EPAA Vol. 10 No. 26 Bauman: Home Schooling in the United States.
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Education Policy Analysis Archives
Volume 10 Number 26 May 16, 2002 ISSN 1068-2341
A peer-reviewed scholarly journal
Editor: Gene V Glass
College of Education
Arizona State University
Copyright 2002, the EDUCATION POLICY ANALYSIS
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Home Schooling in the United States:
Trends and Characteristics
Kurt J. Bauman
U.S. Census Bureau
Citation: Bauman, K. J. (2002, May 16). Home schooling in the United States: Trends and
Characteristics. Education Policy Analysis Archives, 10(26). Retrieved [date] from
http://epaa.asu.edu/epaa/v10n26.html.
Abstract
Home schooling is a subject of great fascination, but little solid
knowledge. Despite its importance, it has received less research attention
than some other recent changes in the educational system, such as the
growth of charter schools. It could be argued that home schooling may
have a much larger impact on educational system, both in the short and
long run. This report uses the 1994 October CPS, and the National
Household Education Survey of 1996 and 1999 to examine popular
characterizations of the home school population. The article assembles
evidence from several sources to confirm that home schooling is
growing. It finds home-schooled children more likely to be middle
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income, white, from larger families, and from two-parent families with
one parent not working. While some authors have described a division
between religiously-motivated and academically-motivated home
schoolers, this research finds more support for a divide based on attitude
towards regular schools.
The Impact of Home Schooling
Home schooling is a subject of great fascination, but little solid knowledge. Compared
with other recent changes in the educational system, such as the growth of charter
schools, home schooling has received relatively little attention (Archer 2000). (Note 1) It
could be argued, however, that home schooling could have a much larger impact on
educational system, both in the short and long run. This is because home schooling
seems to be taking place on a larger scale than many other educational innovations
(Lines 1999, Bieleck 2001), because home schooling may have a greater immediate
impact on educational practices in existing schools (Hill 2000, Lines 2000b), and
because home schooling has brought new institutional forms into being that have the
potential to grow over the longer term (Trotter 2001).
Scale
Although other institutional innovations in the educational system have grown in recent
years, home schooling is probably the largest change in the sheer number of students
involved.
Home schooling directly comprises a larger student population than voucher school
programs—at least those that include private schools, that enroll only a few thousand
students in a few cities (see Gardner 2000). Home schooling also involves a larger
population than charter schools. According to estimates from organizations involved
with charter schools, the student population in the fall of 2000 was just over 500,000
(Center for Education Reform, 2001). Even conservative estimates of the number of
home schoolers put their numbers at that level or above (Lines 1999).
Organizational changes
Charter schools and voucher systems provide competitive challenges to traditional
public schools, and as such, provide a direct incentive to adopt innovations and match
the performance of other schools. However, the main outlines of current schooling
practice have thus far remained intact. The challenge of home schooling, by contrast, is
more profound. Home schooling is a more radical departure from education as it is
currently practiced, it affects more schools, and it has the potential to force numerous
adjustments to current curricular practices.
Public schools in many jurisdictions have already begun to provide services of various
types to home schoolers. Laws in at least seven states permit home schooled students to
participate in sports, music and other extracurricular activities in regular schools (Farris
1997). In Florida and Iowa, schools also allow home schoolers to take individual
courses.
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New Institutions
Perhaps the largest impact of home schoolers has been the concomitant entry of new
educational organizations into the field. Many private organizations and enterprises have
entered the K-12 distance education field with their sights set on home schoolers as a
primary audience (Hill 2000). The State of Florida has developed an extensive set of
courses that can be taken over the Internet for high school credit by home schoolers and
others who choose to use this resource, and Illinois is developing a similar program
(Carothers 2000, Trotter 2001). Meanwhile several for-profit ventures have entered the
field, offering courses and, in one case, accredited diplomas over the Internet (Trotter
1999, Walsh 2001).
If home schooling continues to grow, demand will grow for the types of services that are
starting to be offered by public schools and distance education providers. A result will
be pressure on schools to design school curricula that allow students and parents to pick
and choose what they like. According to some observers, another result will be the
creation of new schools and school-like institutions built around the common needs and
concerns of home-schooling families (Hill 2000) and the growth of public school
programs designed specifically for home schoolers (Lines 2000b).
