38 Monthly Labor Review August 2001

School-to-Work Programs

I

n 1994, the U.S. Congress passed the Schoolto-Work Opportunities Act providing federally

funded grants to the States and to local partnerships of business, government, education, and

community organizations to develop “school-towork systems.”1 The law encouraged the States

and their local partners to develop models that

would work best for their particular situations. As

a result, the features of school-to-work programs

often vary from grant to grant and thus are difficult

to describe in general terms. The Act did, however,

outline three core elements that all school-to-work

programs must entail:2

• School-based learning, which encompasses

rigorous classroom instruction that is

linked to workplace experiences and provides students with the information and

skills needed to identify and prepare for

promising careers;

• Work-based learning, which includes work

experience, structured training, and other

workplace learning experiences appropriate to students’ career interests and linked

to school curricula;

• Connecting activities, which are efforts undertaken to help employers and schools

forge and maintain links between the

school-based and work-based components

of school-to-work programs.

 School-to-Work Programs

Mary Joyce

and

David Neumark

School-to-work programs:

information from two surveys

The general goal of the School-to-Work Act is to

improve the transitions from school to work for all

youths in the United States. The Act points to a “lack

of a comprehensive and coherent system to help

youths acquire the knowledge, skills, abilities, and

information about and access to the labor market that

are necessary to make an effective transition from

school to work or further education.”3

In this article, we are interested in studying

the extent to which school-to-work programs

have been implemented in our Nation’s high

schools since the Act’s passage in 1994, as well

as the extent to which high school students are

choosing to participate in these programs. To inform our study, we use two promising new data

sources. The first, the 1997 National Longitudinal Survey of Youth (NLSY97), provides information obtained directly from students on the extent to which they participated in school-to-work

programs. The second source, the 1996 School

Administrator’s Survey (SAS96), provides information obtained from the schools attended by

the NLSY97 interviewees on whether they offered

any school-to-work programs. Using these data

sources, we examine the prevalence of school-towork programs from two different perspectives,

investigating the kinds of schools offering such

programs and the students participating in them.

These data offer several attractive features for

our study. First, the two surveys asked about a

number of different types of school-to-work

Data from the 1996 School Administrator's Survey show

that three-fifths of U.S. high schools offer school-to-work

programs, while data from the 1997 National Longitudinal Survey

show that nearly two-fifths of students participate in such programs;

also, public high school students and those who work are more

likely to participate in school-to-work programs

Mary Joyce is an

economist formerly

with the Bureau of

Labor Statistics. David

Neumark is a professor of economics at

Michigan State

University and a

research affiliate at

the National Bureau

of Economic

Research.
Monthly Labor Review August 2001 39

programs, which allows us to analyze both work-based activities and school-based activities. Second, both surveys

asked about the same programs and used similar definitions.

Third, responses for the schools in the SAS96 can be linked

to those for individuals in the NLSY97. Finally, the surveys

collected extensive information on the characteristics of the

schools and the youths, thus allowing researchers to examine the characteristics of the high schools that offer schoolto-work programs as well as the characteristics of the students who participate in them. Ultimately, these data should

become an excellent source for studying the effectiveness

of school-to-work programs in helping students settle into

their careers; currently, however, the available data do not

support this line of inquiry.4

Data

1996 School Administrator’s Survey (SAS96). The National

School-to-Work Office sponsored a supplemental data collection effort within the NLSY97 to support their overall research interest in understanding the effectiveness of the

School-to-Work Act. As its name suggests, the SAS96 collects administrative data directly from the schools on the extent to which they offer school-to-work programs; it also provides information on the kinds of schools offering these programs. The sample includes all schools with a 12th grade within

the primary sampling units5 of the NLSY97. The survey asked

questions on school policy generally and on school-to-work

programs in particular, as well as the characteristics of students, teachers, and administrators. The SAS96 questionnaire

was mailed to 7,985 schools in September 1996. Of these

schools, 595 were excluded because they no longer existed

or because they did not have a 12th grade. Of the 7,390 remaining schools, the response rate was about 72 percent.6

Table 1 provides descriptive statistics on the 5,253

schools used in the analysis. We focus on characteristics of

the school that are related to the quality of the school, as

well as characteristics that indicate something about the socioeconomic status of the school’s student population.

These characteristics include the following: whether the

school is private or public; school size; school location; the

graduation rate at the school; the percentage of the school’s

graduates that enroll in a 4-year college; the racial and ethnic composition of the students; and whether or not the

school offered a school breakfast program, Title I services,7

or a dropout prevention program.

Among schools with a 12th grade, 74 percent are public

and 26 percent are private.8 Because public schools tend to

be larger than private schools, we defined school-size variables separately for public and private schools. For example, a

“small” public school is defined as one with fewer than 750

students, whereas a small private school is one with fewer

Table 1. Descriptive statistics on SAS96 sample of schools

 with 12th grade

 Weighted

 percentage

 Total .................................. 5,253 100.0

.............................................................

Type: ....................................................

Public ................................................. 3,401 73.9

Private................................................ 1,852 26.1

.............................................................

 Size ...............................

Public: ..................................................

Small (fewer than 750 students) ........ 1,680 72.2

Medium (750 to 1,500 students) ........ 1,295 22.6

Large (more than 1,500 students) ...... 426 5.2

.............................................................

