Influences of School Environment on the Academic Achievement Scores of Adopted and Nonadopted Children

INTELLIGENCE 17, 79-104 (1993)

Influences of School Environment on the Academic Achievement Scores of Adopted and Nonadopted Children

HILARY COON

GREGORY CAREY

DAVID W . FULKER

J . C . DEFRIES

University of Utah and

University of Colorado, Boulder

Associations between academic achievement and characteristics of the school environ-

ment can result from direct environmental influences of the school, or from placement of

children into particular school environments based on prior ability. To disentangle these

potential influences underlying school effects on children, we analyzed data from parents

and first-grade adopted and nonadopted children in the Colorado Adoption Project. Mea-

sures analyzed included attending a private versus a public school, a variable aggregated

at the school level, and several variables aggregated at the classroom level. If such

aggregated measures are associated with many intercorrelated individual aspects of school

environment, each having a small effect on achievement, the process of aggregation may

offer additional power to detect these small individual environment effects. Several of

these aggregate variables, in addition to measures of children's attitudes about school,

showed direct environmental associations with reading and math achievement indepen-

dent of effects of parental IQ.

Resea rche r s have found ev idence for assoc ia t ions a m o n g var ious aspects o f the

schoo l e n v i r o n m e n t and ch i ld r en ' s a c h i e v e m e n t scores (e .g . , Brookover , Beady,

F lood , Schwei tze r , & W i s e n b a k e r , 1979; Cen t r a & Potter , 1980; G l a s m a n &

B in i am in ov , 1981; M a c P h a i l - W i l c o x & King , 1986; Purkey & Smi th , 1983;

Rutter , 1983; Spady, 1976; S t evenson , & Lee, 1990; S tockard & Mayber ry ,

This research was supported in part by grants HD-10333, HD-18426, and HD-19802 from the

National Institute of Child Health and Human Development (NICHD) and by grant MH-43899 from

the National Institute of Mental Health. The article was written while the first author was under the

support of training grant HD-07289 from NICHD. Preparation of the article was facilitated by grant

RR-07013-20 awarded to the University of Colorado by the Biomedical Research Grant Program,

Division of Research Resources, National Institutes of Health. We would like to thank Robert Plomin

and three anonymous reviewers for their suggestions and advice on an earlier version of the manu-

script. We would also like to thank Rebecca G. Miles for her expert editorial assistance.

Correspondence and requests for reprints should be sent to Hilary Coon, Department of Psychia-

try, University of Utah Medical School, 50 North Medical Drive, Salt Lake City, UT 84132.

79

80 COON, CAREY, FULKER, AND DEFRIES

1985). However, controversy remains over whether these associations reflect

true causal relationships between school environment and achievement. Parents

who send their children to schools with characteristics associated with high

achievement may themselves be more supportive or intelligent (Jencks, 1972;

Smith, 1972). Because parents and their children share genes for intelligence, an

observed association between school environment and child achievement may

occur because the school variable is correlated with parental IQ. Plomin,

Loehlin, and DeFries (1985) referred to this type of indirect association as

"genetic mediation" of the environment.

The question of causality has been particularly important in the debate over

the influence of private schools (Coleman & Hoffer, 1987; Hoffer, Greeley, &

Coleman, 1985). Higher achievement scores of Catholic school students may

result from more emphasis on academic subjects, more homework, or smaller

schools, reasons that would reflect a causal effect of the school environment

(Coleman & Hoffer, 1987). However, children in Catholic school also may come

from a selected population of more intelligent parents. Parents willing to spend

the extra money to place their child in a private school may be more supportive

and have higher academic expectations than parents with children in public

schools. Coleman and Hoffer argued for a direct causal effect between Catholic

school characteristics and achievement, citing results showing that children do

not perform at uniformly higher levels across all subjects. They asserted that

these children would have to be differentially more intelligent, or parents would

have to be more supportive only in certain areas, if Catholic schools had no

causal effects on children.

More direct evidence supporting or refuting these findings could be obtained

by investigating the association between school environment and the achieve-

ment scores of adopted children. In adoptive families, an observed school-

achievement relationship cannot be "genetically mediated" in the absence of

selective placement. Because adopted children and their adoptive parents are

genetically unrelated, even if choice of school is correlated with parental geno-

types for IQ (or other genetic factors that might influence achievement), the child

will not share these genotypes.

Although data from adoptive families provide the most powerful test of direct

environmental effects, adoption studies have focused primarily on the home

environment (e.g., Coon, Fulker, DeFries, & Plomin, 1990; Horn, Loehlin, &

Willerman, 1979; Plomin et al., 1985; Rice, Fulker, DeFries, & Plomin, 1988;

Scarr & Weinberg, 1978), and aspects of the school environment have not been

considered. In this analysis, we explore variables which may have influence on

achievement using data from children in the Colorado Adoption Project (CAP)

who have completed first grade. These variables fall into three broad categories

identified in the school environment literature: (a) private versus public schools,

(b) aspects of the classroom environment, and (c) attitudes about academics.

Most recent reviews agree that measures of the school resources, such as

SCHOOL ENVIRONMENT AND ACHIEVEMENT 81

expenditure per pupil, number of books in the library, and teacher-student ratio,

have shown little association with achievement (Averch, Carroll, Donaldson,

Kiesling, & Pincus, 1974; Centra & Potter, 1980; Coleman et al., 1966; Glasman

& Biniaminov, 1981; Hanushek, 1986; Jencks et al., 1972; Mosteller &

Moynihan, 1972; Purkey & Smith, 1983; Stockard & Mayberry, 1985). One

possible explanation for these results is that, although specific school charac-

teristics may influence children, each may have only a small effect. If this

multifactorial model is correct, then one approach might be to analyze the single

variable of private versus public school, which may serve as a composite for

many such intercorrelated aspects of the school environment. Investigating this

single aggregate measure may capture each of these small influences in one

amplified, and therefore, detectable, effect.

For example, consider the variable of student body composition (overall SES

and achievement level), which has been shown to be associated with individual

student achievement (Coleman et al., 1966; Jencks, 1972; Rutter, 1983). The

strength of this association may be amplified for two reasons. First, student body

composition probably serves as a correlate for many specific variables, such as

peer tutoring, level of competition, academic standards, and expectations of a

child's peer group, and even teacher job satisfaction. Each of these individual

variables' associations with achievement adds weight to the overall association

with the student body composition variable. Second, because student body com-

position is a schoolwide measure, it reflects the abilities of each individual

student. This aggregation across individuals who are similar is also a process of

combining many small effects, as though each student's achievement or SES

were items making up a scale of student body composition.

Whereas an aggregated measure, such as student body characteristics or pri-

vate versus public schools, may offer power to detect environmental influences,

this assumes similarity within the aggregate level of analysis (in this case,

schools), an assumption questioned by some researchers (e.g., Bronfenbrenner

& Crouter, 1983). So, while investigating this variable aggregated across

schools, we also explored more specific measures of classroom,environments.

