U.S. Department of Education

Institute of Education Sciences

NCES 2004–014

Computer and Internet

Use by Children and

Adolescents in 2001

Statistical Analysis Report
Matthew DeBell

Education Statistics

Services Institute/

American Institutes

for Research

Chris Chapman

National Center for

Education Statistics

U.S. Department of Education

Institute of Education Sciences

NCES 2004–014

Computer and Internet

Use by Children and

Adolescents in 2001

Statistical Analysis Report

October 2003
U.S. Department of Education

Rod Paige

Secretary

Institute of Education Sciences

Grover J. Whitehurst

Director

National Center for Education Statistics

Val Plisko

Associate Commissioner

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Suggested Citation

U.S. Department of Education, National Center for Education Statistics. Computer and Internet Use by Children

and Adolescents in 2001, NCES 2004–014, by Matthew DeBell and Chris Chapman. Washington, DC: 2003.

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Content Contact:

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Acknowledgements 

The authors wish to thank John Bailey of the U.S. Department of Education’s Office of 

Educational Technology for helping to make this report possible. The authors would also like to thank

Alex Janus of the U.S. Census Bureau, Nolan Bowie of the John F. Kennedy School of Government at 

Harvard University, and Valena Plisko, Marilyn Seastrom, Jerry West, Bill Hussar, Edith McArthur, and 

Lee Hoffman of the U.S. Department of Education’s National Center for Education Statistics, for their 

detailed reviews and thoughtful comments. The authors would also like to thank staff from the Education 

Statistics Services Institute (ESSI), including Sandy Eyster, who were instrumental in assuring the 

technical quality of the report. 

 

iii
Highlights 

This report uses data from the September Computer and Internet Use supplement to the 

2001 Current Population Survey to examine the use of computers and the Internet by American 

children and adolescents between the ages of 5 and 17.1

 The report examines the overall rate of 

use, the ways in which children and teens use the technologies, where the use occurs (home, 

school, and other locations), and the relationships of these aspects of computer and Internet use 

to demographic and socioeconomic characteristics such as children’s age and race/ethnicity and 

their parents’ education and family income. All statistical comparisons in this report were tested 

for significance at the 95 percent confidence level (p<.05), and all reported differences are 

statistically significant, unless otherwise noted. 

Key findings are as follows: 

• Most children and adolescents use these technologies (table 1). About 90 percent 

of children and adolescents ages 5–17 (47 million persons) use computers, and about 

59 percent (31 million persons) use the Internet. 

• Use begins at an early age (figure 1). About three-quarters of 5-year-olds use 

computers, and over 90 percent of teens (ages 13–17) do so. About 25 percent of 5-

year-olds use the Internet, and this number rises to over 50 percent by age 9 and to at 

least 75 percent by ages 15–17. 

• There is a “digital divide” (table 1). Computer and Internet use are divided along 

demographic and socioeconomic lines. Use of both technologies is higher among 

Whites than among Blacks and Hispanics and higher among Asians and American 

Indians than among Hispanics.2

 Five- through 17-year-olds living with more highly 

educated parents are more likely to use these technologies than those living with less 

 

1

 Current Population Survey interviews were conducted in about 56,000 households in September 2001 and

collected information regarding 28,002 5- to 17-year-olds, including those enrolled in school and those not enrolled

in school. One respondent per household was interviewed and that respondent provided information about the 

household and about individual household members, including information about computer and Internet use. 

Because a household’s respondent may not have full information regarding computer and Internet use by other 

members of the household, this method is a potential source of error in the data. 

2

 “White,” “Black,” “Asian,” and “American Indian” refer to White non-Hispanic; Black non-Hispanic; Asian or 

Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic, respectively, and will be used

throughout this report for ease of presentation. Hispanics may be of any race. 

 

iv
well educated parents, and those living in households with higher family incomes are 

more likely to use computers and the Internet than those living in lower income

households. 

• Disability, urbanicity, and household type are factors in the digital divide. 

Consistent with the findings of previous research (U.S. Department of Commerce 

2002), 5- through 17-year-olds without a disability are more likely to use computers 

and the Internet than their disabled peers, and children and adolescents living outside 

of central cities are more likely to use computers than those living in central cities. 

When not controlling for other factors, children and adolescents from two-parent 

households are more likely to use the computer and the Internet than those from

single-parent households,3

 and children and adolescents living outside of central cities 

are more likely to use the Internet than those living in central cities. However, when 

controlling for other factors such as family income and parent education, the 

association of household type and of Internet use outside of central cities was not 

statistically significant (table 2). 

• There are no differences between the sexes in overall computer or Internet use 

rates. In contrast to the 1990s, when boys were more likely to use computers and the 

Internet than girls were, overall computer and Internet use rates for boys and girls are 

now about the same. 

• More children and adolescents use computers at school (81 percent) than at 

home (65 percent) (table 3). The difference in school versus home computer use is 

larger for groups of 5- through 17-year-olds who are generally less likely to use 

computers. Computer use at school exceeds use at home by 30 percentage points or

more for Blacks and for Hispanics. Use at school also exceeds use at home by 30 

percentage points or more for those whose parents did not complete high school, who 

live with a single mother, who live in households where Spanish is the only language 

spoken by household members age 15 or over, or who live in households where the 

 

3

 The categories for family structure include “male-headed single-householder” and “female-headed singlehouseholder.” “Single father” and “single mother” (or “single parent,” when referring to both) are used for ease of

presentation. Some single-householders include nonrelatives or relatives other than the father or mother such as a

grandfather or grandmother. 

 

v
family income is under $20,000. However, home use is slightly more prevalent than 

school use for two groups: (1) children and adolescents whose parents have at least 

some graduate school education, and (2) children and adolescents who live in families 

with incomes of $75,000 or more per year.4

• Use of home computers for playing games and for work on school assignments 

are common activities. A majority (59 percent) of 5- through 17-year-olds use home

computers to play games, and over 40 percent use computers to connect to the 

Internet (46 percent) and to complete school assignments (44 percent) (table 4). 

Middle-school-age and high-school-age youth (ages 11–17) use home computers to 

complete school assignments (57–64 percent), to connect to the Internet (54-63 

percent), and to play games (60-63 percent). 

• Home is the most common location for Internet access, followed by school. 

Although nearly all schools have Internet access, children and adolescents are more 

likely to access the Internet from their homes (table 6). Of those children and 

adolescents who use the Internet, 78 percent access it at home, compared to 68 

percent who access it at school. Many of those who rely more on access at school 

come from lower income families (less than $35,000 per year) or have parents who 

have not earned at least a high school credential.

• Many disadvantaged children and adolescents use the Internet only at school. 

Among the group of children and adolescents who access the Internet at only one 

location, 52 percent of those from families in poverty and 59 percent of those whose 

parents have not earned at least a high school credential do so at school. In 

comparison, 26 percent of those from families not in poverty and 39 percent of those 

with more highly educated parents do so only at school. This illustrates the role of 

schools in bridging the digital divide (table 7). 

• Considering all locations, use of the Internet for work on school assignments, email, and games are common activities. About 72 percent of Internet users ages 5–

17 (or 42 percent of all youth in this age range) use the Internet to complete school 

 

4

 The prevalence of the use of a technology is measured in this report by the percentage of 5–17 year-olds using the 

technology. This report does not examine other aspects of the frequency of use, such as the number of incidents of 

use or the amount of time spent using technologies, because the CPS does not include these data. 

 

vi
assignments, while 65 percent of users (38 percent of all persons 5–17) use the 

Internet for e-mail or instant messaging and 62 percent of users (36 percent of all 

persons 5–17) use it to play games (tables 8 and 9). 

 

vii
Contents 

Acknowledgements............................................................................................................iii

Highlights........................................................................................................................... iv 

List of Tables ..................................................................................................................... ix 

List of Figures..................................................................................................................... x 

Introduction......................................................................................................................... 1 

Current Use and User Characteristics................................................................................. 3 

Home and School Computer Use...................................................................................... 11 

Home Computer Activities............................................................................................... 15 

Internet Access Locations................................................................................................. 22 

Internet Activities.............................................................................................................. 29 

Conclusions....................................................................................................................... 37 

Methodological and Technical Notes ............................................................................... 39 

References......................................................................................................................... 51 

 

viii
List of Tables 

Table 1. Percentage of children and adolescents age 5–17 who use computers and the 

Internet, by child and family/household characteristics: 2001..................................4 

Table 2. Logistic regression analyses of child and family/household characteristics and 

computer and Internet use: 2001....................................................................9 

Table 3. Percentage of children and adolescents age 5–17 using computers at home and at 

school, by child and family/household characteristics: 2001..................................12 

Table 4. Percentage of persons age 5–17 using home computers for specific activities, by 

child and family/household characteristics: 2001...............................................16 

Table 5. Percentage of home computer users age 5–17 who use home computers for 

specific activities, by child and family/household characteristics: 2001.....................19 

Table 6. Percentage of Internet users age 5–17 who use the Internet at specific locations, 

by child and family/household characteristics: 2001...........................................23 

Table 7. Percentage of children and adolescents who use the Internet at only one location, 

by child and family/household characteristics and by location of use: 2001...............26 

Table 8. Percentage of persons age 5–17 using the Internet for specific activities, by 

selected characteristics: 2001......................................................................30 

Table 9. Percentage of Internet users age 5–17 using the Internet for specific activities, by 

selected characteristics: 2001......................................................................33 

Table A1. Percentage of children and adolescents age 5–17 who use computers and the 

Internet, by age: 2001..................................................................................53 

Table A2. Percentage of adults who use computers and the Internet, by selected 

characteristics: 2001.................................................................................54 

Table A3. Characteristics of persons age 5–17: 2001..........................................55 

Table A4. Characteristics of persons age 5–17 using computers at home and at school: 

2001...................................................................................................56 

 

ix
List of Figures 

Figure 1. Percentage of 5–17-year-olds using computers or the Internet, by age: 2001 .... 5 

Figure 2. Percentage of children and adolescents using computers at home and at school, by 

parent educational attainment: 2001 ......................................................................... 13 

Figure 3. Percentage of children and adolescents using computers at home and at school, by 

family income: 2001 ................................................................................................. 14 

Figure 4. Percentage of children and adolescents using computers at home and at school, by 

race/ethnicity: 2001................................................................................................... 14 

Figure 5. Percentage of children and adolescents age 5–17 who use the Internet at only one 

location, by location and poverty status: 2001.......................................................... 28 

 

 

x
Introduction 

Computers and the Internet recently passed a milestone: both are now used by a majority 

of Americans. Two-thirds of Americans used computers in 2001, up from about one-half in 

1997, and 54 percent used the Internet, up from about a third in 1997. Comparable trend data 

have not been published for 5- to 17-year-olds, but among those ages 9 to 17, Internet use has 

increased from about one third in 1997 to about two thirds in 2001 (U.S. Department of 

Commerce 2002). Currently, the use of these technologies is more widespread among children 

and adolescents ages 5 through 17 than among adults: about 90 percent of 5- to 17-year-olds use 

computers and 59 percent use the Internet (table 1). 

This report describes computer and Internet use by children and teens ages 5–17. This 

age range represents the modal ages for students in grades K-12, and has not been the focus of 

previous reports using the 2001 Current Population Survey (CPS) data. The purpose of this 

report is to provide interested researchers, policymakers, and the general public with a detailed 

view of computer and Internet use, examining the rates of use, how these technologies are used, 

where they are used, and the characteristics of users. This information provides a portrait of 

those who are embracing these technologies in large numbers and those who have yet to do so. 

This report is based on data collected in the September Computer and Internet Use 

supplement to the 2001 Current Population Survey. Interviews were conducted in approximately 

56,000 households. One respondent per household was interviewed and that respondent 

provided information both about the household and about individual household members, 

including information pertaining to their computer and Internet use.1

 Respondents provided 

information about the computer and Internet use experiences of 28,002 5- to 17-year-olds. The 

following questions are addressed using these data: 

1. What percentage of children and adolescents use computers and the Internet? 

 

1

 Because a household’s informant may not have full information regarding computer and Internet use by other 

members of the household (especially when that use occurs at school), this method is a potential source of error in

the data. 

 

1
2. Is use by children and adolescents related to age, socioeconomic and demographic 

characteristics such as race/ethnicity, family income, parents’ educational attainment, 

and other factors?

3. How do children and adolescents use home computers and the Internet? 

4. Where do children and adolescents use computers? Where do they use the Internet? 

How many users use the Internet in only one place, and what locations do these users 

favor?

5. Do the ways children and adolescents use computers and the Internet, and where they 

use them, vary by children’s and adolescents’ demographic or socioeconomic 

characteristics? 

All statistical comparisons in this report were tested for significance at the 95 percent 

confidence level (p<.05), and all reported differences are statistically significant, unless 

otherwise noted. 

 

2
Current Use and User Characteristics 

Growth Over Time 

Rates of computer and Internet use by children and adolescents have increased rapidly. 

In 1984, data from the Current Population Survey indicated that 27 percent of students (from prekindergarten through college) used computers at school. By 1989 this number had increased to 

43 percent; by 1997 it was 69 percent. Student use of computers at home has also shown 

increases, rising from 12 percent in 1984 to 19 percent in 1989, 27 percent in 1993, and 45 

percent in 1997 (U.S. Department of Education 1999). Internet use by children and adolescents 

of elementary and high school age has also increased rapidly, growing from about one third of 9- 

through 17-year-olds in 1997 to about two thirds in 2001 (U.S. Department of Commerce 2002). 

Current Use 

Table 1 shows that about 90 percent of children and adolescents age 5 through 17 (47 

million persons) use computers and about 59 percent (31 million persons) use the Internet. 

Figure 1 graphs the relationship between age and the use of these technologies (data shown in 

appendix table A1). About three quarters of children already use computers by the age of five, 

and a majority use the Internet by the age of nine. Among high-school-age youth (ages 15–17), 

more than 90 percent use computers and at least three quarters use the Internet. 

 

3
 

4

Characteristics Percent s.e. Percent s.e.

Total (persons age 5–17) 53,013 89.5 0.30 58.5 0.49

Child characteristics

Age

5–7 11,990 80.5 0.83 31.4 0.97

8–10 12,455 90.5 0.60 53.5 1.02

11–14 16,493 92.6 0.47 68.3 0.83

15–17 12,075 93.4 0.52 77.1 0.87

Sex

Female 25,835 90.0 0.43 58.6 0.70

Male 27,178 89.1 0.43 58.3 0.68

Race/ethnicity1

White 33,433 93.4 0.31 66.7 0.59

Black 8,275 85.0 1.07 45.3 1.50

Hispanic 8,400 78.7 1.59 37.2 1.87

Asian 2,268 89.7 1.46 64.6 2.29

American Indian 637 89.8 2.74 53.5 4.51

Disability status

Disabled 626 80.0 3.65 48.9 4.56

Not disabled 45,416 89.8 0.32 59.4 0.53

Family & household characteristics

Parent educational attainment

Less than high school credential 5,450 75.6 1.33 31.6 1.44

High school credential 13,611 87.2 0.65 50.2 0.98

Some college 15,665 92.0 0.49 63.2 0.88

Bachelor's degree 6,712 94.2 0.65 69.3 1.29

Graduate education 9,114 96.4 0.45 74.4 1.04

Family/household type

Two parent household 37,230 91.3 0.33 62.2 0.57

Male householder 2,715 86.9 1.48 54.3 2.18

Female householder 12,440 85.5 0.72 48.8 1.02

Other arrangement 628 75.2 3.94 48.8 4.56

Household language

Spanish-only 2,549 70.4 2.06 28.7 2.05

Not Spanish-only 50,464 90.5 0.30 60.0 0.50

Poverty status

In poverty 9,277 80.5 1.33 36.7 1.61

Not in poverty 36,904 92.6 0.44 65.3 0.80

Family income

Under $20,000 8,344 80.1 1.00 36.5 1.20

$20,000–$34,999 8,852 86.3 0.83 48.8 1.21

$35,000–$49,999 7,438 92.0 0.72 62.8 1.28

$50,000–$74,999 9,530 93.6 0.57 67.1 1.10

$75,000 or more 12,018 96.2 0.40 75.4 0.90

Urbanicity

Metropolitan, city center 12,249 84.6 0.74 49.5 1.03

Metropolitan, not city center 23,566 91.1 0.42 61.9 0.72

Non-metropolitan 9,609 91.4 0.80 59.7 1.40

Table 1. Percentage of children and adolescents age 5–17 who use computers and the Internet, by

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Percent using 

computers

Percent using the 

Internet

 child and family/household characteristics: 2001

NOTE: s.e. is standard error. Detail may not sum to total due to rounding or missing data.

