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1 of 21 Education Policy Analysis Archives Volume 10 Number 26May 16, 2002ISSN 1068-2341 A peer-reviewed scholarly journal Editor: Gene V Glass College of Education Arizona State University Copyright 2002, the EDUCATION POLICY ANALYSIS ARCHIVES .Permission is hereby granted to copy any article if EPAA is credited and copies are not sold. EPAA is a project of the Education Policy Studies Laboratory. Articles appearing in EPAA are abstracted in the Current Index to Journals in Education by the ERIC Clearinghouse on Assessment and Evaluation and are permanently archived in Resources in Education .Home Schooling in the United States: Trends and Characteristics Kurt J. Bauman U.S. Census BureauCitation: Bauman, K. J. (2002, May 16). Home school ing in the United States: Trends and Characteristics. Education Policy Analysis Archives 10 (26). Retrieved [date] from http://epaa.asu.edu/epaa/v10n26.html.AbstractHome schooling is a subject of great fascination, b ut little solid knowledge. Despite its importance, it has received less research attention than some other recent changes in the educational s ystem, such as the growth of charter schools. It could be argued that home schooling may have a much larger impact on educational system, bo th in the short and long run. This report uses the 1994 October CPS, an d the National Household Education Survey of 1996 and 1999 to exam ine popular characterizations of the home school population. Th e article assembles evidence from several sources to confirm that home schooling is growing. It finds home-schooled children more likel y to be middle

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2 of 21income, white, from larger families, and from two-p arent families with one parent not working. While some authors have des cribed a division between religiously-motivated and academically-moti vated home schoolers, this research finds more support for a d ivide based on attitude towards regular schools. The Impact of Home SchoolingHome schooling is a subject of great fascination, b ut little solid knowledge. Compared with other recent changes in the educational system such as the growth of charter schools, home schooling has received relatively lit tle 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 man y 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 institutiona l forms into being that have the potential to grow over the longer term (Trotter 200 1). ScaleAlthough other institutional innovations in the edu cational system have grown in recent years, home schooling is probably the largest chang e 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 school s, that enroll only a few thousand students in a few cities (see Gardner 2000). Home s chooling also involves a larger population than charter schools. According to estim ates 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 conservat ive estimates of the number of home schoolers put their numbers at that level or a bove (Lines 1999). Organizational changesCharter schools and voucher systems provide competi tive challenges to traditional public schools, and as such, provide a direct incen tive to adopt innovations and match the performance of other schools. However, the main outlines of current schooling practice have thus far remained intact. The challen ge of home schooling, by contrast, is more profound. Home schooling is a more radical dep arture from education as it is currently practiced, it affects more schools, and i t has the potential to force numerous adjustments to current curricular practices.Public schools in many jurisdictions have already b egun to provide services of various types to home schoolers. Laws in at least seven sta tes permit home schooled students to participate in sports, music and other extracurricu lar activities in regular schools (Farris 1997). In Florida and Iowa, schools also allow home schoolers to take individual courses.

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3 of 21New InstitutionsPerhaps the largest impact of home schoolers has be en the concomitant entry of new educational organizations into the field. Many priv ate organizations and enterprises have entered the K-12 distance education field with thei r 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 hig h school credit by home schoolers and others who choose to use this resource, and Illinoi s is developing a similar program (Carothers 2000, Trotter 2001). Meanwhile several f or-profit ventures have entered the field, offering courses and, in one case, accredite d diplomas over the Internet (Trotter 1999, Walsh 2001).If home schooling continues to grow, demand will gr ow for the types of services that are starting to be offered by public schools and distan ce education providers. A result will be pressure on schools to design school curricula t hat allow students and parents to pick and choose what they like. According to some observ ers, another result will be the creation of new schools and school-like institution s 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 att empts 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 giv ing a thorough overview of the home-schooled population (Smith & Sikkink 1999,Weln er 2000a, Welner 2000b, Lines 2000b). The two exceptions are reports by Lines (19 99) and the National Center for Education Statistics (Bielick 2001) who provide est imates of the home-school population. Lines conducted a careful analysis stat e education agency records of registered home schoolers, adjusting for probable l evels of non-registered home schooling. She estimated that there were 690,000 ho me-schooled children in 1995. The National Center for Education Statistics report ana lyzed the results of the 1999 National Household Education Survey, which is also one of th e data sets also analyzed in this article. They produced basic tabulations of the cha racteristics of home-schoolers, including grade equivalent, race, sex, family chara cteristics, 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 th e 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 re sports, 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 m easuring 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 s ubject by looking simultaneously at three national datasets on home schooling. The repo rt 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 tren ds and compositional changes in the home-schooled population. It examines their geograp hic location and potential for growth. Finally, it examines whether there are iden tifiable groups of home schoolers

