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Early ethnic educational inequality: the influence of duration of preschool attendance and social composition*
Names of the authors:
Nicole Biedinger, Mannheimer Centre for European Social Research, Birgit Becker, Mannheimer Centre for European Social Research, Inge Rohling, Health Service of County and City of Osnabrueck.
Presented by: Nicole Biedinger
Please do not quote!
* This paper will be published soon. I acknowledge that the article has been accepted for publication in the European Sociological Review published by Oxford University Press. All rights reserved.
1
Abstract
Ethnic inequality in education is a well-established topic among the scientific community. We
assume that ethnic inequality is constituted early in life – before a child has even started
school. Differences between natives and immigrants with regard to preschool attendance (if,
when, and which preschool is attended) may account for some of the ethnic educational
inequality upon entering school. We use the school entrance examination data of the City of
Osnabrueck (Germany) for the years 2000 to 2005 to analyse the school readiness of six-to-
seven-year old children as an indicator of early school success. It is apparent that the amount
of preschool experience improves school readiness, even when controlling for family
background. While this is true for all children, immigrant children nonetheless exhibit lower
scores on school readiness when all these individual explaining factors are controlled for.
Multilevel analysis shows that the ethnic effect differs among preschools. A preschool’s
influence depends on its social composition: Preschools with a beneficial social composition
are better able to promote children’s development than those with a poorer learning context.
Immigrant children benefit particularly from longer attendance at preschools with a positive
context.
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1. Introduction Ethnic inequality in education is a well-established topic among the scientific community in
Western countries. Immigrants perform worst, for example, in Germany, the United States,
and the United Kingdom (for details see Alba et al., 1994; Betts and Lofstrom, 2000; Kristen,
2005; Lange and Rupp, 1992; Neild, 2001; OECD, 2006; Portes and MacLeod, 1999; West,
2006). The search for the causes behind and the potential cures for these problems has
focussed almost exclusively on schools and on the schooling process. Especially since the
“Program for International Student Assessment (PISA)” (for details see Entorf et al., 2004)
was conducted and whose results in most countries exposed huge drawbacks on the part of
immigrant pupils, research efforts have even been intensified (cf. Marks, 2005). In particular,
the early childhood years are increasingly seen as a period crucial to the growth and
consolidation of important skills necessary for successful school transition and later academic
functioning (e.g. Barnett, 1995; Entwisle, 1995; Gormley et al., 2005).
Major individual differences emerge well before children arrive at school. We will focus on
the role of preschool for the early educational success of children. Preschool attendance has
been shown to positively influence children’s development and school success, although the
debate about the long-term effect is ongoing (e.g. Aughinbaugh, 2001). One main finding
from the literature on early child development is that it is not only a matter of whether
children attend preschools, but also a matter of which preschool they attend. The quality of a
preschool has proven to be an important moderating factor of the preschool influence (Love et
al., 2003). Thus, we will not only focus on the individual preschool attendance, but also take
into account the differences among preschools. Hence, in this paper, we use a multilevel
design to study preschool effects. An interaction of preschool duration and preschool context
also seems plausible, meaning that long preschool attendance can only yield positive effects if
the quality of the preschool attended is high or its social composition is beneficial. Some
findings indicate that disadvantaged children can especially profit from attending high-quality
preschools (e.g. Magnuson and Waldfogel, 2005). Since ethnic minorities are mostly
disadvantaged, the consideration of individual preschool attendance, as well as preschools’
context variables may help to explain the early ethnic educational gap.
Our analysis is based on school entrance examination data of the City of Osnabrueck for the
years 2000 to 2005. The school entrance examination takes place in all of the federal states in
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Germany. A paediatrician examines the child’s development and then gives a
recommendation whether or not the child is ready to start school. The recommendation relies
on certain standardised tests, as well as on the paediatrician’s own assessment. We use
multilevel analysis to test the impact of preschool attendance on the children’s school
readiness and on the early ethnic educational gap. In the following section we will give first of
all a short review of current research and explanations of ethnic inequality in education
(section 2). Then we will provide a short introduction to the German preschool system, given
the origin of the data (section 3). Thereafter, we will introduce our analysis and the results
(section 4), followed by conclusions and discussions (section 5).
2. Ethnic educational inequality
Ethnic educational inequality is a global phenomenon and can be found in most Western
societies. In the United States ethnic and racial disadvantages are hard to separate. Although
racial and ethnic inequality cannot be equated, similar mechanisms are used to explain the
phenomenon. To keep matters simple, within our theoretical framework we do not distinguish
between racial and ethnic inequality. From 1972 up to 2004, status dropout rates for white,
black, and Hispanic young adults have declined in the United States, with rates remaining
lowest for whites and highest for Hispanics. Additionally, college enrolment among minority
groups is less frequent, and gaps between whites and blacks with regard to completion of
bachelor’s or advanced degrees have even widened over time (Livingston, 2006). These
disadvantages in the United States may be comparable to disadvantages of the main ethnic
groups in the United Kingdom, where especially Pakistani and Bangladeshi are deprived. The
gap between the highest- and the lowest-achieving ethnic groups continues to grow. At Key
Stage 1 (at age 7 years), there is a achievement gap of 15 percentage points between the
highest- and lowest-attaining ethnic group, but at Key Stage 4 (at age 16 years), the equivalent
gap has widened to 42 percent (Department for Education and Skills, 2005). In the case of
Germany, the situation of immigrant children also is very well established; there exist gaps
between various ethnic groups. Especially Turkish children are disadvantaged (e.g. Alba et
al., 1994; Dinkel et al., 1999). Equal descriptions may be given for most Western countries
(see Bade, 2001). We assume that educational disadvantages are set in quite early during
preschool education. In the case of the United States, both black and Hispanic children scored
about two-thirds of a standard deviation below whites in math and just under half a standard
deviation below whites in reading at age 6 (Duncan and Magnuson, 2005). In the case of
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Germany, some similar descriptions can be made (see Mengering, 2005; Schöler et al., 2004).
