37% of the variance of children’ 5 school
performance in second grade. As expected, children who lived in a more supportive home
environment and had mothers with higher parenting skills during the preschool years had
higher competencies prior to school entry. In turn, they also had higher school

performance at the beginning of school and in second grade.

84

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86

CHAPTER 5

DISCUSSION AND CONCLUSION

This chapter is divided into three parts. The first part presents a summary of the
findings and discussions. The second part presents the limitation of this study. The last

part presents recommendations for future research.

Summary of the Findings and Discussions

The main purpose of this study was to investigate factors which contribute to
individual differences in the school performance of second grade children born to
adolescent mothers. Two specific questions were addressed: (1) how do parenting
practices during the first five years relate to maternal support for academic success in first
grade and to children’s school performance in second grade? And (2) how do children’s
competencies prior to school entry relate to their school performance in first and second
grade?

In this first section, finding pertaining to the research questions and hypotheses
are summarized and discussed. Six hypotheses were tested to answer the question stated
earlier regarding what factors relate to the school performance of second grade children

born to adolescent mothers.

87

Hypothesis 1

The first hypothesis was that adolescent mothers’ supportive parenting during
early childhood has a positive direct effect on their children’s competence prior to school
entry.

The results from the path analyses showed that children who experienced home
environments that supported their cognitive development and had mothers with positive
parenting skills had higher receptive vocabulary and Vineland Adaptive Behavior scores
at 54 months. Consistently, the results from the structural equation model showed that
home environment/parenting skills predicted children’s competencies prior to school
entry. Thus, hypothesis 1 was supported.

The results from this study are consistent with other studies which have shown
that home environment in early childhood contributes to children’s cognitive
competencies at an early age (Dubow & Luster, 1990; Moore & Snyder, 1991). A
number of researchers have found that quality of parent-child interactions, specifically,
maternal positive interactions, sensitivity to children’s requests and feelings, and warmth,
are significantly associated with early academic achievement, cognitive development,
and language development such as receptive vocabulary scores (Barratt, 1991; Hann et
al., 1996; Hess et al., 1984; Miller et al., 1996). Maternal responsiveness and verbal
reinforcement predicted vocabulary growth during the first 5 years of life (Morrison &
Cooney, 2001).

Parental control, such as setting and maintaining rules, standards, and limits
establishes parental authority and creates a supportive, structured context for children’s

cognitive development. Morrison and Cooney (2002) found that parental control had an

88

indirect relationship with children’s academic achievement during the early school years
through child’s developing social skills (independence, responsibility, self-regulation,
and cooperation).
Hypothesis 2

The second hypothesis was that adolescent mothers’ supportive parenting during
early childhood is predictive of maternal support for academic success in first grade.

The results showed that adolescent mothers who provided a positive home
environment at 24 and 36 months and who had high parenting skills ratings from the
advocates tended to have a high level of involvement in school. Moreover, mothers who
provided a positive home environment at 36 months and who had high parenting skills
ratings tended to participate more frequently in reading activities with their children in
first grade. As expected, the results from the path analyses showed that home
environment and maternal parenting skills had a positive effect on maternal support for
academic success in first grade. Thus hypothesis 2 was supported.

Maternal support for academic success in early elementary school was viewed as
a continuation of earlier positive parenting practices, which facilitated children’s
development, reinforced children’s competence, and promoted learning.
Hymthesis 3

The third hypothesis was that children’s competence prior to school entry has a
positive direct effect on children’s school performance in first grade.

In general, children who had high competencies prior to school entry, including
high receptive vocabulary and adaptive behavior scores, tended to have high scores on

the PIAT-R at the beginning of first grade. Their teachers also rated them high on school

89

performance in all areas at the end of first grade. The results from the path analyses
showed that the children’s receptive vocabulary assessed at 54 months predicted their
academic achievement at the beginning of the first grade. Receptive vocabulary at 54
months had an indirect effect on school performance at the end of first grade through
academic achievement at the beginning of first grade. The results from the structural
equation model showed that children’s competencies prior to school entry had a direct
effect on the children’s school performance in first grade. Thus, a hypothesis 3 was also
supported.

These findings are consistent with other studies (e. g. Kastner, May, & Hildman,
2001; Bramlett, Rowell, & Mandenberg, 2000), which showed that recognizing letters
and having verbal skills are predictors of academic achievement in first grade. Basic
academic competencies (e.g. vocabulary and reading) are viewed as a foundation for later
school performance. Children who entered first grade knowledgeable about letters and
words were at a lower risk for difficulties in reading. They could comprehend the
meaning of what they read. As a result, they had high academic achievement scores,
which measure children’s lmowledge based on their reading and math skills (T orgesen,
2001).
Hypothesis 4

The fourth hypothesis was that maternal support for academic success has a
positive direct effect on children’s school performance in first grade.