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4 of 21with different reasons for pursuing home-schooling, as has been posited by many observers.The article proceeds as follows. It starts with a d iscussion 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 Househol d Education Surveys (NHES) of 1996 and 1999 (Nolin et al. 2000). All three are na tional household surveys of high quality. The CPS relies on a combination of in-pers on and telephone interviewing of a large sample (approximately 60,000 households) of t he U.S. population. I use 24,829 CPS cases where subjects were age 6 to 17. In Octob er of each year, a supplement on school enrollment of children and adults is adminis tered in all CPS households. The content of this supplement varies slightly from yea r to year, and in 1994 questions on home schooling were added to the main enrollment qu estions in the supplement for children. The questions differed according to the r esponse to the initial question on school enrollment. If it was reported that a child was not currently e nrolled 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 w as: "Are you/Is ... attending (1) a regular day school, (2) boarding school, (3) schooled primarily at home by someone paid by the s chool, (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 a s "home schooling." The NHES surveys are nationally-representative tele phone surveys administered by the National Center for Education Statistics. The two m ost recent surveys, in 1996 and 1999 have included questions on home schooling. The numb er 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 c hildren: "Some parents decide to educate their children at h ome rather than sending them to school. Is ... being schooled at home?" The datasets also provide several types of informat ion on characteristics of home schoolers and their families. All provide race, His panic ethnicity, age, and sex of children. They also provide information on the hous ehold: number of adults in the

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5 of 21 household, their education, labor force participati on and household income. In both the CPS and NHES, income was given in ranges. For regre ssion analyses, these were recoded to the midpoints and differenced from the m ean. CPS provided state of residence, metropolitan status and urban/rural loca tion. Although it is traditional to use Census-defined regions for analyses, it was felt th at home schooling may not be following traditional patterns. Frey (2000) develop ed a regional taxonomy that reflects the major migration patterns of recent years, and t hese are probably more closely related to the types of social trends that would affect hom e-schooling decisions. The states were recoded to regions following this migration taxonom y. An urban-rural division was developed from metropolitan and urban/rural variabl es 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 a sked to select reasons from a list of 16. All analyses in this article use weighted data, adj usted to reflect an assumed design effect of 2.0, except that the standard errors asso ciated with the total number of home schoolers were estimated using the Taylor-series li nearization 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 grow th from 360,000 in 1994 to 790,000 in 1999. By 1999, then, around 1.7 percent of child ren 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 ran ge, the home-school population is under 1 million and less then 2 percent of all chil dren 6-17.Table 1Estimates of the Number of U.S. Children Schooled a t Home: Current Population Survey & National Household Educ ation Surveys Estimate Standard error CPS 1994356,00040,000NHES 1996636,00054,000NHES 1999791,00062,000 Under-reportingBecause home schooling has become legal in most sta tes only recently, and because regulations are sometimes cumbersome, there are a n umber of home-schoolers who have not reported their status to the state or local edu cational authorities, and would presumably be reluctant to report their status to i nterviewers. At the same time, other households may claim they are "home schooling" when they keep children away from

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6 of 21school for other reasons or when they instruct thei r 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 wit h estimates of reporting rates from a survey by Ray (1997). It is possible to similarly c heck the CPS estimates against state agency reports state-by-state.I examined the 10 states with the highest and lowes t 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 simplifyi ng assumptions, I calculated an "adjusted" number of home schoolers of 750,000 in 1 994. (Note 4) If we assume 8 percent annual growth in home schooling, the NHES e stimate from 1999 would be about 25% too low, and the actual number of home schooler s could be close to 1.1 million. However, this estimate depends critically on the va lidity 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 schoolingUnfortunately, 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 s tatistically 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 u nable 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 qu estion depended on the previous answer to the question on school enrollment. If a h ousehold reported children were attending school, they were not asked directly abou t home schooling, but had to choose it from a list. That this results in a lower respon se is evident from the extremely low rate of home schooling observed in the subset of CPS res pondents who responded affirmatively to the enrollment question. In the CP S, only 190,000 children were reported as in school, but also home schooled. In t he 1996 NHES, 450,000 children were reported this way. By contrast, people who initiall y 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 tr end 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 dec line 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 1 999 was unlikely to have exceeded 15 percent per year.