Number of

children 

(in thousands)

1 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, nonHispanic; Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, nonHispanic. 
5

Figure 1. Percentage of 5–17 year-olds using computers or the Internet, by age: 2001

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

“Digital Divide”

Although the adoption of these technologies has been rapid, it has occurred at disparate 

rates in different parts of American society. How computers and the Internet are used, and 

whether they are used at all, often vary by socioeconomic status (assessed in this report with 

measures of parent educational attainment, poverty status and/or family income) and other 

characteristics such as race/ethnicity, household composition, and urbanicity, such that the 

inequality of use has been termed a “digital divide” (U.S. Department of Commerce 1998; Norris 

2001). This is particularly true of adults. While 82 percent of adults with an annual family 

income over $75,000 used the Internet in 2001, only 24 percent of adults with an annual family 

income below $20,000 did so (table A2). Large racial/ethnic and educational differences exist as 

well. Sixty percent of White and Asian adults used the Internet, compared to 47 percent of 

American Indians, 39 percent of Blacks, and 31 percent of Hispanics. 2 About 80 percent of 

adult college graduates used the Internet, but 42 percent with only a high school education were 

Internet users, and the rate of Internet use was only 17 percent among adults who had not 

 

2

“White,” “Black,” “Asian,” and “American Indian” refer to White non-Hispanic; Black non-Hispanic; Asian or 

Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic, respectively, and will be used 

throughout this report for ease of presentation. Hispanics may be of any race.

0

25

50

75

100

5 6 7 8 9 10 11 12 13 14 15 16 17

Percent

Age

Computer

use

Internet

use
graduated from high school. This digital divide exists for children and adolescents as well

though many differences are smaller than those found between various groups of adults. 

,

able 1 shows computer and Internet use rates by individual, family, and household 

charact re

lds

he family and household settings children and adolescents experience are also related to 

compu

g

e

ore 

closer look at these differences provides a better picture of the magnitude of the 

differen ance,

 

T

eristics for 5–17-year-olds.

3

 Looking at individual characteristics, older adolescents a

as much as 20 percentage points more likely to use computers than younger children and as 

much as 50 percentage points more likely to use the Internet (table A1). White 5–17-year-o

are more likely to use these technologies than their Black or Hispanic counterparts. In addition, 

those who are not disabled are more likely to use computers and the Internet than those with 

disabilities. 

T

ter and Internet use. Five- through seventeen-year-olds from two-parent households are 

more likely to use these technologies than those from single-parent households,4

and those livin

with more highly educated parents are more likely to use these technologies than those living 

with less well educated parents. In addition, those living in households where Spanish is not th

only language spoken are more likely to use computers and the Internet than those living in 

Spanish monolingual homes. Children and adolescents in families with higher incomes are m

likely to use computers and the Internet than those in families with lower incomes. Children and 

adolescents who live outside of central cities are more likely to use computers and the Internet 

than those living in central cities. 

A

ces in technology use between certain groups of children and adolescents. For inst

the rate of computer use for Black 5–17-year-olds is 8 percentage points lower than that of their 

White counterparts, and the difference in Internet use is even more pronounced at 21 percentage 

points. Differences between Whites and Hispanics are even larger (15 percentage points and 30 

3

 Appendix table A3 shows the characteristics of users and non-users, indicating the number and percentage of all

users and non-users who belong to selected groups. 

4

 The categories for family structure in the CPS data are “two parent, male-headed single-householder, femaleheaded single-householder, and other arrangement.” When referring to the single householder categories, we use 

“single parent” or “single father” and “single mother” for ease of presentation. Some single-householders include 

non-relatives or relatives other than the father or mother such as a grandfather or grandmother. 

 

6
percentage points, respectively). Among all racial/ethnic groups, Hispanics have the lowest rates

of computer and Internet use, while Whites and Asians have the highest rates. Approximately 76 

percent of children and adolescents from households where no parent has graduated from high 

school use computers and 32 percent of them use the Internet. Approximately 96 percent of 

children and adolescents from households where at least one parent attended graduate school

computers and 74 percent of them use the Internet. Eighty percent of poor 5- through 17-yearolds use computers compared to 93 percent of non-poor children, and the difference in Internet

use is even larger. 

use

here is also a clear difference in children’s and adolescents’ use in households where 

Spanis

e is 20

lf

isabilities are another source of differences. Adults with a disability are roughly half as 

likely t

r

One important difference in use has all but disappeared, however. In the past, males have 

used co

es has 

er

T

h is the only language spoken compared to other households. For children and 

adolescents living in households that are Spanish-monolingual, the rate of computer us

percentage points lower than those in households where other languages (usually English) are 

spoken. Internet use by 5-through 17-year olds in Spanish-monolingual households is about ha

that of 5-through 17-year olds in households where Spanish is not the only language spoken. 

D

o use the Internet as non-disabled adults and even less likely to have ever used a computer 

(U.S. Department of Commerce 2000). Adults with visual impairments use computers and the 

Internet at significantly lower rates than the rest of the adult population (Gerber and Kirchner 

2001). The differences between disabled and non-disabled 5- through 17-year-olds are smalle

than those found for adults, but they still exist. Comparing 5- through 17-year-olds with and 

without disabilities, the rates of computer and Internet use are both about 10 percentage points

lower for those with disabilities. 

mputers and the Internet at significantly higher rates than females (Clemente 1998; 

Riccobono 1986) and have reported more experience and skill with these technologies 

(Schumacher and Morahan-Martin 2001). More recently, as the use of these technologi

become more widespread, this gender gap has closed for both adults and children, and among 

both adults and youths today there are now no differences between the sexes in overall comput

 

7
or Internet use rates (U.S. Department of Commerce 2002; Miller, Schweingruber, and 

Brandenburg 2001, reporting on computers only). Figures in table 1 and appendix table

consistent with this pattern. 

 

A2 are

to study how various factors related to computer and Internet use behave when 

they ar

mily 

able 2 shows the results of regression analyses of the characteristics associated with

compu

he

he 

 

In order

e looked at simultaneously, multiple logistic regression analyses were performed. 

Regressions can help answer questions such as, “If one controls for parent education, is fa

income still positively related to Internet use?” 

T

ter and Internet use discussed to this point.

5 Table 2 verifies several of the key findings

about the digital divide that were shown in table 1. Increases in age,6

 parental education, and 

family income are all associated with an increase in a child’s odds of using computers and the

Internet. Black and Hispanic children are less likely to use computers and the Internet than 

White children, and Asian children are less likely to use computers than White children. 

Children living in central cities are less likely to use computers (but not less likely to use t

Internet) than those living outside central cities. Those with disabilities are less likely to use t

technologies than their non-disabled peers, and those from Spanish monolingual households are 

less likely to use the technologies than those from households where other languages are spoken.

Also, no differences between boys and girls are observed. In these respects, the overall picture 

of technology use that is revealed by the regression analysis is essentially the same as the picture

suggested by the bivariate analyses in table 1. 

5

 Multiple regression is a statistical procedure that identifies the association between each independent variable and 

the dependent variable while the other independent variables are held constant, or statistically controlled. This

statistical control reveals each independent variable’s association with the variable being predicted. For details, see 

the Methodological and Technical Notes section. 

6

 Note that in the regression analyses, age is measured as a continuous variable. Age groupings were used in the 

bivariate tables. 

 

8
 

9

Independent variables

Parameter 

estimate

Standard 

error

Odds

ratio

Parameter 

estimate

Standard

error

Odds

ratio

Child characteristics

Age 0.14 * 0.01 1.16 0.24 * 0.01 1.27

Sex

Female

Male -0.13 0.15 0.89 -0.03 0.05 0.98

Race/ethnicity

1

White

Black -0.45 * 0.10 0.64 -0.60 * 0.07 0.55

Hispanic -0.59 * 0.12 0.55 -0.69 * 0.09 0.50

Asian -0.35 * 0.16 0.71 0.00 0.11 1.00

American Indian -0.01 0.31 0.99 -0.12 0.20 0.89

Disability status

Not disabled

Disabled -0.74 * 0.26 0.48 -0.49 * 0.21 0.62

Missing disability status -0.17 0.10 0.84 -0.39 * 0.07 0.68

Family & household characteristics

Parent educational attainment

Less than high school credential

High school credential 0.43 * 0.12 1.54 0.46 * 0.10 1.58

Some college 0.79 * 0.12 2.20 0.89 * 0.10 2.42

Bachelor's degree 0.99 * 0.16 2.70 1.02 * 0.11 2.77

Graduate education 1.33 * 0.17 3.77 1.17 * 0.11 3.22

Missing parent education 0.06 0.16 1.06 0.27 0.14 1.31

Family/household type

Two parent household

Male householder -0.13 0.15 0.88 -0.11 0.11 0.89

Female householder 0.00 0.09 1.00 0.00 0.06 1.00

Other arrangement -0.84 * 0.24 0.43 -0.24 0.21 0.79

Household language

Not Spanish-only

Spanish-only -0.21 * 0.08 0.81 -0.16 * 0.08 0.85

Poverty status

Not in poverty

In poverty 0.02 0.16 1.02 -0.10 0.12 0.90

Family income

Under $20,000

$20,000–$34,999 0.29 0.16 1.34 0.27 * 0.12 1.31

$35,000–$49,999 0.61 * 0.19 1.85 0.68 * 0.14 1.97

$50,000–$74,999 0.64 * 0.19 1.90 0.65 * 0.14 1.92

$75,000 or more 0.90 * 0.20 2.45 0.90 * 0.14 2.47

Missing family income -0.04 0.18 0.96 0.18 0.14 1.20

Urbanicity

Metropolitan, city center

Metropolitan, not city center 0.21 * 0.09 1.23 0.09 0.06 1.10

Non-metropolitan 0.32 * 0.12 1.38 0.10 0.08 1.11

Missing urbanicity 0.21 0.12 1.23 0.16 * 0.08 1.17

Constant -0.29 0.24 0.75 -3.30 * 0.19 0.04

NOTE: The number of cases analyzed is 28,002. Missing data are modeled to retain 10,370 cases for which data are missing

for one or more independent variables.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

reference category reference category

reference category reference category

* p < .05 1

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or

Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic. 

Table 2. Logistic regression analyses of child and family/household characteristics and computer and Internet use: 2001

reference category reference category

reference category reference category

reference category reference category

reference category reference category

reference category

reference category

Internet Use

reference category

Computer Use

reference category

reference category

reference category
 Other findings from table 1 do not appear significant in the regression analysis. Although 

table 1 shows differences between children in single-parent households and children in other 

family situations and between those living in poverty and those not in poverty, these results are 

not observed in the regression analysis. When studied in isolation in table 1, these factors are 

related to computer and Internet use, but when other factors are considered these relationships 

are no longer significant. This suggests that other characteristics that were controlled for in the 

regression model, such as income and parent education level, may account for the differences in 

children’s odds of using computers and the Internet. Notwithstanding the non-significance of 

certain variables in the regression analysis, it is still important to examine the bivariate statistics 

for these variables because the bivariate statistics accurately describe the population.7

Having looked at the overall rate of computer use among 5–17 year olds and the 

characteristics of users, the next few sections describe where and how the children and 

adolescents use computers and the Internet.8

 

 

7

 For example, after controlling for other factors such as household income, family structure is not significantly 

related to computer and Internet use. However, it is the case that fewer children from single-parent families use 

computers and the Internet. 

8

 This report does not examine the frequency of use or the amount of time spent using computers or the Internet

because the CPS does not collect such data. 

 

10
Home and School Computer Use 

 

Home and school are the primary locations where children and adolescents use 

computers. Table 3 compares the rates of computer use at these two locations.9

 Eighty-one 

percent of 5–17 year-olds use computers at school and 65 percent use computers at home.

10 In 

general, more use computers at school than at home, but among those from households where the 

highest parental education was a graduate education, and those from families with incomes 

above $75,000, the rate of use at home (90 and 89 percent, respectively) was slightly higher than 

the rate of use at school (85 percent).11

Table 3 reveals demographic and socioeconomic differences in the use of home

computers that parallel those found in the overall use of computers. There are racial/ethnic gaps 

in home use: 41 percent of Blacks and Hispanics use computers at home and 54 percent of 

American Indians do so, compared to 76–77 percent of Whites and Asians. There is also a 

difference in home use between children and adolescents from the lowest and highest family 

incomes. Only 31 percent of those from families with incomes less than $20,000 use computers 

at home, compared to 89 percent of those living in families with annual incomes over $75,000. 

Larger still is the gap between children and adolescents whose parents have the least and the 

most education: while 26 percent of those whose parents did not complete high school use 

computers at home, 90 percent of those living with at least one parent who has attended graduate 

school use a computer at home. 

Table 3 also shows that differences between groups in home computer use are generally 

not as pronounced when focusing on school computer use. While the gap in home computer use 

by parental education level noted above is 64 percentage points, at school it is 14 percentage 

points. While the differences in home computer use between 5–17-year-olds living in two-parent 

households compared to those living in single father or single mother households was 20 and 29 

 

9

 For estimates of characteristics of persons using computers at home and at school, see appendix table A3. 

10 Analyses in this report include children and adolescents who are enrolled in school and those who are not. About

93 percent of individuals age 5–17 in the 2001 September CPS are enrolled in school. Among those enrolled, 87

percent use computers at school and 67 percent use computers at home. 

11 There is substantial overlap in these two populations; 63 percent of 5–17 year-olds who have a parent with a 

graduate education also have a family income over $75,000 per year. 

 

11
 

12

Characteristics Percent s.e. Percent s.e.

All persons age 5–17 53,013 65.2 0.47 80.7 0.39

Child Characteristics

Age

5–7 11,990 56.4 1.03 68.2 0.97

8–10 12,455 62.7 0.99 83.1 0.77

11–14 16,493 68.6 0.82 85.2 0.63

15–17 12,075 72.0 0.93 84.5 0.75

Sex

Female 25,835 65.7 0.67 81.6 0.55

Male 27,178 64.8 0.66 79.9 0.55

Race/ethnicity

1

White 33,433 76.9 0.53 83.5 0.46

Black 8,275 41.0 1.48 79.8 1.21

Hispanic 8,400 40.6 1.90 71.8 1.74

Asian 2,268 75.7 2.06 76.1 2.04

American Indian 637 54.1 4.51 83.0 3.40

Disability status

Disabled 626 58.4 4.50 71.5 4.12

Not disabled 45,416 65.7 0.51 81.4 0.42

Family & household characteristics

Parent educational attainment

Less than high school credential 5,450 26.2 1.36 70.6 1.41

High school credential 13,611 53.7 0.98 80.2 0.78

Some college 15,665 70.7 0.83 82.0 0.70

Bachelor's degree 6,712 80.8 1.10 84.8 1.00

Graduate education 9,114 90.2 0.71 85.0 0.85

Family/household type

Two parent household 37,230 73.3 0.52 81.5 0.46

Male householder 2,715 53.8 2.18 78.6 1.80

Female householder 12,440 44.1 1.02 79.6 0.82

Other arrangement 628 51.1 4.56 63.6 4.38

Household language

Spanish-only 2,549 29.2 2.06 64.2 2.17

Not Spanish-only 50,464 67.0 0.48 81.6 0.39

Poverty status

In poverty 9,277 31.9 1.56 75.2 1.44

Not in poverty 36,904 75.2 0.72 83.1 0.63

Family income

Under $20,000 8,344 31.2 1.16 75.3 1.08

$20,000–$34,999 8,852 50.9 1.21 78.3 1.00

$35,000–$49,999 7,438 70.7 1.20 83.1 0.99

$50,000–$74,999 9,530 80.1 0.93 83.9 0.86

$75,000 or more 12,018 89.3 0.64 85.4 0.74

Urbanicity

Metropolitan, city center 12,249 52.7 1.03 76.0 0.88

Metropolitan, not city center 23,566 71.9 0.67 81.4 0.58

Non-metropolitan 9,609 63.1 1.38 84.3 1.04

Table 3. Percentage of children and adolescents age 5–17 using computers at home and at

Number of

children 

(in thousands)

Percent using 

computers at

home

Percent using 

computers at 

school

 school, by child and family/household characteristics: 2001

1 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, nonHispanic; Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, nonHispanic.