The correlational results showed that no aspect of maternal support for academic
success was related to children’s school performance in first grade except for a relation

between maternal expectations for children’s school success and academic performance

90

at the end of first grade. Mothers with higher expectations had children with relatively
high ratings of academic performance in math and reading at the end of first grade.
Contrary to expectations, the results fi'om the path analysis showed that maternal support
for school success in first grade did not contribute to any aspects of children’s school
performance in first grade, including social adjustment, academic performance, and
academic motivation. Thus, hypothesis 4 was not supported in this study.

The results differ from other studies, which found relationships between early
home environment-- such as home literacy activities and access to print (e.g., de Jong &
Leseman, 2001; Griffin & Morrison, 1997), involvement in school activities, such as
participating in school activities and serving as classroom volunteers (e.g., D’Agostino,
Hedges, Wong, & Borrnan, 2001) and parental expectations of children’s academic
success (Alexander & Entwisle, 1988)-- and academic achievement. However, in this
study, it is not clear why maternal support for academic success did not contribute to
children’s school performance. It could be that early positive parenting promotes
children’s school competence prior to school entry, which in turn has stronger effects on
children’s school performance in first grade than maternal support for academic success.
The children’s verbal and cognitive abilities prior to school are viewed as necessary skills
for later school performance. In addition, this study focused only on the quantity of
maternal involvement in school activities and reading activities but not the quality of
their participation. It would be desirable for a future study to include both quantitative
and qualitative measures. For example, future studies should explore the quality of
parental involvement in school, such as the amount of time mothers participate in

schools, as well as the quality of school related activities at home, such as the amount of

91

time spent helping with schoolwork and monitoring study time (Izzo, Weissberg,
Kasrow, & Fendrich, 1999).
Hypothesis 5

The fifth hypothesis was that children’s school performance in first grade has a
positive direct effect on children’s school performance in second grade.

The results from the path analyses showed that children’s first grade school
performance, including academic performance, PBI academic motivation, and SSRS-T
social adjustment, had a direct effect on children’s second grade school performance.
Children who had good performance in an area in first grade tended to perform well in
the same area at the end of second grade. In addition, academic achievement in first
grade measured with the Peabody Individual Achievement Test-Revised (PIAT-R) during
the fall semester indirectly predicted second grade teachers’ ratings of school
performance through first grade children’s school performance. The results from the
structural equation model also showed that children’s school performance in first grade
positively predicted school performance in second grade. Thus, hypothesis 5 was
supported.

This is consistent with other studies (e. g. Alexander, Entwisle, & Dauber, 1993;
Entwisle & Hayduk, 1988; Reynolds, 1991), which found that earlier academic
achievement in elementary school predicted later academic achievement. For example,
reading and mathematics scores in first grade predicted scores in second grade (Reynolds,
1991). Children who adjust easily into the student role in the first grade enhance their
own development later. The first two grades were considered a critical period for the

development of later school performance because children’s cognitive skills are

92

increasing rapidly and the cumulative nature of the curriculum makes it hard for a child
to achieve at a high level in later grades without achieving at a high level in earlier grades
(Entwisle & Alexander, 1998). Therefore, children who get off to a good start have a
competitive advantage from then on (Entwisle and Hayduk, 1988).

However, in addition to academic performance, children’s behaviors in first grade
also play an important role for later school performance. Alexander et a1. (1993) found
that classroom behaviors rated by teachers in the fall of first grade predicted both short-
terrn and long-term standardized academic achievement test scores and classroom
behaviors at the end of first grade and in fourth grade. Another study also found that
there were bi-directional relationships between academic achievement and social
competence over time from first grade through third grade (Welsh, Park, Widarnarr, &
O’Niel, 2001). Positive social behaviors were directly related to later academic
competence over time. Young children who were interested and involved in classroom
activities, followed the rules of the classroom, paid attention and spent more time on
tasks performed better academically than children who were uninterested or distracted.
These qualities contributed to test score gains especially during the first year (Alexander
etal., 1993).

Hypothesis 6

The last hypothesis was that adolescent mothers’ parenting and maternal support

for academic success have positive indirect effects on children’s school performance in

second grade through children’s competence prior to school entry and children’s school

success in first grade.