This leads to the assumption that the foundation of ethnic educational inequality is constituted
even before children start school. Moreover, this kind of ethnic disadvantage at an early age is
disturbing if one considers that skills can be treated as human capital and tend to accumulate
(Kalter, 2003). Even though these disadvantages might still be quite small at early ages, in the
long run, the accumulation process can produce great differences.
Ethnic, as well as racial, educational inequality can be explained by the lack of resources
within families (most notably economic, cultural, social, and language resources), the
unfavourable choices some families make (self-selection), and by discrimination. Empirically,
the transition between resources and self-selection is smooth because they more or less
depend on each other or are highly correlated. We try to separate these explanations as far as
possible.
The most central issue in current research on ethnic and racial inequality is the resources
within families. These resources consist mainly of cultural and human capital (for details
about cultural capital, see DiMaggio, 1982; about human capital, see Becker, 1964). The
cultural capital of parents directly stimulates the activities of their children. Sullivan
concludes that cultural capital is transmitted within homes and has significant effects on
children’s performance in educational systems (Sullivan, 2001). Furthermore, cultural capital
among ethnic groups differs significantly from the cultural capital among natives (Portes and
Rumbaut, 2001). Ethnic inequality in the cultural capital of the receiving country can
therefore be described as the result of an accumulation process: Since ethnic groups often
possess less of the cultural capital of the receiving country (especially in the first generation),
parents thus have less capital to transmit to their children. An analogous mechanism holds
true for the case of human capital (Borjas, 1992): If parents are highly educated, the
probability rises that their children will also be highly educated. It is assumed that highly
educated parents may be better able to help their children. Conclusively, a child’s chance of a
positive school outcome depends on the (educational) resources of its parents. This is true for
natives as well as for immigrant children. In comparison to native parents, immigrants have a
shortage of the capital particular to the receiving country (e.g. language and specific
knowledge). In sum, the social and ethnic backgrounds, especially family origin, have
systematic effects on educational attainment amongst social, ethnic, and racial groups (e.g.
Blau and Duncan, 1967; Mare, 1980).
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In the case of ethnic inequality, language constitutes the most important type of human
capital. It is a fundamental resource which parents exhibit and which can be transferred
directly to the personal property of their children (e.g. Borjas, 1992). Language proficiency
per se is determined by family background. Worswick showed in the case of Canada that the
shortage of language as capital explains disadvantages among immigrant children (Worswick,
2004). If the children’s mother tongue corresponds to the official language, then there are no
educational disadvantages for immigrant children. In the case of Germany, the educational
inequality among immigrant children is also mainly explained by language proficiency, but
disadvantages still persist after controlling for language (e.g. Helmke et al., 2002).
Apparently, children have linguistic disadvantages if their parents use languages different
from the language of the receiving country (Bleakley and Chin, 2004). Boudon (1974)
describes these transmissions of parental capital as primary effects. He distinguishes between
the so-called primary and secondary effects of stratification. While the primary effect
describes the initial differentials in school achievement, for instance, ability differentials
between social and ethnic groups, the secondary effect refers to the families’ choices of their
children’s educational tracks.
The secondary effect described by Boudon points out that ethnic groups exercise a kind of
self-selection. Parental choices are mainly explained in light of the opportunities they exhibit.
The opportunities determining parents’ choices are influenced by their economic and cultural
resources, their social capital, their language proficiency, and their residential areas. The
direct influence of resources has already been discussed. These factors indirectly lower
families’ options to choose and influence the choices parents may make. Therefore, families’
endowment with resources affects ethnic educational inequality both directly and indirectly.
Kristen verified one established indirect effect in the case of Germany. She found that
especially a lack of information about the German school system put parents of Turkish
children at a disadvantage when choosing schools for their children (Kristen, 2005). The lack
of information is possibly due to a lack of proficiency in the German language and the lack of
advantageous social capital. This is one example of how resources (and language) indirectly
influence parents’ choices. Additionally, school attainment could also be explained by parents
making choices that are influenced by their residential area. Leventhal and Brooks-Gunn
found three theoretical frames for understanding how neighbourhoods affect children’s well-
being: institutional resources, relationships and norms, and collective efficacy (for details, see
Leventhal and Brooks-Gunn, 2003). These three sets of factors affect the choices of the
6
parents and therewith the children’s well-being. In the case of ethnic inequality, residential
segregation has to be considered as well. Western societies differ greatly in the degrees and
the development of residential segregation (for details, see Friedrichs, 2000; Fong and
Shibuya, 2005). Nevertheless, residents of different neighbourhoods have access to different
institutional resources and have different relationships and norms, which may influence the
educational outcome of immigrant children. Additionally, segregated residential areas are
reflected within the educational system as segregated school classes. And in turn, segregation
within classes leads to different levels of educational attainment (e.g. Lanfranchi, 2002).