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7 of 21 More evidence on growthThe NHES data are insuficient to show growth in a s tatistical 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 est imates show non-enrollment remained consistently at or below 1 percent from th e mid 1950s to the early 1990s. From 1995 to 1999, however, non-enrollment exceeded 1 pe rcent 4 out of 5 years (Jamieson et al. 2001). An increase in the non-enrolled populati on is not the same as an increase in home schooling, but there is overlap. In the 7 to 1 4 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 ho me-schooling and non-enrollment across states. A regression analysis of non-enrollm ent 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 increa se in recent years is not attributable to sampling error.A group that is especially likely to be home school ed consists of two-adult families with one not working (as will be shown below). In this g roup, 60 percent of non-enrolled children are home schooled. The regression of non-e nrollment 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 d irect 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 th is 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 an d 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-con tained. 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 respect s. Table 2 shows how they compare, using data from all three surveys under considerati on. 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 so me ways, however, home-schoolers do stand out. Home schooled children are more likely t o be non-Hispanic White, they are likely to live in households headed by a married co uple 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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8 of 21 Characteristics of Home-Schooled Children and their Families Current Population Survey & National Household Educ ation Surveys 199419961999 Home School Regular School Home School Regular School Home School Regular School Age6-724.017.211.717.413.817.88-1030.625.625.925.626.125.011-1427.833.834.033.131.732.415-1717.523.428.524.028.424.9SexMale46.851.142.251.546.250.9Female53.248.957.848.553.849.1Number of childrenOne child15.220.618.921.216.321.4Two children20.939.425.839.429.838.3Three or more63.940.155.239.453.940.4Race, ethnicityWhite91.967.686.867.775.864.8Black2.815.92.215.68.816.1Hispanic4.412.88.012.59.113.9Other0.83.73.14.26.25.2Family structureSingle parent11.329.920.830.820.634.5Two parent88.770.179.269.279.465.6Non-working parentParents work34.068.141.372.038.874.0Non-working parent66.031.958.728.061.226.0Family incomeUp to 14,99918.823.221.121.112.318.615,000 to 29,99914.920.426.922.625.721.330,000 to 49,99940.426.529.125.524.823.750,000 or more25.929.922.930.737.136.4Mother's education

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9 of 21 Less than h.s.8.817.714.216.45.316.4High school31.235.423.633.728.929.2Some college37.928.940.528.334.329.9Bachelor's19.312.917.515.122.516.3Advanced2.95.14.26.59.08.1 Table 3 shows these relationships in a multiple reg ression framework. This regression can't be interpreted as causal, as it includes seve ral 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 u sed to develop a pared down regression equation because some coefficients were sensitive to the inclusion or exclusion of other variables in the model. The init ial set of variables included all those in Table 2, along with interactions of all variable s 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 3Logistic Regression of Home-school Status on Background and Family Characteristics: Pooled Data from CPS & NHES Regression Coefficient Standard Errort–statistic Two-parent family0.313(0.177)1.8Non-working parent1.337*(0.131)10.2Income squared-0.018*(0.004)-4.1Mother postsecondary educ.0.601*(0.143)4.2Father postsecondary educ.0.293(0.173)1.7Age 14 to 170.283*(0.132)2.1Number of children in household0.300*(0.039)7.8Male-0.213(0.124)-1.7Hispanic-1.015*(0.245)-4.1Black-0.521(0.348)-1.5

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10 of 21 Black 1994-1.584*(0.766)-2.1Black 1996-1.750*(0.788)-2.2West0.461*(0.160)2.9South0.484*(0.146)3.31994-0.472*(0.169)-2.8Intercept-6.170*(0.249)-24.8Observations55,204Null likelihood2,936.7Residual likelihood2,606.7Difference330.1Model degrees of freedom15* 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 sli ghtly more likely to be home schooled than boys, and teenagers more likely than younger c hildren. Household variables had stronger effects—family structure, mother's educati on, 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 mos t likely to home-school their children are of middle income—neither rich nor poor. Race an d ethnicity clearly had strong effects. Hispanics were less likely to be home scho oled and Blacks were much less likely to be home schooled—especially in the two earlier y ears under study, 1994 and 1996. It seems that convergence between Blacks and Whites ha s taken place from 1994 to 1999, but the effect is not quite significant. We will ha ve to await new rounds of surveys in order to see if this is a sustained trend.One of the strongest influences on home schooling f rom 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. H owever, 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 th is 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 sho wn). Fewer than 10 percent lived with two full-time working adults. If home schooling is primarily an activity undertaken by