Despite these broad impacts there have been few attempts to examine the characteristics
of home schoolers and their households in the U.S. Many studies that have been
conducted have relied on highly selective samples (Rudner 1999, Welner & Welner
1999) or have examined selective issues without giving a thorough overview of the
home-schooled population (Smith & Sikkink 1999,Welner 2000a, Welner 2000b, Lines
2000b). The two exceptions are reports by Lines (1999) and the National Center for
Education Statistics (Bielick 2001) who provide estimates of the home-school
population. Lines conducted a careful analysis state education agency records of
registered home schoolers, adjusting for probable levels of non-registered home
schooling. She estimated that there were 690,000 home-schooled children in 1995. The
National Center for Education Statistics report analyzed the results of the 1999 National
Household Education Survey, which is also one of the data sets also analyzed in this
article. They produced basic tabulations of the characteristics of home-schoolers,
including grade equivalent, race, sex, family characteristics, participation in public
schools and reasons for home schooling. They found 850,000 home schooled children in
the United States. (This is a larger figure than the one reported here, because they
decided to include 5-year-olds in the count of home-schooled children, while this report
includes only those age 6 to 17.) Prior to these resports, there was also an especially
careful attempt by researchers associated with the U.S. Department of Education to
reconcile results from two major national surveys measuring the home school population
(Henke et al. 2000). Unfortunately, the authors of that publication did not have more
recent data available to them.
This article adds to the current knowledge on the subject by looking simultaneously at
three national datasets on home schooling. The report takes a closer look at the
characteristics of home schoolers and tests for the significance of differences between
home-schooled children and others. It examines trends and compositional changes in the
home-schooled population. It examines their geographic location and potential for
growth. Finally, it examines whether there are identifiable groups of home schoolers
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with different reasons for pursuing home-schooling, as has been posited by many
observers.
The article proceeds as follows. It starts with a discussion of the data sources used in the
analysis. Next the number of home schoolers and the rate of growth is estimated from
various data sets. The subsequent section examines characteristics of home schooled
children and their families, with a focus on those characteristics most relevant for
gauging trends in home schooling. Finally, there is a discussion of some of the
implications of home schooling for regular schools and a brief conclusion.
Data on Home Schooling
The data for this project include the 1994 October Current Population Survey (CPS)
(U.S. Census Bureau 2000) and the National Household Education Surveys (NHES) of
1996 and 1999 (Nolin et al. 2000). All three are national household surveys of high
quality. The CPS relies on a combination of in-person and telephone interviewing of a
large sample (approximately 60,000 households) of the U.S. population. I use 24,829
CPS cases where subjects were age 6 to 17. In October of each year, a supplement on
school enrollment of children and adults is administered in all CPS households. The
content of this supplement varies slightly from year to year, and in 1994 questions on
home schooling were added to the main enrollment questions in the supplement for
children. The questions differed according to the response to the initial question on
school enrollment.
If it was reported that a child was not currently enrolled in school, the child
or proxy was asked:
"Were you/Was ... being schooled primarily at home?"
If the child was currently in school the question was:
"Are you/Is ... attending (1) a regular day school, (2) boarding school, (3)
schooled primarily at home by someone paid by the school, (4) schooled
primarily at home by a parent or other person paid or chosen by a parent, (5)
someplace else."
The number choosing answer (3) was relatively small, and for the purposes of this
research, responses (3) and (4) were both counted as "home schooling."
The NHES surveys are nationally-representative telephone surveys administered by the
National Center for Education Statistics. The two most recent surveys, in 1996 and 1999
have included questions on home schooling. The number of children 6 to 17 was 16,257
in 1996 and 10,718 in 1999.
In both years, the same question was asked of all children:
"Some parents decide to educate their children at home rather than sending
them to school. Is ... being schooled at home?"
The datasets also provide several types of information on characteristics of home
schoolers and their families. All provide race, Hispanic ethnicity, age, and sex of
children. They also provide information on the household: number of adults in the
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household, their education, labor force participation and household income. In both the
CPS and NHES, income was given in ranges. For regression analyses, these were
recoded to the midpoints and differenced from the mean. CPS provided state of
residence, metropolitan status and urban/rural location. Although it is traditional to use
Census-defined regions for analyses, it was felt that home schooling may not be
following traditional patterns. Frey (2000) developed a regional taxonomy that reflects
the major migration patterns of recent years, and these are probably more closely related
to the types of social trends that would affect home-schooling decisions. The states were
recoded to regions following this migration taxonomy. An urban-rural division was
developed from metropolitan and urban/rural variables in CPS. (Note 2) In both 1996
and 1999, the NHES asked parents of home schoolers about their motivations for
teaching their children at home. Respondents were asked to select reasons from a list of
16.
All analyses in this article use weighted data, adjusted to reflect an assumed design
effect of 2.0, except that the standard errors associated with the total number of home
schoolers were estimated using the Taylor-series linearization method available in the
SAS statistical package. Specific types of analysis are described as they appear in the
following discussion.
Extent and Growth of Home Schooling
Table 1 shows the number of home schooled children age 6 to 17 estimated from these
data sources. Taken at face value, they show a growth from 360,000 in 1994 to 790,000
in 1999. By 1999, then, around 1.7 percent of children in the 6 to 17 age range were
schooled at home. A 95 percent confidence interval for the 1999 figure goes from
670,000 to 910,000. Even at the high end of the range, the home-school population is
under 1 million and less then 2 percent of all children 6-17.