Private: ................................................

Small (fewer than 100 students) ........ 818 53.3

Medium (100 to 300 students) ........... 624 34.6

Large (more than 300 students) ......... 410 12.1

.............................................................

 Location ........................

Urban ................................................... 1,765 20.8

Suburban .............................................. 2,822 44.4

Rural ..................................................... 571 33.2

 High school graduates ............

Graduation rates by quartile: ..........................

1st quartile (less than 85 percent) ..... 1,574 29.1

2nd quartile (86 to 94 percent) ........... 1,066 22.8

3rd quartile (94.8 to 97 percent) ......... 1,016 26.6

4th quartile (98 percent or more) ........ 826 21.5

.............................................................

Percent of graduates who

 attend 4-year college: .........................

1st quartile (less than 30 percent) ..... 1,073 29.3

2nd quartile (31 to 44 percent) ........... 702 21.0

3rd quartile (45 to 67 percent) ............ 1,133 24.9

4th quartile (68 percent or more) ........ 1,584 24.8

 Student body .......................

Black:

Less than 25 percent ......................... 3,633 83.3

25 to 75 percent ................................. 696 12.4

More than 75 percent ......................... 265 4.4

.............................................................

Hispanic: ..............................................

Less than 25 percent ......................... 3,457 89.8

25 to 75 percent ................................. 709 9.1

More than 75 percent ......................... 166 1.1

.............................................................

 School breakfast program .........

Yes ....................................................... 2,521 52.3

No ......................................................... 2,732 47.7

.............................................................

 Title I .........................

Yes ....................................................... 1,763 43.1

No ......................................................... 3,490 56.9

 Dropout prevention program

Yes ....................................................... 2,028 42.5

No ........................................................ 3,225 57.5

Note: Missing information on a particular characteristic will result in

numbers (Ns) that do not add up to 5,253. Due to bunching, the percent in

each quartile does not necessarily equal 25 percent.

Characteristic Unweighted N
40 Monthly Labor Review August 2001

School-to-Work Programs

Table 2. Descriptive statistics on NLSY97 sample of youths

 in 9th grade or higher in 1997

 Weighted

 percentage

 Total ................................................ 4,484 100.0

.........................................................

 Sex ...........................

Male ...................................................... 2,213 50.4

Female ................................................. 2,271 49.6

 Grade level ......................

 9th ...................................................... 1,925 41.5

10th ...................................................... 1,635 36.3

11th ...................................................... 850 20.3

12th or higher ....................................... 74 1.9

 Race ..........................

White .................................................... 2,625 72.4

Black .................................................... 1,176 15.3

Other .................................................... 643 11.5

Unknown ............................................... 40 0.8

 Ethnicity .........................

Hispanic ................................................ 935 13.0

Non-Hispanic ....................................... 3,537 87.0

.............................................................

 Household income ............

1st quartile: Less than $26,000 .......... 1,002 25.1

2nd quartile: $26,001 to $45,015 ........ 774 24.9

3rd quartile: $45,016 to $70,002 ......... 689 25.0

4th quartile: $70,003 or more .............. 665 25.0

.............................................................

 Biological mother's education

Less than high school .......................... 710 11.7

GED ...................................................... 227 5.0

High school graduate ........................... 1,413 32.6

Some college, no degree ...................... 641 15.1

Associates degree ............................... 388 9.4

College graduate .................................. 1,059 26.3

 School type ...................

Public ................................................... 4,013 90.2

Private .................................................. 276 6.9

Other .................................................... 158 2.9

.............................................................

 Location .....................

Urban ................................................... 2,631 54.4

Rural ..................................................... 1,853 45.6

 GPA in 8th grade .................

Low (Cs and/or Ds) ............................... 469 9.9

Medium (Cs and/or Bs) ......................... 2,359 50.2

High (As and/or Bs) ............................. 1,656 39.9

.............................................................

 Employment status last week ....

Working ................................................ 1279 32.5

Not working ........................................... 3205 67.5

 College expectations .............

0 percent chance ................................. 164 5.3

1 to 33 percent chance ........................ 297 8.2

34 to 66 percent chance ...................... 628 17.7

More than 66 percent chance .............. 2,250 68.9

.............................................................

 Course of study in high school ....

General ................................................. 2,593 56.0

Vocational, technical, or business ........ 500 10.4

College prep ......................................... 1,391 33.6

Note: Missing information on a particular characteristic will result in

numbers (Ns) that do not add up to 4,484. Due to bunching, the percent in

each quartile does not necessarily equal 25 percent.

than 100 students. The majority of both public and private

schools fall into the smallest size categories.

Among the schools in our study, 44 percent were in suburban areas, 21 percent were in urban areas, and 33 percent were

in rural areas. In addition, only 4 percent of schools reported

that 75 percent or more of their student body was black, and

only 1 percent reported that 75 percent or more of their student body was Hispanic. A sizable number of schools (43 to

52 percent) have school breakfast programs, receive Title I

funding, or have a dropout prevention program.

The National Longitudinal Survey of Youth, 1997 (NLSY97).