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11 of 21 two-parent families with a non-working parent, it c ould 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 ha s 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 schoo led children could grow from 790,000 to over 30 million without exhausting this core constituency. Is it possible that home schooling may spread beyon d this core group of two-parent families with a parent at home? Must it also be lim ited to households where parents have moderate to high education? While it would seem tha t having a (well educated) parent at home would be a prerequisite for engaging in home s chooling, this is not an absolute requirement. Many home school households have worki ng adults and adults with low education. In all three surveys a small number of h ome-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 sch oolers showed that many of the home-schooled children who lived with working adult s 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 b eing home themselves. Further exploration of these cases might turn up special ci rcumstances (home businesses, odd working hours, cooperative instructional arrangemen ts) that could provide an explanation. Alternatively, these families could be making use of Internet courseware or other technologies to avoid the need for direct ins truction. 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 distributionOne final way in which home school children differ from their peers is geographic location, as shown in Table 4. Home schoolers are m ore likely to be located geographically in places that have been destination s for internal migration. Using a division of the country according to migration patt erns developed by Frey (2000), home schoolers are seen to be located in rural and subur ban 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 popu lation 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) ma kes it evident that home schooling is not found in booming growth areas nor in areas of d ecline but in places with moderate to high rates of growth. Nonetheless, if a person want ed to make a case that home schooling is on a path towards further growth, it w ould 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 sc hooling is tied to a broad social trend that has not yet played itself out.

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12 of 21 Table 4Estimated Percentage of Children Home Schooled by Geographic Location: CPS 1994 GeographicRegion MetropolitanStatus Lower bound Point estimate Upper bound White gainersNon-metro1.692.343.00White gainersSuburb1.271.812.34Melting potsNon-metro1.141.602.06Black&WhiteCity0.441.001.56Black&WhiteSuburb0.680.981.28Slow growthNon-metro0.600.800.99Slow growthSuburb0.520.660.81Melting potsSuburb0.480.620.76White gainersCity0.130.581.02Slow growthCity0.320.500.68Black&WhiteNonmetro0.190.380.57Melting potsCity0.220.350.49Geographic 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, Massac husetts, New Hampshire, Vermont, D.C., Kentucky, Maryland, W Virginia, Pennsylvania, Michi gan, Ohio, Illinois, Indiana, Wisconsin, Kansas, Missouri, Nebraska, Oklahoma, Iowa, Minneso ta, N Dakota, S DakotaAttitudes toward home schoolingThe 1996 and 1999 NHES asked parents their reasons for undertaking home schooling, with 16 possible responses. Several themes emerge f rom these responses. See Table 5. First is the issue of educational quality. The pare nts 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 short comings of regular schools: the parents of 30 percent of home-schoolers felt the regular sc hool had a poor learning environment,

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13 of 21 14 percent objected to what the school teaches, and another 11 percent felt their children weren't being challenged at school. Another theme h ad to do with religion and morality. Religion was cited by 33 percent of parents and mor ality by 9 percent. Practical considerations (transportation to school, the cost of private school) seemed of relatively minor importance. If attitudinal responses are to b e 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, ev en though one might presume that private schools could respond to their academic and moral concerns.Table 5Reasons Given by Parents for Choosing Home Schoolin g: 1996 and 1999 Home Schooled Children: NHES Surveys Reason Percent Can give child better education at home50.8Religious reasons33.0Poor learning environment at school29.8Other reasons 23.0 Object to what school teaches14.4School does not challenge child11.5Family reasons 11.0 Child has special needs/disability9.0To develop character/morality8.5Other problem with available public/private schools 6.2 Student behavioral problems5.3Want private school but cannot afford it3.4Child has temporary illness2.9Parent's career 2.2 Transportation/distance/convenience1.9Could not get into a desired school1.3 Many discussions of home school as a phenomenon ref er to two classes of home schoolers—those from families with religious motiva tions and those with primarily academic concerns (Dobson 2000, Lines 2000a). To te st this proposition, a latent class analysis was performed on the set of attitudinal qu estions 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 f it of such models (see Raftery 1997), favors the null (one class) model over the two-clas s model. On the other hand, if weight is given to prior observations of two groups with t wo different sets of motivations, the