Table 1
Estimates of the Number of U.S. Children Schooled at Home:
Current Population Survey & National Household Education Surveys
Estimate Standard error
CPS 1994 356,000 40,000
NHES 1996 636,000 54,000
NHES 1999 791,000 62,000
Under-reporting
Because home schooling has become legal in most states only recently, and because
regulations are sometimes cumbersome, there are a number of home-schoolers who have
not reported their status to the state or local educational authorities, and would
presumably be reluctant to report their status to interviewers. At the same time, other
households may claim they are "home schooling" when they keep children away from
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school for other reasons or when they instruct their children while also sending them to
school. Lines (1999) produced a reasonable estimate of home-schooling by using reports
from state education departments in conjunction with estimates of reporting rates from a
survey by Ray (1997). It is possible to similarly check the CPS estimates against state
agency reports state-by-state.
I examined the 10 states with the highest and lowest reporting rates for which Lines was
able to get state education department figures. CPS estimates were slightly lower than
the number from state agencies in both cases. (Note 3) If Ray's estimates of reporting
rates are reliable, therefore, in states where few home-schoolers reported to authorities,
few reported to interviewers. Using a few simplifying assumptions, I calculated an
"adjusted" number of home schoolers of 750,000 in 1994. (Note 4) If we assume 8
percent annual growth in home schooling, the NHES estimate from 1999 would be about
25% too low, and the actual number of home schoolers could be close to 1.1 million.
However, this estimate depends critically on the validity of Ray's estimates of
non-reporting (see discussion in Lines 1999). Until there is better evidence on the true
rate of reporting, the unadjusted NHES figures are clearly the best available estimates.
Growth in home schooling
Unfortunately, the point estimates from these data cannot be used directly to make such
inferences. The 1994 CPS estimate of 360,000 is not much more than half the size of the
1996 NHES estimate of 640,000. This difference is statistically significant, but is too
large to be explained by growth in the home-school population. Hemke et al. (2000),
noted that the gap is implausibly large, but were unable to pinpoint an explanation. A
likely reason for the discrepancy is the difference in question wording between CPS and
NHES. In the CPS, the form of the home schooling question depended on the previous
answer to the question on school enrollment. If a household reported children were
attending school, they were not asked directly about home schooling, but had to choose
it from a list. That this results in a lower response is evident from the extremely low rate
of home schooling observed in the subset of CPS respondents who responded
affirmatively to the enrollment question. In the CPS, only 190,000 children were
reported as in school, but also home schooled. In the 1996 NHES, 450,000 children were
reported this way. By contrast, people who initially indicated non-enrollment faced
similar yes/no questions on home schooling in both surveys. They were much closer in
number—170,000 home schoolers in CPS and 190,000 in the 1996 NHES.
The 1999 NHES data seem also to show growth in home schooling. However, the
growth is not quite statistically significant from 1996, given the sample size (the p-value
of the 1996 to 1999 difference is between .05 and .10). Since the two NHES surveys are
nearly identical in content and methodology, the trend based on these two data points
provide the best estimate of growth, but the range is wide. A 95 percent confidence
interval provides a range from 3 percent annual decline to 15 percent annual growth.
At the first level of analysis, therefore, we can't say a lot about the growth of the home
schooling population. We can, however, refute some of the grander claims that have
been made by advocates. The number of home schooled children was well under 1
million in 1999, and the growth rate from 1996 to 1999 was unlikely to have exceeded
15 percent per year.
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More evidence on growth
The NHES data are insuficient to show growth in a statistical sense. However, if we can
bring additional evidence to bear, we can increase our confidence that growth is actually
taking place. One way to get additional evidence on trends in home schooling is to
examine trends in reports of school non-enrollment. For children in the prime
school-enrollment ages 7-9 and 10-13, published estimates show non-enrollment
remained consistently at or below 1 percent from the mid 1950s to the early 1990s. From
1995 to 1999, however, non-enrollment exceeded 1 percent 4 out of 5 years (Jamieson et
al. 2001). An increase in the non-enrolled population is not the same as an increase in
home schooling, but there is overlap. In the 7 to 14 age range, just under one-half of
non-enrolled students were home schooled, according to tabulations from the 1994 CPS,
and there is a correlation of around 0.5 between home-schooling and non-enrollment
across states. A regression analysis of non-enrollment across years, using CPS data for
1989 to 1999 shows a significant upward trend (data not shown—available from author
on request). This confirms that the observed increase in recent years is not attributable to
sampling error.
A group that is especially likely to be home schooled consists of two-adult families with
one not working (as will be shown below). In this group, 60 percent of non-enrolled
children are home schooled. The regression of non-enrollment on years shows an equally
large and significant coefficient for this group as it does for all school-aged children.