The first round of the NLSY97 was administered in 1997 to a

nationally representative sample of 8,984 young men and

women who were ages 12 to 16 as of December 31, 1996. The

survey was administered through personal interviews with

the youths and one of their parents, and it gathered extensive

information on the youths’ labor market behavior, education

and training, family and community background, as well as

important life events such as marriage or the birth a child.

Through annual follow-up interviews, the NLSY97 will continue to track these youths as they make the transition from

school to the world of work.

In the 1997 interview, youths who had attended the 9th grade

or higher were asked a number of questions about participation in school programs designed to help them prepare for the

world of work. Of the nearly 9,000 respondents, roughly half

were asked the school-to-work questions.9 The present analysis is restricted to these respondents, and table 2 provides some

basic descriptive information on the group. The first column

of table 2 provides the number of respondents with a particular

characteristic, and the second column provides the weighted

percentage that those respondents represent in the national

population of youths born between 1980 and 1984.

The sample contains roughly equal numbers of girls and

boys. Given the ages of the NLSY97 cohort, however, the majority of the high school respondents were in either the 9th or

10th grades in 1997. Only 74 respondents were in the 12th

grade or higher. To the extent that participation in school-towork programs is greater in the upper grades of high school,

which we suspect is likely, our estimates on overall participation from the NLSY97 would underestimate school-to-work

participation in high school.10 While table 1 showed that almost three-quarters of the schools are public, table 2 shows

that more than 90 percent of youths in 9th grade or higher attended public schools, again reflecting the fact that public

schools tend to be larger than private schools.

The variables listed in table 2 are youth characteristics that

we conjectured might be related to participation in school-towork programs. These characteristics can be divided into two

groups. The first set consists of characteristics related to socioeconomic status and is aimed at assessing the extent to

Characteristic Unweighted N
Monthly Labor Review August 2001 41

which disadvantaged youths are targeted for school-to-work

programs. These characteristics include gender, race, ethnicity,

household income, education level of the youth’s biological

mother, whether the youth attends a public or private school,

and whether the youth lives in an urban or rural location. The

second set includes other characteristics that are related to the

youth’s work or school performance and are aimed at investigating what kinds of students tend to participate in these programs. These include academic performance in 8th grade,

whether or not the youth is currently working, his or her expectations for completing college, and the course of study the

youth is pursuing in high school.

Due to missing information, data on some of these youth

characteristics are not available for all 4,484 respondents who

were asked the questions about school-to-work programs.11 For

example, household income is missing for more than 1,300 youths

in our analysis sample. There are two reasons for the high rate of

missing data on income: First, respondents often refuse to answer questions about their income; second, the income information was collected in a separate interview with one of the youth’s

parents and not all parents provided an interview.

School-to-work programs

Under the guidance of the National School-to-Work Office,

a limited number of school-to-work programs were chosen

for inclusion in both the SAS96 and the NLSY97 questionnaires: internship/apprenticeship programs (asked about

separately in SAS96, but combined in the NLSY97), job shadowing, mentoring, school-sponsored enterprise, career

major, and cooperative education. The definitions given to

respondents in the two surveys are similar but not identical.

(See Appendix 1.)

Although the two surveys ask about the same programs,

the students and the school administrators may not interpret

the questions in exactly the same way. For example, a student

who has received some career counseling may incorrectly respond that they had participated in a “career major” program,

whereas a school administrator, who may have read the definition more closely, probably would not categorize career

counseling as a career major program.

Given that the schools in the SAS96 were selected from the

primary sampling units’s where the NLSY97 youths live, we

are able to match the NLSY97 youths with the high schools

that they attend to examine the consistency in reporting of

school-to-work programs between youths and schools. If the

school reports offering a program and the student does not

report participating, then no inconsistency need exist, since

some students may not participate. On the other hand, if a

school reports not offering a particular program and the student reports participating in this program, then there is a potential inconsistency.12

Comparison of participation rates. Table 3 shows participation rates in school-to-work programs for four different groups of youths who have attended 9th grade or higher:

all youths, youths in schools that reported having the program, youths in schools that reported no corresponding program, and youths in schools that did not participate in the

SAS96.

We find the results in Table 3 troubling because the participation rates among youths in schools with a particular program are very similar to those of youths in schools not offering the program. It is not clear whether the schools or the

youths are incorrectly reporting. One problem with the school

survey data is the substantial non-response to individual

questions about school-to-work programs—roughly 12 to 18

percent of administrators did not respond to individual questions on whether or not the school offered a particular program. In defining whether a school offered a program in table

3, we treated nonresponses as “no” responses. For instance,

if a school administrator did not respond to the question on whether

the school offered an apprenticeship program, then it was assumed

that the school did not have the program. Because this approach

could result in misclassifying a school as not offering a program

when in fact it did (but just failed to respond), we recalculated table

3 treating nonresponses to a particular program as nonrespondents

(that is, we moved them to the “not surveyed or not responding”

column of table 3). This reduced the discrepancy slightly, but by no

means eliminated it. Another possible explanation for the inconsistency between school and youth reports is misclassification on

the part of the youths. It may be that youths participated in schoolto-work programs, but because they did not fully understand the