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14 of 21 two-class model might be preferred. Table 6 shows s ome of the characteristics of the two classes that emerge (using modal category extra ction) 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. Ar eas 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 h olding the attitude). The second, smaller class was more likely to name academic and other sh ortcomings of available schools, especially objections to what the school teaches, l ack 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 ef fect was smaller than with the academic attitudes.Table 6Latent Class Analysis Results: Characteristics of Two Classes of Parents with Diff erent Patterns of Reasons Given for Choosing Home Schooling: NHES Surveys Class 1Class 2 Total percentage in class90.39.7Object to what school teaches9.160.2School does not challenge child8.936.3Poor learning environment at school25.364.8Religious reasons30.959.8 In summary, if there are two classes of home school ers, they differ mostly in terms of the degree to which they express negative attitudes tow ards 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 fragme ntary on this point.Discussion and ConclusionDiscussionAlthough the evidence on characteristics of home sc hoolers is still incomplete, it is important that we take account of these characteris tics now, rather than waiting for further data collections to provide additional deta il. Home schooling, despite being smaller and slower-growing than claimed by some adv ocates, is still an important emerging phenomenon. What it portends for our curre nt system of schools is still unknown. Home schooling has emerged with, and indeed is link ed to, other emerging educational trends—on-line education and other systems that all ow families and individuals to choose their own educational paths (school vouchers charter schools). At the same time,

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15 of 21it flies in the face of trends towards educational standardization, such as national curricula and systems of assessment. Another type o f standardization is resulting from establishment of increasingly detailed systems of o ccupational credentialing and licensure (Adelman 2000). These trends might not be easily reconciled. High stakes testing, especially, has come under strong attack f rom home-schooling groups (see, for example, Home School Legal Defense Association 2001 ). The period of institutional flux now reigning in ed ucation may be the start of a departure from the 20th century model of regimented instructi on for students entering an industrializing world. Schools seem to have lost so me 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, hom e 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 cu ltural 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 th e way he describes. There is a true tension between home educators and the school stand ards movement, just as there is between home schooling and the increasing demand by employers for occupationally specific training and credentials. What these movem ents have in common is not a conservative agenda but an attempt by each sector w ith 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 i ndependent. In either case, however, as home schooling grows, calls will continue for ex isting public schools to provide services that cannot be provided easily by home-sch ool families themselves—such as advanced courses and extracurricular activities. Li nes (2000b) has shown how schools in the state of Washington have reacted to this challe nge. They have designed special programs and learning centers where parents can oft en 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 partic ipation in ways they have not in the past. At the same time, certain families will be al lowed to pick and choose among school offerings. The pressures on schools that might resu lt, in an environment with increasing competition from other instructional providers, are easily envisioned. The alternative to accommodating home schoolers wou ld involve political difficulties. First, home schoolers making no use of regular scho ol facilities could not be counted on to provide political support for school funding. Se cond, the schools would lose an ally in fighting battles against standardization, test requ irements 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. ConclusionThe data examined here show that it has established itself as an alternative to regular school for a small set of families, and is poised t o continue its growth. In 1999 around

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16 of 21790,000 children between the ages of 6 and 17—aroun d of 1.7 percent of the population that age—were being schooled at home, and in the la te 1990s the number was apparently growing.Home schoolers and their families were different fr om regular school attenders and their families, but the differences weren't that large. S ome of the distinctive characteristics of home schoolers seemed to be decreasing. Home school ers 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. Hom e-schoolers were likely to live with two adults, with one not in the labor force or work ing part time. We have just begun to see the emergence of home sch ooling 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.NotesThe author would like to thank Wendy Bruno for her helpful advice and Karen Kosanovich for providing tables on family employmen t 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 lim ited review than official Census Bureau publications. This report is released to inf orm 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 avail able. 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 r epresent 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-reportin g 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. How ever, this result isn't really plausible, as the bulk of the home schooled populat ion turns up in a few states where Ray found extremely low rates (e.g., 0.5 million, o r nearly half of all home-schoolers, in Oklahoma). I adopted a the simple assumption that t he interview reporting rate is never lower than 20 percent. This eliminated the implausi bly large numbers and resulted in what I believe is a fairly reasonable high-end esti mate.