In sum, evidence on non-enrollment reinforces the direct evidence available from the
two NHES surveys: there seems to be an upward trend in home schooling. Other
evidence might also be interpreted as supporting this conclusion, including demographic
characteristics and geographic location. These are explored next.
Characteristics of Home-Schooled Children
To better understand trends in home schooling it is helpful to know what similarities and
differences exist between home-schooled children and those in regular school. If home
schoolers are currently limited to a portion of the population with distinct characteristics
it is possible that the phenomenon will be self-contained. On the other hand, if those
characteristics are becoming more prevalent in the population, then home schooling
might grow along with the group in which it's found.
Home schoolers are like their peers in many respects. Table 2 shows how they compare,
using data from all three surveys under consideration. Home schoolers are not especially
likely to be young or old. They are about as likely to be of one sex or the other, with
perhaps a slightly greater percentage female. In some ways, however, home-schoolers do
stand out. Home schooled children are more likely to be non-Hispanic White, they are
likely to live in households headed by a married couple with moderate to high levels of
education and income. They are more likely to live in households with three or more
children and they are likely to live in a household with an adult not in the labor force.
Table 2
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Characteristics of Home-Schooled Children and their Families
Current Population Survey & National Household Education Surveys
1994 1996 1999
Home
School
Regular
School
Home
School
Regular
School
Home
School
Regular
School
Age
6-7 24.0 17.2 11.7 17.4 13.8 17.8
8-10 30.6 25.6 25.9 25.6 26.1 25.0
11-14 27.8 33.8 34.0 33.1 31.7 32.4
15-17 17.5 23.4 28.5 24.0 28.4 24.9
Sex
Male 46.8 51.1 42.2 51.5 46.2 50.9
Female 53.2 48.9 57.8 48.5 53.8 49.1
Number of children
One child 15.2 20.6 18.9 21.2 16.3 21.4
Two children 20.9 39.4 25.8 39.4 29.8 38.3
Three or more 63.9 40.1 55.2 39.4 53.9 40.4
Race, ethnicity
White 91.9 67.6 86.8 67.7 75.8 64.8
Black 2.8 15.9 2.2 15.6 8.8 16.1
Hispanic 4.4 12.8 8.0 12.5 9.1 13.9
Other 0.8 3.7 3.1 4.2 6.2 5.2
Family structure
Single parent 11.3 29.9 20.8 30.8 20.6 34.5
Two parent 88.7 70.1 79.2 69.2 79.4 65.6
Non-working parent
Parents work 34.0 68.1 41.3 72.0 38.8 74.0
Non-working parent 66.0 31.9 58.7 28.0 61.2 26.0
Family income
Up to 14,999 18.8 23.2 21.1 21.1 12.3 18.6
15,000 to 29,999 14.9 20.4 26.9 22.6 25.7 21.3
30,000 to 49,999 40.4 26.5 29.1 25.5 24.8 23.7
50,000 or more 25.9 29.9 22.9 30.7 37.1 36.4
Mother's education
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Less than h.s. 8.8 17.7 14.2 16.4 5.3 16.4
High school 31.2 35.4 23.6 33.7 28.9 29.2
Some college 37.9 28.9 40.5 28.3 34.3 29.9
Bachelor's 19.3 12.9 17.5 15.1 22.5 16.3
Advanced 2.9 5.1 4.2 6.5 9.0 8.1
Table 3 shows these relationships in a multiple regression framework. This regression
can't be interpreted as causal, as it includes several factors that are probably endogenous
to the home-schooling decision (e.g., parental work status and household income). What
can be seen, however, is the relative magnitude of different influences when taken
together. Automatic model selection routines were used to develop a pared down
regression equation because some coefficients were sensitive to the inclusion or
exclusion of other variables in the model. The initial set of variables included all those
in Table 2, along with interactions of all variables with survey year. Two of the effects
(the main effect of being Black, and the effect of father's education) were retained even
though they didn't meet the cutoff criterion in the selection routine, because of their
possible substantive importance.
Table 3
Logistic Regression of Home-school Status
on Background and Family Characteristics:
Pooled Data from CPS & NHES
Regression
Coefficient
Standard
Error
t–
statistic
Two-parent family 0.313 (0.177) 1.8
Non-working parent 1.337 * (0.131) 10.2
Income squared -0.018 * (0.004) -4.1
Mother postsecondary educ. 0.601 * (0.143) 4.2
Father postsecondary educ. 0.293 (0.173) 1.7
Age 14 to 17 0.283 * (0.132) 2.1
Number of children in household 0.300 * (0.039) 7.8
Male -0.213 (0.124) -1.7
Hispanic -1.015 * (0.245) -4.1
Black -0.521 (0.348) -1.5
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Black * 1994 -1.584 * (0.766) -2.1
Black * 1996 -1.750 * (0.788) -2.2
West 0.461 * (0.160) 2.9
South 0.484 * (0.146) 3.3
1994 -0.472 * (0.169) -2.8
Intercept -6.170 * (0.249) -24.8
Observations 55,204
Null likelihood 2,936.7
Residual likelihood 2,606.7
Difference 330.1
Model degrees of freedom 15
* Significant at the .05 level.