Therefore, ethnic inequality in education can also be explained partly by the choices of
parents, who often follow given opportunities (e.g. segregated residential areas). We term this
aspect self-selection, because while immigrant parents are supposed to have choices, there
exist nonetheless distinct opportunity structures, as well as some restrictions.
A further explanation of ethnic inequality may lie in mechanisms of discrimination
(Carmichael and Hamilton, 1967; Feagin and Booher Feagin, 1986; for Germany: Gomolla
and Radtke, 2002). Because of data limitations, our approach will not analyse the issue of
discrimination (for details about kinds of discrimination, see Kalter and Granato, 2002).
However, we think that it may also be a central cause of ethnic educational inequality.
We assume that ethnic educational inequality is already established before children start
school. Therefore, we shall extend these basic explanations to include an earlier stage: We
assume that the preschool years are a very crucial period. We will analyse early educational
inequality using the example of school readiness. School readiness itself is the acquisition of
those abilities that are necessary in order to start school. Preschool gives children one main
opportunity (aside from their family background) to acquire important skills necessary for
their educational success. Thus, preschool also strongly determines their school readiness by
stimulating the development of such skills mainly through beneficial activities. We assume
that differences in school readiness may lead to growing differences in educational careers.
Therefore, the preschool represents an opportunity to achieve better academic outcomes (cf.
Andersson, 1992; Goodman and Sianesi, 2005; Magnuson et al., 2004). Besides the rather
individual influence of the duration of preschool attendance, different preschools have
different characteristics, and these characteristics may have an independent influence on
children. We assume that preschools with a positive learning context and a high quality
improve the school readiness of children more than below-average preschools may do. Since
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our data do not include a measure of quality, we will focus on the children’s social
composition as an important determinant of the learning environment. These assumptions can
be deduced from the effects of class composition on the achievement of the pupils (cf. Dar
and Resh, 1986; U.S. Department of Education and National Center for Education Statistics
by Kristin Denton and Jerry West and Jill Walston, 2003). Dar and Resh found in an Israeli
sample that classroom intellectual composition positively affects the pupil’s objective
academic achievement, beyond the potent effect of his or her personal intellectual resources.
A prolific body of research on early childhood programmes in the United States focuses on
the effects of programmes intended for disadvantaged children (e.g. ethnic minorities, low-
educated, single-parent and low-income families). Such programmes include small-scale
models, or experiments such as the High/Scope Perry Preschool Project, as well as ongoing,
large-scale public programmes such as Head Start. Albeit not completely free from
methodological problems like small sample sizes, short follow-up periods, or non-random
attrition, the evidence from these studies has consistently pointed to short-term cognitive
improvements, as well as to long-term gains in terms of academic achievement, employment,
and earnings, and to a reduction in special education placement, and a reduction of crime (cf.
Aughinbaugh, 2001; Haskins, 1989) (For reviews of programmes and studies in the US and
UK, see: Currie and Thomas, 1995; Garces et al., 2002 ; Gramlich, 1986; Lamb, 2000;
Sammons et al., 2004; West, 2005). Thus, the choice of when and which preschool children
attend is an important determinant for their acquisition of skills. Additionally, we assume that
immigrant children may especially profit from attending a beneficial preschool for as long a
time as possible. Immigrant children in preschools have the chance to make contact with the
culture and the language of the receiving country (besides the other beneficial effects of
stimulating activities and contact with other children), which additionally stimulates their
development and increases the chance of a better academic outcome (cf. Magnuson and
Waldfogel, 2005). Rumberger and Tran already found differences between the influence of
child care arrangements and Head Start programmes on the language proficiency of English-
speaking and non-English-speaking children (Rumberger and Tran, 2006). This leads to the
assumption that the quality of the preschool does indeed matter. In sum, preschool per se is
very important to children’s development, but perhaps even more so for immigrant children:
It is assumed that preschool may compensate for some disadvantages within immigrant
families (Brandon, 2004).
8
Even though the disadvantages of ethnic or racial groups might still be quite small at early
ages, in the long run, the accumulation process produces great differences. The differences at
the beginning of school may, of course, be explained by resources, self-selection, and
discrimination just as for ethnic educational inequality per se. We assume, independently of
these causes, that the amount of preschool experience and the social composition of preschool
groups have an additional direct effect on school readiness. Therefore, we analyse the
importance of preschool over and above family background for further school careers in the
case of Germany. We do not analyse the influences of language, self-selection, or
discrimination, since our focus is on the subsidiary influence of preschool for school readiness
when controlling for family background.