NOTE: s.e. is standard error. Detail may not sum to total due to rounding or missing data. 

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.
13

percentage points, respectively, no differences are detectable between these groups in terms of 

computer use at school. Although there are gaps in school computer use by race/ethnicity, home 

language, and socioeconomic status (parental education, family income, and poverty), most of 

these gaps are narrower than they are for home computer use.

The narrowing of differences in use rates at school compared to home use is illustrated in 

figures 2, 3, and 4. Figure 2 shows that the percentage of children and adolescents using 

computers at home increases as their parents’ educational attainment increases, but that the 

percentage using computers at school is more nearly equal across the levels of parental 

education. Figure 3 shows the same pattern for family income: home computer use rates 

increase as family income increases, but use of computers at school remains relatively high 

across all levels of income. Similarly, figure 4 shows that differences in computer use between 

some racial/ethnic groups are smaller at school than at home. 

Figure 2. Percentage of children and adolescents using computers at home and at school, by 

Figure 2. parent educational attainment: 2001

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

23

51

69

80

89

69

79 82 84 84

0

25

50

75

100

Less than

high school

credential

High school

credential

Some college Bachelor's

degree

Graduate

education

Percent

Parent educational attainment

Home

use

School

use
14

Figure 3. Percentage of children and adolescents using computers at home and at school, by 

Figure 3. family income: 2001

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Figure 4. Percentage of children and adolescents using computers at home and at school, by 

Figure 4. race/ethnicity: 2001

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

31

51

71

80

89

75 78 83 84 85

0

25

50

75

100

under

$20,000

$20,000-

$34,999

$35,000-

$49,999

$50,000-

$74,999

$75,000 or

more

Percent

Family income

Home

use

School

use

77

41 41

71

84 80

72

78

0

25

50

75

100

White Black Hispanic Other

Percent

Race/ethnicity

Home

use

School

use
Home Computer Activities 

It is useful to examine computer use in two ways.12 First, this section estimates the 

percentage of children and adolescents ages 5–17 who use computers in various ways. Second, 

it controls for computer use by looking at just those children and adolescents who use computers 

at home. When home computer use is controlled, some apparent group differences in the ways 

5- through 17-year-olds use computers appear to be a function of home use. 

Table 4 shows how 5- through 17-year-olds use home computers. Children use 

computers for a wide variety of activities encompassing work, education, and play, making 

computers a significant part of young people’s everyday lives. Most play computer games, and a 

majority of middle-school-age and high-school-age youth (ages 11–17) use home computers to 

complete school assignments and connect to the Internet. A majority of teens ages 15–17 also 

use home computers for e-mail, and about half use them for word processing.13 

The percentage of children and adolescents who use computers in various ways varies by 

individual, family, and household characteristics. As shown in table 4, most of the characteristics 

that are associated with the digital divide (e.g., race/ethnicity, family income, and parent 

educational attainment) are also associated with differences in the ways children and adolescents 

use computers at home. In many cases, differences in how computers are used are even more 

pronounced than the differences in the rates of use. For example, there is a 21 percentage point 

gap in computer use between children and adolescents from households where no parent has 

received a high school credential and those from households where at least one parent has some

graduate school education (table 1). The difference between these two groups’ use of computers 

for word processing is about 41 percentage points, and is about 44 percentage points for using 

computers to complete school assignments. The disparity is even larger for the use of home

computers to connect to the Internet. Approximately 15 percent of those ages 5–17 with the 

 

12 The data do not support analysis of the quality of software or hardware available or the convenience of access. 

13 CPS data concerning computer activities were only collected for activities with home computers, not computers at 

school or any other location. Questions concerning some computer applications were only asked for users age 15

and older. These applications were spreadsheets or databases, graphics and design, and managing household records 

or finances. Activities analyzed here are based on the wording of survey questions; further details on activities are 

not available. 

 

15
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

All persons age 5–17 53,013 32.4 0.5 45.6 0.5 34.4 0.5 — † — † 44.2 0.5 — † 59.2 0.5 2.8 0.2

Child characteristics

Age

5–7 11,990 9.4 0.6 22.6 0.9 9.5 0.6 — † — † 13.8 0.7 — † 54.0 1.0 1.2 0.2

8–10 12,455 23.8 0.9 39.5 1.0 23.9 0.9 — † — † 37.7 1.0 — † 58.8 1.0 1.5 0.2

11–14 16,493 42.1 0.9 54.1 0.9 43.3 0.9 — † — † 56.6 0.9 — † 62.9 0.9 2.6 0.3

15–17 12,075 50.9 1.0 62.9 1.0 57.7 1.0 17.1 0.8 23.6 0.9 64.2 1.0 2.9 0.3 59.6 1.0 5.7 0.5

Sex

Female 25,835 34.7 0.7 45.7 0.7 36.1 0.7 3.9 0.3 5.6 0.3 45.4 0.7 0.7 0.1 58.3 0.7 2.7 0.2

Male 27,178 30.3 0.6 45.5 0.7 32.7 0.6 3.9 0.3 5.2 0.3 43.1 0.7 0.6 0.1 60.0 0.7 2.8 0.2

Race/ethnicity2

White 33,433 39.3 0.6 55.2 0.6 42.7 0.6 4.7 0.3 6.4 0.3 52.1 0.6 0.8 0.1 70.2 0.6 3.3 0.2

Black 8,275 18.9 1.2 27.3 1.3 18.8 1.2 2.0 0.4 3.0 0.5 28.3 1.4 0.5 0.2 37.7 1.5 1.9 0.4

Hispanic 8,400 17.0 1.5 23.1 1.6 15.1 1.4 2.3 0.6 3.1 0.7 26.7 1.7 # † 35.6 1.9 1.3 0.4

Asian 2,268 40.4 2.3 57.3 2.4 43.7 2.4 5.0 1.0 7.1 1.2 54.3 2.4 0.6 0.4 64.3 2.3 2.8 0.8

American Indian 637 20.7 3.7 31.7 4.2 20.8 3.7 2.1 1.3 2.3 1.4 32.0 4.2 0.5 0.6 51.7 4.5 1.9 1.2

Disability status

Disabled 626 23.5 3.9 29.8 4.2 21.1 3.7 3.0 1.6 5.1 2.0 34.4 4.3 # † 54.4 4.5 2.1 1.3

Not disabled 45,416 33.0 0.5 45.9 0.5 35.0 0.5 3.8 0.2 5.5 0.2 45.0 0.5 0.5 0.1 59.8 0.5 2.8 0.2

See footnotes at end of table.

Graphics and 

design1

Manage 

household 

records or 

finances1

Play games Other

Complete 

school 

assignments

Table 4. Percentage of persons age 5–17 using home computers for specific activities, by child and family/household characteristics: 2001

User Characteristics

Total number 

of children 

(in thousands)

Home computer activity

Word 

processing

Connect to the 

Internet E-mail

Spreadsheets 

or databases1

16
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Family & household characteristics

Parent educational attainment

Less than high sch. credential 5,450 11.1 1.0 14.5 1.1 10.4 0.9 1.5 0.4 1.9 0.4 18.3 1.2 # † 22.8 1.3 1.0 0.3

High school credential 13,611 22.8 0.8 35.1 0.9 27.3 0.9 2.8 0.3 3.8 0.4 35.5 0.9 # † 49.3 1.0 2.0 0.3

Some college 15,665 34.3 0.9 48.7 0.9 36.0 0.9 4.0 0.4 5.8 0.4 47.5 0.9 0.7 0.2 64.6 0.9 2.9 0.3

Bachelor's degree 6,712 42.8 1.4 60.8 1.4 45.2 1.4 5.3 0.6 7.2 0.7 55.5 1.4 0.9 0.3 72.9 1.2 3.1 0.5

Graduate education 9,114 52.2 1.2 67.6 1.1 52.1 1.2 6.2 0.6 8.3 0.7 62.5 1.2 0.9 0.2 81.7 0.9 4.7 0.5

Family/household type

Two parent household 37,230 36.6 0.6 51.6 0.6 38.8 0.6 4.4 0.2 5.8 0.3 49.6 0.6 0.7 0.1 66.6 0.6 2.9 0.2

Male householder 2,715 26.7 1.9 37.8 2.1 29.8 2.0 4.0 0.9 6.7 1.1 37.9 2.1 1.0 0.4 48.5 2.2 3.5 0.8

Female householder 12,440 21.9 0.8 29.7 0.9 22.4 0.9 2.6 0.3 3.7 0.4 30.3 0.9 # † 40.1 1.0 2.1 0.3

Other arrangement 628 19.1 3.6 36.3 4.4 26.9 4.0 1.8 1.2 4.5 1.9 30.4 4.2 0.7 0.8 43.8 4.5 3.2 1.6

Household language

Spanish-only 2,549 12.0 1.5 14.5 1.6 10.7 1.4 1.3 0.5 2.2 0.7 19.1 1.8 # † 23.5 1.9 1.0 0.4

Not Spanish-only 50,464 33.5 0.5 47.1 0.5 35.6 0.5 4.0 0.2 5.5 0.2 45.5 0.5 0.7 0.1 61.0 0.5 2.8 0.2

Poverty status

In poverty 9,277 12.5 1.1 17.2 1.3 12.1 1.1 1.6 0.4 1.9 0.5 20.1 1.3 # † 28.7 1.5 1.5 0.4

Not in poverty 36,904 38.7 0.8 53.7 0.8 40.7 0.8 4.5 0.3 6.4 0.4 51.4 0.8 0.7 0.1 68.5 0.8 3.1 0.3

Family income

Under $20,000 8,344 13.1 0.8 16.8 0.9 11.8 0.8 1.7 0.3 2.1 0.4 20.0 1.0 # † 28.3 1.1 1.7 0.3

$20,000–$34,999 8,852 21.0 1.0 30.8 1.1 22.7 1.0 2.1 0.3 3.2 0.4 31.4 1.1 # † 46.3 1.2 1.9 0.3

$35,000–$49,999 7,438 32.1 1.2 47.7 1.3 34.9 1.3 3.6 0.5 5.0 0.6 46.7 1.3 0.6 0.2 65.6 1.3 2.2 0.4

$50,000–$74,999 9,530 40.0 1.1 56.9 1.2 42.6 1.2 4.6 0.5 6.8 0.6 55.2 1.2 0.7 0.2 73.8 1.0 3.2 0.4

$75,000 or more 12,018 52.2 1.0 69.3 1.0 54.0 1.0 6.5 0.5 8.8 0.6 63.7 1.0 1.1 0.2 79.8 0.8 4.3 0.4

Urbanicity

Metropolitan, city center 12,249 25.0 0.9 36.1 1.0 26.0 0.9 3.0 0.4 4.2 0.4 35.1 1.0 0.6 0.2 48.3 1.0 2.3 0.3

Metropolitan, outlying areas 23,566 36.5 0.7 50.8 0.7 38.5 0.7 4.4 0.3 5.7 0.3 49.2 0.7 0.7 0.1 64.4 0.7 2.9 0.2

Non-metropolitan 9,609 30.8 1.3 42.6 1.4 33.3 1.3 3.6 0.5 5.4 0.6 42.3 1.4 0.7 0.2 58.5 1.4 2.5 0.4

— Not available. Data were not collected.

2

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic.

E-mail Total number 

of children 

(in thousands)

# Percentage less than 0.5.

1

 Questions about some computer activities were asked only about persons age 15 and older.

Word 

processing

Connect to the 

Internet Other

Graphics and 

design1

Complete 

school 

assignments

Manage 

household 

records or 

finances1

Play games

Spreadsheets 

or databases1

NOTE: s.e. is standard error. Detail may not sum to total due to rounding, missing data, and multiple response.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

† Not applicable.

Table 4. Percentage of persons age 5–17 using home computers for specific activities, by child and family/household characteristics: 2001—Continued

User Characteristics

Home computer activity

17
least educated parents use computers for this purpose compared to 68 percent of those living 

with the most educated parents (a 53 percentage point difference). 

There are other differences in home computer use activities by race/ethnicity and family 

income. Whites and Asians are more likely than Blacks, Hispanics, and American Indians to use 

computers for word processing (39 percent and 40 percent versus 19 percent, 17 percent, and 21 

percent, respectively), connecting to the Internet (55 percent and 57 percent versus 27 percent, 

23 percent, and 32 percent, respectively), e-mail (43 percent and 44 percent versus 19 percent, 15 

percent, and 21 percent, respectively), and completing school assignments (52 percent and 54 

percent versus 28 percent, 27 percent, and 32 percent, respectively). Children and adolescents 

living in families with incomes of $75,000 or more per year are more than four times as likely to 

use e-mail at home than children and adolescents from families with incomes under $20,000 

annually. They are also about four times as likely to do word processing, and about three times 

as likely to use home computers to complete school assignments. 

Although there is no difference between boys and girls in overall use of computers, boys 

and girls differ in some of the ways they use computers. When looking at 5- through 17-yearolds, girls are slightly more likely than boys to use home computers for e-mail, word processing, 

and completing school assignments. 

Table 4 presents data on what child and adolescent characteristics are associated with

particular kinds of home computer activities for the entire 5–17 -year-old population. Table 5 

controls for home computer use by looking at just those children and adolescents who use 

computers at home. Many general patterns found in the broader 5- through 17-year-old age 

group hold when focusing just on those who use computers at home. For instance, the most 

popular home computer activity among children ages 5-7, 8- 10, and 11-14 is playing games. 

Indeed, nearly all young children who use computers at home use them to play games. For older 

teens (ages 15–17) who use computers at home, activities such as word processing, connecting to 

the Internet, e-mailing, completing school assignments, and playing games are all common; 71 to 

89 percent of home users ages 15–17 use the home computer for these activities. 

 

18
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

All persons age 5–17 34,573 49.7 0.6 69.9 0.6 52.7 0.6 — † — † 67.8 0.6 — † 90.8 0.4 4.2 0.2

Child Characteristics

Age

5–7 6,760 16.7 1.0 40.1 1.4 16.9 1.0 — † — † 24.4 1.2 — † 95.8 0.6 2.2 0.4

8–10 7,810 38.0 1.3 63.0 1.2 38.1 1.3 — † — † 60.1 1.3 — † 93.8 0.6 2.4 0.4

11–14 11,312 61.4 1.0 78.9 0.9 63.1 1.0 — † — † 82.6 0.8 — † 91.8 0.6 3.8 0.4

15–17 8,691 70.7 1.1 87.4 0.8 80.2 1.0 23.8 1.0 32.8 1.1 89.2 0.8 4.0 0.5 82.8 0.9 8.0 0.7

Sex

Female 16,963 52.8 0.9 69.6 0.8 55.0 0.9 5.9 0.4 8.5 0.5 69.2 0.8 1.1 0.2 88.8 0.6 4.1 0.3

Male 17,609 46.8 0.9 70.2 0.8 50.5 0.9 6.0 0.4 8.0 0.5 66.5 0.8 0.9 0.2 92.7 0.4 4.4 0.4

Race/ethnicity2

White 25,715 51.1 0.7 71.8 0.6 55.5 0.7 6.2 0.3 8.4 0.4 67.7 0.7 1.0 0.1 91.3 0.4 4.3 0.3

Black 3,389 46.2 2.3 66.5 2.2 46.0 2.3 4.9 1.0 7.4 1.2 69.2 2.2 1.3 0.5 92.2 1.3 4.7 1.0

Hispanic 3,408 41.9 3.0 56.9 3.0 37.3 2.9 5.6 1.4 7.7 1.6 65.8 2.9 0.9 0.6 87.6 2.0 3.3 1.1

Asian 1,716 53.4 2.7 75.7 2.4 57.7 2.7 6.6 1.4 9.4 1.6 71.8 2.5 0.8 0.5 85.0 2.0 3.7 1.0

American Indian 345 38.3 6.0 58.6 6.1 38.5 6.0 3.8 2.4 4.2 2.5 59.1 6.0 0.9 1.2 95.6 2.5 3.5 2.3

Disability status

Disabled 365 40.2 5.9 51.1 6.0 36.2 5.7 5.2 2.7 8.7 3.4 59.0 5.9 ‡ † 93.2 3.0 3.6 2.2

Not disabled 29,832 50.2 0.7 69.9 0.6 53.3 0.7 5.9 0.3 8.4 0.4 68.4 0.6 0.8 0.1 91.0 0.4 4.3 0.3

See footnotes at end of table.