Most of the same variables that showed differences across home-school status in cross
tabulations were also significant in the regression analysis. Sex and age were retained as
marginally significant. It seems that girls are slightly more likely to be home schooled
than boys, and teenagers more likely than younger children. Household variables had
stronger effects—family structure, mother's education, father's education, region of
residence. The number of children in the household had a very strong effect. The main
effect of income was not significant. However, the square of income had a relatively
strong effect. This indicates that the families most likely to home-school their children
are of middle income—neither rich nor poor. Race and ethnicity clearly had strong
effects. Hispanics were less likely to be home schooled and Blacks were much less likely
to be home schooled—especially in the two earlier years under study, 1994 and 1996. It
seems that convergence between Blacks and Whites has taken place from 1994 to 1999,
but the effect is not quite significant. We will have to await new rounds of surveys in
order to see if this is a sustained trend.
One of the strongest influences on home schooling from Table 3 is that of having a
non-working adult in the household. The coefficient of there being a non-working adult
is large and highly significant. The cross-tabular results of Table 2 gave a hint that this
relationship was diminishing across years, but the interaction with year was not
significant in the multiple regression framework. However, the main effect of
non-working remains. Sixty percent of home schooled children have a non-working
adult in the home, compared with thirty percent of other children. If home schooling is
limited to a particular subgroup, it is probably this one.
A major issue arising from the association of home schooling with the presence of a
non-working adult is the possible limitations this presents to future growth. Although 40
percent of home-schoolers lived with working adults, at least one adult was in the labor
force only part time in most cases (figures not shown). Fewer than 10 percent lived with
two full-time working adults. If home schooling is primarily an activity undertaken by
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two-parent families with a non-working parent, it could be a self-limiting phenomenon.
However, even if home schooling does remain mainly within this group, it has not come
close to exhausting its constituency. Seven and one-half million two-adult households
have a non-working adult at home, and the number has remained stable in recent years,
despite declines in previous decades. More broadly, of 36 million women with children
under 18, ten million do not work, and another 6.5 million work part time (U.S. Bureau
of Labor Statistics 2000). The number of home schooled children could grow from
790,000 to over 30 million without exhausting this core constituency.
Is it possible that home schooling may spread beyond this core group of two-parent
families with a parent at home? Must it also be limited to households where parents have
moderate to high education? While it would seem that having a (well educated) parent at
home would be a prerequisite for engaging in home schooling, this is not an absolute
requirement. Many home school households have working adults and adults with low
education. In all three surveys a small number of home-schooled children lived with a
single parent or with two adults in the labor force full time. In addition, a small number
had no adult in the home with a high school diploma. A follow-up question in the 1999
NHES on participation in regular school by home schoolers showed that many of the
home-schooled children who lived with working adults were also attending school at
least part of the time. Still, a portion of parents remained who seemed to be defying
logic by schooling their children at home without being home themselves. Further
exploration of these cases might turn up special circumstances (home businesses, odd
working hours, cooperative instructional arrangements) that could provide an
explanation. Alternatively, these families could be making use of Internet courseware or
other technologies to avoid the need for direct instruction. Many advice books and
curricula promise home education can be successful even when parents have little time
or training for the job. (Note 5)
Geographic distribution
One final way in which home school children differ from their peers is geographic
location, as shown in Table 4. Home schoolers are more likely to be located
geographically in places that have been destinations for internal migration. Using a
division of the country according to migration patterns developed by Frey (2000), home
schoolers are seen to be located in rural and suburban areas of the West which have been
the recipient of migration streams from California and other immigration gateway states.
Many of these areas have experienced explosive population growth. Growth, however, is
not the main feature of areas where home-schoolers are found. The correlation of growth
rate and home schooling rate of geographic areas is positive but small (around 0.2).
Looking at a scatter plot of the two (not shown) makes it evident that home schooling is
not found in booming growth areas nor in areas of decline but in places with moderate to
high rates of growth. Nonetheless, if a person wanted to make a case that home
schooling is on a path towards further growth, it would not hurt to point out that it is
prevalent in growing areas that are at the leading edge of one of the major changes in
migration patterns of the last few decades. Home schooling is tied to a broad social trend
that has not yet played itself out.