3. Data The German preschool system The German preschool system is very homogeneous. The typical, and often only, chargeable
preschool establishment available for children from age three years until they enter school is
the so-called kindergarten (Jonen et al., 2005: 68-75). Kindergarten provides care, but for the
last fifteen years the strengthening of the educational mission is claimed as well. However,
even today, there is no systematic link to schools. Kindergarten is usually operated by the
community or by non-profit organizations. The quality is generally regulated at the state level,
with a focus on structural features such as staff-to-child ratios, group size, or building
standards. Although in Germany, attendance at preschool is not mandatory, preschool
nonetheless is intended to prepare children for school. By a law of 1996, preschool is
supposed to be available to every child, and a preschool can not refuse any child for reasons
other than an obvious shortage of places. Furthermore, the preschool is supposed to help
parents to meet their work and family life responsibilities, while at the same time providing
the first stage of education within the general educational system.
In Germany, attending preschool for at least one year before school begins has become the
norm for young children. In the year 2003, about 90 percent of the children between five and
six years of age attended preschool (Statistisches Bundesamt, 2004: 218). But differences in
attendance rates still persist; especially immigrant children on average start preschool a few
months later than German children (also see Ondrin and Spiess, 1998: 39). These differences
in the time children have spent in preschools could be one reason for some of the ethnic
9
differences at the end of preschool, respectively at the start of school. Ethnic differences
between preschool contexts have not yet been analysed.
Sample The empirical results are based on data of the school entrance examination of the City of
Osnabrueck for the years 2000 to 2005. Osnabrueck is the third largest city of the Federal
State of Lower Saxony and has about 160,000 residents. The school entrance examination
takes place in all federal states in Germany. Paediatricians examine the children’s
development and recommend whether or not a child is ready to start school. The given
recommendation is mandatory, but school principals generally use it as a baseline. This
examination is compulsory, but without penalties if children do not take part. In sum, nearly
all children go through this process. During the examination, a number of medical and
developmental tests in different domains are performed. In the case of Osnabrueck, the school
entrance examination has been arranged in a highly standardized manner since the year 2000
(for details, see Rohling, 2002). The examination of a normally developed child takes about
40 to 60 minutes. Before visiting the paediatrician, parents fill out a short questionnaire. The
questions cover preschool experiences of the children, demographic information, and social
background.
The data as a whole are not representative of Germany. However, it is not intended here to
provide concrete information about the school readiness of children in Germany, but rather to
test general hypotheses among some variables. The data are applicable for this purpose; thus
ethnic inequality in school readiness as determined by preschool education und family
background can be analysed.
In the years 2000 to 2005, 8,601 school entrance examinations took place. The following
analysis contains 6,777 cases. We lost about 1,900 cases because we considered only regular
examinations and dropped all cases with missing values for the model variables, aside from
the educational and occupational variables of parents, for which missing-variables have been
generated. The variables are operationalised in the following way:
School readiness (dependent variable):
The school readiness of children was measured with the help of six subscales: gross motor
skills, fine motor skills, perception, language, cognition, and working habits. All subscales
10
range from 0 to 2. Children with disorders score 0 points, children with some developmental
deficits score 1 point, and fully developed children score 2 points. A factor analysis with the
principal-component factor method revealed only one main factor (eigenvalue: 2.42), which is
used as a score of the overall development of the children.
Preschool attendance (L1 variable): 1: more than two years of preschool experience, 0: less
than two years of preschool experience.
Preschool composition (context) (L2 variable):
We construct an index of the social composition of the population of preschool children. The
social composition determines the learning context in preschool and thus may be an important
moderating variable of the preschool effect. The index consists of the following composition
variables within the relevant preschool:
• Percentage of families with at least one parent with a college degree,
• Percentage of families with at least one parent without any formal education (negative),
• Percentage of families with both parents unemployed (negative),
• Percentage of families with both parents living in the household,
• Percentage of families making special efforts to ensure the health of their children,
• Mean number of children in the families (negative),
• Percentage of children with a lack of proficiency in the German language (negative).
A factor analysis using the principal-component factor method reveals one main factor
(eigenvalue: 4.33), which constitutes the learning context. A factor score for each preschool is
computed.
The operationalisation of the family background and demographic variables is shown in table
I.
-- About here, table I --
4. Results Table II shows the descriptive statistics for all variables separately for German and immigrant
children. There exist considerable differences in school readiness between Germans and
11
immigrants. This result confirms our assumption that ethnic inequalities already exist at an
early stage of education - at the beginning of children’s elementary education.
-- About here, table II --
There are also clear differences in other characteristics. Immigrant children are on average
slightly older than Germans at the time of their school entrance examination. In immigrant
(basically Turkish) families, there are also significantly more siblings than in German
families. The family situation in German and in immigrant families differs only slightly, there
being a greater number of intact immigrant families. German parents have on average a better
education than parents in immigrant families. It can not be overlooked that many immigrant
parents have no formal education at all. Additionally, more German parents than immigrant
parents are employed. In both groups, fathers, rather than mothers, are employed and then
about three times more often than the mothers. While there are just a few children who never
attend preschool, German children attend preschool longer than immigrant children do: 83 per
cent of the German children attend preschool for more than two years. That is true for just 60
per cent of the immigrant children. Furthermore, German and immigrant children attend very
different types of preschools. The composition of the preschools attended by German children
is significantly more beneficial than that of the preschools attended by immigrant children.