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17 of 215. 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 a dvertise their wares on the Internet and appear at home scho olers' conferences.ReferencesAdelman, Clifford. 2000. A Parallel Postsecondary Universe: The Certificatio n System in Information Technology. Washington, D.C.: Office of Educational Research a nd Improvement, U.S. Department of Education.Apple, Michael W. 2000. "The Cultural Politics of H ome Schooling." Peabody Journal of Education 75(1&2):256-271. Archer, Jeff. 2000. "Home Study." Teacher Magazine. February. Bielick, Stacey, Kathryn Chandler and Stephen P. Br oughman. 2001. Homeschooling in the United States: 1999 (NCES 2001-033) Washington, DC: National Center f or Education Statistics.Bowles, Samuel & Herbert Gintis. 1976. Schooling in Capitalist America Basic Books. Carothers, Mary Lou. 2000. "Florida Home Education Programs, 19992000." In Florida Department of Education: Statistical Brief. . Center for Education Reform. 2001. "Charter School Highlights and Statistics." Web address: www.edreform.com/pubs/chglance.htm.Dobson, Linda. 2000. "A Brief History of American H omeschooling." Online article www.geocities.com/homeschoolers_success_stories/par t1.html Dreeben, Robert. 1968. On What is Learned in School AddisonWesley. Education Week. 2001. "Private Schools: Help at Hom e." Education Week April 11. Farris, Michael. 1997. The Future of Home Schooling: A New Direction for H ome Education. Washington, D.C.: Regnery Publishing, Inc. Frey, William H. 2000. "Regional Shifts in America' s Voting Aged Population: What do they mean for National Politics?" Population Studie s Center Research Report 00459. Ann Arbor, Mich: Institute for Social Research, Uni versity of Michigan. Gardner, Howard. 2000. "Paroxysms of Choice." New York Review of Books October 19.Henke, Robin R., Phillip Kaufman, Broughman, and Ka thryn Chandler. 2000. Estimating the Home Schooled Population in the Unit ed States Technical Report (Draft). Washington, DC: National Center for Educat ion Statistics. Hill, Paul T. 2000. "Home Schooling and the Future of Public Education." Peabody Journal of Education 75(1&2):2031.

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18 of 21Home School Legal Defense Association. 2001. "HSLDA News: Is this the Calm Before the Storm?" http://www.hslda.org/docs/news/hslda/20 0104201.asp Jamieson, Amie, Andrea Curry and Gladys Martinez. 2 001. School Enrollment in the United States, Social and Economic Characteristics: October 1999 Series P20-533. Washington, D.C.: U.S. Census Bureau.Lines, Patricia M. 1999. "Homeschoolers: Estimating Numbers and Growth." Web edition. Washington, D.C.: Office of Education Rese arch and Improvement, U.S. Department of Education.Lines, Patricia M. 2000a. "Homeschooling Comes of A ge." The Public Interest. (Summer):74-85.Lines, Patricia M. 2000b. "When Home Schoolers Go t o School: a Partnership Between Families and Schools." Peabody Journal of Education 75(1&2):159186. Nolin, Mary Jo, Jill Montaquila, Jean Lennon, Brian Kleiner, Kwang Kim, Christopher Chapman, Kathryn Chandler, Sean Creighton, and Stac ey Bielick. 2000. National Household Education Survey of 1999: Data File User' s Manual, Volume I. Washington, D.C.:National Center for Education Statistics.Raftery, Adrian. 1995. "Bayesian Model Selection in Social Research." In Sociological Methodology 1995. Peter V. Marsden, ed. Oxford: Basil Blackwell. Pp. 111-164. Ray, Brian. 1997. Strengths of Their Own Salem, Oregon: NHERI Publications. Rudner, Lawrence M. 1999. "Scholastic Achievement a nd Demographic Characteristics of Home School Students in 1998." Educational Policy Analysis Archives 7 (8). .Smith, Christian and David Sikkink. 1999. "Is Priva te Schooling Privatizing?" First Things 92(April): 1620. Swidler, Ann. 1986. "Culture in Action: Symbols and Strategies." American Sociological Review. 51(2, Apr.):273286. Trotter, Andrew. 1999. "For Profit Company to Offer High School Diploma over Internet." Education Week April 21. Trotter, Andrew. 2001. "Cyber Learning at Online Hi gh." Education Week January 24. U.S. Bureau of Labor Statistics. 2000. "Distributio n of families by type and labor force status of family members, 1940-2000" and "Employmen t status of women by presence and age of youngest child, March 1975-2000." Unpubl ished tables. Washington, D.C.: U.S. Bureau of Labor Statistics.U.S. Census Bureau. 2000. Current Population Survey Design and Methodology Technical Paper 63. Washington, D.C.: U.S. Census B ureau and U. S. Bureau of Labor Statistics.