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Table 4
Estimated Percentage of Children Home Schooled
by Geographic Location: CPS 1994
Geographic
Region
Metropolitan
Status
Lower
bound
Point
estimate
Upper
bound
White gainers Non-metro 1.69 2.34 3.00
White gainers Suburb 1.27 1.81 2.34
Melting pots Non-metro 1.14 1.60 2.06
Black&White City 0.44 1.00 1.56
Black&White Suburb 0.68 0.98 1.28
Slow growth Non-metro 0.60 0.80 0.99
Slow growth Suburb 0.52 0.66 0.81
Melting pots Suburb 0.48 0.62 0.76
White gainers City 0.13 0.58 1.02
Slow growth City 0.32 0.50 0.68
Black&White Nonmetro 0.19 0.38 0.57
Melting pots City 0.22 0.35 0.49
Geographic Definitions
Immigrant melting pots
California, Hawaii, New Mexico, Texas, Florida, New Jersey, New York
Mostly White gainers
Alaska, Idaho, Montana, Oregon, Washington, Arizona, Colorado, Nevada, Utah, Wyoming
White and Black gainers
Alabama, Arkansas, Mississippi, Georgia, Tennessee, Delaware, N Carolina, S Carolina, Virginia
Slow growth/decliners
Louisiana, Connecticut, Rhode Island, Maine, Massachusetts, New Hampshire, Vermont, D.C.,
Kentucky, Maryland, W Virginia, Pennsylvania, Michigan, Ohio, Illinois, Indiana, Wisconsin,
Kansas, Missouri, Nebraska, Oklahoma, Iowa, Minnesota, N Dakota, S Dakota
Attitudes toward home schooling
The 1996 and 1999 NHES asked parents their reasons for undertaking home schooling,
with 16 possible responses. Several themes emerge from these responses. See Table 5.
First is the issue of educational quality. The parents of one-half the home schoolers in
these surveys were motivated by the idea that home education is better education. A
large share also viewed the issue in terms of shortcomings of regular schools: the parents
of 30 percent of home-schoolers felt the regular school had a poor learning environment,
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14 percent objected to what the school teaches, and another 11 percent felt their children
weren't being challenged at school. Another theme had to do with religion and morality.
Religion was cited by 33 percent of parents and morality by 9 percent. Practical
considerations (transportation to school, the cost of private school) seemed of relatively
minor importance. If attitudinal responses are to be believed, home schooling is not
primarily a religious phenomenon, although religion is important. Families participating
in home schooling do not cite cost as a barrier, even though one might presume that
private schools could respond to their academic and moral concerns.
Table 5
Reasons Given by Parents for Choosing Home Schooling:
1996 and 1999 Home Schooled Children: NHES Surveys
Reason Percent
Can give child better education at home 50.8
Religious reasons 33.0
Poor learning environment at school 29.8
Other reasons 23.0
Object to what school teaches 14.4
School does not challenge child 11.5
Family reasons 11.0
Child has special needs/disability 9.0
To develop character/morality 8.5
Other problem with available public/private schools 6.2
Student behavioral problems 5.3
Want private school but cannot afford it 3.4
Child has temporary illness 2.9
Parent's career 2.2
Transportation/distance/convenience 1.9
Could not get into a desired school 1.3
Many discussions of home school as a phenomenon refer to two classes of home
schoolers—those from families with religious motivations and those with primarily
academic concerns (Dobson 2000, Lines 2000a). To test this proposition, a latent class
analysis was performed on the set of attitudinal questions listed above. The two-class
model, however, provided only marginally better fit to the data than the null model. The
BIC criterion, traditionally used to evaluate the fit of such models (see Raftery 1997),
favors the null (one class) model over the two-class model. On the other hand, if weight
is given to prior observations of two groups with two different sets of motivations, the
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two-class model might be preferred. Table 6 shows some of the characteristics of the
two classes that emerge (using modal category extraction) from such a model. The first
class of home schoolers contains 90 percent of the total, and resembles the smaller
second class in all but a few attitudinal areas. Areas where there was a substantial
difference between classes are shown in the bottom four rows of Table 6 (ranked from
the largest to the smallest difference in odds of holding the attitude). The second, smaller
class was more likely to name academic and other shortcomings of available schools,
especially objections to what the school teaches, lack of challenge for the
home-schooled child and poor learning environment. Religion was also likely to be
named by the second, smaller class, although the effect was smaller than with the
academic attitudes.
Table 6
Latent Class Analysis Results:
Characteristics of Two Classes of Parents with Different Patterns
of Reasons Given for Choosing Home Schooling: NHES Surveys
Class 1 Class 2
Total percentage in class 90.3 9.7
Object to what school teaches 9.1 60.2
School does not challenge child 8.9 36.3
Poor learning environment at school 25.3 64.8
Religious reasons 30.9 59.8
In summary, if there are two classes of home schoolers, they differ mostly in terms of the
degree to which they express negative attitudes towards the schools available to them
now. No simple division exists between religiously motivated and academically
motivated parents. Due to the small sample of home schoolers available in the two
NHES surveys, however, the evidence is still fragmentary on this point.