Findings from the literature suggest that variables describing characteristics of

the classroom may have detectable environmental effects on school achievement.

Studies of classroom variables more often use measures pertaining to individual

teacher-student and student-student interactions and relationships, variables

that are more directly associated with the social aspects of school environment

rather than physical resources. Indeed, several recent studies investigating vari-

ables relating to school social variables have found significant associations with

achievement (Brookover et al., 1979; Rutter, Maughan, & Mortimore, Ouston,

& Smith, 1979). Attempts to pinpoint these effects have revealed significant,

consistent relationships with variables defining teacher performance (Brophy,

1979; Centra & Potter, 1980; Glasman & Biniaminov, 1981; Good, 1979; Purkey

& Smith, 1983; Stockard & Mayberry, 1985). These important teacher charac-


teristics include discipline methods and control, an emphasis on active instruc-

tion, an open and friendly atmosphere (particularly for younger children), well-

defined goals, higher expectations for achievement, and an emphasis on over-

coming feelings of futility and fatalism.

Children's sense of futility versus control over their environment, in addition

to other attitudes about school, appears to be one of the most important predictors

of achievement, and may provide a key to one of the mechanisms underlying

associations found with variables aggregated at higher levels. Even the Coleman

et al. (1966) report, with its abundance of negative findings, found an association

between such student attitudes and achievement: "Of all the variables measured

in the survey, including all measures of family background and all school vari-

ables, these attitudes showed the strongest relation to achievement" (p. 319).

Parental and teacher attitudes also appear to be important. Using a cross-cultural

design, Stevenson and Lee (1990) investigated achievement differences in Japa-

nese, Taiwanese, and American children and found evidence for several factors

that explained these differences: (a) emphasis on group participation in the class-

room, (b) realistic evaluation of children by both parents and teachers, (c) a

strong emphasis on achievement in the home and classroom, and (d) the underly-

ing assumption that effort rather than ability controls test scores. These results,

though perhaps not replicable on a sample of only American children, suggest

that parental, child, and teacher attitudes may all be important for achievement.

Although the CAP was not designed specifically to investigate school en-

vironment, data are available to examine several of the preceding variables. By

using the adoption design, we can begin to explore the nature of school-achieve-

ment associations.

METHOD

Sample The subjects for this study are participants in the Colorado Adoption Project

(CAP), a longitudinal adoption study designed to investigate genetic and en-

vironmental aspects of behavioral development. Adopted children were separated

from their biological mothers a few days after birth and placed in adoptive homes

within 1 month on average. Tests were administered to both biological and

adoptive parents of the adopted children. The adopted children were then tested

annually within 2 weeks of their birthdays. Tests were conducted in the children's

homes (ages 1-4) and through questionnaires and telephone interviews (ages 5

and 6). The children and their adoptive parents were brought into a laboratory

setting for an extensive test session after the child completed first grade, at 7.4

years of age c_, average. Information from teachers was also collected after first

grade. Younger siblings of the adopted children were also tested using this

longitudinal design.

In addition, the study includes a control group of nonadoptive families. Non-


adoptive families were matched to adoptive families on the basis of gender of the

proband child, number of children in the family, age of the father (--- 5 years),

occupational rating of the father (--- 8 points on the National Opinion Research

Center [NORC] rating), and total years of education of the father (--- 2 years).

Although levels of education and occupation in the CAP exceed the national

norms, the sample contains a wide range of subjects. Educational levels in the

nonadoptive and adoptive parents range from 6 to 22 years, with a mean of 15

years. Occupations range from floor layer, farm worker, and miner to engineer,

bank president, and surgeon. Further detail concerning the CAP can be found in

DeFries, Plomin, Vandenberg, and Kuse (1981), Plomin and DeFries (1985), and

Plomin, DeFries, and Fulker (1988).

Measures

The original adult test battery administered to CAP parents includes 13 tests of

specific cognitive abilities. To assess adult general cognitive ability, we used the

first unrotated principal component from these 13 scores after correcting for age

and gender effects (DeFries et al., 1981).

Aspects of the school environment may be associated differently with differ-

ent specific measures of academic achievement. To address this issue, we used

scores from achievement-oriented tests of both reading and mathematics skills.

Math achievement was indexed by three subtests from the Key Math Arithmetic

Test (Connolly, Nachtman, & Pritchett, 1976): Numeration, Addition, and Sub-

traction. Reading achievement was assessed through the Reading Recognition

subtest of the Peabody Individual Achievement Test (PLAT; Dunn & Markwardt,

1970) and two subtests (Producing Model Sentences and Processing Word and

Sentence Structure) from the Clinical Evaluation of Language Functions (CELF)

test battery (Semel & Wiig, 1980).

The achievement scores were age adjusted, and reading and math composite

scores were generated by forming first principal component scores from two

separate component analyses. The reading principal component had loadings of

.75, .81, and .54 for the PIAT, Model Sentences, and Procesiing Word and

Sentence Structure, respectively. This component explained 50.0% of the vari-

ance in the reading measures. In the second component analysis, loadings for the

three math tests were .80, .78, and .79 for Numeration, Addition, and Subtrac-

tion, respectively, and the component explained 62.7% of the total variance in

these three tests.

CAP measures of the first-grade school environment came from two sources.

Three items were used from the Social Adjustment Questionnaire: (a) child

bothered that school is too hard, (b) child bothered that school is too easy, and (c)

child bothered by academic pressure at home or in school. The Social Adjust-

ment Questionnaire is based upon the Coddington Life Events measure (Cod-

dington, 1972), but uses stressful events relevant to the first-grade experience.

The questionnaire was designed primarily to measure general emotional adjust-

8 4 C O O N , CAREY, F U L K E R , A N D DEFRIES

ment rather than attitudes about academics; however, we felt that because at-

titudes appear in the literature to be important for achievement outcomes, these

few measures should be included. The questionnaire was filled out by both

parents and children• If an item was endorsed, the parent or child entered how

severely the child was affected on a scale from 0 (not at all) to 3 (very much).

Given the young age of the children, the child ratings are likely to be somewhat

unreliable; therefore, parental ratings were also analyzed.