Graphics and 

design1

Table 5. Percentage of home computer users age 5–17 who use home computers for specific activities, by child and family/household characteristics: 2001

User Characteristics

Number of 

children using 

computers at 

home 

(in thousands)

Home computer activity

Word 

processing

Connect to the 

Internet E-mail

Spreadsheets or 

databases1

Complete school 

assignments

Manage 

household 

records or 

finances1Play games Other

19
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Family & household characteristics

Parent educational attainment

Less than high sch. credential 1,431 42.5 3.0 55.2 3.0 39.5 3.0 5.7 1.4 7.1 1.6 69.6 2.8 1.5 0.7 86.8 2.0 3.8 1.2

High school credential 7,306 42.5 1.3 65.4 1.3 50.9 1.3 5.3 0.6 7.0 0.7 66.1 1.3 0.7 0.2 91.8 0.7 3.7 0.5

Some college 11,076 48.5 1.1 68.9 1.0 51.0 1.1 5.7 0.5 8.1 0.6 67.2 1.0 1.0 0.2 91.4 0.6 4.0 0.4

Bachelor's degree 5,425 53.0 1.5 75.2 1.3 55.9 1.5 6.6 0.8 8.9 0.9 68.7 1.4 1.1 0.3 90.1 0.9 3.9 0.6

Graduate education 8,216 57.9 1.2 75.0 1.1 57.8 1.2 6.9 0.6 9.2 0.7 69.3 1.2 1.0 0.3 90.6 0.7 5.2 0.6

Family/household type

Two parent household 27,304 49.9 0.7 70.3 0.6 53.0 0.7 5.9 0.3 8.0 0.4 67.6 0.6 1.0 0.1 90.8 0.4 4.0 0.3

Male householder 1,460 49.7 3.0 70.2 2.7 55.5 3.0 7.4 1.6 12.6 2.0 70.5 2.7 1.9 0.8 90.2 1.8 6.4 1.5

Female householder 5,488 49.7 1.5 67.3 1.4 50.7 1.5 5.9 0.7 8.4 0.9 68.8 1.4 1.0 0.3 90.8 0.9 4.9 0.7

Other arrangement 321 37.3 6.2 70.9 5.8 52.5 6.4 3.5 2.3 8.8 3.6 59.5 6.3 ‡ † 85.7 4.5 6.3 3.1

Household language

Spanish-only 744 41.0 4.1 49.6 4.2 36.8 4.0 4.4 1.7 7.5 2.2 65.6 4.0 1.2 0.9 80.4 3.3 3.5 1.5

Not Spanish-only 33,828 49.9 0.6 70.3 0.6 53.1 0.6 6.0 0.3 8.2 0.3 67.8 0.6 1.0 0.1 91.0 0.4 4.2 0.2

Poverty status

In poverty 2,955 39.2 2.9 54.1 3.0 38.1 2.9 5.1 1.3 5.9 1.4 63.2 2.9 1.2 0.6 90.0 1.8 4.6 1.2

Not in poverty 27,763 51.4 1.0 71.4 0.9 54.1 1.0 6.0 0.5 8.5 0.5 68.3 0.9 0.9 0.2 91.1 0.6 4.2 0.4

Family income

Under $20,000 2,600 42.1 2.2 53.9 2.2 37.9 2.2 5.5 1.0 6.6 1.1 64.3 2.1 1.4 0.5 90.8 1.3 5.4 1.0

$20,000–$34,999 4,503 41.3 1.7 60.5 1.7 44.6 1.7 4.2 0.7 6.3 0.8 61.7 1.7 # † 90.9 1.0 3.7 0.6

$35,000–$49,999 5,257 45.3 1.6 67.5 1.5 49.3 1.6 5.0 0.7 7.1 0.8 66.1 1.5 0.9 0.3 92.9 0.8 3.1 0.5

$50,000–$74,999 7,632 50.0 1.3 71.0 1.2 53.2 1.3 5.8 0.6 8.6 0.7 68.9 1.2 0.8 0.2 92.1 0.7 3.9 0.5

$75,000 or more 10,726 58.5 1.1 77.7 0.9 60.5 1.1 7.3 0.6 9.9 0.7 71.4 1.0 1.2 0.2 89.4 0.7 4.8 0.5

Urbanicity

Metropolitan, city center 6,460 47.4 1.4 68.4 1.3 49.2 1.4 5.7 0.7 8.0 0.8 66.6 1.3 1.1 0.3 91.5 0.8 4.4 0.6

Metropolitan, outlying areas 16,937 50.8 0.9 70.7 0.8 53.5 0.9 6.1 0.4 7.9 0.5 68.5 0.8 1.0 0.2 89.6 0.5 4.0 0.3

Non-metropolitan 6,063 48.8 1.8 67.6 1.7 52.8 1.8 5.7 0.8 8.6 1.0 67.0 1.7 1.1 0.4 92.7 0.9 3.9 0.7

† Not applicable. 

# Percentage less than 0.5.

‡ Too few cases to report.

E-mail

2

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic.

— Not available. Data were not collected.

Other

Graphics and 

design1

Complete school 

assignments

Manage 

household 

records or 

finances1Play games

Word 

processing

Connect to the 

Internet

Number of 

children using 

computers at 

home 

(in thousands)

Spreadsheets or 

databases1

Home computer activity

NOTE: s.e. is standard error. Detail may not sum to total due to rounding, missing data, or multiple response.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

1

 Questions about some computer activities were asked only of persons age 15 and older.

Table 5. Percentage of home computer users age 5–17 who use home computers for specific activities, by child and family/household characteristics: 2001—Continued

User Characteristics

20
Controlling for the use of computers at home reduces the magnitude of many group 

differences in computer use and eliminates some of them, but differences remain nonetheless. 

For instance, comparing children and adolescents from households where parents have not 

completed high school to those from households where parents have attended graduate school, 

differences in the use of computers for word processing, connecting to the Internet, and emailing range between 15 and 20 percentage points. The differences are smaller than observed 

in the larger 5–17 population where differences between these two groups for these activities 

ranged between 41 and 53 percentage points. Differences in the use of computers for school 

assignments by parent education essentially disappear once home use of computers is controlled. 

Racial/ethnic differences in the use of computers seem to largely be a function of home

access. Looking just at those children and adolescents with access to computers at home, few of 

the differences between racial/ethnic groups seen in the 5- through 17-year-old population at 

large remain or, if they do, are largely reduced. No differences were detected between 

racial/ethnic groups who had access to computers at home in terms of their use of computers to 

complete school assignments. Some differences between White and Black or Hispanic children 

do persist (e.g. connecting to the Internet, word processing, and e-mailing), but even these 

differences are significantly reduced once home computer access is taken into account. 

Differences between 5- through 17-year-olds living in families with incomes under 

$20,000 per year and those with incomes of $75,000 or more per year persist for certain 

activities: word processing, connecting to the Internet, e-mailing, and completing school 

assignments. However, the magnitude of the differences is significantly reduced when home

computer use is kept constant. 

Controlling for home use does not change the differences in computer use between girls 

and boys for most types of activities. Girls are still slightly more likely than boys to use home 

computers for e-mail, word processing, and school assignments. Boys, on the other hand, are 

still more likely to use home computers to play games than are girls; this finding was not present 

when looking at all boys and girls. 

 

21
Internet Access Locations 

The high rate at which young people use the Internet is partly attributable to the 

availability of this technology in schools, where a major effort to move schools online 

contributed to nearly all public schools (98%) having some level of Internet access by 2000 

(Cattagni and Farris 2001; U.S. Department of Education 2000). Although a comparable 

estimate is not available for private schools, they have made major gains as well (Levin, Hurst, 

and Burns 2000). However, differences among schools persist in student access to computer 

resources, including student/computer and computer/classroom ratios, both of which affect the 

availability and convenience of Internet access at school (Parsad, Skinner, and Farris 2001; 

Rathbun and West, 2003). 

Although nearly all schools have Internet access, the home is more widely used as an 

Internet access location. In the CPS, respondents are asked to identify locations where 

household members use the Internet. Of those children and adolescents who use the Internet, 78 

percent access the Internet from home, compared to 68 percent who access it from school. 

About 15 percent of children and adolescents access the Internet from someone else’s home or 

from a public library. About 1 percent each access the Internet from a community center or 

some other place (table 6). 

Inequalities in computer and Internet use manifest themselves in the locations where 

children and adolescents log in to the Internet. Given the role of computers in accessing the 

Internet, it is not surprising that Internet home-use rates are highest among those groups who are 

most likely to have computers at home. These groups include Asians, Whites, children and 

adolescents living with more highly educated parents, those living with two parents, and those 

from families with higher incomes. 

 Although the largest overall percentage of users logs in from home, several groups of 

users rely more heavily on access through schools or other locations. Children and adolescents 

more likely to connect to the Internet from school than from home are from households where no 

parent has earned a high school diploma or equivalent, households headed by single mothers, 

 

22
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

All persons age 5–17 30,989 77.9 0.54 67.7 0.61 15.4 0.47 1.1 0.14 15.1 0.46 1.2 0.14

Child characteristics

Age

5–7 3,766 72.0 1.67 53.3 1.86 10.1 1.12 0.8 0.33 8.7 1.05 1.7 0.48

8–10 6,658 74.0 1.23 63.4 1.35 12.2 0.92 0.8 0.25 11.4 0.89 0.9 0.26

11–14 11,260 79.2 0.87 70.8 0.98 17.3 0.81 1.3 0.24 16.6 0.80 1.2 0.23

15–17 9,306 81.6 0.92 72.9 1.05 17.6 0.90 1.3 0.27 18.4 0.92 1.1 0.25

Sex

Female 15,149 77.9 0.77 67.8 0.87 16.2 0.68 1.0 0.18 15.8 0.68 1.0 0.18

Male 15,840 78.0 0.75 67.7 0.85 14.7 0.64 1.2 0.20 14.4 0.64 1.3 0.21

Race/ethnicity1

White 22,316 82.7 0.58 68.5 0.71 12.4 0.50 0.8 0.14 16.0 0.56 1.1 0.16

Black 3,747 60.2 2.19 66.5 2.11 29.2 2.03 2.9 0.75 14.5 1.57 1.2 0.49

Hispanic 3,120 62.1 3.08 67.0 2.99 20.0 2.54 1.6 0.80 12.5 2.10 1.2 0.69

Asian 1,465 88.6 1.90 58.7 2.94 16.9 2.23 0.9 0.56 8.8 1.69 1.8 0.79

American Indian 341 59.3 6.07 75.3 5.33 11.2 3.90 # † 10.7 3.82 # †

Disability status

Disabled 306 61.0 6.36 71.7 5.88 28.3 5.88 10.5 4.00 22.3 5.43 10.9 4.07

Not disabled 26,976 77.3 0.58 67.8 0.65 17.2 0.52 1.1 0.14 16.9 0.52 1.1 0.14

See footnotes at end of table.

Table 6. Percentage of Internet users age 5–17 who use the Internet at specific locations, by child and family/household characteristics: 2001

Characteristics of users

Number of 

children 

(in thousands)

Internet use locations

Own Home School Public Library

Community 

Center

Someone Else's 

Home

Some Other 

Place

23
 2001—Continued

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Family & household characteristics

Parent educational attainment

Less than high sch. credential 1,724 45.8 2.74 74.8 2.39 21.8 2.27 1.4 0.65 17.1 2.07 2.5 0.86

High school credential 6,839 69.9 1.27 69.5 1.27 15.5 1.00 1.3 0.31 16.4 1.02 1.3 0.31

Some college 9,898 77.1 0.96 67.2 1.08 15.8 0.84 0.9 0.22 16.0 0.84 1.1 0.24

Bachelor's degree 4,650 87.8 1.10 64.4 1.60 12.9 1.12 0.6 0.26 13.7 1.15 1.1 0.35

Graduate education 6,778 90.9 0.80 66.9 1.30 13.9 0.96 1.5 0.34 13.3 0.94 1.0 0.28

Family/household type

Two parent household 23,140 83.0 0.56 67.0 0.71 13.0 0.50 0.8 0.13 13.1 0.51 1.0 0.15

Male householder 1,475 69.5 2.74 67.2 2.79 18.8 2.32 1.8 0.79 23.1 2.51 1.7 0.77

Female householder 6,068 60.9 1.43 70.8 1.33 23.7 1.25 2.1 0.42 20.7 1.19 1.5 0.36

Other arrangement 306 74.3 5.70 63.9 6.27 15.0 4.66 ‡ † 15.9 4.77 2.7 2.11

Household language

Spanish-only 730 50.5 4.22 73.6 3.72 19.9 3.37 ‡ † 12.8 2.82 0.6 0.65

Not Spanish-only 30,259 78.6 0.54 67.6 0.61 15.3 0.47 1.1 0.14 15.1 0.47 1.2 0.14

Poverty status

In poverty 3,408 46.9 2.75 71.9 2.48 25.2 2.40 2.1 0.79 17.7 2.11 2.0 0.77

Not in poverty 24,089 82.3 0.79 67.2 0.97 14.7 0.74 1.1 0.22 15.4 0.75 1.1 0.22

Family income

Under $20,000 3,045 46.0 2.06 73.8 1.82 27.1 1.84 2.4 0.63 19.6 1.64 1.7 0.53

$20,000–$34,999 4,320 63.0 1.68 69.4 1.60 18.9 1.36 1.5 0.42 17.4 1.32 1.6 0.44

$35,000–$49,999 4,670 76.0 1.43 67.2 1.57 15.4 1.21 1.1 0.35 17.1 1.26 1.2 0.36

$50,000–$74,999 6,396 84.8 1.02 65.7 1.35 16.1 1.05 0.8 0.25 15.1 1.02 1.0 0.28

$75,000 or more 9,066 91.9 0.65 66.8 1.13 11.0 0.75 1.0 0.24 13.2 0.81 1.1 0.25

Urbanicity

Metropolitan, city center 6,059 72.9 1.30 64.1 1.41 21.3 1.20 2.2 0.43 13.4 1.00 1.1 0.31

Metropolitan, not city center 14,576 82.2 0.72 67.1 0.89 14.8 0.67 0.9 0.18 15.0 0.68 1.0 0.19

Non-metropolitan 5,732 71.5 1.67 74.0 1.62 13.2 1.25 0.6 0.29 15.8 1.35 1.7 0.48

# Percentage less than 0.5.

‡ Too few cases to report.

Table 6. Percentage of Internet users age 5–17 who use the Internet at specific locations, by child and family/household characteristics: 

Characteristics of users

Number of 

children 

(in thousands)

Internet use locations

Own home School

Community 

center

Someone else's 

home

NOTE: s.e. is standard error. Detail may not sum to total due to rounding, missing data, or multiple response. 

Some other 

place

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Public library

† Not applicable.

1

 White, Black, Asian, and Am. Indian indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pac. Islander, non-Hispanic; and Am. Indian, Aleut, or Eskimo, non-Hispanic.