Discussion and Conclusion
Discussion
Although the evidence on characteristics of home schoolers is still incomplete, it is
important that we take account of these characteristics now, rather than waiting for
further data collections to provide additional detail. Home schooling, despite being
smaller and slower-growing than claimed by some advocates, is still an important
emerging phenomenon. What it portends for our current system of schools is still
unknown.
Home schooling has emerged with, and indeed is linked to, other emerging educational
trends—on-line education and other systems that allow families and individuals to
choose their own educational paths (school vouchers, charter schools). At the same time,
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it flies in the face of trends towards educational standardization, such as national
curricula and systems of assessment. Another type of standardization is resulting from
establishment of increasingly detailed systems of occupational credentialing and
licensure (Adelman 2000). These trends might not be easily reconciled. High stakes
testing, especially, has come under strong attack from home-schooling groups (see, for
example, Home School Legal Defense Association 2001).
The period of institutional flux now reigning in education may be the start of a departure
from the 20th century model of regimented instruction for students entering an
industrializing world. Schools seem to have lost some of their legitimacy as they have
lost a clear functional role in preparing youth for their role in the larger economic system
(cf. Bowles and Gintis 1976, Dreeben 1968). Rather than representing a definite trend
towards "individualizing" instruction, however, home schooling may represent an
attempt by parents to reclaim the schooling process—to make schooling valuable in
ways that are understandable to them through the cultural means at their disposal
(Swidler 1986). This is not incompatible with Apple's (2000) description of home
schooling as part of "conservative modernization." Yet home schooling may not be
linked to a unified conservative agenda in quite the way he describes. There is a true
tension between home educators and the school standards movement, just as there is
between home schooling and the increasing demand by employers for occupationally
specific training and credentials. What these movements have in common is not a
conservative agenda but an attempt by each sector with an interest in schooling to gain
greater control over the system.
It may be that home schoolers come to create their own, new schools, as predicted by
Hill (2000). It may be that home schoolers remain independent. In either case, however,
as home schooling grows, calls will continue for existing public schools to provide
services that cannot be provided easily by home-school families themselves—such as
advanced courses and extracurricular activities. Lines (2000b) has shown how schools in
the state of Washington have reacted to this challenge. They have designed special
programs and learning centers where parents can often take a more active role in the
instructional process. If this continues as a trend, schools will find themselves
increasingly opening their doors to parental participation in ways they have not in the
past. At the same time, certain families will be allowed to pick and choose among school
offerings. The pressures on schools that might result, in an environment with increasing
competition from other instructional providers, are easily envisioned.
The alternative to accommodating home schoolers would involve political difficulties.
First, home schoolers making no use of regular school facilities could not be counted on
to provide political support for school funding. Second, the schools would lose an ally in
fighting battles against standardization, test requirements and credentialing that make it
increasingly difficult to provide a broad, general education to children. Dealing with
home schoolers will require a difficult balance of competing claims. The success of
traditional schools in dealing with the home-school phenomenon will depend on school
leadership.
Conclusion
The data examined here show that it has established itself as an alternative to regular
school for a small set of families, and is poised to continue its growth. In 1999 around
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790,000 children between the ages of 6 and 17—around of 1.7 percent of the population
that age—were being schooled at home, and in the late 1990s the number was apparently
growing.
Home schoolers and their families were different from regular school attenders and their
families, but the differences weren't that large. Some of the distinctive characteristics of
home schoolers seemed to be decreasing. Home schoolers were likely to be
non-Hispanic White, but there was some evidence of fading racial differences over time.
Some distinctive characteristics of home schoolers seemed not to be changing very
rapidly, but the characteristics needn't be thought of as limitations to future growth.
Households with home-schooled children had moderate to high education and income
and were located in the rural or suburban West. Home-schoolers were likely to live with
two adults, with one not in the labor force or working part time.
We have just begun to see the emergence of home schooling as an important national
phenomenon. Unless the needs of parents are met in different ways, it is likely that home
schooling will have a large impact on the school as an institution in coming decades.
Notes
The author would like to thank Wendy Bruno for her helpful advice and Karen
Kosanovich for providing tables on family employment trends. An earlier version of this
article was presented at the annual meetings of the Population Association of America,
Washington, D.C., March 2001. I report the results of research and analysis undertaken
by Census Bureau Staff. It has undergone a more limited review than official Census
Bureau publications. This report is released to inform interested parties of research and
to encourage discussion.
1. A search of the ERIC database for 1999 revealed 106 citations under "charter
schools," but only 47 under "home schooling."