Our main focus rests upon the explanation of ethnic inequality in school readiness and we
assume that preschool attendance, as well as family background, plays a fundamental role.
We postulate that not only the duration of preschool attendance, but also the composition of
the preschool population is important. To examine the group effect of preschools, we
calculated some hierarchical linear models, using STATA (for details see Rabe-Hesketh and
Skrondal, 2005; Snijders and Bosker, 1999). When the explanatory variables at level 1 are
denoted as , the explanatory variables at level 2 are denoted as , and the outcome (school
readiness) is denoted as , the hierarchical linear model leads to the following formula for
individual i in preschool j (see Snijders and Bosker, 1999: 76):
ijx jz
ijY
. ijhij
p
hhjj
q
k
p
hhijkjhk
q
kkjk
p
hhijhij RxUUxzzxY ++++++= ∑∑∑∑∑
== === 10
1 110
1000 γγγγ
This formula includes the main effects of each X and Z variable, as well as all cross-level
product interactions. The groups are characterised by p+1 random coefficients to .
These random coefficients are independent between groups, but may be correlated within
jU 0 pjU
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groups. It is further assumed that the vector ( , …, ) is independent of the level-one
residual and that all these residuals have a mean of zero, given the values of all
explanatory variables. The variances and covariances are denoted as follows (see Snijders and
Bosker, 1999: 68, 76):
jU 0 pjU
ijR
2)var( σ=ijR
200 )var( rU j =
2)var( hhj rU =
hkkjhj rUU =),cov( .
This hierarchical linear model implies that there is variation between the preschools in the
general level of children’s school readiness (random intercept). But we also assume that the
slopes of certain level 1 variables are random and depend (at least to some extent) on level 2
variables. For theoretical reasons, we assume that the ethnic effect and also the duration of
preschool attendance vary among preschools (random slope). Longer preschool attendance
will result in various developmental outcomes, depending on the preschool context. While
longer attendance at a preschool with a positive context may lead to especially strong positive
effects, longer attendance at a preschool with a negative context may even do harm.
Analogous thereto, some preschools may be better able than others to fulfil immigrant
children’s needs, so that differences among preschools with regard to the ethnic effect are also
plausible. We consider only one level 2 variable, the social composition of the preschools;
hence, our final model contains two cross-level interactions: ethnic origin x preschool context,
and attendance duration x preschool context.
Table III shows the results of our analysis on school readiness of children.
-- About here, table IIIa --
The first step in table IIIa is to show the empty model without any explanatory variables. It is
obvious that there is variation among different preschools regarding the school readiness of
their children (model 1). In model 2, a significant negative influence of the immigration status
on development is found after additionally controlling for age, sex, and year of investigation.
This confirms the descriptive statistics of table II. Immigrant children score a third of a
standard deviation lower on the school readiness index than native children do. It can also be
seen that girls and older children score higher on school readiness than do boys and younger
13
children. Model 3 adds the family background: Children of highly educated parents have a
higher probability of being ready for school than do children of less educated fathers and
mothers. There is also a positive effect of the parents’ occupational status and of the presence
of both parents in the household. In sum, all family background variables significantly affect
the school readiness of children in the manner expected. The influence of the immigration
status is clearly reduced after controlling for family background. Furthermore, the variance
among preschools is also slightly reduced, meaning that certain parts of the group variance are
based on differences in the distribution of certain individual variables. Model 4 additionally
controls for the duration of preschool attendance. Controlling for preschool attendance leads
to a reduction of some other effects. Preschool attendance per se improves the school
readiness of children – independent of all other influences. This shows that the quantity of
preschool experience (duration of attendance) is an important factor for explaining early
educational outcomes.
-- About here, table IIIb--
In model 5, an interaction of the ethnic origin and the duration of preschool attendance is
tested (see table IIIb). This interaction effect is significant and positive, meaning that the
negative effect of immigrant status is reduced for immigrant children with more preschool
experience. Or stated the other way around: Immigrant children can gain more from attending
a preschool for a longer period. Model 6 tests the hypothesis that the influences of the
immigration status and the amount of preschool experience differ among preschools.
Therefore, a random slope of immigration status and preschool attendance is added. The
ethnic effect varies significantly among preschools. Also, the effect of the duration of
attendance differs according to preschool. The extension of the model leads to a change in the
effect of the interaction between preschool attendance and immigration status, which is
reduced and no longer significant. A likelihood-ratio test shows that models 5 and 6 are
significantly different (LR (5) = 92.61). This demonstrates the correctness of the
assumption that immigration status and preschool attendance have a different influence in
various preschools.
2χ
In model 7, a level 2 variable is added, the social composition of the preschools: This
constitutes the learning context for the children. This context variable has a significant
positive effect on the school readiness of children. Attending a preschool with a beneficial
14
social composition seems to be more important than the duration of preschool attendance. But
in this model, each variable, the individual attendance duration and the preschool context, has
an independent effect. In the final model (model 8), a three-way interaction effect among
immigrant status, duration of preschool attendance, and preschool context is tested (all two-
way interactions are also included). This tests the assumption that the duration of preschool
attendance is more important for immigrant children than for natives, but only in positive
learning contexts. The existence of such an effect can be verified, and it is demonstrated in
figure 1.