24
Spanish-monolingual households, and families with incomes below $35,000 per year (table 6). 

Many of these users do not have computers at home (Newburger 2001), while nearly all schools 

have Internet access, which may explain the tendency of these populations to connect to the 

Internet from school.14 

There are no detectable race/ethnicity differences in rates of Internet use at school among 

Whites, Blacks, Hispanics, and American Indians; the use rate at school is approximately 68 

percent for all four groups.15 Among Asians the use rate at school is lower than the rate for 

whites, but is not detectably different from the rates for other groups. There are also no 

detectable differences between the use rates at home and at school for Blacks and Hispanics, 

though more Whites use the Internet at home than at school, and a greater percentage of Whites 

use the Internet at home than do Blacks or Hispanics. 

Some groups are more reliant on Internet access through public libraries than others. 

Some of the same groups who rely relatively heavily on school facilities for Internet access are 

the most likely to use public libraries for Internet access. These groups include children and 

adolescents from families with incomes under $20,000 per year and those from single-mother 

households. In addition, about 30 percent of Black children and adolescents and about 25 

percent of 5- through 17-year-olds living in poverty use public libraries to get on the Internet. 

These statistics suggest that public libraries serve as a significant point of access. 

Table 7 looks at children and adolescents who access the Internet through one location 

only. Such youth make up approximately 39 percent of all 5- through 17-year-olds who use the 

Internet and number approximately 12.2 million. Looking at the data in this way helps to more 

clearly illustrate the role schools play in providing Internet access for children and adolescents 

by showing how heavily students from some backgrounds rely on schools for access. The table 

shows that the home is the most likely point of access among those who access the Internet from

only one location. Nearly two-thirds of these Internet users rely solely on home access. 

 

14 No statistical difference between home and school Internet use was detected for 5- through- 17-year-olds with

disabilities. Large standard errors associated with these estimates require that the results be interpreted with caution.

15 The estimate for American Indian is 75 percent, but this is not statistically distinguishable from the estimates of

67–69 percent for White, Black, and Hispanic, due to the large standard error of the American Indian estimate. 

 

25
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

All persons age 5–17 12,163 64.0 0.99 30.8 0.96 2.1 0.30 # † 2.6 0.33 # †

Child characteristics

Age

5–7 2,281 63.0 2.31 31.6 2.22 1.9 0.65 ‡ † 2.8 0.79 0.6 0.37

8–10 3,205 62.2 1.96 33.8 1.91 1.6 0.51 # † 1.9 0.55 # †

11–14 3,865 64.4 1.76 29.8 1.68 2.3 0.55 # † 3.0 0.63 # †

15–17 2,812 66.3 2.03 28.2 1.94 2.6 0.69 ‡ † 2.7 0.70 # †

Sex

Female 5,847 64.9 1.42 29.6 1.36 2.2 0.44 # † 2.6 0.48 # †

Male 6,316 63.2 1.39 31.9 1.34 2.0 0.40 # † 2.6 0.46 # †

Race/ethnicity1

White 8,142 69.2 1.17 26.6 1.12 1.2 0.28 # † 2.5 0.39 # †

Black 1,665 48.7 3.35 42.1 3.31 6.1 1.60 ‡ † 2.8 1.11 ‡ †

Hispanic 1,562 47.9 4.49 44.5 4.47 3.2 1.58 ‡ † 3.8 1.72 0.5 0.63

Asian 618 84.0 3.37 14.0 3.19 0.8 0.82 ‡ † 0.5 0.65 ‡ †

American Indian 175 40.9 8.47 56.2 8.55 1.8 2.29 ‡ † ‡ † ‡ †

Disability status

Disabled 95 38.2 11.38 49.8 11.71 ‡ † ‡ † ‡ † ‡ †

Not disabled 10,308 63.7 1.08 30.3 1.03 2.4 0.34 # † 3.1 0.39 # †

See footnotes at end of table.

Some Other 

Place

Table 7. Percentage of children and adolescents who use the Internet at only one location, by child and family/household characteristics and by location of use: 2001

Characteristics of persons

Number of 

children 

(in 

thousands)

Internet use locations

Own Home School Public Library

Community 

Center

Someone Else's 

Home

26
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Parent & household characteristics

Parent educational attainment

Less than high sch. credential 868 32.7 3.63 58.8 3.81 3.4 1.40 ‡ † 3.9 1.50 1.1 0.81

High school credential 2,857 55.3 2.12 38.6 2.08 2.7 0.69 # † 2.8 0.70 # †

Some college 3,927 63.8 1.75 30.0 1.67 2.2 0.53 # † 3.7 0.69 # †

Bachelor's degree 1,775 75.5 2.33 21.5 2.23 1.6 0.68 ‡ † 1.4 0.64 ‡ †

Graduate education 2,272 81.5 1.86 15.9 1.75 1.1 0.50 ‡ † 1.0 0.48 0.5 0.34

Family/household type

Two parent household 9,054 69.9 1.89 26.8 1.83 1.4 0.49 # † 1.5 0.50 # †

Male householder 589 49.7 4.70 41.9 4.64 3.0 1.60 ‡ † 5.5 2.14 ‡ †

Female householder 2,404 45.6 2.32 43.1 2.31 4.6 0.98 0.6 0.36 5.8 1.09 # †

Other arrangement 116 61.5 10.32 30.9 9.80 # † ‡ † 5.0 4.62 ‡ †

Household language

Spanish-only 397 35.5 5.48 58.3 5.65 # ‡ ‡ † 4.9 2.47 ‡ †

Not Spanish-only 11,766 65.0 1.00 29.9 0.96 2.2 0.31 # † 2.5 0.33 # †

Poverty status

In poverty 1,691 34.5 3.72 52.1 3.91 7.1 2.01 ‡ † 4.6 1.64 0.9 0.74

Not in poverty 8,946 69.8 1.56 26.1 1.50 1.4 0.40 ‡ † 2.4 0.52 # †

Family income

Under $20,000 1,422 33.5 2.86 53.2 3.02 6.9 1.53 0.9 † 4.8 1.29 0.8 0.54

$20,000–$34,999 1,899 50.4 2.62 40.5 2.57 3.6 0.98 # † 4.9 1.13 0.5 0.37

$35,000–$49,999 1,873 60.9 2.57 34.1 2.50 2.0 0.74 ‡ † 3.1 0.91 ‡ †

$50,000–$74,999 2,300 73.5 2.10 22.5 1.99 1.5 0.58 ‡ † 2.2 0.70 ‡ †

$75,000 or more 3,145 81.7 1.57 17.1 1.53 # † ‡ † 0.7 0.34 # †

Urbanicity

Metropolitan, city center 2,589 62.0 2.18 30.4 2.06 4.1 0.89 # † 2.7 0.73 0.5 0.32

Metropolitan, not city center 5,528 69.4 1.41 27.2 1.37 1.1 0.32 ‡ † 2.1 0.44 # †

Non-metropolitan 2,201 52.4 2.98 41.5 2.94 3.1 1.03 ‡ † 2.7 0.97 # †

# Percentage less than 0.5.

‡ Too few cases to report.

1

 White, Black, Asian, and Am. Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and Am. Indian, Aleut, or Eskimo, non-Hispanic.

Own home School Community center

Someone else's 

home

NOTE: s.e. is standard error. Detail may not sum to total due to rounding or missing data. Totals may exceed 100 percent because individuals may use the Internet in more than one place.

Some other place

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Public library

† Not applicable. 

 2001—Continued

Characteristics of persons

Number of 

children 

(in 

thousands)

Internet use locations

Table 7. Percentage of children and adolescents who use the Internet at only one location, by child and family/household characteristics and by location of use:

27
However, several groups—those from households where no parents have a high school 

credential, those from monolingual Spanish households, and those in poverty—rely more heavily 

on access to the Internet from school than from any other single location. Fifty-nine percent of 

children and adolescents who have parents who have not earned a high school credential and 

who have only one point of access for the Internet rely on school facilities for this access. 

Conversely, 16 percent of children and adolescents living with parents who attended graduate 

school and who use the Internet in only one place do so through school facilities. Fifty-eight 

percent of users with one point of access who belong to Spanish-monolingual households rely 

solely on school for access, compared to 30 percent of users with one access point who belong to 

other households, and about half of poor users with one access point do so, compared to about a 

quarter of non-poor users with only one access point (figure 5). Without access at school, these 

users would be forced to find alternative points of access or would cease using the Internet. 

Figure 5. Percentage of children and adolescents age 5–17 who use the Internet at only 

Figure 5. one location, by location and poverty status: 2001 

Not in poverty 

Pub. lib. 1% Pub. lib. 7%

Own home 70%

Other 

home 

2%

School 26%

Other 1%

Other 

home 

5% 

School 52%

Own home 

35%

In poverty 

NOTE: Estimates may not sum to 100 percent because of rounding. 

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001. 

 

28
Internet Activities16

The Internet supports a broad range of activities it supports. Children and adolescents 

use the Internet as a medium to communicate, to find information, to have fun, and to do 

homework. While electronic mail is the Internet application most widely used by adults (U.S. 

Department of Commerce 2000), among youth age 5 through 17, e-mail (or instant messaging) 

and playing games are the second most popular Internet activities, after completing school 

assignments. About 42 percent of all youth in this age range use the Internet for school work, 

while 38 percent use e-mail or instant messaging and about the same percentage play games. 

As shown in table 8, from 6 to 22 percent of children and adolescents use the Internet to 

find information about news, weather, sports, and products, to participate in chat rooms or 

listservs (discussion groups or mailing lists), to watch or listen to television, movies, or radio, 

and to make purchases.17 Smaller percentages use the Internet for other purposes. 

Table 9 controls for Internet use by looking at just those 5- through 17-year-olds who use 

the Internet. General patterns found for the broader 5–17 year-old age group hold when 

focusing just on those who use the Internet. Completing school assignments is the most popular 

activity, followed by e-mail and playing games, all of which are done by a majority of users. 

Older children tend to use the Internet for more applications than do younger children. 

Table 9 shows that, with the exception of playing games, other activities such as completing 

school assignments, e-mail, and finding information about news, weather, or sports increase 

steadily with age. 

Although the gender gap in Internet use rates has closed, there are gender differences in 

Internet activities. As shown in table 9, girls who use the Internet are more likely to use it for 

 

16 In contrast to the discussion of computer activities, which was limited by the CPS design to activities at home, this 

discussion of Internet activities applies to activities at any location where the Internet is used. CPS data do not allow 

separate examination of Internet activities at home or at school. 

17 The large number of Internet use options makes presenting extensive demographic details by type of activity

unwieldy. In order to keep the tables to a practical size, characteristics associated with differences in computer use 

in earlier sections of the report are presented in tables 7 and 8. 

 

29
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 42.1 0.5 42.9 0.7 41.3 0.7 11.7 0.7 31.9 1.0 54.3 0.9 66.2 1.0

E-mail or instant messaging 38.0 0.5 39.7 0.7 36.4 0.7 11.1 0.7 26.8 0.9 47.0 0.9 63.8 1.0

Playing games 36.4 0.5 34.6 0.7 38.1 0.7 20.5 0.8 33.7 1.0 43.0 0.9 46.1 1.0

News/weather/sports 21.8 0.4 19.9 0.6 23.6 0.6 4.6 0.4 13.0 0.7 27.4 0.8 40.2 1.0

Find information on products 19.9 0.4 18.9 0.6 20.9 0.6 3.9 0.4 9.9 0.6 23.6 0.8 40.9 1.0

Chat rooms or listservs 11.9 0.3 12.4 0.5 11.4 0.4 1.3 0.2 3.5 0.4 14.3 0.6 27.8 0.9

Watch/listen to TV, movies, or radio 11.1 0.3 10.3 0.4 11.8 0.4 3.0 0.4 6.5 0.5 13.0 0.6 21.1 0.8

Make purchases 6.2 0.2 5.2 0.3 7.1 0.4 0.7 0.2 2.3 0.3 6.4 0.4 15.6 0.8

Phone calls 1.9 0.1 2.1 0.2 1.7 0.2 0.5 0.1 1.1 0.2 1.8 0.2 4.1 0.4

Taking a course on-line 0.5 0.1 0.5 0.1 0.6 0.1 # † # † # † 1.2 0.2

Other 0.9 0.1 0.9 0.1 1.0 0.1 # † 0.6 0.2 1.0 0.2 1.9 0.3

Find government information1 — † — † — † — † — † — † 7.6 0.6

Find health information1 — † — † — † — † — † — † 7.4 0.5

Find a job1 — † — † — † — † — † — † 3.6 0.4

Online banking1 — † — † — † — † — † — † 1.7 0.3

Trading stocks1 — † — † — † — † — † — † 0.7 0.2

See footnotes at end of table.

5–7 8–10 11–14 15–17

Table 8. Percentage of persons age 5–17 using the Internet for specific activities, by selected characteristics: 2001 

Internet activity

Sex Age group

All persons age 

5-17 Female Male

30
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 21.4 1.3 34.6 0.9 44.2 0.9 51.4 1.4 58.2 1.2 48.9 0.6 29.7 1.4 26.1 1.7 48.9 2.4 33.5 4.3

E-mail or instant messaging 13.8 1.1 30.7 0.9 39.7 0.9 48.9 1.4 55.6 1.2 46.7 0.6 22.2 1.2 17.5 1.5 44.8 2.4 30.2 4.2

Playing games 18.8 1.2 30.7 0.9 39.2 0.9 45.5 1.4 47.3 1.2 41.5 0.6 29.8 1.4 21.9 1.6 38.9 2.3 38.5 4.4

News/weather/sports 9.2 0.9 17.4 0.7 23.4 0.8 25.9 1.2 31.8 1.1 25.7 0.5 15.1 1.1 11.9 1.3 25.9 2.1 20.4 3.6

Find information on products 7.1 0.8 15.1 0.7 20.9 0.7 24.8 1.2 30.8 1.1 24.4 0.5 11.9 1.0 10.1 1.2 21.3 2.0 12.3 3.0

Chat rooms or listservs 6.9 0.8 10.3 0.6 12.7 0.6 13.7 1.0 15.6 0.9 14.0 0.4 6.4 0.7 7.9 1.0 14.4 1.7 13.8 3.1

Watch/listen to TV, movies, or radio 5.2 0.7 9.4 0.6 12.0 0.6 12.3 0.9 15.2 0.9 12.3 0.4 10.1 0.9 6.9 1.0 11.8 1.5 11.5 2.9

Make purchases 1.4 0.4 3.7 0.4 5.6 0.4 8.7 0.8 12.8 0.8 8.1 0.3 2.7 0.5 2.4 0.6 5.9 1.1 3.9 1.8

Phone calls 0.8 0.3 1.4 0.2 2.2 0.3 2.4 0.4 2.3 0.4 2.1 0.2 1.7 0.4 1.0 0.4 2.0 0.7 2.4 1.4

Taking a course on-line 0.6 0.2 # † 0.5 0.1 # † 0.8 0.2 0.5 0.1 # † 0.5 0.3 0.9 0.5 1.3 1.0

Other # † 0.8 0.2 1.1 0.2 0.5 0.2 1.7 0.3 1.1 0.1 0.6 0.2 0.8 0.3 0.8 0.4 1.4 1.1

Find government information1 — † — † — † — † — † — † — † — † — † — †

Find health information1 — † — † — † — † — † — † — † — † — † — †

Find a job1 — † — † — † — † — † — † — † — † — † — †

Online banking1 — † — † — † — † — † — † — † — † — † — †

Trading stocks1 — † — † — † — † — † — † — † — † — † — †

American 

Indian

Race/ethnicity2

See footnotes at end of table.