Table 3. Participation rates in school-to-work programs

 by school reports

Participation rates of youths

attending 9th grade or higher

Youths in Youths in Youths in

schools schools not surveyed

reporting reporting schools

program no program or not

responding

Any school- or work-

 based activity .............. 38.3 38.5 36.4 38.7

Any work-based activity . 24.2 26.1 23.7 22.4

 Job shadowing ............. 12.6 15.1 12.1 11.5

 School-sponsored

 enterprise .................. 9.1 13.5 8.7 8.3

Mentoring ........................ 4.8 5.9 4.7 4.3

 Apprenticeship/

internship .................... 4.3 4.6 2.9 5.9

Any school-based

activity.......................... 24.9 25.1 21.0 26.6

 Career major ............... 18.1 19.6 16.6 19.9

 Tech prep ................... 7.6 7.4 6.5 8.9

Cooperative

education .................. 6.8 6.3 6.5 7.5

Characteristic

Total
42 Monthly Labor Review August 2001

School-to-Work Programs

definitions of the various types of programs, they misreported their

participation in them; or, they simply interpreted the definitions

differently from the school survey respondents.

Short of conducting a validation study, we have no way of

knowing the source of the reporting error. As a result, the actual levels of participation rates by youths and incidence rates

by schools should be viewed as rough estimates. However, unless reporting errors vary systematically by youth or school

characteristics, differences across groups in participation or

offering rates should be less affected by measurement error.

Incidence rates in SAS96

According to the SAS96 64.2 percent of schools with a 12th

grade offered at least one school-to-work program to their

students.13 (See table 4.) The most prevalent work-based activity offered by schools was job shadowing, with nearly 29

percent of schools offering such programs. Job shadowing

was followed by internship, mentoring, apprenticeship, and

school-sponsored enterprise programs, with incidence rates

for these programs ranging from 13 to 17 percent. In 1996,

school-based activities were more commonly offered by

schools than were work-based activities. Technical preparatory and cooperative education programs were the most common school-based activities and were offered by approximately 33 percent of schools. Career major programs were less

prevalent, with 13.2 percent of schools offering them.

Next, we examine the extent to which schools offer more

than one of these school-to-work programs. While 64 percent

of schools offered at least one program, 26 percent offered

three or more programs, and about 9 percent offered five or

more programs. (See table 5.) About 22 percent of schools

offered only one program, while 31 percent of schools offered

at least one work-based and one school-based activity.

Table 6 shows the proportion of schools offering various

school-to-work programs by characteristics of the school and

its student body. In the discussion that follows, we only mention differences in incidence rates that were found to be statistically significant.14 In general, private schools have much

smaller incidence rates for school-to-work programs. Only 24

percent of private schools offered at least one school-to-work

program in 1996, compared with 78 percent of public schools.

Incidence rates for each individual school-to-work program

also were considerably lower among private schools than

public schools. Among public schools, the percent of schools

providing any school-to-work programs was highest among

medium-size schools (750 to 1,500 students). This size pattern

among public schools also holds for most of the individual

school-to-work programs. Among private schools, the largest schools (i.e., schools with more than 300 students) were

more likely to offer any school-to-work programs. However,

this size pattern does not hold consistently for all of the various school-to-work programs.

In 1996, a higher percentage of suburban schools offered

school-to-work programs than did urban or rural schools. This

was particularly true for apprenticeship, school-sponsored

enterprise, cooperative education, and technical preperatory

programs. School-to-work programs were considerably less

prevalent in schools with high graduation rates and a high

percentage of graduates who go on to attend 4-year colleges.

Table 6 shows that schools from which 98 percent or more of

the students graduate had incidence rates for any school-towork programs of 43 percent compared with about 70 percent

for schools with lower graduation rates. We found similar differences between schools in which 68 percent or more of the

students went on to attend 4-year colleges and schools with

Table 4. Percentage of schools with a 12th grade offering school-to-work programs in 1996 (SAS96)

Percent

 Percentage of schools

in 1996 that offered

Any school- or work-based activity ........... 64.2

..................................................................

Any work-based activity ............................ 44.9

 Job shadowing ........................................ 28.7

 Internship ................................................ 16.6

 Mentoring ................................................ 15.1

 Apprenticeship ........................................ 13.9

 School-sponsored enterprise .................. 12.7

..................................................................

Any school-based activity ......................... 50.4

 Cooperative education ............................ 32.5

 Tech prep ................................................ 33.2

 Career major ............................................ 13.2

 Activity

Table 5. Co-existence of selected school-based and

 work-based activities in school with 12th grade

SAS96

Percentage of schools

 in 1996 that offered:

 Total activities

 At least 1 .................................................... 64.2

 At least 2 .................................................... 42.6

 At least 3 .................................................... 26.0

 At least 4 .................................................... 15.2

 At least 5 .................................................... 9.1

......................................................................

 Work-based activities .................

 At least 1 .................................................... 44.9

 At least 2 .................................................... 23.3

 At least 3 .................................................... 11.6

......................................................................

 School-based activities ................

 At least 1 .................................................... 50.4

 At least 2 .................................................... 22.7

 At least 3 .................................................... 5.7

 Exactly one school-to-work activity .... 21.6

 At least one work-based and one-school

based activity ............................................ 31.2

 Activity
Monthly Labor Review August 2001 43

Table 6. Prevalence of selected work- or school-based activities by school characteristics

 Percentage of schools

Work-based activities School-based activities

Apprentice- Job Career Tech

ship shadowing major prep

 Total ......................................... 64.2 13.9 16.6 28.7 15.1 12.7 13.2 32.5 33.2

........................................................