To determine if the child attended public or private school, and to assess

aspects of the classroom environment, a short questionnaire was administered to

all CAP families with children who had completed first grade (please see Appen-

dix A for a copy of this questionnaire). Questions followed either a yes-no

format or a multiple-choice format with three possible answers. Although the

questions were retrospective, the variables appear to measure meaningful dimen-

sions of the school environment. Principal-component analysis of the question-

naire items generated five factors--Private versus Public, Traditional,

Discipline, Orderly/Fair, and Competition--with eigenvalues greater than 1.0,

explaining 68.6% of the total variance (see Table 1 for factor loadings). Allowing

an oblique rotation generated low intercorrelations among factors (from - . 0 9 to

• 14); thus, an orthogonal solution was accepted. Estimates of the internal con-

TABLE 1

Principal-Component Analysis of First-Grade Environment Variables for 493 Adopted and

Nonadopted CAP Children

Schoo l Factor

Private/Public Traditional Discipline Orderly/Fair Competition

Private vs. public .93 - . 11 .02 - .00 - .04

Parochial vs. other .94 .06 .03 .05 .02

Catholic vs. other .87 .03 - . 0 5 .00 .06

Choice in activities .01 - .70 - . 0 1 .09 .10

Activi ty centers / .05 - . 6 8 .03 - . 3 4 - . 3 0

assigned seats

O w n work pace - . 0 7 - . 5 8 .15 .21 .16

Nontradi t ional / - . 03 - . 6 6 - . 15 - . 07 .01

tradit ional

Many rules .04 .05 .84 - . 0 7 .02

Rules often enforced - . 0 2 - . 0 8 .88 .04 - . 0 3

Fair vs. unfai r - .00 - . 3 1 - . 16 .62 - . 0 4

Loud vs. quiet - .07 - .21 - . 12 - . 7 8 .11

Many contests .05 - .06 - . 0 1 - . 16 .95

Eigenvalues and % Variance

Eigenvalue 2 .72 1.89 1.43 1.19 1.00

% variance 22.7 15.8 11.9 9 .9 8.3

Cumulat ive % 22.7 38.4 50.4 60.3 68 .6

Note. Boldface type indicates those items which defined the component .


TABLE 2

I tem Correlations for 46 Sibling Pairs Who

Attended First Grade at the Same School

Item Correlation

Private vs. public 1.00

Parochial vs. other 1.00

Catholic vs. other 1.00

Choice in activities .83

Activity centers/assigned seats .66

Own work pace .74

Nontraditional/traditional .55

Many rules .80

Rules often enforced .64

Fair vs. unfair .86

Loud vs. quiet .42

Many contests .65

sistency of the factors were computed using Cronbach's (1951) alpha coefficients

on the set of items which loaded on each factor. Items were standardized for unit

weighting. Alpha coefficients were as follows: .90 for Private versus Public; .62

for Traditional; .68 for Discipline; and .26 for Orderly/Fair (alpha cannot be

computed for Competition because it is a singleton factor).

Rough estimates of item reliability were obtained by using the 46 CAP fami-

lies having two children who had completed first grade in the same school.

Correlations between ratings for the first sibling and ratings for the second

sibling appear in Table 2. Although it is unknown whether the two siblings had

the same teacher, possible classroom environment differences (which would tend

to lower the correlations) may be offset by consistency in parental rating style for

the two siblings (which would tend to raise the correlations).

Model

We formulated the model shown in Figure 1 (p. 86) from one previously devel-

oped by Plomin et al. (1985) to assess genetic and environmental relationships

between measures of the home environment and child IQ. The model was altered

to allow children to be considered separately by gender and to analyze different

phenotypes in parents and children (IQ and academic achievement, respectively).

Using this model, we estimated the influence of each measure of the school

environment on children's phenotypes, an influence independent from the direct

effects of mother and father IQ phenotypes on the children.

Figure 1 depicts transmission effects in adoptive families assuming the hypo-

thetical case that Child 1 is female and Child 2 is male (subscripts f and m on

path coefficients denote female and male, respectively). Maternal and paternal

IQ phenotypes (PMo, PFa) may influence the children's achievement phenotypes

(Pol, Po2) through the environmental pathways t and u. In adoptive families,


/.t

r Mo,Sch ~ f r

School Environment

FIt,Sch

I

t, I w,/ XWm I Um

U t f m

Z I ~ J Z m

s m,!

Figure 1. Path model for the analysis of genetic and environmental transmission between adoptive

parents, children, and a measure of the school environment. Arbitrarily, Offspring 1 is female

(subscript f) and Offspring 2 is male (subscript m). Subscripts Mo, Fa, and Sch represent mother,

father, and school, respectively. The children's phenotypes for achievement (Po], Po2) are influ-

enced by the school environment independent of the direct effects of parental IQ phenotypes (PMo,

PFa)- Genetic associations between variables are zero in adoptive families (see text for further

explanation of variables and parameters).

variables can only be linked through these environmental pathways because the

parents and children are genetically unrelated. In nonadoptive families, this

transmission is increased by the genes shared between parents and children. The

genetic component of parent-offspring transmission (gMo, gFa) is the product of

the genetic correlation between parents and offspring (Vz), the square root of

heritability of IQ in the parents, and the square root of heritability of achievement

in the children (see Figure 2). Because IQ and achievement are not isomorphic,

heritability is not assumed to be the same in parents and children, and is therefore

not explicitly estimable (cf. Coon, Carey, & Fulker, 1990). Figure 3 (p. 88)

shows the associations among the variables in nonadoptive families.


11

Figure 2. Path models showing genetic transmission using a traditional parameterization (left) com-

pared to the simple parameterization used in this analysis that does not assume isomorphism between

IQ in the mother and achievement in the child (right). In the figure on the left, the IQ genotype of the

mother (GMo) influences the mother's observed IQ (PMo) by the amount hlo (square root of

heritability of IQ). Similarly, the achievement genotype of the child (Go) influences the child's

observed achievement score (Po) by the amount hgc h (square root of heritability of achievement).

The mother and child genotypes are correlated V2. In the figure on the right, these three parameters

(l/2hlQhAch) have been collapsed into the single parameter gMo.

The genetic contribution to the correlation between sibling pairs (gsib) will

also be zero in adoptive families. For nonadoptive sibling pairs, this correlation

will be the product of the genetic correlation between full siblings (V2) and the

heritability for achievement. Preliminary tests indicated that family resemblance

for parent-offspring and sibling pairs could be modeled using one parameter

(gFamily = gMo,m = gFa,m = gMo,f = gFa,f = gSib:m,m = gSib:m,f = gSib:f,f) ' This result indicates that in these data, heritability of adult IQ and heritability of child

achievement are not significantly different.

The school environment measure influences adopted children through the

direct environmental path w. In nonadoptive families, there is an additional

genetic component (gSch) because the school environment may be correlated

with the child's genotype for achievement. Such a correlation would occur if the

school measure were correlated with the parental genotypes contributing to

achievement, which the parents then transmit to their children (genetic mediation

of the school environment). Thus, the genetic association between the school

measure and child phenotype is the product of this parental genotype-school

correlation, the genetic transmission from parent to child for achievement, and

the heritability for achievement. Results from preliminary analyses indicated that

this parameter could be pooled across gender (gsch = gsch,m = gsch,f)"

The model also allows maternal and paternal IQ phenotypes to be correlated

Ix, and for each to be correlated with the school m e a s u r e (rMo,Sch , rFa,Sch ).