Internet activity

Less than high 

school 

credential

Bachelor's 

degree

Table 8. Percentage of persons age 5–17 using the Internet for specific activities, by selected characteristics: 2001—Continued

Parent educational attainment

High school 

credntial Some college

Graduate 

education White Black Hispanic Asian 

31
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 23.2 1.1 32.1 1.1 43.2 1.3 49.1 1.2 59.0 1.0

E-mail or instant messaging 16.6 0.9 26.5 1.1 38.7 1.3 45.8 1.2 57.2 1.0

Playing games 21.2 1.0 30.0 1.1 41.0 1.3 42.8 1.2 47.2 1.0

News/weather/sports 11.7 0.8 16.5 0.9 20.7 1.1 26.1 1.0 31.9 1.0

Find information on products 8.7 0.7 14.0 0.8 18.9 1.0 23.3 1.0 31.4 1.0

Chat rooms or listservs 7.3 0.7 8.5 0.7 12.2 0.9 13.8 0.8 17.0 0.8

Watch/listen to TV, movies, or radio 7.0 0.6 8.8 0.7 12.2 0.9 12.4 0.8 15.4 0.8

Make purchases 2.2 0.4 3.0 0.4 4.2 0.5 7.0 0.6 12.7 0.7

Phone calls 1.7 0.3 1.6 0.3 2.1 0.4 1.8 0.3 2.3 0.3

Taking a course on-line 0.5 0.2 # † 0.7 0.2 # † 0.7 0.2

Other 0.6 0.2 0.9 0.2 0.8 0.2 1.3 0.3 1.3 0.2

Find government information1 — † — † — † — † — †

Find health information1 — † — † — † — † — †

Find a job1 — † — † — † — † — †

Online banking1 — † — † — † — † — †

Trading stocks1 — † — † — † — † — †

† Not applicable.

# Too small to report.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

— Not available. Data were not collected.

Internet activity

Family income

$75,000 or more

1

 The survey did not ask about these activities for persons less than 15 years old.

2

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and 

American Indian, Aleut, or Eskimo, non-Hispanic.

Table 8. Percentage of persons age 5–17 using the Internet for specific activities, by selected characteristics: 2001—Continued

NOTE: s.e. is standard error. Detail may not sum to total due to rounding and multiple response.

Less than 

$20,000

 $20,000– 

$34,999

 $35,000– 

$49,999

 $50,000– 

$74,999

32
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 72.0 0.6 73.2 0.8 70.9 0.8 37.2 1.8 59.7 1.4 79.5 0.9 85.8 0.8

E-mail or instant messaging 65.0 0.6 67.6 0.9 62.4 0.9 35.5 1.8 50.1 1.4 68.8 1.0 82.8 0.9

Playing games 62.3 0.6 59.1 0.9 65.4 0.9 65.3 1.8 63.0 1.4 63.0 1.0 59.8 1.2

News/weather/sports 37.3 0.6 33.9 0.9 40.5 0.9 14.7 1.3 24.4 1.2 40.1 1.1 52.2 1.2

Find information on products 34.0 0.6 32.2 0.9 35.8 0.9 12.5 1.2 18.6 1.1 34.6 1.0 53.1 1.2

Chat rooms or listservs 20.3 0.5 21.2 0.8 19.5 0.7 4.1 0.7 6.6 0.7 20.9 0.9 36.1 1.1

Watch/listen to TV, movies, or radio 18.9 0.5 17.5 0.7 20.3 0.7 9.4 1.1 12.2 0.9 19.0 0.8 27.4 1.1

Make purchases 10.6 0.4 8.9 0.5 12.3 0.6 2.1 0.5 4.2 0.6 9.3 0.6 20.2 1.0

Phone calls 3.2 0.2 3.5 0.3 2.9 0.3 1.7 0.5 2.0 0.4 2.7 0.3 5.3 0.5

Taking a course on-line 0.9 0.1 0.8 0.2 1.0 0.2 0.6 0.3 0.8 0.2 0.6 0.2 1.5 0.3

Other 1.6 0.2 1.6 0.2 1.6 0.2 0.7 0.3 1.1 0.3 1.5 0.3 2.5 0.4

Find government information1 — † — † — † — † — † — † 9.8 0.7

Find health information1 — † — † — † — † — † — † 9.7 0.7

Find a job1 — † — † — † — † — † — † 4.7 0.5

Online banking1 — † — † — † — † — † — † 2.3 0.4

Trading stocks1 — † — † — † — † — † — † 0.9 0.2

Table 9. Percentage of Internet users age 5–17 using the Internet for specific activities, by selected characteristics: 2001

Internet activity

Sex Age group

Male

See footnotes at end of table.

All users age 

5–17 Female 5–7 8–10 11–14 15–17

33
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 67.6 2.6 68.9 1.3 70.0 1.1 74.1 1.5 78.2 1.1 73.3 0.7 65.5 2.1 70.3 2.9 75.8 2.6 62.6 6.0

E-mail or instant messaging 43.6 2.7 61.2 1.3 62.9 1.1 70.5 1.5 74.8 1.2 70.0 0.7 48.9 2.2 47.0 3.2 69.4 2.7 56.5 6.1

Playing games 59.3 2.7 61.2 1.3 62.0 1.1 65.7 1.6 63.6 1.3 62.1 0.7 65.8 2.1 59.1 3.1 60.2 2.9 71.9 5.6

News/weather/sports 29.2 2.5 34.5 1.3 37.0 1.1 37.3 1.6 42.8 1.4 38.5 0.7 33.4 2.1 32.0 3.0 40.1 2.9 38.1 6.0

Find information on products 22.3 2.3 30.1 1.3 33.1 1.1 35.9 1.6 41.4 1.4 36.5 0.7 26.3 2.0 27.2 2.8 33.0 2.8 23.0 5.2

Chat rooms or listservs 21.8 2.3 20.6 1.1 20.2 0.9 19.7 1.3 20.9 1.1 21.0 0.6 14.2 1.6 21.2 2.6 22.3 2.5 25.9 5.4

Watch/listen to TV, movies, or radio 16.3 2.0 18.7 1.1 19.0 0.9 17.8 1.3 20.5 1.1 18.4 0.6 22.4 1.9 18.6 2.5 18.3 2.3 21.4 5.1

Make purchases 4.4 1.1 7.3 0.7 8.9 0.7 12.6 1.1 17.2 1.0 12.1 0.5 5.9 1.1 6.6 1.6 9.2 1.7 7.3 3.2

Phone calls 2.5 0.9 2.9 0.5 3.5 0.4 3.4 0.6 3.1 0.5 3.1 0.3 3.8 0.9 2.7 1.0 3.1 1.0 4.4 2.5

Taking a course on-line 1.7 0.7 0.8 0.2 0.8 0.2 0.5 0.2 1.1 0.3 0.8 0.1 0.9 0.4 1.4 0.7 1.4 0.7 2.4 1.9

Other 1.1 0.6 1.6 0.3 1.7 0.3 0.8 0.3 2.3 0.4 1.6 0.2 1.4 0.5 2.0 0.9 1.3 0.7 2.7 2.0

Find government information1 — † — † — † — † — † — † — † — † — † — †

Find health information1 — † — † — † — † — † — † — † — † — † — †

Find a job1 — † — † — † — † — † — † — † — † — † — †

Online banking1 — † — † — † — † — † — † — † — † — † — †

Trading stocks1 — † — † — † — † — † — † — † — † — † — †

American 

Indian

See footnotes at end of table.

White Black Hispanic Asian

Table 9. Percentage of persons age 5–17 using the Internet for specific activities, by selected characteristics: 2001—Continued

Internet activity

Parent educational attainment

Less than high 

school 

credential

High school 

credential Some college

Bachelor's 

degree

Graduate 

education

Race/ethnicity2

34
Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Completing school assignments 63.5 2.0 65.8 1.6 68.7 1.5 73.2 1.3 78.2 1.0

E-mail or instant messaging 45.6 2.1 54.3 1.7 61.6 1.6 68.3 1.3 75.8 1.0

Playing games 58.1 2.0 61.4 1.7 65.3 1.6 63.7 1.4 62.6 1.2

News/weather/sports 32.2 1.9 33.8 1.6 33.0 1.6 38.9 1.4 42.3 1.2

Find information on products 24.0 1.8 28.7 1.6 30.2 1.5 34.7 1.4 41.6 1.2

Chat rooms or listservs 20.1 1.7 17.4 1.3 19.5 1.3 20.6 1.2 22.5 1.0

Watch/listen to TV, movies, or radio 19.3 1.6 18.1 1.3 19.4 1.3 18.5 1.1 20.4 1.0

Make purchases 5.9 1.0 6.1 0.8 6.7 0.8 10.5 0.9 16.8 0.9

Phone calls 4.5 0.9 3.3 0.6 3.3 0.6 2.6 0.5 3.0 0.4

Taking a course on-line 1.5 0.5 0.7 0.3 1.2 0.4 0.7 0.2 0.9 0.2

Other 1.7 0.5 1.7 0.4 1.3 0.4 2.0 0.4 1.7 0.3

Find government information1 — † — † — † — † — †

Find health information1 — † — † — † — † — †

Find a job1 — † — † — † — † — †

Online banking1 — † — † — † — † — †

Trading stocks1 — † — † — † — † — †

— Not available. Data were not collected.

† Not applicable.

# Percentage less than 0.5.

Table 9. Percentage of persons age 5–17 using the Internet for specific activities, by selected characteristics: 2001—Continued

Internet activity

Family income

Less than 

$20,000

 $20,000– 

$34,999

 $35,000– 

$49,999

 $50,000– 

$74,999 $75,000 or more

1

 The survey did not ask about these activities for persons less than 15 years old.

NOTE: s.e. is standard error. Detail may not sum to total due to rounding and multiple response.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

2

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and 

American Indian, Aleut, or Eskimo, non-Hispanic.

35
e-mail, and boys who use the Internet are more likely to use it for games, shopping, and finding 

information about news, weather, or sports. This is consistent with research on adults’ uses of 

the Internet, which has shown that although gender differences in overall use rates have 

vanished, gender differences persist in preferences for Internet activities, with men favoring 

entertainment and women favoring communication and educational assistance (Weiser 2000; 

also see Odell et al. 2000; Singh 2002). Some recent research on college students has revealed 

similar differences in Internet activities—women used more e-mail and men used the web more 

(Jackson et al. 2001). 

 

36
Conclusions 

 

This report uses data from the September 2001 Current Population Survey to examine the 

use of computers and the Internet by children and adolescents. The report examines children’s 

and adolescents’ overall use, how children and teens use these technologies, where they use 

them, and the relationships of patterns of use to socioeconomic and demographic characteristics 

such as age, race/ethnicity, parental education, and family income. 

Computer and Internet use by children and adolescents is widespread and begins at an 

early age. About nine in ten Americans age 5 through 17 use computers, and more than half use 

the Internet. Computer use is common at an earlier age than Internet use, but by high-school-age 

(15–17) about three quarters of youth are on-line. 

Children and adolescents commonly use computers for playing games, completing school 

assignments, word processing, email, and connecting to the Internet. On-line, the most frequent 

activities are school work, email, games, and finding information. 

There are significant demographic and socioeconomic differences in the use of these 

information technologies. Family income and parents’ education are both positively associated 

with computer and Internet use, and proportionally fewer children and adolescents who live in 

households where Spanish is the only language spoken use computers and the Internet. Use of 

both technologies is higher among Whites than among Blacks and Hispanics and is higher 

among the non-disabled than among the disabled. The findings for each variable remain 

statistically significant when controlling for other variables. In contrast to findings from

previous studies (e.g. Clemente 1998; Riccobono 1986), however, gender differences in rates of 

computer and Internet use no longer exist. 

Looking at where children and adolescents use computers, more use computers at school 

than at home. For some groups of 5–17-year-olds, use at school exceeds use at home by 30 

percentage points or more. These groups include Blacks and Hispanics, those whose parents did 

not complete high school, those living with a single mother, those living in households where 

 

37
Spanish is the only language spoken, and those living in families with incomes below $20,000 

per year. Home use is more prevalent among children and adolescents who are members of 

families with incomes of $75,000 or more per year, and whose parents attended graduate school. 

Schools do appear to help narrow the digital divide in terms of computer use. 

Differences in the rates of computer use are smaller at schools than they are at home when 

considering such characteristics as race/ethnicity, family income, and parental education. 

Although nearly all schools have Internet access and more children and adolescents use 

computers at school than at home, the home is the most widely used Internet access location. Of 

those children and adolescents who use the Internet, 78 percent use it at home, compared to 68 

percent at school. Highlighting the digital divide, those who rely more heavily on access at 

school come from households with annual family incomes below $35,000 and whose parents did 

not complete high school. 

While CPS data do support analyses of the use of technology, they do not support 

analysis of the quality of hardware and software available or the convenience of access. Future 

research could address these issues of quality and convenience, and also continue to study the 

digital divide to track trends in usage. 

 

38
Methodological and Technical Notes18

Current Population Survey (CPS) Design 

The CPS is a representative sample survey of all households in the United States. The 

survey is conducted in approximately 56,000 dwelling units in 754 primary sampling units. 

Dwelling units are in-sample for 4 successive monthly interviews, out-of-sample for the next 8 

months, and then returned to the sample for the following 4 months. The sample frame is a 

complete list of dwelling-unit addresses at the time of the Census updated by demolitions and 

new construction and field listings. The population surveyed excludes members of the armed 

forces, inmates of correctional institutions, and patients in long-term medical or custodial 

facilities; it is referred to as the civilian, noninstitutionalized population. Typically about 4 

percent of dwelling units are not interviewed because occupants are not at home after repeated 

callbacks or for some other reason. 

A member of each household who is at least 15 years old serves as the informant for that 

household, supplying data for each member of the household. As a result of this data collection 

method, data regarding computer and Internet use by children and adolescents were not collected 

directly from the users in most cases, but from another member of the user’s household. Because 

a household’s informant may not have full information regarding computer and Internet use by 

other members of the household (especially when that use occurs at school), this method is a 

potential source of error in the data. 

In September 2001, supplementary questions regarding computer and Internet use were 

asked about eligible household members 3 years old and over. (This report examines persons 

ages 5–17 because this range corresponds to the modal ages of students in kindergarten through 

twelfth grade.) Most interviews were conducted by phone using computer-assisted telephone 

interviewing. 

 

18 Part of this section on the CPS and statistical procedures is reprinted from Appendix C of U.S. Department of

Education, National Center for Education Statistics, Dropout Rates in the United States: 1999, NCES 2001-022, by

Phillip Kaufman, Jin Y. Kwon, Steve Klein, and Christopher D. Chapman. Washington, DC, 2000. Also see U.S. 

Census Bureau, Technical Paper 63 Revised: Current Population Survey – Design and Methodology, TP63RV. 

Washington, DC, 2002. 

 

39
Standard Errors and the Accuracy and Precision of Estimates 

The estimates in this report are derived from samples and are subject to two broad classes 

of error—sampling and nonsampling error. Sampling errors can occur when the data are 

collected from a sample of a population rather than from the entire population. To the extent that 

the sample differs from the population it is supposed to represent, estimates based on a sample 

can differ from the values that would have been obtained from a universe survey using the same

instruments, instructions, and procedures. Nonsampling errors come from a variety of sources 

and affect all types of surveys, universe as well as sample surveys. Examples of sources of 

nonsampling error include item wording, reporting error by respondents, and data processing 

errors. The effects of nonsampling errors are more difficult to evaluate than those that result from

sampling variability. As much as possible, procedures are built into surveys in order to minimize 

nonsampling errors. 

The standard error is a measure of the variability due to sampling when estimating a 

parameter. It indicates how much variance there is in the population of possible estimates of a 

parameter for a given sample size. Standard errors can be used as a measure of the precision 

expected from a particular sample. The chances that a sample estimate would differ from a 

population parameter by less than the standard error are about 68 out of 100; the chances that the 

difference would be less than 1.96 times the standard error are about 95 out of 100. 

Since the CPS sample is not a simple random sample, the methods that are most 

frequently used to compute standard errors must be adjusted to account for the effects of the 

sample design. Standard errors for percentages based on CPS data were calculated using the 

following formula: 

se = (b / N)( p)(100 − p)

 

40
where b = the parameter associated with the characteristic,19

N = the population on which the percentage is based, and 

p = the percentage (0<p<100). 

 For example, where table 1 shows an estimate that 89.5 percent of persons ages 5–17 

use computers, the standard error is calculated as follows. The variable b is 5211 (this can be 

found in the Census Bureau technical report previously cited); the N is 53,013,000, and the 

percentage is 89.5. Using the formula given above, the standard error is .30. 