2. Due to rules of disclosure limitation, there was no complete taxonomy of
metropolitan/non-metropolitan status or urban/rural status in the CPS files. In this
research a composite measure was created, using the three way central city, balance of
MSA and Metropolitan classification if it was available. Otherwise, MSA size was used,
with over 5 million classified as "city" and under 100,000 or non-metro classified as
non-metro.
3. Lines data were for the 1995 school year, while the CPS data were collected in 1994. I
adjusted Lines estimates downward by 5 percent to represent interim growth. If growth
were faster, the proper adjustment would raise the estimate of CPS coverage relative to
state reports, making my subsequent adjustment for undercount slightly too large.
4. To adjust home schooling to include non-reporting families I simply divided the CPS
estimate in each state by the reporting rate found by Ray. Doing so provides a point
estimate of well over 1 million home schoolers. However, this result isn't really
plausible, as the bulk of the home schooled population turns up in a few states where
Ray found extremely low rates (e.g., 0.5 million, or nearly half of all home-schoolers, in
Oklahoma). I adopted a the simple assumption that the interview reporting rate is never
lower than 20 percent. This eliminated the implausibly large numbers and resulted in
what I believe is a fairly reasonable high-end estimate.
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5. An example of this is the recent publication of a book entitled The Complete Idiot's
Guide to Home Schooling (Education Week 2001). Many curriculum providers advertise
their wares on the Internet and appear at home schoolers' conferences.
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About the Author
Kurt J. Bauman
Education and Social Stratification Branch
Population Division
U.S. Census Bureau
Washington, DC 20233-8800
Email: kurt.j.bauman@census.gov
Kurt Bauman is a demographer in the Education and Social Stratification Branch in the
U.S. Census Bureau. His past research has explored the finding that, controlling for
family background factors, predicted education levels for blacks are higher than those of
whites in the U.S. He found that black educational attainment net of family background
influences was found to have emerged in the 1950s or earlier, well in advance of
affirmative action programs emerging in the 1960s. He has also researched school work,
grades and family background influences on educational attainment. Other work has
included projected educational attainment levels in the United States under varying
assumptions about immigration trends.
Copyright 2002 by the Education Policy Analysis Archives
The World Wide Web address for the Education Policy Analysis Archives is epaa.asu.edu
General questions about appropriateness of topics or particular articles may be
addressed to the Editor, Gene V Glass, glass@asu.edu or reach him at College
of Education, Arizona State University, Tempe, AZ 85287-2411. The
Commentary Editor is Casey D. Cobb: casey.cobb@unh.edu .
EPAA Editorial Board
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Michael W. Apple
University of Wisconsin
Greg Camilli
Rutgers University
John Covaleskie
Northern Michigan University
Alan Davis
University of Colorado, Denver
Sherman Dorn
University of South Florida
Mark E. Fetler
California Commission on Teacher Credentialing
Richard Garlikov
hmwkhelp@scott.net
Thomas F. Green
Syracuse University
Alison I. Griffith
York University
Arlen Gullickson
Western Michigan University
Ernest R. House
University of Colorado
Aimee Howley
Ohio University
Craig B. Howley
Appalachia Educational Laboratory
William Hunter
University of Calgary
Daniel Kallós
Umeå University
Benjamin Levin
University of Manitoba
Thomas Mauhs-Pugh
Green Mountain College
Dewayne Matthews
Education Commission of the States
William McInerney
Purdue University
Mary McKeown-Moak
MGT of America (Austin, TX)
Les McLean
University of Toronto
Susan Bobbitt Nolen
University of Washington
Anne L. Pemberton
apembert@pen.k12.va.us
Hugh G. Petrie
SUNY Buffalo
Richard C. Richardson
New York University
Anthony G. Rud Jr.
Purdue University
Dennis Sayers
California State University—Stanislaus
Jay D. Scribner
University of Texas at Austin
Michael Scriven
scriven@aol.com
Robert E. Stake
University of Illinois—UC
Robert Stonehill
U.S. Department of Education
David D. Williams
Brigham Young University
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Roberto Rodríguez Gómez
Universidad Nacional Autónoma de México
roberto@servidor.unam.mx
Adrián Acosta (México)
Universidad de Guadalajara
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J. Félix Angulo Rasco (Spain)
Universidad de Cádiz
felix.angulo@uca.es
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Centro de Investigación y Docencia
Económica-CIDE
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Alejandro Canales (México)
Universidad Nacional Autónoma de
México
canalesa@servidor.unam.mx
Ursula Casanova (U.S.A.)
Arizona State University
casanova@asu.edu
José Contreras Domingo
Universitat de Barcelona
Jose.Contreras@doe.d5.ub.es
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Loyola University of Chicago
Eepstein@luc.edu
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Arizona State University
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Departamento de Investigación
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Universidad Federal de Rio Grande do
Sul-UFRGS
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Universidad Nacional Autónoma de
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Fundação Instituto Brasileiro e Geografia
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