(i . . . . .

/,t

MO Environment Fa

g~

POl I I Po2

z f z

m

S m,f

Figure 3. Path model for the analysis of genetic and environmental transmission among nonadaptive

parents, children, and a measure of the school environment. Arbitrarily, Offspring l is female

(subscript f) and Offspring 2 is male (subscript m). Subscripts Mo, Fa, and Sch represent mother,

father, and school, respectively. The children's phenotypes for achievement (Pol, POE) are influ-

enced by the school environment independent of the direct effects of parental IQ phenotypes (PMo,

PFa)- Genetic associations among variables are now included (see text for further explanation of

variables and parameters).

Residuals (Uot, U o 2 ) may also influence the children's achievement phenotypes

through the z paths; these residuals are allowed to correlate between siblings.

Possible confounding effects using this model include selective placement and

child genotype-environment (GE) correlation. If an association occurs between

a school measure and the IQ of the child's birth parents, selective (nonrandom)


placement of the child has occurred. Correlations between the school environ-

ment of the adopted child and the IQ scores of the 216 matching biological

mothers were low, ranging from - . l l to . 10, indicating negligible selective

placement. In addition, there can be a correlation between a child's genotype and

environment such that a child with a certain genotype may expose himself more

to certain environments (Plomin, DeFries, & Loehlin, 1977). In this analysis,

this effect will only be important to the extent that the GE correlation involves

genetic influences not shared between parent and child (shared genetic effects

that are correlated with the environmental measures will be subsumed in the

genetic mediation pathway). Although such effects are not directly testable using

our model, indirect evidence can be obtained by using child cognitive ability at

age 4 as a predictor of the school environment measures. Such regressions

produced nonsignificant results, with multiple R scores ranging from .01 to .07

for the school questionnaire measures, and from .02 to .12 for the attitude

measures. This indicates minimal effects of the child's prior ability which are

independent of the genetic mediation effects through parental IQ.

Expectations for this model appear in Appendix B; note that the model also

provides estimates of the means and variances of the measures of school environ-

ment, of adult cognitive ability, and of child achievement. This model gives

estimates that are functions of the parameters of interest, rather than the param-

eters themselves. Likelihood-ratio chi-square statistics were used to assess fit.

For a more detailed description of model fitting with adoption data, see Coon,

Carey, and Fulker (1990) and Coon, Fulker, DeFiles, and Plomin (1990).

RESULTS

Parent-Offspring Transmission The influence of school environment on child achievement may be mediated by

influences of parental IQ. our model separates these two potential effects on the

child. Table 3 (p. 90) presents correlations of parent general intelligence and

child achievement scores. Approximate estimates of genetic and 'environmental

influences of parental IQ can be obtained by comparing the correlations for

adoptive families, for whom the association will be entirely environmental, with

those for nonadoptive families, for whom the association has both genetic and

environmental components.

Using this preliminary estimation method, a negative association between

mothers' IQ scores and boys' achievement appears in adoptive families, but not

in nonadoptive families. These contrary findings may suggest a negative en-

vironmental influence mitigated by a positive genetic effect. The positive cor-

relations between mothers and girls in both adoptive and nonadoptive families

provides evidence for a weak positive environmental effect. Fathers' IQ scores

and daughters' reading achievement scores show a strong positive association in

both adoptive and nonadoptive families, again suggesting a positive environmen-


TABLE 3

Correlations Between Parental General Intelligence and Child Achievement

Adoptive Families Nonadoptive Families

Child Measure n Mothers Fathers n Mothers Fathers

Math Achievement

Boys 117 - . 18 a* .05 149 .11 .18"

Girls 108 .17 a .03 123 .17" .16

All 225 - .05 .04 272 .13" .17"*

Reading

Achievement

Boys 114 - . 19 a* - . 00 147 .09 .25**

Gids 105 .16 a .23* 120 .10 .28**

All 219 - .05 .10 267 .09 .26**

aSignificant gender difference.

*p -< .05. **p -< .001.

tal effect. Math achievement in girls and both reading and math achievement in

boys appears to have only a genetic association with paternal IQ.

Gender differences were found in these correlations, and in several of the

correlations with school measures. These gender differences were unexpected

and may be due to chance. However, it is also possible that the gender of the

child may moderate parental and environmental influences on achievement at age

7. Considering both possibilities, we present all subsequent results separately by

gender and pooled across gender.

More rigorous tests of these associations can be obtained by fitting the model

shown in Figure 1 to CAP data. The preliminary results suggested by the correla-

tions are reflected in the maximum likelihood estimates of parameters associated

with parents and offspring. Table 4 presents these estimates from the model fit

with the private-public school factor; the estimates for models testing the other

school factors varied only in the second decimal place from those presented here.

The stability of these results across all school environmental measures indicates

that these parent-offspring parameter estimates are not dependent on which

environmental variable is tested. This stability is to be expected across the

univariate model results for each school environment measure; even if a school

variable is associated with parental IQ or child achievement, this association

should not affect the correlation between spouses or between parent and child.

The pooled estimates were taken from a model where all parameters were equat-

ed across gender; all other estimates were taken from the baseline models used in

the likelihood-ratio chi-square significance tests of parameters.

Model fitting confirmed the negative environmental effect of mothers on

boys' achievement (tin) and the positive influence of fathers on girls' reading

achievement (uf). For reading achievement, the residual correlation between

same-sexed sibling pairs and opposite-sexed pairs were significantly different,

SCHOOL ENVIRONMENT AND ACHIEVEMENT

TABLE 4

Maximum Likelihood Estimates for Parent-Offspring Parameters

91

Parameter Reading Math

Parent-Offspring Parameters

ix (marital correlation) .29 a .28 ~

gFamily (shared genetic effects) .13 a . l 0 a

Environmental transmission:

t m (mother-son) - . 15 a - . 12 t'c

tf (mother-daughter) .04 .13 b¢

tpooled (mother-child) - . 0 9 - . 03

Um (father-son) .10 .08

uf (father-daughter) .19a .04

upootea (father-child) .12 .05

Residuals

z (effect on child phenotype) .80 a .58 a

Ssame (residual r: same-sexed pairs) .62 ad .57 a

Sm. f (residual r: opposite-sexed pairs) - . 1 0 d .44 a

Spooled (residual r: all pairs) .47 a .53 a

Means and Standard Deviations

Xpa r .01 .01

XBoy(adopted )e . ! 5 a --.05

Xgirl(adopted) --. 11 a --. 15 a

Xpooled(adopted ) - - . 12 a - . 10 a

XBoy(nonadopted) . 1 2 a .26 a

XGirl(nonadopted) .10 --.07

Xpooled(nonadopted) .1 I a .10 a

O'pa r .99 a .99 a

OrChil d 1.07 a .99 a

Note. Parameters conform to those depicted in Figure 1, with the following simplifications:

z m = Zf = Z, Sra ,m = Ssame. Pooled estimates were obtained from models equating across gender.