.30 = (5211/ 53,013,000)(89.5)(100 − 89.5)

Response Rates 

The unweighted response rate for the September 2001 core CPS was 93.5 percent, and 

the response rate for the computer and Internet use supplement was 92.1 percent, for an overall 

response rate on the supplement of 86.1 percent. 

Method and Statistical Procedures for the Comparison of Estimates

The comparisons in the text have all been tested for statistical significance to ensure that 

the differences are larger than those that might be expected due to sampling error. Four types of 

comparisons have been made in the text. All statistical comparisons in this report were tested for 

significance at the 95 percent confidence level (p<.05), and all reported differences are 

statistically significant, unless otherwise noted. One type of comparison tests the significance of

a statistic’s relationship to a specified value, such as 50 percent. A 95 percent confidence 

interval is computed and the statistic is treated as though the true value falls within this range, 

supporting a statement that the statistic is more than, less than, or not distinguishable from a 

specified value. The confidence interval for an estimate is determined by the following formula: 

 CI = x ± t (se) 

 

19 These parameters and their use are explained in U.S. Census Bureau, Source and Accuracy Statement for the 

September 2001 CPS Microdata File for Internet and Computer Use in the U.S., Washington, DC, 2002. Available 

at http://www.bls.census.gov/cps/computer/2001/ssrcacc.htm 

 

41
 where x = the estimate for which the confidence interval is desired 

t = the critical value, which is 1.96 for a 95 percent interval 

se = the standard error of the estimate 

For example, the statement on page 3 of this report that “among high-school-age youth 

(ages 15–17), more than 90 percent use computers,” was tested as follows: 

 CI = x ± t (se) 

CI = 93.4 ± 1.96 (0.52) 

92.4 to 94.4 = 93.4 ± 1.0 

In repeated sampling, the population parameter (i.e., the “true” value) can be expected to 

fall within the range of the 95 percent confidence interval 95 percent of the time. In the previous 

example, the true value is expected to be between 92.4 and 94.4, so the statement in the text that 

“among high-school-age youth (ages 15–17), more than 90 percent use computers” is supported. 

Had the confidence interval included the range 89.0 to 97.8, for example, the statement would 

not have been supported because the range extends below 90 percent. 

The second type of comparison tests the hypothesis that there is a linear relationship 

between two variables with multiple categories. A bivariate linear regression model is specified, 

and a statistically significant regression coefficient supports the hypothesis that there is a linear 

association between the dependent and independent variables. To account for the complex 

sampling methods of the CPS, a weighted least squares (WLS) regression is used in which the 

model (e.g. the percentage of children who use computers) is weighted by the variance of the 

dependent variable. 

The third type of comparison tests the statistical significance of the difference of two 

statistics. The student’s t statistic can be used to test the likelihood that the differences between 

two percentages are larger than would be expected by sampling error alone. 

 

42
2

2

2

1

1 2

se se

P P

t

+

− =

where P1 and P2 are the estimates to be compared and se1 and se2 are their respective standard 

errors. 

For example, the statement on page 6 of this report that “those who are not disabled are 

more likely to use computers... than those with disabilities” was tested as follows. The estimate 

for the percentage of non-disabled children and adolescents ages 5–17 who use computers is 

89.8 percent, and the standard error of this estimate is .32 percent; the estimate and standard 

error for disabled children and adolescents in the same age group are 80.0 percent and 3.65 

percent, respectively (table 1). The t value is 2.67, as shown below. 

2.67

.32 3.65

89.8 80.0

2 2 =

+

− t =

Since the t value exceeds the critical value of 1.96, readers can conclude that children and 

adolescents who are not disabled are more likely to use computers than those with disabilities. 

As the number of comparisons on the same set of data increases, the likelihood that the t

value for at least one of the comparisons will exceed 1.96 simply due to sampling error increases. 

For a single comparison, there is a 5 percent chance that the t value will exceed 1.96 due to 

sampling error. For five tests, the risk of getting at least one t value that high increases to 23 

percent, and for 20 comparisons, to 64 percent. 

One way to compensate for this danger when making multiple comparisons is to adjust 

the alpha level to take into account the number of comparisons being made. The alpha rate is the 

probability of falsely rejecting the hypothesis that there are no differences between groups in the 

population. For example, rather than establishing an alpha level of 0.05 for a single comparison, 

the alpha level is set to ensure that the likelihood is less than 0.05 that the t value for any of the 

comparisons exceeds the critical value by chance alone when there are truly no differences for 

any of the comparisons. For this report, the alpha level is reduced using the Bonferroni 

adjustment. The adjustment is calculated by dividing the desired alpha level by the number of 

 

43
possible comparisons, based on the variable(s) being compared (Dunn, 1961). The t value 

corresponding to the revised, lower alpha level must be exceeded in order for any of the 

comparisons to be considered significant. For example, to test for differences in computer use 

rates among non-Hispanic Whites, non-Hispanic Blacks, and Hispanics, the following steps 

would be taken: 

• Establish the number of comparisons. The number of two-way comparisons that can 

be made equals [(n)(n-1)]/2, where n is the number of variable categories. Thus, with 

three categories (Whites, Blacks, and Hispanics) the number of possible comparisons 

is [(3)(2)]/2 = 3 (Whites and Blacks, Whites and Hispanics, Blacks and Hispanics). 

• Divide the desired alpha level, 0.05, by the number of comparisons (e.g. 3) to obtain 

the new alpha level (0.05/3 = 0.0167). 

• Consult a table of t statistics (or the standard normal table for z values if the N is 

large) to find the t value that corresponds to that alpha (t = 2.39 for alpha = 0.0167). 

All t test comparisons in this report were tested using the Bonferroni adjustment. Where 

categories of two variables were involved, the number of comparisons to make the number of 

comparisons used to make the Bonferroni adjustment was based on the relationship(s) being 

tested. This technique reduces the frequency of Type I errors (rejecting the null hypothesis when 

it is true) while increasing Type II errors (failing to reject the null hypothesis when it is false). 

The fourth type of comparison is an equivalence test (Rogers, Howard, and Vessey 

1993), which determines whether there is any substantive difference between two statistics. 

This test requires an a priori determination of the minimum difference considered 

substantively important (delta). Equivalence tests in this report were conducted with a delta 

value of two percentage points, meaning that differences smaller than this are not considered 

meaningful. A delta of two percentage points is commensurate with the statistical properties of 

the data presented in this report; considering the sources of non-sampling error that affect survey 

data, including proxy reporting errors and data processing errors, it may not be reasonable to 

attribute substantive importance to differences smaller than about two percentage points. 

 

44
The equivalence test uses one-tailed t-tests to construct a confidence interval for the 

difference between two statistics. This confidence interval is compared to the minimum

substantively significant difference described by delta and negative delta. If the confidence 

interval is within the range of negative delta and delta—that is, if the upper bound of the 

confidence interval is less than delta and the lower bound of the interval is more than negative 

delta—this indicates that the difference between the two statistics is less than the smallest 

difference that can be considered important, so the two statistics are equivalent. 

The formula for the confidence interval of the difference is as follows: 

( . .) 1 2 CI = p − p ± t s e

 where p1 = the first statistic being compared 

 p2 = the second statistic being compared 

t = the critical value20

s.e. = the standard error of the difference of p1 and p2 

In this report the estimate of the percentage of females age 5–17 who use computers is 

90.0 percent (s.e. = 0.43) and the estimate for males is 89.1 percent (s.e. = 0.43). The difference 

is 0.9 percent (s.e. = 0.61). To test the equivalence of these two statistics at the 95 percent 

confidence level when the minimum substantively important difference, delta, is two percentage 

points, compare confidence interval for the difference to delta. In this case the confidence 

interval for the difference is –0.10 to 1.90. Since this interval is within the delta interval of –2 to 

2, the percentages of males and females age 5–17 who use computers are about the same. 

Logistic Regression Analysis 

Regression is a procedure that uses one or more independent variables to predict the 

values of a dependent variable and to reveal each independent variable’s association with the 

variable being predicted. In the two analyses presented in table 2, computer use and Internet use 

 

20 For 95 percent confidence in equivalency, using a one-tailed test, the critical value is 1.645. 

 

45
(the dependent variables) were analyzed using several independent variables that have previously 

been found to be associated with the use of information technologies. 

Logistic regression is a form of regression used when the dependent variable is 

dichotomous (that is, when it can take only two different values, such as “computer user” or 

“computer non-user”). In logistic regression, the equation predicts the natural log of the odds 

(the “log odds”) of an event occurring, such as the sampled individual being a computer user.21 

The form of the equation is as follows: 

Log[P/(1-P)] = B0 + B1X1 + ... + BpXp

In this equation, the value B0 is a constant. The X values are the observed values of 

independent variables such as age or income, and the corresponding B values are parameters 

indicating the effect of a one-unit change in X on the log odds of the event. The B parameters 

indicate the association between the independent variable and the dependent variable when all 

the other independent variables are statistically controlled, or held constant. 

 

Dichotomous independent variables and the “reference category.” Most of the 

independent variables in the logistic regression equations are treated as dichotomous. For 

example, the five categories of race/ethnicity are included in the regressions as four variables: 

Black, non-Hispanic; Hispanic; Asian or Pacific Islander, non-Hispanic, and American Indian, 

Aleut, or Eskimo, non-Hispanic. White, non-Hispanic is the “reference category.” The indicated 

parameter estimate and odds ratio (explained below) are interpreted in comparison with the 

reference category. For example, since the male parameter estimate in the computer use analysis 

is negative (or, since the odds ratio is less than one), this indicates that males are less likely than 

females (the reference category) to use computers. (However, the association is not statistically 

 

21 Odds are the probability of an event occurring divided by the probability of it not occurring. For example, 

consider the data reported in table 1 indicating that 58.5 percent of children 5–17 years old use the Internet. The 

odds of someone from this population using the Internet are (.585)/(1-.585) = 1.41 to one. This means that someone 

5–17 is 1.41 times more likely to use the Internet than to not use the Internet. 

 

46
significant.) Similarly, the negative parameter estimate for “Black, non-Hispanic” (or the odds 

ratio less than one) indicates that a Black child is less likely to use computers than a White child. 

Odds ratio. The results of the regression analysis include an “odds ratio” for each 

independent variable. The odds ratio shows each independent variable’s statistical relationship 

to the dependent variable when all of the other independent variables are held constant. More 

specifically, it shows how the odds of the dependent variable event occurring (i.e. the odds of a 

child being a computer user or being an Internet user) change when the independent variable 

changes. For example, table 2 shows that a child from a family in the highest income group is 

about two and a half times as likely to use the Internet as a child from a family in the lowest 

income group, all else being equal. This is indicated by the odds ratio of 2.46 for the highest 

income category. 

Continuous independent variables. Continuous variables do not have a reference 

category. Age is the only continuous variable in this analysis. The odds ratio and parameter 

estimate for this variable describe the statistical effect of a one-unit change in age on the 

dependent variable. For example, the odds ratio shows that a child who is one year older than 

another child is estimated to be 1.15 times more likely to use computers than the younger child 

(table 2), all else being equal. 

Significance tests and CPS sample design. Significance tests were conducted after 

adjusting for the effects of the CPS sample design. Since the CPS sample is not a simple random

sample, the methods that are normally used to compute the significance of parameter estimates in 

regression must be adjusted to account for the sample design. Adjustments were made to the 

weight variable to reflect design effects before the regression analysis was conducted. The new 

weight variable used in the regression analyses was calculated as follows: 

w DEFF

w

wn × =

where w = the new final weight for a case used in regression n

 

47
 = the original final weight for the case w

w = the mean of the original final weight, or 1748.3414 

DEFF = the design effect for the case 

The DEFF is the square of the factor by which standard errors are inflated due to the 

characteristics of the complex sample design used in the Current Population Survey. The DEFF 

equals the product of two parameters that account for race and urbanicity (which are factors in 

the CPS sample design) divided by the survey sampling interval, which is 2,255. The parameters 

for White, non-Hispanic; Black, non-Hispanic; Hispanic; and other non-Hispanic are, 

respectively, 5,211, 7,486, 12,616, and 5,211. These parameters are increased by a factor of 1.5 

for persons living in non-metropolitan areas and are unchanged for persons living in 

metropolitan areas. The DEFF ranges from 2.31 for a White or other non-Hispanic child living 

in a metropolitan area (5,211/2,255 = 2.31) to 8.39 for a Hispanic child living in a nonmetropolitan area (12,616 × 1.5 / 2,255 = 8.39). 

Variables Used in the Analysis 

Race/Ethnicity: The race/ethnicity variable is derived from two CPS questions that ask 

the subject’s race (classified as White, Black, American Indian/Aleut/Eskimo, Asian or Pacific 

Islander, or other) and whether or not he or she is Hispanic. These data were used to derive a 

race/ethnicity variable with five mutually exclusive categories: White, non-Hispanic; Black, nonHispanic; Asian or Pacific Islander, non-Hispanic; American Indian, Aleut, or Eskimo, nonHispanic, and Hispanic. 

Parent Educational Attainment: The CPS collects data about the highest level of school 

completed or the highest degree received for each person over the age of 15. Household 

respondents are also asked if subjects have taken any graduate or professional coursework since 

completing a bachelor’s degree. Responses for these two variables were collapsed into an 

education variable with categories corresponding to five levels of educational attainment: less 

than a high school diploma, a high school diploma or equivalent (GED), some college education 

but no bachelor’s degree (including people with an associate’s degree), college degree (i.e. 

people with a bachelor’s degree), and graduate education beyond a bachelor’s degree, including 

 

48
people who have taken graduate coursework but have not earned a degree. These data were then 

grouped by parent-child relationship and the highest level of education achieved by either parent 

residing with the child was assigned as the level of parent educational attainment. Those 

children and adolescents who do not reside with a parent are dropped from the analysis of 

parental education, and parents who do not live with their children are not included in the 

computation of parent educational attainment. 

Family/Household Type: Each household in the sample is classified as one of four types. 

In a “two-parent household” the child or adolescent lives with a married couple. In “male 

householder” or “female householder” households the child or adolescent lives with an 

unmarried male or female adult. Children and adolescents whose housing arrangements fit none 

of these categories are classified as an “other arrangement.” 

Household Language: Households are classified according to whether or not Spanish is 

the only language spoken by all members of the household who are 15 years of age or older. 

Disability Status: Each child and adolescent is classified as disabled or not disabled. 

Subjects who were reported to have any one or more of the following “long-lasting physical 

conditions” were classified as disabled: “blindness or a severe vision impairment even with 

glasses or contact lenses;” “deafness or a severe hearing impairment even with a hearing aid;” “a 

physical condition that substantially limits [the person’s] ability to walk or climb stairs;” or “a 

condition that makes it difficult to type on an ordinary typewriter or traditional computer 

keyboard.” Note that it is not possible to infer that children and adolescents identified as 

disabled in this report receive any services or accommodation as a result of disability. 

Family Income: Family income is derived from a single question asked of the household 

respondent. Income includes money from all sources including jobs, business, interest, rent, 

social security payments, and so forth that was received in the preceding 12 months. The income

of all family members 15 years old and over is included. Income is reported in fourteen 

categories ranging from “less than $5,000” to “$75,000 or more.” For convenience in tabular 

 

49
presentation, these fourteen categories were collapsed to five: under $20,000, $20,000-$34,999, 

$35,000-49,999, $50,000-$74,999, and $75,000 or more. 

Poverty Status: Poverty status is deduced from household size and reported household 

income categories. Households with reported income in categories below the poverty threshold 

for their household size (as currently defined by the U.S. Census Bureau for 2001) were 

classified as poor, and those households with income categories above the poverty threshold 

were classified as not poor. Some households reported income in a range that straddles the 

poverty threshold. It is likely that some of these households meet the Census Bureau definition 

of poverty and that some do not, but the CPS data do not allow discrimination between poor and 

non-poor status for these households. For the purposes of this analysis, all households in an 

income category that straddles a poverty threshold were classified as poor.22 

Urbanicity: The location of each subject’s residence is considered metropolitan and part 

of a central city, metropolitan and not part of a central city, or non-metropolitan. Metropolitan 

status is defined by the Office of Management and Budget and indicates that an area has a total 

population of at least 75,000 in New England or 100,000 elsewhere and also contains a place 

with a population of at least 50,000 or an area that meets the Census Bureau’s definition of an 

“urbanized” area. Metropolitan areas often include several counties and may include territory in 

more than one state. Central cities usually are one or more of the most populous areas in each 

metropolitan area. 