93

 

The results from the path analyses showed that home environment and parenting
skills predicted children’s second grade school performance including social adjustment,
academic performance, and academic motivation through the PPVT-R at 54 months, the
PIAT-R and school performance in first grade. Although home environment and
maternal parenting skills had both direct and indirect effects on maternal support for
academic success in first grade through the Vineland, maternal support for school success r
in first grade did not contribute to children’s school performance in first and second

grade. Consistently, the results from structural equation model of each aspect of school

 

performance were similar to the path analyses. The results from the structural equation r
model consistently showed that home environment/parenting skills had a positive effect
on children’s school performance in second grade through children’s competencies prior
to school entry and children’s school performance in first grade. Thus, hypothesis 6 was
partially support. Parenting during the preschool year had an indirect effect on second
grade achievement via children’s competencies prior to school entry and first grade.
However, maternal support from academic success in first graded did not have an indirect
effect on second grade achievement.

Supportive parenting and a high quality home environment in early childhood
promote the development of abilities and skills that are needed for early school success,
such as communication and interpersonal skills (Hess et al., 1984). Once a trajectory for
verbal and cognitive abilities that are necessary for good communication skills is
established prior to school entry, it strongly influences later literacy and school
achievement. Unfavorable early childhood environments often continue through later

childhood which are viewed as risk factors for their later development. On the other

94

hand, better quality home environments after the preschool years affect improvement in
cognitive ability in later life (Baydar et al., 1993). '

However, it seems likely that the relationships among home environment, early
school experience, and school performance are likely to be more complex than the tested
models which were limited by the availability of the data. The relation between home
environment and early children’s competence might not be viewed as unidirectional. A
post hoc analysis revealed that children who had high cognitive ability when they were
young, measured with the Bayley MDI at 18 months, tended to have mothers who
provided higher quality home environment at 36 months and had high parenting skills at

54 months. Precocious children may elicit more stimulating care from their mothers.

Limitations

Several limitations of this study should be acknowledged. First, a small sample
size of fewer than a hundred mothers and their children, as well as the attrition that is
natural to any longitudinal study, limited the types of analyses that could be conducted
and the power to detect relations among the variables. Second, the adolescent mothers
recruited in this study were from low-income families and were part of a family support
program. The findings of this study are only generalizable to similar populations. Third,
because this study included a secondary data analysis of longitudinal data set, the
analyses have been limited by the available data and the temporal order of when variables
were assessed. This constrained the models that could be tested and the analytic
techniques that could be used. For example, data on home environment after the children

were in school were not available, which precluded studying the effect of later home

95

environment and the change of home environment over a period of time on children’s
school performance. Home environment at the elementary level may also contribute to
children’s school performance. Fourth, this study focused on the effects of home
environment and the parenting practices of the adolescent mothers; thus only one
microsystem of the child was studied intensively. However, when the children were
young, they spent most of their time at home. Therefore, home environment and
parenting practices of adolescent mothers were viewed as fundamental factors
influencing the early competencies and later school performance of the children. After
the children entered school, other microsystems may also influence children’s school
performance, such as the school system, which includes teachers, peers, and school
quality. In this study, however, the children attended 47 different elementary schools. It
was not feasible to study all of those school environments. These limitations suggest

directions for future study.

Future Research

This study followed young adolescents mothers from pregnancy until their
children were in second grade. Future studies should focus on the years after second
grade in order to study the lasting effect of home environment, parenting, and early
children’s competencies on later children’s school performance such as in middle school
or high school.

Since this study focused on the microsystem of the children, which included home
environment/parenting and child characteristics, future research might continue to

explore other microsystems of the child such as the school, peers, and neighborhoods. For

96

 

example, research should explicate how the school environment, such as the instructional
environment and relationships between teachers and children as well as peers relate to
children’s school performance. The relationship between the quality of neighborhood
that the family resides in and children’s school performance should be explored also.
The quality of neighborhood may include perceptions of safety in the neighborhood,
witnessing violence, and resources for children such as a library and playgrounds. In

addition, future research should explore the effects of interactions between microsystems

 

on children’s school performance. For example, the interaction between home
environment and neighborhood characteristics on children’s school performance could be

examined.

Conclusions

The findings of this study have demonstrated that some children born to low-
income adolescent mothers could perform well in school, at least through second grade.
Consistent with Bronfenbrenner’s (1989) assumption that environments surrounding the
children influence their developmental outcomes, this study found that the caregiving that
these children received at an early age was an important factor, which contributed to their
positive developmental trajectories. Contrary to stereotypes regarding adolescent
mothers, some children lived in a positive home environment and had mothers with high
parenting skills; as a result, they had high competencies prior to school entry. It seems
likely that these differences in competencies at the beginning of school contributed to

later individual differences in school performances, at the end of first and second grade.

97

APPENDIX A

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101

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