-- About here, figure 1 --
Figure 1 shows the effects of the duration of preschool attendance and preschool context on
the school readiness of children. The social composition of the preschool is more important
for a child than the amount of his or her preschool experience. German and immigrant
children profit from attending a preschool with a positive learning context. In preschools with
a beneficial social composition, all children can benefit from a longer attendance (the longer,
the better), but immigrant children can profit more. The opposite is true for preschools with a
disadvantageous social composition: In these preschools, the duration of attendance has no
effect at all on immigrant children, while German children still can profit from a longer
preschool experience.
In sum, the school readiness of children depends on their family background and preschool
attendance. There really do exist differences between German and immigrant children with
regard to this early educational outcome. It is noteworthy that in preschools with beneficial
compositions, hardly any ethnic differences are left. The last results show that for German
children, the quantity of preschool experience is not that important as long as the preschool
context is positive. But immigrant children ought to attend preschools with a positive context
and they ought to attend these preschools for more than two years. In brief: The quantity and
the quality of a preschool do indeed matter.
5. Conclusion and discussion Ethnic educational inequality is not just a phenomenon in traditional school systems; it is also
a phenomenon in the preschool system. The present paper shows alarming ethnic differences
15
in school readiness in the case of Germany. Immigrant children are already disadvantaged
before they have even started school. We assume that these disadvantages will hardly be
compensated for during their educational career, but we do not exclude the possibility that
some children might catch up.
This paper analyses ethnic inequality in school readiness as one aspect of early education,
considering both family background and preschool. We assume that besides other influences,
preschools have additional and independent effects on school readiness. On the one hand, we
demonstrate that family background is very important, and on the other hand, that preschool is
also explanatorily relevant. To test our assumptions that preschool experience and social
composition have a direct effect on school readiness, we calculated hierarchical linear models.
The results showed that it is important that a child attend preschool for at least two years.
What we did not show, but already know from other analyses, is that in the case of Germany,
there exists a linear effect of preschool attendance if children attended preschool for more
than one year (see Becker and Biedinger 2006). Moreover, the results indicate that children
should attend preschools with a beneficial social composition since this offers them a positive
learning context. All children can profit from attending preschools with positive contexts, but
immigrant children especially profit from attending such preschools for more than two years.
That confirms findings by Ding and Davison, who found that immigrant children must learn
more in order to compensate for the gap between themselves and native children (Ding and
Davison, 2005). Transferred to our results, immigrant children should not only attend
preschools for as long as possible, but they should attend preschools with special social
compositions in order to close this gap.
Nevertheless, some of our results are problematic. Preschool effects may be due to selection.
Perhaps especially those immigrant parents who tend to take their child to preschool at an
early age and to special-composition preschools are unique, and differ from other immigrant
parents in terms of some other (unmeasured) criteria. Furthermore, the cognitive development
at the time of entrance into kindergarten is not measured or controlled. Perhaps immigrant
children who are farther along in their development attend kindergarten earlier and for a
longer period. We need longitudinal data to control for this in detail. Unfortunately, data of
this kind are not available at the moment in Germany. On the other hand, the exact
mechanism behind the way(s) in which preschool influences school readiness is not
explained. We can only assume that there are a great many variables involved, e.g. social
16
composition and size of groups, and/or the type of education and motivation of the teacher.
Additionally, our dependent variable is based on the examination by a paediatrician, and in
some ratings, it is conceivable that subjective influences might disadvantage children with a
migration background. But since most tests are highly standardised, this potential bias is
presumably rather small.
As a main result, we can see that ethnic educational inequality in Germany begins within
preschool education. Many immigrant children have more than one disadvantage. Because
immigrant families are often in a worse economic situation – like the working class – the
primary and secondary effects of Boudon are also at work at this early stage. These can be
indicated as a shorter duration of preschool attendance. Additionally, there exist some specific
ethnic disadvantages, basically caused by language deficits, self-selection, and mechanisms of
discrimination. The lesser amount of preschool experience on the part of immigrant children
could also be explained by a specific ethnic component, e.g., the absence of cultural
knowledge (e.g., information about term of application) (cf. Santel, 2000). The role of cultural
knowledge and attitudes in ethnic educational inequality has not yet been analysed clearly.
Our results bear implications for research on ethnic inequality, especially in Europe. The
research on ethnic inequality has focussed so far on the explanation of ethnic inequality in
labour forces or in educational systems. There has been little or no focus on early periods of
education or even on preschool systems. We maintain that immigrants often start their
educational careers burdened by a sum of disadvantages. Preschool is supposed to be one
important opportunity to compensate for disadvantages caused by the lack of resources within
immigrant families. As we have shown, the quantity, in terms of the amount of preschool
experience, and the (beneficial) social composition of preschool are important. Immigrant
children should mainly attend high-quality preschools for a longer period, because they suffer
even more if they do not. If immigrant children continue to attend poor-quality preschools, or
good ones only for a short time, their educational disadvantages will increase rather than
decrease.