aparameter estimate significantly different from zero.

bSignificant gender difference.

cParameters significantly different from zero only in test with two degrees of freedom.

dSignificant difference between residual correlations for same-sexed versus'opposite-sexed sib-

ling pairs. eAlthough means for boys and girls can be pooled within family types, means for adopted

children were significantly lower than means for nonadopted children.

r e f l e c t i n g d i f f e r e n c e s b e t w e e n a d o p t e d a n d n o n a d o p t e d c h i l d r e n a n d a t r e n d in

t h e d a t a f o r s a m e - s e x e d p a i r s to c o r r e l a t e m o r e s t r o n g l y t h a n o p p o s i t e - s e x e d

pa i r s . ~ T a b l e 4 a l s o p r e s e n t s e s t i m a t e d m e a n s a n d s t a n d a r d d e v i a t i o n s fo r p a r e n t s

a n d c h i l d r e n . F o r b o t h r e a d i n g a n d m a t h a c h i e v e m e n t , n o n a d o p t e d c h i l d r e n

qn nonadoptive families, the gender of the child is determined largely by chance, resulting in an

equal ratio of same-sexed to opposite-sexed sibling pairs. However, adoptive parents more often

choose opposite-sexed adopted sibling pairs. Because of this preference, in the CAP there were too

few same-sexed adoptive pairs (4 boy-boy and 9 girl-girl pairs) to make meaningful comparisons.


performed better than adopted children; however, differences were less than one

quarter of a standard deviation. Moreover, the standard deviations could be

pooled across groups. Because the analyses focus on correlation structures,

differences in variance are more important than mean differences; thus, the mean

differences should not influence the pattern of results.

School Factors

Table 5 presents correlations of school factor scores with parental IQ and child

achievement. Parental IQ and education appear to be largely unrelated to the

school factors. A similar pattern of low correlations appears for the children,

with a few notable exceptions. Because the overall correlation matrix does not

meet a multivariate test of significance (Steiger, 1980), interpretation of the

following univariate effects should be made cautiously. Strong discipline is asso-

ciated with lower reading achievement for both adopted and nonadopted girls,

indicating a negative environmental effect. For boys' math achievement, the

correlations suggest positive effects of private schools due to a combination of

TABLE 5

Correlations of School Questionnaire Factor Scores With Parental Measures and Child

Achievement Scores

School Factors

n Private/Public Traditional Discipline Order/Fair Competitive

Parental Measures

Mothers' IQ 363 .11 *

Mothers' educ. 369 .05

Fathers' IQ 359 .08

Fathers' educ. 370 .08

Reading Achievement

Adopted boys 107 .02

Adopted girls 97 .18

All adopted 204 .09

Nonadopted boys 126 .12

Nonadopted girls 111 .12

All nonadopted 237 .12

Math Achievement

Adopted boys 109 .15

Adopted girls 98 .05

All adopted 207 .06

Nonadopted boys 127 .21 *

Nonadopted girls 114 .06

All nonadopted 241 .14"

.03 .01 - . 0 3 - . 1 3 "

- . 0 5 .04 .05 - . 0 9

- . 0 4 .03 - . 0 3 - . 0 2

- . 0 8 - . 0 0 .03 - . 0 6

- . 0 4 .06 a .04 .02

- . 0 7 - . 2 4 a* .01 - . 0 3

- . 0 5 - . 0 6 .03 - . 01

- . 0 6 .02 a .11 - . 0 5

- . 0 4 - . 2 4 a* .02 - . 0 9

- . 0 5 - . 1 0 .07 - . 0 7

- . 0 9 .00 .14 .00

- . 0 4 --.16 - . 0 6 .03

- . 0 6 - . 0 6 .05 .02

- . 1 5 a - . 0 3 - . 0 8 .22 a*

.17 ~ - . 0 5 .02 - . 0 8 a

.02 - . 0 3 - . 0 4 .11

aSignificant gender difference.

*p -< .05.


genetic and environmental influences, and a genetically mediated effect of com-

petitive environment.

More rigorous model-fitting tests once again revealed much the same results

(see Table 6, pp. 94-95). A significant negative environmental effect of disci-

pline appears for girls' reading achievement (We), and the positive association of

boys' math achievement scores with competitive school environments is genet-

ically mediated (gSch,m)" Positive genetic mediation through the private school

factor appears for boys' reading achievement. The relationship between private

school and boys' math achievement remains inconclusive. Although the genetic

and environmental parameters (gsch,m and Wm) can be dropped individually from

the model, both cannot be dropped together, !2(2) = 9.42, p < .01. Thus,

private schools do have a significant effect on children, but the effect may be due

to a direct environmental association or to genetic mediation.

Estimated correlations between parental IQ and the school factors (rFa.S~h,

rMo,S~h) and school factor means and standard deviations are included for both

reading and math achievement to demonstrate the stability of the model. Al-

though a significant mean difference occurs for the private-public factor, stan-

dard deviations could be pooled across family type.

Results of overall tests of gender differences indicate that gender may be

important for all but the Order/Fair and Discipline factors when math achieve-

ment was the outcome variable. Because this test equates all parameters in the

model, the chi-square values that indicate a worsening in fit are also due to

gender differences in parent-offspring parameters (see Table 4).

School Attitudes

Because of small sample size and because no significant gender differences were

found in the correlations, analyses of the school attitudes measures were carded

out for children pooled across gender groups. As with the school factor scores,

associations between parental measures and ratings from the school events ques-

tionnaire are weak (see Table 7, p. 96). However, several substantial correlations

appear between child achievement and the school events ratings.dndeed, a test of

the overall matrix showed significant associations with achievement at the multi-

variate level [!2(45) --- 76.60, p < .005; Steiger, 1980]. Positive genetic media-

tion of distress over school being too easy appears for reading achievement;

children with a genetic background conducive to high achievement are bothered

by an unchallenging environment. Interestingly, this result occurs only for the

parent-rated item, though a weak trend toward genetic mediation occurs for the

child-rated item. The pattern of correlations between reading achievement and

distress over school being too hard suggests a negative environmental influence.

This same pattern emerges much more strongly for math achievement. Distress

over academic pressure also may have a direct negative influence on math

achievement, though evidence supporting this conclusion occurs only for the

parent-rated item.

~D

4

~

TA

BL

E

6

Est

ima

tes

of

Pa

ram

eter

s A

sso

cia

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cho

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act

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ram

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itio

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om

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itiv

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gsc

h,m

(b

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s)

.23

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00

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22

-.

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1

--.0

12

gsc

h,f

(g

irls

) --

.01

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5

--.0

37

--

.08

5

-- .