 Type ........................

Public .............................................. 78.3 17.8 20.1 36.1 19.2 15.0 17.0 42.1 43.4

Private ............................................. 24.2 3.1 6.9 7.9 3.7 6.0 2.3 5.3 4.3

........................................................

 Size .......................

Public: .............................................

 Small ............................................. 75.3 16.0 16.4 34.3 15.6 12.3 14.8 36.1 40.3

 Medium .......................................... 87.3 23.2 30.0 43.4 29.6 23.2 22.8 57.8 54.7

 Large ............................................. 82.1 18.4 28.1 30.5 23.9 18.2 23.7 57.3 38.1

........................................................

Private: ...........................................

 Small ............................................. 22.3 5.0 8.3 5.9 4.6 5.1 2.4 5.8 2.6

 Medium .......................................... 24.6 .7 5.6 9.0 3.0 8.0 1.8 3.8 5.4

 Large ............................................. 31.2 1.5 4.6 13.4 1.7 4.3 3.8 7.6 8.6

 Location ....................

Urban ............................................... 57.5 12.6 20.4 26.9 17.5 13.7 13.7 30.6 26.7

Suburban ......................................... 67.4 16.2 18.9 29.5 18.4 16.0 14.3 36.2 40.7

Rural ................................................ 64.2 10.9 11.1 29.6 9.6 7.2 11.6 30.1 28.0

........................................................

 Graduation rates quartile ......

1st quartile (less than 85 percent) .. 67.9 14.4 20.0 31.8 23.9 15.5 20.4 35.3 37.2

2nd quartile (86 to 94 percent) ........ 71.6 17.3 18.6 33.4 13.1 14.1 11.2 45.3 42.9

3rd quartile (94.8 to 97 percent) ...... 72.3 14.2 18.7 40.3 14.7 15.3 12.8 28.9 38.5

4th quartile (more than 98 percent) . 42.5 7.9 7.3 10.3 7.3 4.4 7.1 18.8 14.7

........................................................

 Percentage of graduates who

 attend 4-year college .......

1st quartile (less than 30 percent) .. 70.3 10.8 15.9 30.8 15.9 14.8 16.2 33.9 35.7

2nd quartile (31 to 44 percent) ........ 76.7 23.0 23.6 45.7 26.9 20.3 15.0 47.0 44.1

3rd quartile (45 to 67 percent) ......... 74.6 18.3 22.0 35.5 17.1 13.4 15.2 35.2 44.6

4th quartile (more than 68 percent) . 42.5 5.7 11.0 14.0 6.6 5.8 3.9 15.9 18.2

Black: ..............................................

 Less than 25 percent .................... 67.0 14.5 16.3 32.4 15.6 14.0 11.2 34.0 37.6

 25 to 75 percent ............................ 72.8 17.6 22.8 26.6 22.0 13.1 23.4 41.8 35.6

 More than 75 percent .................... 67.3 21.8 15.9 17.5 16.7 17.2 32.2 24.1 23.4

Hispanic: .........................................

 Less than 25 percent .................... 69.8 14.8 18.1 33.3 16.3 14.6 12.1 35.0 37.4

 25 to 75 percent ............................ 69.1 10.2 17.9 24.9 19.7 13.3 28.4 39.0 34.3

 More than 75 percent .................... 67.6 18.1 24.1 22.7 22.0 13.9 26.9 39.4 41.4

 School breakfast

Yes .................................................. 78.2 17.3 20.5 33.4 18.4 14.7 18.3 41.4 40.6

No .................................................... 48.8 10.2 12.3 23.6 11.5 10.5 7.6 22.7 25.1

........................................................

 Title I .........................

Yes .................................................. 68.1 11.1 15.4 30.3 13.5 10.5 14.4 32.7 34.6

No .................................................... 61.2 16.1 17.5 27.5 16.4 14.3 12.3 32.3 32.1

........................................................

 Dropout prevention ...........

Yes .................................................. 73.8 18.7 21.5 35.0 19.0 15.6 18.7 43.3 38.7

No .................................................... 57.1 10.4 13.0 24.0 12.3 10.5 9.1 24.5 29.1

Internship Cooperative

Any

activities

Mentoring

Schooleducation

enterprise

 Characteristic
44 Monthly Labor Review August 2001

School-to-Work Programs

lower college enrollment rates—the schools with the higher

college enrollment rates were less likely to offer any of the

individual school-to-work programs.

As mentioned previously, the School-to-Work Act emphasizes the need to improve the transition from school to

work for all students, but especially students from disadvantaged backgrounds. To see if school-to-work programs are

more typical for such students, we next show how incidence

rates of school-to-work programs vary with our descriptors

for disadvantaged student bodies.

Schools in which 25 to 75 percent of the student body is

black had a higher incidence rate for any school-to-work programs than did schools in which less than 25 percent of the

student body is black.15 This pattern also holds for the provision of apprenticeship, internship, mentoring, career major,

and cooperative education programs. Provision of job shadowing programs, however, was highest among schools with

the lowest percentage of black students. The provision of

school-to-work programs does not appear to vary systematically by the percentage of Hispanic students. However,

schools that offer a breakfast program or a dropout prevention program were more likely to provide school-to-work programs. The results for Title I schools were mixed, with higher

incidence rates than non-Title I schools for some school-towork programs and lower incidence rates for other programs.