Consequently, residential segregation is one main factor which determines compositions
within preschools: Immigrant families often live in areas with a disadvantageous social
composition. Since most families choose preschools which are located near their homes,
immigrant children have a greater risk for attending preschools with less beneficial learning
17
contexts. Therefore, long-term measures of urban planning to reduce residential segregation
should be addressed in the range of politics. Since this is a difficult endeavour, the focus of
action should also be on improving the quality of preschools in socially disadvantaged
locations. A high preschool quality (in terms of qualification level of the personnel,
stimulating materials and activities, special programmes for disadvantaged children, etc.)
might compensate for the less beneficial social composition within preschools of such an area.
This, of course, is already being attempted in many places. Results on the success of such
programmes are rather mixed. There is still a great need for research to discover which
children can profit from which preschool attendance, and which conditions in preschools
might lead to greater educational equality at school start.
18
Tables and figures Table I: Operationalisations of model variables
Variable name Description Values Family background Number of siblings Number of siblings of the child Range [0; 10] Family situation Both parents present in the household or another
family constellation (e.g. single parent) 0: different family situation 1: both parents in the household
Education of father/mother
Dummy variables indicating the highest educational level of the child’s father/mother
- no formal education - vocational training - college degree
Employment status of father/mother
Dummy variable for the father’s/mother’s employment status
0: not employed 1: employed
Health security Effort to have medical prevention (approximate value of the parents’ effort on behalf of their children)
0: no 1: yes
Demographic characteristics of the child Immigrant children Ethnic origin of the child. A child is categorised as
an immigrant if neither parent was born in Germany. If parents were born in different countries, the native country of the mother is used as the basis for classification.
0: native 1: immigrant
Age Age of the child in months up to the time of the examination
Range [64.4; 90.7]
Sex Sex of the child 0: boy 1: girl
19
Table II: Descriptive statistics
Germans mean (std)
Immigrantsmean (std)
Score on school readiness 0.11 (0.93) -0.20 (1.05) *
Age in months 74.52 (3.51) 74.85 (3.67) *
Sex (female) 0.48 (0.50) 0.50 (0.50)
Number of siblings 1.19 (0.95) 1.46 (1.14) *
Family situation 0.86 (0.35) 0.89 (0.31) * Education of mothera,b
- No education - Voc. training - College degree (number of missing values)
0.07 (0.26)0.68 (0.47)0.25 (0.43)
(813)
0.44 (0.50)0.43 (0.49)0.14 (0.34)
(617)
***
Education of fathera,b
- No education - Voc. training - College degree (number of missing values)
0.04 (0.21)0.59 (0.49)0.36 (0.48)
(1208)
0.32 (0.47)0.49 (0.50)0.19 (0.39)
(702)
***
Employment status of mothera
(number of missing values)
Employment status of fathera
(number of missing values)
Health security
0.35 (0.48)(647)
0.94 (0.24)(1148)
0.95 (0.22)
0.22 (0.42)(326)
0.78 (0.42)(506)
0.78 (0.42)
*
* *
Preschool attendance
- More than 2 years
0.83 (0.38)
0.60 (0.49)
*
Context (social composition) 0.33 (0.78) -0.43 (0.97) *
N 5017 1760
Source: School entrance examination of Osnabrueck in the years 2000 to 2005, own calculations Notes: Means, standard deviation in brackets a) As far as education and employment status of parents are concerned, there are generally many missing values. The number of missing values is given in brackets. We did not want to reduce the number of cases in the analysis, so we constructed four missing-dummies. b) Differences to one are caused by truncation errors. * Differences between German and immigrant children are significant at p≤ 0.01.
20
Table IIIa: Preschool influence on school readiness (hierarchical linear model) Model 1 Model 2 Model 3 Model 4 Immigrant childrena -0.29 (0.00)* -0.15 (0.03)* -0.12 (0.03)*
Age in Months 0.04 (0.03)* 0.04 (0.00)* 0.04 (0.00)* Sexb 0.29 (0.02)* 0.29 (0.02)* 0.29 (0.02)* Year of investigationc
- 2001 - 2002 - 2003 - 2004 - 2005
0.050.180.220.250.29
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
0.010.120.170.210.26
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
0.000.110.160.190.23
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
Number of siblings -0.06 (0.01)* -0.06 (0.01)* Family situationd 0.11 (0.04)* 0.10 (0.04)* Education of mothere
- Voc. training - College degree - Missing values
0.160.210.02
(0.04)(0.05)(0.05)
* *
0.150.200.02
(0.04)(0.05)(0.05)
* *
Education of fathere
- Voc. training - College degree - Missing values
Employment status of motherf
- Employed - Missing values
Employment status of fatherf
- Employed - Missing values
0.100.240.06
0.090.09
0.080.06
(0.05)(0.05)(0.06)
(0.03)(0.04)
(0.04)(0.05)
* * * * *
0.090.230.05
0.070.09
0.080.05
(0.05)(0.05)(0.06)
(0.03)(0.04)
(0.04)(0.05)
* * *
Health security 0.16 (0.04)* 0.13 (0.04)* Preschool attendanceg 0.20 (0.03)* Constant -0.13 (0.09) -3.48 (0.25)* -4.16 (0.26)* -3.95 (0.26)* Level 2:
20r (var( )) jU 0
0.58 (0.10)* 0.56 (0.10)* 0.50 (0.09)* 0.47 (0.09)*
Level 1: σ2 (var( )) ijR 0.76 (0.04)* 0.71 (0.01)* 0.68 (0.01)* 0.67 (0.01)*
Number of children 6777
Number of preschools 78
Source: School entrance examination of Osnabrueck in the years 2000 to 2005, own calculations Notes: Regression coefficients, standard errors in parentheses Reference groups: a) Germans, b) boys, c) 2000, d) family situation without two parents, e) no education, f) unemployed, g) less than 2 years of preschool attendance. * p ≤ 0.05.