 

22 For example, the poverty threshold for a family of three persons including one related child is currently $14,255. 

A family of three that reported an income in the category “$12,500 to $14,999” is classified as poor in this analysis. 

 

50
References 

Cattagni, A., and Farris, E. (2001). Internet Access in U.S. Public Schools and Classrooms: 

1994-2000. NCES 2001-071. Washington, DC: U.S. Department of Education, National 

Center for Education Statistics. 

Clemente, P. C. (1998). State of the Net: The New Frontier. New York: McGraw-Hill. 

Dunn, O.J. (1961). Multiple Comparisons Among Means. Journal of the American Statistical 

Association, 56: 52-64. 

Gerber, E., and Kirchner, C. (2001). Who’s Surfing? Internet Access and Computer Use by 

Visually Impaired Youths and Adults. Journal of Visual Impairment and Blindness, 95(3): 

176-181. 

Jackson, L.A., Ervin, K.S., Gardner, P.D., and Schmitt, N. (2001). Gender and the Internet: 

Women Communicating and Men Searching. Sex Roles, 44(5-6): 363-379. 

Levin, D., Hurst, D., and Burns, S. (2000). Computer and Internet Access in Private Schools and 

Classrooms: 1995 and 1998. Stats in Brief. NCES-2000-044. Washington, DC: U.S. 

Department of Education, National Center for Education Statistics. 

Miller, L.M., Schweingruber, H., and Brandenburg, C.L. (2001). Middle School Students’ 

Technology Practices and Preferences: Re-examining Gender Differences. Journal of 

Educational Multimedia & Hypermedia, 10(2): 125-140. 

Newburger, E.C. (2001). Home Computers and Internet Use in the United States: August 2000. 

Washington, DC: U.S. Department of Commerce. 

Norris, P. (2001). Digital Divide: Civic Engagement, Information Poverty, and the Internet 

Worldwide. New York: Cambridge University Press. 

Odell, P.M., Korgen, K.O., Schumacher, P., and Delucchi, M. (2000). Internet Use Among 

Female and Male College Students. CyberPsychology and Behavior, 3(5): 855-862. 

Parsad, B., Skinner, R., and Farris, L. (2001). Advanced Telecommunications in U.S. Private 

Schools: 1998-99. NCES 2001-037. Washington, DC: U.S. Department of Education, 

National Center for Education Statistics. 

Rathbun, A.H., and West, J. (2003). Young Children’s Access to Computers in the Home and at 

School in 1999 and 2000. NCES 2003-036. Washington, DC: U.S. Department of Education, 

National Center for Education Statistics. 

Riccobono, J.A. (1986). Use of Electronic Information Technologies for Non-School Learning in 

American Households: Report of Findings From the 1985 Home Information Technology 

 

51
Study (HITS). CS-86-215. Washington, DC: U.S. Department of Education, Center for 

Statistics. 

Rogers, J.L., Howard, K. I., and Vessey, J. T. (1993). Using significance tests to evaluate 

equivalence between two experimental groups. Psychological Bulletin, 113: 553-565. 

Schumacher, P. and Morahan-Martin, J. (2001). Gender, Internet, and Computer Attitudes and 

Experiences. Computers in Human Behavior, 17(1): 95-110. 

Singh, S. (2002). Gender and the Use of the Internet at Home. New Media & Society, 3(4): 395-

415. 

U.S. Department of Commerce (1998). Falling Through the Net II: New Data on the Digital 

Divide. Washington, DC. 

U.S. Department of Commerce (2000). Falling Through the Net: Toward Digital Inclusion. 

Washington, DC. 

U.S. Department of Commerce (2002). A Nation Online: How Americans are Expanding their 

Use of the Internet. Washington, DC. 

U.S. Department of Education (2000). Office of Educational Technology, Progress Report on 

Educational Technology. Washington, DC. 

U.S. Department of Education (1999). National Center for Education Statistics, The Condition of 

Education 1999. NCES 2000–062, Washington, DC. 

Weiser, E.B. (2000). Gender Differences in Internet Use Patterns and Internet Application 

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52
Appendix 

Characteristics Percent s.e. Percent s.e.

Total (persons age 5–17) 53,013 89.5 0.30 58.5 0.49

Age

5 3,992 73.4 1.60 25.0 1.56

6 3,989 81.9 1.39 30.1 1.66

7 4,009 86.1 1.25 39.0 1.76

8 3,905 88.6 1.16 44.6 1.82

9 4,201 91.4 0.99 55.1 1.75

10 4,350 91.3 0.98 59.8 1.70

11 4,263 91.7 0.96 63.4 1.68

12 4,179 92.5 0.93 67.2 1.66

13 4,103 92.8 0.92 71.7 1.61

14 3,948 93.4 0.90 71.1 1.65

15 4,016 94.2 0.84 76.8 1.52

16 4,003 94.7 0.81 78.7 1.48

17 4,055 91.2 1.02 75.8 1.54

 age: 2001

NOTE: s.e. is standard error. Detail may not sum to total due to rounding.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Table A1. Percentage of children and adolescents age 5–17 who use computers and the Internet, by

Number of

children 

(in thousands)

Percent using 

computers

Percent using the

Internet

 

53
 

54

Characteristics Percent s.e. Percent s.e.

Total (persons age 18 and over) 204,299 60.1 0.25 54.2 0.25

Adult characteristics

Age

18-29 44,717 70.6 0.49 65.0 0.51

30-39 40,927 71.4 0.51 65.3 0.54

40-49 43,384 69.3 0.51 62.3 0.53

50-64 42,430 58.2 0.55 51.2 0.55

65 and over 32,842 22.1 0.52 18.7 0.49

Sex

Male 97,970 59.7 0.36 54.3 0.36

Female 106,329 60.5 0.34 54.1 0.35

Race/ethnicity1

White 148,620 65.2 0.28 59.7 0.29

Black 23,826 46.5 0.88 39.2 0.87

Hispanic 22,221 38.7 1.16 31.1 1.10

Asian 8,083 67.0 1.19 61.2 1.24

American Indian 1,548 50.5 2.90 45.8 2.89

Disability status

Disabled 17,302 27.7 0.78 24.4 0.75

Not disabled 160,947 62.6 0.28 56.8 0.28

Educational attainment

Less than high school credential 32,451 21.3 0.52 16.6 0.47

High school credential 67,305 49.4 0.44 42.2 0.43

Some college 55,421 73.0 0.43 65.8 0.46

Bachelor's degree 23,539 84.3 0.54 80.2 0.59

Graduate education 25,582 87.4 0.47 84.3 0.52

Family & household characteristics

Household language 

Spanish-only 7,478 26.7 1.17 21.4 1.08

Not Spanish-only 196,821 61.4 0.25 55.4 0.26

Poverty status

In poverty 23,414 29.6 0.96 24.8 0.91

Not in poverty 147,060 67.3 0.39 61.3 0.41

Family income

Under $20,000 32,652 28.4 0.57 24.1 0.54

$20,000–$34,999 33,721 47.8 0.62 40.9 0.61

$35,000–$49,999 27,411 64.9 0.66 57.5 0.68

$50,000–$74,999 33,851 76.1 0.53 69.2 0.57

$75,000 or more 42,839 86.5 0.38 82.1 0.42

Urbanicity

Metropolitan, city center 49,076 55.9 0.51 49.8 0.52

Metropolitan, not city center 88,223 65.5 0.37 59.9 0.38

Non-metropolitan 38,087 52.6 0.72 46.3 0.71

Table A2. Percentage of adults who use computers and the Internet, by selected characteristics: 2001

NOTE: s.e. is standard error. Detail may not sum to total due to rounding or missing data. Estimates are based 

on public-use data and may differ from estimates based on restricted-use data.

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Percent using 

computers

Percent using the

Internet

Number of

adults 

(in thousands)

1

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; 

Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, non-Hispanic.
Number of

children

Characteristics (in thousands) Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e.

Child characteristics

Age

5–7 11,990 22.6 0.41 20.3 0.42 42.2 1.51 12.2 0.42 37.3 0.74

8–10 12,455 23.5 0.42 23.8 0.45 21.3 1.26 21.5 0.53 26.3 0.68

11–14 16,493 31.1 0.46 32.2 0.49 22.0 1.27 36.3 0.62 23.8 0.66

15–17 12,075 22.8 0.42 23.7 0.45 14.5 1.08 30.0 0.59 12.6 0.51

Sex

Female 25,835 48.7 0.50 49.0 0.52 46.4 1.53 48.9 0.65 48.5 0.77

Male 27,178 51.3 0.50 51.0 0.52 53.6 1.53 51.1 0.65 51.5 0.77

Race/ethnicity

1

White 33,433 63.1 0.48 65.8 0.50 40.1 1.50 72.0 0.58 50.5 0.77

Black 8,275 15.6 0.43 14.8 0.45 22.3 1.53 12.1 0.51 20.6 0.75

Hispanic 8,400 15.8 0.56 13.9 0.56 32.2 2.23 10.1 0.61 24.0 1.02

Asian 2,268 4.3 0.20 4.3 0.21 4.2 0.61 4.7 0.27 3.6 0.29

American Indian 637 1.2 0.11 1.2 0.11 1.2 0.33 1.1 0.14 1.3 0.17

Disability status

Disabled 626 1.4 0.12 1.2 0.12 2.6 0.53 1.1 0.14 1.7 0.22

Not disabled 45,416 98.6 0.12 98.8 0.12 97.4 0.53 98.9 0.14 98.3 0.22

Family & household characteristics

Parent educational attainment

Less than h. s. credential 5,450 10.8 0.32 9.1 0.31 26.3 1.41 5.8 0.31 18.0 0.61

High school credential 13,611 26.9 0.45 26.1 0.47 34.6 1.53 22.9 0.55 32.8 0.75

Some college 15,665 31.0 0.47 31.7 0.50 24.9 1.39 33.1 0.62 27.9 0.71

Bachelor's degree 6,712 13.3 0.34 13.9 0.37 7.7 0.86 15.6 0.48 10.0 0.48

Graduate education 9,114 18.0 0.39 19.3 0.42 6.5 0.79 22.7 0.55 11.3 0.50

Family/household type

Two parent household 37,230 70.2 0.45 71.6 0.47 58.3 1.51 74.7 0.56 64.0 0.74

Male householder 2,715 5.1 0.22 5.0 0.23 6.4 0.75 4.8 0.28 5.6 0.35

Female householder 12,440 23.5 0.42 22.4 0.44 32.5 1.44 19.6 0.51 28.9 0.70

Other arrangement 628 1.2 0.11 1.0 0.10 2.8 0.51 1.0 0.13 1.5 0.19

Household language

Spanish-only 2,549 4.8 0.21 3.8 0.20 13.6 1.05 2.4 0.20 8.3 0.42

Not Spanish-only 50,464 95.2 0.21 96.2 0.20 86.4 1.05 97.6 0.20 91.7 0.42

Poverty status

In poverty 9,277 20.1 0.60 17.9 0.61 39.9 2.34 12.4 0.64 31.4 1.09

Not in poverty 36,904 79.9 0.60 82.1 0.61 60.1 2.34 87.6 0.64 68.6 1.09

Family income

Under $20,000 8,344 18.1 0.41 16.1 0.41 36.5 1.63 11.1 0.43 28.4 0.75

$20,000–$34,999 8,852 19.2 0.42 18.3 0.43 26.8 1.50 15.7 0.50 24.3 0.72

$35,000–$49,999 7,438 16.1 0.39 16.4 0.41 13.1 1.14 17.0 0.52 14.8 0.59

$50,000–$74,999 9,530 20.6 0.43 21.4 0.46 13.5 1.16 23.3 0.58 16.8 0.62

$75,000 or more 12,018 26.0 0.47 27.8 0.50 10.1 1.02 33.0 0.65 15.8 0.61

Urbanicity

Metropolitan, city center 12,249 27.0 0.48 25.5 0.49 39.2 1.61 23.0 0.59 32.5 0.77

Metropolitan, not city center 23,566 51.9 0.54 52.9 0.57 43.5 1.63 55.3 0.70 47.2 0.83

Non-metropolitan 9,609 21.2 0.54 21.6 0.57 17.3 1.52 21.7 0.71 20.3 0.81

NOTE: s.e. is standard error. Detail may not sum to total due to rounding or missing data. 

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

Table A3. Characteristics of persons age 5–17: 2001

All persons age 

5–17 Computer users

Computer nonusers Internet usersInternet nonusers

1

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, non-Hispanic; Asian or Pacific Islander, non-Hispanic; and 

American Indian, Aleut, or Eskimo, non-Hispanic.

 

55
 

56

Characteristics Percent s.e. Percent s.e.

Child characteristics

Age

5–7 9,650 19.6 0.49 19.1 0.43

8–10 11,275 22.6 0.51 24.2 0.47

11–14 15,270 32.7 0.58 32.9 0.52

15–17 11,254 25.1 0.53 23.8 0.47

Sex

Female 23,257 49.1 0.61 49.3 0.55

Male 24,192 50.9 0.61 50.7 0.55

Race/ethnicity2

White 31,201 74.4 0.54 65.2 0.53

Black 7,033 9.8 0.44 15.4 0.48

Hispanic 6,609 9.9 0.57 14.1 0.60

Asian 2,033 5.0 0.27 4.0 0.22

American Indian 573 1.0 0.12 1.2 0.12

Disability status

Disabled 500 1.2 0.14 1.2 0.13

Not disabled 40,759 98.8 0.14 98.8 0.13

Family & household characteristics

Parent educational attainment

Less than high school credential 4,121 4.3 0.25 9.4 0.33

High school credential 11,863 21.8 0.52 26.6 0.50

Some college 14,403 33.1 0.59 31.3 0.52

Bachelor's degree 6,317 16.2 0.46 13.9 0.39

Graduate education 8,786 24.6 0.54 18.9 0.44

Family/household type

Two parent household 33,988 79.0 0.50 70.9 0.50

Male householder 2,357 4.2 0.25 5.0 0.24

Female householder 10,635 15.9 0.45 23.1 0.47

Other arrangement 469 0.9 0.12 0.9 0.10

Household language

Spanish-only 1,794 2.2 0.18 3.8 0.21

Not Spanish-only 45,655 97.8 0.18 96.2 0.21

Poverty status

In poverty 7,462 9.6 0.54 18.5 0.64

Not in poverty 34,172 90.4 0.54 81.5 0.64

Family income

Under $20,000 6,682 8.5 0.36 16.7 0.44

$20,000–$34,999 7,638 14.7 0.46 18.4 0.46

$35,000–$49,999 6,838 17.1 0.49 16.4 0.44

$50,000–$74,999 8,919 24.8 0.56 21.2 0.48

$75,000 or more 11,557 34.9 0.62 27.3 0.52

Urbanicity

Metropolitan, city center 10,357 21.9 0.55 25.4 0.52

Metropolitan, not city center 21,463 57.5 0.66 52.4 0.60

Non-metropolitan 8,774 20.6 0.66 22.1 0.61

1 This figure is the number of people age 5 to 17 in the designated category who use computers at

home and/or at school. The number using computers at either location may be lower.

NOTE: s.e. is standard error. Detail may not sum to total due to rounding. 

SOURCE: U.S. Census Bureau, Current Population Survey, September 2001.

2

 White, Black, Asian, and American Indian respectively indicate White, non-Hispanic; Black, nonHispanic; Asian or Pacific Islander, non-Hispanic; and American Indian, Aleut, or Eskimo, nonHispanic.

Table A4. Characteristics of persons age 5–17 using computers at home and at school: 2001

Computer users

Number of 

children1 

(in thousands)

Using computers 

at home

Using computers 

at school