Regression analysis. Thus far in our analysis, we have

shown incidence rates for school-to-work programs by various characteristics of the schools. Next, we use logistic regression analysis to estimate the probability that a school

with any given set of characteristics offers school-to-work

programs. This approach allows us to see the independent

relationship of a particular characteristic with incidence rates,

while holding constant the relationship of school-to-work programs to other characteristics.

We ran logistic regressions for three different dependent

variables: provision of any school-to-work program, provision of any work-based program, and provision of any schoolbased program. Table 7 provides the odds ratios obtained

from the logistic regressions. The odds ratios indicate how

much more likely schools that differ with respect to a particular characteristic are to offer a given program, compared

with other schools.16 An odds ratio of 2 on the dummy variable for private school indicates that private schools are

twice as likely to offer school-to-work programs as public

schools. Similarly, an odds ratio of 1 indicates that they are

equally likely, and an odds ratio of 0.5 indicates that they are

half as likely. Table 7 shows that the actual odds ratio is 0.14,

indicating that private schools are roughly 1/7th as likely as

public schools to offer any school-to-work programs.

For characteristics that are continuous, such as school

size, the odds ratio tells us how much more likely schools

that are one unit away from the mean for that characteristic

are to offer a given program compared with schools at the

mean for that characteristic. Because a change of one unit

is not always the most meaningful, we divided school size

by 100 and the percentage of blacks and Hispanics by 10

before entering them into the logistic analysis. By doing

this, the resulting odds ratio for school size represents the

change attributable to a change in school size of 100, and

the odds ratio for percentage black or Hispanic represents

the change attributable to a 10 percentage-point change in

the percentage black or Hispanic.

The results from the regression analysis largely confirm

our findings from the cross-tabulation analysis—namely,

private schools are significantly less likely to provide

school-to-work programs than are public schools. They are

0.3 times as likely as public schools to provide any workbased programs and 0.1 as likely to provide any school-based

programs. School size is somewhat positively related to provision of school-to-work programs, particularly schoolbased programs. However, among private schools, large

schools are slightly less likely to offer school-to-work programs. In terms of location, urban schools are less likely

than suburban schools to provide school-based programs,

while rural schools are less likely than suburban schools to

provide work-based programs.

Schools with the highest graduation rates are less likely

than other schools to provide any school-to-work programs,

work-based programs, or school-based programs. Schools

with the highest percentage of graduates going on to 4-year

colleges also are less likely to provide any school-to-work

program, especially school-based programs.

The findings are mixed regarding whether schools with

less privileged student populations are more likely to offer

school-to-work programs. For example, the percentage of black

students at a school is not significantly related to the probability of providing school-to-work programs, whereas the

percent Hispanic is slightly negatively related to provision of

Table 7. Logistic regression results for probability

 of offering school-to-work programs

Private school .............................. 10.14 10.26 10.11

School size/100 ............................ 1

1.03 1.01 11.05

Private school size/1001 .......................... 1

.92 1.91 1.95

Urban ........................................... .97 1.12 1.84

Rural ............................................. .85 1

.78 1.03

Highest graduation rate quartile

(98 percent or more) .................. 174 1.69 1

80

Highest 4-year college

enrollment rate quartile

 (68 percent or more) .................. 1.68 93 1.48

1

 Significantly different from 1 at 5-percent level.

Characteristic

Odds ratio

Any Schoolbased Work-based
Monthly Labor Review August 2001 45

these programs. Furthermore, Title I schools are slightly less

likely than non-Title I schools to offer school-to-work programs, but schools with dropout prevention programs are

more likely to offer school-to-work programs.

Participation rates in the NLSY97

After examining how many and what types of schools offer

school-to-work programs, we now turn to the question of how

many students participate in these programs and what kinds

of students choose to participate. To examine participation in

school-to-work programs, we use data from the NLSY97. The

data show that 38 percent of youths who have attended 9th

grade or higher participated in at least one of the school-towork programs covered in the survey. (See table 8.)

Among work-based activities, job shadowing was the most

prevalent, with nearly 13 percent of youths participating in

such programs. School-sponsored enterprise ranked second

at 9.1 percent, and apprenticeships/internships and mentoring

programs followed, with participation rates of about 4 percent

each. In terms of school-based learning activities, the most

common program was career major, with 18.2 percent of youths

reporting having participated in such a program. This was

followed by technical preparatory at 7.6 percent, and cooperative education at 6.8 percent.

Table 9 shows the extent to which the youths in our study

participated in more than one school-to-work program. Participation in multiple programs is not common: only 6 percent

of youths participated in three or more programs, and fewer

than 1 percent participated in five or more programs. About 10

percent of youths who have attended the 9th grade or higher

participated in at least one work-based activity and one

school-based activity. The majority of students that participated in at least one program tended to participate in only

that program—23 percent of youths reported participating in

only one activity.