21
Table IIIb: Preschool influence on school readiness (hierarchical linear model) [continued] Model 5 Model 6 Model 7 Model 8 Immigrant childrena -0.20 (0.05)* -0.20 (0.06)* -0.21 (0.06)* -0.24 (0.06)*
Age in Months 0.04 (0.00)* 0.04 (0.00)* 0.04 (0.00)* 0.04 (0.00)* Sexb 0.29 (0.02)* 0.29 (0.02)* 0.29 (0.02)* 0.29 (0.02)* Year of investigationc
- 2001 - 2002 - 2003 - 2004 - 2005
0.000.110.160.190.23
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
-0.000.110.170.190.24
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
-0.000.110.170.190.24
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
-0.000.110.170.190.24
(0.04)(0.04)(0.04)(0.04)(0.04)
* * * *
Number of siblings -0.06 (0.01)* -0.05 (0.01)* -0.05 (0.01)* -0.05 (0.01)* Family situationd 0.10 (0.04)* 0.10 (0.04)* 0.10 (0.04)* 0.09 (0.04)* Education of mothere
- Voc. training - College degree - Missing values
0.150.200.02
(0.04)(0.05)(0.05)
* *
0.160.210.02
(0.04)(0.05)(0.05)
* *
0.160.210.02
(0.04)(0.05)(0.05)
* *
0.150.200.02
(0.04)(0.05)(0.05)
* *
Education of fathere
- Voc. training - College degree - Missing values
Employment of motherf
- Employed - Missing values
Employment of fatherf
- Employed - Missing values
0.090.220.05
0.070.09
0.070.05
(0.05)(0.05)(0.06)
(0.02)(0.04)
(0.04)(0.05)
* * *
0.090.230.06
0.060.08
0.070.05
(0.05)(0.05)(0.06)
(0.02)(0.04)
(0.04)(0.05)
* * *
0.090.220.06
0.060.08
0.070.05
(0.05)(0.05)(0.06)
(0.02)(0.04)
(0.04)(0.05)
* * *
0.090.220.06
0.060.08
0.070.05
(0.05)(0.05)(0.06)
(0.02)(0.04)
(0.04)(0.05)
* * *
Health security 0.12 (0.04)* 0.13 (0.04)* 0.13 (0.04)* 0.13 (0.04)* Preschool attendanceg 0.15 (0.03)* 0.17 (0.06)* 0.17 (0.05)* 0.16 (0.06)* Immigrants*preschool 0.11 (0.05)* 0.05 (0.06) 0.03 (0.06) 0.07 (0.06) Preschool context 0.27 (0.06)* 0.28 (0.07)* Preschool*context 0.01 (0.06) Immigrants*context -0.11 (0.06) Immigrant*preschool*context 0.12 (0.06)* Constant -3.93 (0.26)* -3.90 (0.25)* -3.93 (0.25)* -3.95 (0.25)* Level 2:
20r (var( )) jU 0
0.48 (0.09)* 0.39 (0.08)* 0.32 (0.07)* 0.30 (0.06)*
21r (var( ))jU1
h 0.10 (0.03)* 0.10 (0.03)* 0.10 (0.03)* 2
2r (var( ))jU 2i 0.12 (0.04)* 0.11 (0.04)* 0.11 (0.04)*
Level 1: σ2 (var( )) ijR 0.67 (0.01)* 0.65 (0.01)* 0.65 (0.01)* 0.65 (0.01)*
Number of children 6777
Number of preschools 78
Source: School entrance examination of Osnabrueck in the years 2000 to 2005, own calculations Notes: Regression coefficients, standard errors in parentheses Reference groups: a) Germans, b) boys, c) 2000, d) family situation without two parents, e) no education, f) unemployed, g) less than 2 years of preschool attendance, h) random slope immigration status, i) random slope of preschool attendance duration. * p ≤ 0.05.
22
-2
-1,5
-1
-0,5
0
0,5
1
< 2 years > 2 years
preschool attendance duration
scho
ol re
adin
ess
German children,negative context
Immigrant children,negative context
German children,positive context
Immigrant children,positive context
Figure 1: Influence of preschool on school readiness. Source: School entrance examination of Osnabrueck in the years 2000 to 2005, own calculations. Notes: Predicted values of model 8 are displayed for mean immigrant and German children (= all independent variables are set at mean). A positive preschool context means that the composition variable is two standard deviations above the mean of all preschools and a negative context means that the composition variable is two standard deviations below the mean.
23
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