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19 of 21 Walsh, Mark. 2001. "Former Education Secretary Star ts Online-Learning Venture." Education Week January 10. Welner, Kariane Mari. 2000a. "Goodbye Public School s: Homeschoolers Who Want to Dismantle the System." Paper presented at the annua l meeting of the American Educational Research Association, New Orleans, Loui siana. (April) Welner, Kariane Mari. 2000b. "Private Endeavors, Pu blic Vision: Homeschoolers Who Support Public Schools." Paper presented at the ann ual meeting of the American Educational Research Association, New Orleans, Loui siana. (April) Welner, Kariane Mari and Kevin G. Welner. 1999. "Co ntextualizing Homeschooling Data: A Response to Rudner." Educational Policy Analysis Archives 7 (13). http://epaa.asu.edu.Washington Post. 2000. "Home Schooling's Net Effect ." July 7.About the AuthorKurt J. BaumanEducation and Social Stratification BranchPopulation DivisionU.S. Census BureauWashington, DC 20233-8800Email: kurt.j.bauman@census.govKurt Bauman is a demographer in the Education and S ocial Stratification Branch in the U.S. Census Bureau. His past research has explored the finding that, controlling for family background factors, predicted education leve ls 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 o r earlier, well in advance of affirmative action programs emerging in the 1960s. He has also researched school work, grades and family background influences on educatio nal 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 ArchivesThe World Wide Web address for the Education Policy Analysis Archives is epaa.asu.edu General questions about appropriateness of topics o r 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 8 5287-2411. The Commentary Editor is Casey D. Cobb: casey.cobb@unh.edu .EPAA Editorial Board

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20 of 21 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 Kalls Ume 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 EPAA Spanish Language Editorial BoardAssociate Editor for Spanish Language Roberto Rodrguez Gmez Universidad Nacional Autnoma de Mxico roberto@servidor.unam.mx Adrin Acosta (Mxico) Universidad de Guadalajaraadrianacosta@compuserve.com J. Flix Angulo Rasco (Spain) Universidad de Cdizfelix.angulo@uca.es

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21 of 21 Teresa Bracho (Mxico) Centro de Investigacin y DocenciaEconmica-CIDEbracho dis1.cide.mx Alejandro Canales (Mxico) Universidad Nacional Autnoma deMxicocanalesa@servidor.unam.mx Ursula Casanova (U.S.A.) Arizona State Universitycasanova@asu.edu Jos Contreras Domingo Universitat de Barcelona Jose.Contreras@doe.d5.ub.es Erwin Epstein (U.S.A.) Loyola University of ChicagoEepstein@luc.edu Josu Gonzlez (U.S.A.) Arizona State Universityjosue@asu.edu Rollin Kent (Mxico)Departamento de InvestigacinEducativa-DIE/CINVESTAVrkent@gemtel.com.mx kentr@data.net.mx Mara Beatriz Luce (Brazil)Universidad Federal de Rio Grande do Sul-UFRGSlucemb@orion.ufrgs.brJavier Mendoza Rojas (Mxico)Universidad Nacional Autnoma deMxicojaviermr@servidor.unam.mxMarcela Mollis (Argentina)Universidad de Buenos Airesmmollis@filo.uba.ar Humberto Muoz Garca (Mxico) Universidad Nacional Autnoma deMxicohumberto@servidor.unam.mxAngel Ignacio Prez Gmez (Spain)Universidad de Mlagaaiperez@uma.es Daniel Schugurensky (Argentina-Canad)OISE/UT, Canadadschugurensky@oise.utoronto.ca Simon Schwartzman (Brazil)Fundao Instituto Brasileiro e Geografiae Estatstica simon@openlink.com.br Jurjo Torres Santom (Spain)Universidad de A Coruajurjo@udc.es Carlos Alberto Torres (U.S.A.)University of California, Los Angelestorres@gseisucla.edu


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