What kinds of students tend to participate in school-to-work

programs? Table 10 shows participation rates in the various

programs by characteristics of the youths that we felt may influence the quality of worker that the youth ultimately may

become when he or she joins the workforce. In the discussion

that follows, we only mention differences in participation rates

across groups that were found to be statistically significant.17

Participation in any school-to-work program does not appear to vary according to the youths’ academic performance

when in 8th grade. However, participation rates in certain programs do differ by grade point average. For example, youths

whose grades were average had higher participation rates in

apprenticeship/internship programs than youths with higher

grades. Those with higher grades were more likely to participate in job shadowing.

Youths who worked while going to school were more likely

to participate in school-to-work programs: 43 percent of the

youths who reported working during the survey week participated in at least one school-to-work program, compared with

36 percent of the youths who did not work. Participation

rates in most of the individual programs also were higher

for working youths.18

Although the School-to-Work Act emphasizes the need

to make school-to-work programs available to all students,

we wondered if college-bound youths are as likely to participate in these programs as youths who do not intend to go

to college. To address this question, we examine how parTable 8. Participation rates in school-to-work programs

NLSY97

Percentage of students in

9th grade or higher in

1997 who participated

Any school- or work-based activity ...... 38.3

.............................................................

Any work-based activity ....................... 24.2

 Job shadowing ................................... 12.6

 School-sponsored enterprise ............. 9.1

 Mentoring ........................................... 4.7

 Apprenticeship/internship ................... 4.3

.............................................................

Any school-based activity .................... 24.9

 Career major ....................................... 18.2

 Tech prep ........................................... 7.6

 Cooperative education ....................... 6.8

Table 9. Co-existence of selected school-based

 and work-based activities (NLSY97)

Total activities: ............................

 At least 1 .................................... 38.3

 At least 2 .................................... 16.1

 At least 3 .................................... 5.6

 At least 4 .................................... 1.9

 At least 5 .................................... .8

Work-based activities: ................

 At least 1 .................................... 24.2

 At least 2 .................................... 5.3

 At least 3 .................................... 1.1

School-based activities: ..............

 At least 1 .................................... 24.9

 At least 2 .................................... 6.7

 At least 3 .................................... 1.0

....................................................

Exactly one school

to work activity ............................. 22.7

....................................................

At least one work-based

and one-school based activity .... 10.3

Characteristics

Characteristics

Percentage of students

in 9th grade or higher

in 1997 who participated

in activities
46 Monthly Labor Review August 2001

School-to-Work Programs

ticipation in various school-to-work programs differs by the

youth’s self-reported expectations about completing college,

while recognizing that these expectations may be influenced

by school-to-work programs.

In the NLSY97 questionnaire, youths were asked: “What

is the percent chance that you will have a four-year college

degree by the time you turn 30?” Youths were then placed

into four groups: those who said they had zero chance of

receiving a college degree, those who said they had a 1- to

33-percent chance, those who said they had a 34- to 66-

percent chance, and those who said their chance was greater

than 66 percent. Interestingly, nearly 70 percent of the

youths fell into the latter category, and only 5 percent said

they had no expectations of completing a degree. Findings

in Table 10 show that, if anything, individuals who perceive

themselves as more likely to complete college have greater

participation in school-to-work programs.

Participation in school-to-work programs was considerably higher for youths who characterized their course of

study in high school as being a vocational, technical, or

business program as opposed to a general or college preparatory program. This strong positive relationship is not

surprising given that vocational, technical, or business-oriented programs are by their nature more focused on linking educational curricula to careers.

Table 11 shows participation rates in the various programs

by youth characteristics related to socioeconomic status.

These characteristics are of interest given the emphasis

placed in the School-to-Work Act on providing school-to-work

opportunities to youths that may ultimately become high school

dropouts or have difficulties in the workforce.

Although women’s labor force participation rates are approaching those of men, gender differences still exist in terms

of occupational choices and long-term attachment to the

workforce. Some of these differences may influence decisions

about participating in certain school-to-work programs. Overall,

participation rates in school-to-work programs are similar for

young men and women. However, high school girls are more

likely than their male counterparts to participate in a job shadowing program, and high school boys are more likely than their female counterparts to participate in a technical preparatory program.

Findings from NLSY97 indicate that black youths were more

likely than other racial groups to participate in at least one

school-to-work program. Blacks also had higher participation

rates than whites in apprenticeship or internship programs, as

well as in mentoring, career major, cooperative education, and

technical preparatory programs. Hispanics, on the other hand,

were less likely than non-Hispanics to participate in at least

one school-to-work program, with significantly lower participation in job shadowing, school-sponsored enterprise, and

career major programs.

As part of the interview with one of the youth’s parents,

information was collected on total income for the household

in which the youth resides. Using this information, we were

able to group the youths into four equal-sized income groups

to see if participation in school-to-work programs varies by

 Percentage of youths in 9th grade or higher in 1997 who participated in activities

Work-based activities School-based activities

Any Apprentice- Job School- Career Cooperative

program ship or shadowing Mentoring sponsored major education Tech prep

internship enterprise

 Total ............................ 38.3 4.3 12.6 4.8 9.1 18.1 6.8 7.6

..................................................

GPA in 8th grade ............................