05

9

gsc

~ (

all

ch

ild

ren

) .1

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.0

50

-.

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9

-.0

73

-.

02

0

Dir

ec

t E

nv

iro

nm

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w m

(b

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1

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.0

64

-.

03

3

wf

(gir

ls)

.15

4

-.0

93

-.

22

3 a

b

.09

8

-.0

49

w

(all

ch

ild

ren

) .0

76

-.

05

8

-.0

26

.0

77

-.

03

6

Co

rre

lati

on

s w

ith

Pa

ren

tal

IQ

rFa,

Sch

(f

ath

ers

) .0

79

-.

03

8

.02

3

-.0

24

--

.03

7

rMo

,sch

(m

oth

ers

) . l

11

.0

34

.0

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02

9

-.

15

3 a

Me

an

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s

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a

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a

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1

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1

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2

1.5

52

1

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1

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p

<.0

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<

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.00

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.05

Ma

th

A

ch

iev

em

en

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ne

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gsc

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(b

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.18

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ab

gsc

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(g

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) .0

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86

--

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--

.03

1 b

gsc

h (

all

ch

ild

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) .0

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1

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nm

en

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(b

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- .0

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wf

(gir

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w

(all

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) .0

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01

.0

89

-.

05

7

Co

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lati

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s w

ith

Pa

ren

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IQ

rFa,

Sch

(f

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) .0

78

-.

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9

.02

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-.0

21

-.

05

0

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ch

(mo

the

rs)

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a

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est

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te t

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t g

en

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r d

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pa

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pa

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rs (

Ta

ble

3)

als

o c

on

trib

ute

to

th

is !

2.

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TA

BL

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7

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rrela

tio

ns

of

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oo

l E

ven

ts I

tem

s R

ate

d b

y P

aren

ts a

nd

Ch

ild

ren

Wit

h P

aren

tal

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asu

re

s a

nd

C

hil

d A

ch

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em

en

t S

co

res

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ren

t R

ati

ng

of

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ild

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tress

C

hil

d R

ati

ng

of

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ild

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tress

Sc

ho

ol

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o

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rd

Sc

ho

ol

To

o

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sy

A

ca

de

mic

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tre

ss

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ho

ol

To

o

Ha

rd

Sc

ho

ol

To

o

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sy

A

ca

de

mic

S

tres

s

Pa

ren

tal

IQ a

nd

Ed

uc

ati

on

Mo

the

rs'

inte

llig

en

ce

.1

5

-.0

3

.01

-.

02

.0

6

.02

Mo

the

rs'

ed

uc

ati

on

-.

01

.0

1

-.

11

.0

7

.02

.0

7

Fa

the

rs'

inte

llig

en

ce

-.

01

.I

1

.04

-.

06

.1

2

.09

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the

rs'

ed

uc

ati

on

.0

4

.10

-.

08

-.

07

.0

7

.18

"*

n

13

9

10

2

14

0

16

8

22

8

18

9

Ch

ild

A

ch

iev

em

en

t

Ad

op

ted

ch

ild

ren

Re

ad

ing

a

ch

iev

em

en

t -.

1

6

.01

-.

1

0

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2*

-

.04

-.

02

Ma

th

ac

hie

ve

me

nt

-.3

2"

**

.1

8

-.2

8"

*

-.3

4"

**

-.

1

3

-.

12

n

91

5

2

89

1

11

1

35

1

30

No

na

do

pte

d

ch

ild

ren

Re

ad

ing

ac

hie

ve

me

nt

-.

19

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1"

**

-.

07

.0

1

.10

-.

07

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th

ac

hie

ve

me

nt

- .2

6*

.0

3

-.

10

-.

1

8

.07

-

.01

n

84

8

9

86

1

05

1

68

1

17

*p

--

< .0

5.

**

p

--<

.01

*

**

p

--<

.00

5.


Table 8 (p. 98) presents parameter estimates from model fitting of the school

attitudes measures. For reading achievement, significant genetic mediation

(gSch) was confirmed only for the parental rating of the child's distress that

school is too easy. In addition, children's feelings that school was too hard

reflected a direct environmental influence of schools (w), although the estimate

of positive genetic influence for this variable approaches significance. Table 8

also shows a direct negative environmental association (w) between math

achievement and both child and parental feelings that school was too hard. For

the child-rated item, positive genetic mediation again mitigates this direct nega-

tive effect. As with the school factor analysis, parental correlations with school

events measures (rMo,Sch, rFa,Sch) and means and standard deviations demon-

strate the stability of the model. No mean differences were found for the school

events measures.

DISCUSSION

Although parental IQ appears to influence child achievement, our analysis sepa-

rates these influences from the effects of school environment. The negative

environmental influence of maternal IQ on boy's achievement scores is, at first, a

surprising finding. However, mothers with higher intelligence tend to have more

prestigious jobs (the correlation between intelligence and NORC job rating is

.20, p < .01). Among the complex effects of maternal employment found on

children, some negative influences have been found with achievement scores in

early-school-aged samples (Gold & Andres, 1977; Gotffried, Gottfried, &

Bathurst, 1988; Hoffman, 1980, 1989). The interpretation of the positive influ-

ence of father's IQ on reading achievement is more straightforward. In-

terestingly, however, the effect occurs for girls only, suggesting that reading

achievement in boys at this age may not b e as sensitive to paternal influence.

We hypothesized that influences of school environment on children may be

highly multifactorial. The factor score of private versus public school and other

factor scores of variables aggregated at the classroom level are assumed to index

many intercorrelated individual variables of school environment, each of which

may have a small effect on child achievement. Some significant associations

were found between the school factor scores and child achievement. However,

given the lack of multivariate significance of the scales, the findings should be

interpreted with caution. For boys' reading achievement, the data are consistent

with a selection effect, such that boys with better reading skills tend to be placed

in private schools. Our results are inconclusive regarding private versus public

schools and math achievement. Although a significant association between pri-

vate school and boys' math achievement emerges in our data, we cannot attribute

it to either a direct environmental effect or genetic mediation. Perhaps the en-

vironmental association with private schools will be clarified through future

analyses of data from older CAP children. Coleman and Heifer (1987) found that

~D

o

0

TA

BL

E 8

Es

tim

ate

s o

f P

ara

met

ers

Ass

oci

ate

d W

ith

Sch

oo

l E

ven

ts M

easu

res

Fro

m B

ase

lin

e M

od

els

Pa

ram

eter

Pa

ren

t R

ati

ng

of

Ch

ild

Dis

tres

s C

hil

d R

ati

ng

of

Ch

ild

Dis

tres

s

Sc

ho

ol

To

o H

ard

S

ch

oo

l T

oo

Ea

sy

A

ca

de

mic

Str

ess

Sc

ho

ol

To

o H

ard

S

ch

oo

l T

oo

E

as

y

Ac

ad

em

ic S

tre

ss

Rea

din

g A

chie

vem

ent

Ge

ne

tic

M

ed

iati

on

gsc

h (

all

ch

ild

ren

) .0

34

.3

47

a

-.0

63

.2

45

-.0

20

-.0

01

Dir

ec

t E

nv

iro

nm

en

tal

Eff

ec

ts

w

(all

ch

ild

ren

) -.

1 l0

.0

31

-

.02

9

-.

171 a

-.

11

9

.10

2

Co

rre

lati

on

wit

h P

are

nta

l IQ

rFa,

Sch

(f

ath

ers

) -.

18

4 a

.0

36

.0

53

.0

58

.0

80

.0

86

rMo

,Sch

(m

oth

ers

) .1

45

.0

99

.0

81

-

.01

7

-.0

88

.1

17

Me

an

s a

nd

Sta

nd

ard

De

via

tio

ns

Xsc

hool

(ado

ptea

) 1

.61

5 a

1

.60

5 a

1

.61

3 a

1

.44

1 a

1

.59

7 a

1

.71

3 a

Xsc

hool

(non

adop

ted)

1

.47

2a

1

.69

2a

1

.71

1 ~

1

.86

3a

1

.77

9a

1

.84

8a

trsc

h

.69

0 a

.7

01

a

.69

7 a

.7

62

a

.83

2 a

.7

98

a

Ma

th A

chie

vem

ent

Ge

ne

tic

M

ed

iati

on

gsc

h

.08

7

-,

16

9

.20

1

.30

6 a

.1

65

-.2

17

Dir

ec

t E

nv

iro

nm

en

tal

Eff

ec

ts

w

-.

26

5 a

.2

04

-.

20

9

-.4

34

a

-.

18

6

.09

8

Co

rre

lati

on

s w

ith

Pa

ren

tal

IQ

rFa.

Sch

(fa

the

rs)

-.

16

-.0

13

.0

55

.0

47

.0

79

.0

69

rMo

,Sch

(m

oth

ers

) .1

62

.0

96

.1

00

.0

17

-.0

95

.1

11

Me

an

s a

nd

Sta

nd

ard

De

via

tio

ns

Xsc

h(a

dopte

d)

1.5

84

a

1.5

56

a

1.5

95

a

1.3

78

a

1.5

84

a

1.7

15

a

XS

ch(n

onad

opte

d )

1.4

45

a

1.7

62

a

1.7

11

a

1.8

52

a

1.7

32

a

1.8

49

a

trsc

h

.69

3 a

.7

00

a

.70

2 a

.7

65

a

.83

6 a

.7

99

a

aS

ign

ific

an

t p

ara

me

ter

esti

ma

te.


private Catholic schools directly influence the achievement (particularly in the

area of math) of high-schoolers.

Significant negative environmental influences of a more strict disciplinary

classroom environment were found for girls' reading achievement. The positive

influence that fathers' IQ has on daughters' environments for reading skills

suggests that discipline styles in the home and in the school may be important for

girls' reading ability. The discipline structure for learning situations in the home,

which may be more informal and directed more by the child, may provide a

setting more conducive to acquiring reading skills than a controlled classroom

setting. This hypothesis is supported by evidence that a warm, friendly class-

room environment has a positive influence on the achievement of younger chil-

dren (Purkey & Smith, 1983).

The positive genetic association between a competitive school environment

and boys' math achievement is more difficult to interpret. This result would

suggest a correlation between parental genotypes important for achievement and

competitive school environments; however, the observed correlations with pa-

rental IQ are negative. A positive relationship may exist between competitive

school environments and parental characteristics other than IQ, which are then

genetically transmitted to the child. Alternatively, this significant association

may only be due to chance.

Results from the school attitudes measures are consistent with the findings of

Coleman et al. (1966) and Stevenson and Lee (1990) that attitudes may be an

important moderator of school environment-achievement relationships. Not sur-

prisingly, we found genetic mediation of school being too easy. This result

suggest that children with aptitudes for high achievement found an unchallenging

school environment distressing. It is interesting to note that this finding occurred

for the parent-rated item only. Although many first graders rated school as being

too easy, few recognized this as a problem.

Of more interest is the result that school difficulty has a negative environmen-

tal association with achievement, significant for all but the parent rating when

reading achievement was the outcome variable. Given the result with easy school

environments, we expected to find genetic mediation for this variable as well,

such that children with lower aptitudes would find that school was too hard.

Instead, our results suggest that a school environment that is too demanding may

have a direct causal effect on achievement. Perhaps an overly challenging school

environment engenders feelings of futility and helplessness that result in the

poorer achievement scores.

Alternatively, this result may reflect the case where children with genetic

backgrounds for lower IQ, who find themselves in challenging school environ-

ments, are at higher risk for poor achievement. The question is one of causality:

Does the environment cause the poor attitude and achievement, or is the attitude

that school is too hard caused by poor prior ability? If the latter explanation is

correct, then the association between the attitude measure and that portion of

prior ability not shared genetically between parents and children will be con-


founded with what we are calling direct environmental effects. However, our

results suggest the first explanation. Correlations between 4-year-old IQ and

parent and child ratings that school was too hard were as follows: r = - . 12 (n =

159, p = .12) for the parent rating, and r = - . 1 2 (n = 194, p = .11) for the

child rating. Thus, although there is a trend toward an association between prior

IQ and this attitude measure, these small correlations could not account for the

strong relationships found for this measure and the achievement variables.

We present these findings with the caveats that the CAP children are young,

and that our measures of school environment are less refined than those used in

many previous studies of school-achievement associations. If effects of the

school environment are cumulative, we may observe larger associations when

the children are older, after they have been exposed to more than 1 year of

school. However, the study has the advantage of analyzing only the variance

identified with a single teacher and classroom environment, unmodified by influ-

ences of many types of teachers and classrooms over years of schooling. Replica-

tion of this post-first-grade study using other samples will be needed to confirm

the associations found here between achievement and the initial school environ-

ment to which a child is exposed.

The analysis of these associations using the adoption design has offered new

evidence concerning their etiology. Our results have suggested a few aggregate

measures of school environments that may be important for achievement, in

addition to a possible mechanism underlying such associations, that is, attitudes

about school. Analysis of more variables obtained through direct observation of

classroom environments may reveal further mechanisms which account for these

observed effects.

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APPENDIX A

First-Grade Environment Questionnaire

Dear Parents,

As a result o f our studies on the specific effects o f the school env i ronment on

children, we have decided to ask a few additional quest ions about exper iences in

first grade. We hope you will be wil l ing to take a few minutes to fill out the short

quest ionnaire below. I f you are not sure about a quest ion, please give your best

guess. I f you are comple te ly unable to guess, leave the quest ion blank. Please

return the quest ionnaire in the enclosed reply envelope .

Thank you again for your cont inued t ime and effort.

Please give the name and locat ion o f the school where your child at tended first

grade.

public school _ _ private school _ _


O n a v e r a g e , w h i c h b e s t d e s c r i b e s y o u r c h i l d ' s f i r s t - g r ade c l a s s r o o m :

o r d e r l y ; qu i e t

_ _ e n e r g e t i c ; l o u d

T h e t e a c h e r in y o u r c h i l d ' s f i r s t - g r a d e c lass

c h e c k one :

h a d m a n y ru les

h a d f e w ru l e s

_ _ h a d n o d e f i n e d ru l e s

c h e c k one :

_ _ e n f o r c e d ru l e s o f t e n

_ _ e n f o r c e d ru les o n l y w h e n a b s o l u t e l y n e c e s s a r y

_ _ r a r e ly o r n e v e r e n f o r c e d ru les

c h e c k one :

_ _ h a d s e v e r a l u n f a i r / a r b i t r a r y ru l e s

_ _ h a d o n l y fa i r ru les

D i d the c h i l d r e n in y o u r c h i l d ' s f i r s t - g r a d e c l a s s r o o m

sit at a s s i g n e d sea ts (or d e s k s ) m o s t o f the t i m e ?

_ _ s p e n d m o s t o f the t i m e at ac t iv i ty c e n t e r s ?

D i d the t e a c h e r f r e q u e n t l y ask the c h i l d r e n to pa r t i c ipa t e in c l a s s r o o m c o n t e s t s ?

Yes _ _ N o _ _

D i d y o u r c h i l d

_ _ w o r k at h is o r h e r o w n p a c e in all s u b j e c t s ?

_ _ w o r k at h is o r h e r o w n p a c e in a f e w s u b j e c t s ?

_ _ w o r k at t he p a c e o f t he en t i r e c l ass in all s u b j e c t s ?

In s o m e c l a s s r o o m s , c h i l d r e n c h o o s e w h i c h ac t iv i t i e s t hey w o u l d l ike to pa r t i c i -

p a t e in at a g i v e n t i m e . In y o u r c h i l d ' s f i r s t - g r ade c l a s s r o o m , th is h a p p e n e d

m o s t o f t he t i m e .

_ _ a b o u t h a l f o f t he t i m e .

_ _ a l m o s t never .

D i d y o u r c h i l d ' s f i r s t - g r a d e t e a c h e r g e n e r a l l y use

_ _ fami l i a r , t r ad i t iona l t e a c h i n g m e t h o d s ?

_ _ u n i q u e , c r e a t i v e t e a c h i n g m e t h o d s ?

Note. Name and location of school were not scored. Scoring of subsequent items was as follows

(in the order the questions occur): l = private, 2 = public; l = parochial, 2 = other; 1 = Catholic, 2

= other; 1 = orderly, 2 = energetic; l = many, 2 = few, 3 = none; l = often, 2 = as necessary, 3 =

rarely; l = unfair, 2 = fair; 1 = assigned seats, 2 = activity centers; l = yes, 2 = no; l = pace of

class, 2 = mixed, 3 = own pace; 1 = never, 2 = half the time, 3 = most of the time; 1 = traditional,

2 = nontraditional.


APPENDIX B

Expectations for the Path Model (Figure 1) of Genetic and Environmental Transmission

Among Parents, Children, and a Measure of the School Environment

Variables a Expected Covariances

Adoptive Families

PMo, Pva

PMo,Sch

PFa, Sch

PMo, Pogirl

PMo, Poboy l'Fa, POvrl PFa, Poboy

School, Pogirl

School, Poboy

Pogi~l, ao~irl

POboy, POboy

Pogirl, Poboy

Nonadoptive Families

PMo, PFa

PMo,Sch

PFa, Sch

PMo, Pogirl

PMo, eoboy

PFa, Pogi,1

PFa, POboy

School, eogirl

School, Poboy

Pogirl, Pogir,

POboy, POboy

Pogirl, POboy

tl*l~Lr [rMo,Sch]O'ParO'Sch

[rFa.Sch]O'ParO'Sch

[tf + rMo,SchW f + [.LUf]O'ParO'Chil d

[t m + rMo,SchWm + ~LUm]O'PartYChild

[Uf + rFa.SchW f + Fktf]OrParO'Child

[Um + rFa.SchWm + [Ltm]O'PartYChil d

[Wf + rMo.Scht f + tFa.SchUf]OrSchOrChil d

[W m + rMo Schtm + rFa SchUm]O'SchOrChild 2 ' 2 "

[tf + tI~ + Wf + 2tfrMo SchWf + 2UfrFa SchWf + 2tfp~Uf • 2 2 ' '

+ ZfSff]O'Chil d

[t~ + U2m + W2m + 2tmrMo,SchW m + 2UmrFa.SchW m + tmbl.U m

+ Z~mSmml~i,d [tft m + UfU m + WfW m + tfrMo.SchW m + tmrMo.SchW f

+ UfrFa.SchW m + UmrFa.SchW f + tfp.U m +tmFLUf

+ ZfZmSfm]O~Child

[~]~,~ [rMo, Sch]O'parO'Sch

[rFa,Sch]O'ParO'Sch

[tf + rMo,SchW f + ~Uf + gFamily]O'parentO'Child

[t m + rMo.SchW m + FLUm + gFamily]OrParOrChild

[uf + rea.schwf + p~tf + GFamily]O'PartIChild

[U m + rFa.SchW m + FLtm + gFamily]O'ParO'Child

[Wf + rMo,Scht f + rFa,SchLlf + gsch]O'SchOrChild

[W m + rMo Schtm + rFa.SchUm + gsch]OrSchtYChild [tf2 + 2 ' a Uf + wf + 2tfrMo.SchW f + 2ufrFa,SchW f + 2tfp,Uf

+ 2gFamit~tf + 2gFamityUf + 2gSchWf + gFamily

+ +dCrChild [t2m + I1~ + w 2 + 2tmrMo,SchWm + 2UmrFa.SchWm + 2tmp~Um

+ 2gFamilytm + 2gFamilyUm + 2gschWm + gFamily

+ Z~Smm]O2Child

[tft m + UfU m + WfW m + tffMo,SchWm + tmrMo,SchWf

+ UfrFa.SchWrn + UmrFa,SchW f + tf[.Ln m + tmlAU f

+ gFamily(tm + tf + Uf + U m ) + gsch(Wf + Wm)

+ gFamily + ZfZrnSfm]O'c2hild

ap = phenotype; Mo = mother; Fa = father; O = offspring; subscript m = male; subscript

f = female, Par = parent, Sch = school environment. See Figure 1 and text for explanation of path

coefficients.

Influences of School Environment on the Academic Achievement Scores of Adopted and Nonadopted Children

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