Low (Cs and/or Ds) ........................ 38.8 3.8 10.4 4.2 6.9 16.1 8.3 10.0

Medium (Cs and/or Bs) .................. 38.6 5.4 11.7 5.0 9.0 19.1 6.8 7.7

High (As and/or Bs) ....................... 37.8 3.1 14.3 4.6 9.7 17.6 6.4 6.9

..................................................

 Employment status

 last week ..................

Working .......................................... 43.1 4.7 14.3 5.9 11.4 20.1 8.1 7.0

Not working .................................... 36.0 4.1 11.8 4.2 8.0 17.2 6.1 7.9

..................................................

 College expectations ......

0 percent chance ........................... 34.2 3.7 9.4 2.5 7.9 15.6 7.0 8.5

1 to 33 percent chance .................. 37.3 6.2 8.8 4.4 7.3 19.4 6.3 9.9

34 to 66 percent chance ................ 37.9 3.9 11.7 4.5 8.2 20.7 8.7 7.8

More than 66 percent chance ........ 40.5 4.9 4.2 5.6 10.1 18.8 6.6 8.0

..................................................

 Course of study in high school

General ........................................... 33.7 3.7 11.0 3.8 7.4 16.0 5.3 5.7

Vocational, technical, or business ..... 63.5 10,7 13.8 6.6 14.9 36.5 20.0 20.7

College prep ................................... 38.1 3.4 15.0 5.8 10.0 16.1 5.2 6.8

Table 10. Participation in school-to-work program by worker-related charcteristics

Characteristic
Monthly Labor Review August 2001 47

household income. Participation rates in any school-to-work

program do not vary systematically by income level. However,

some differences do exist for individual programs. Youths in

the highest income group, for example, were more likely to

participate in job shadowing programs than those in the lowest

income group. Youths in the bottom two income groups were

more likely to participate in a career major program than were

youths in the highest income group. Youths in the highest income

group also were less likely than youths in the lowest income group

to participate in cooperative education programs.

Although participation rates did not vary much by students’

college expectations, the education level of the youth’s biological mother does appear to be negatively related to participation in school-to-work programs. Youths whose mothers are

college graduates are less likely to participate in at least one

school-to-work program than are youths whose mothers are

high school graduates. This relationship also holds for participation in apprenticeship or internship, career major, cooperative education, and technical preparatory programs. Youths

whose mothers have less than a high school education are less

likely to participate in at least one school-to-work program

than are youths whose mothers are high school graduates.

Consistent with the school survey, youths attending private high schools are less likely to participate in school-towork programs than are those attending public schools. Approximately 26 percent of youths in private schools participated in at least one school-to-work program, whereas nearly

39 percent of public school students did.

Regression analysis. Similar to the strategy used in analyzing the school data, we now turn to our logistic regression

analyses that estimate the probability that a youth with any

given set of characteristics participates in school-to-work programs. This approach allows us to see the independent relationship of a particular characteristic with participation rates

while holding constant the relationship of other characteristics. We ran regressions for three different dependent variables: participation in any school to work program, participaTable 11. Participation in school-to-work programs by socioeconomic status-related characteristics

 Percentage of youths in 9th grade or higher in 1997 who participated in activities

Work-based activities School-based activities

Apprentice Schoolship or sponsored

 internship enterprise

 Sex

Male ............................... 38.4 4.3 11.0 4.6 9.0 18.9 7.3 8.7

Female .......................... 38.2 4.3 14.3 5.0 9.2 17.4 6.3 6.6

......................................

Race ..............................

White ............................. 37.7 3.9 13.2 4.2 8.6 17.4 6.2 7.2

Black ............................. 44.8 6.7 11.1 6.2 10.3 24.2 10.1 10.7

Other ............................. 34.5 4.3 10.9 6.0 10.5 15.9 5.6 6.5

......................................

 Ethnicity ...........

Hispanic ........................ 32.0 4.1 8.9 4.7 7.3 15.8 5.4 6.9

Non-Hispanic ................ 39.2 4.4 13.1 4.8 9.4 18.5 7.0 7.7

......................................

 Household income ...

Less than $26,000 ........ 39.5 6.1 11.3 3.9 8.1 20.5 8.5 7.7

$26,001 to 45,015 ......... 40.8 3.2 12.6 5.7 10.0 19.2 6.9 8.6

$45,016 to 70,002 ......... 38.8 3.6 14.1 5.4 10.2 18.0 5.5 8.7

$70,003 or more ............ 38.6 4.3 14.7 4.3 9.2 15.1 6.0 6.3

......................................

 Biological mother’s

 education .........

Less than high school ... 36.3 4.3 9.7 5.0 8.2 19.0 7.1 7.4

GED .............................................. 42.0 7.9 13.0 5.8 9.4 17.9 10.0 9.6

High school graduate .... 41.1 5.5 12.7 4.6 9.0 21.5 7.8 8.2

Some college, no degree . 41.1 2.8 14.1 5.5 11.1 17.1 6.6 9.0

Associates degree ........ 40.1 4.3 13.8 5.4 10.3 19.7 5.1 8.2

College graduate ........... 32.9 3.0 12.7 4.0 8.1 13.6 5.4 5.5

 School type .......

Public ............................ 38.5 4.0 12.8 4.7 9.0 18.6 6.5 7.5

Private .......................... 25.9 3.2 9.5 2.5 8.6 6.8 3.5 1.8

 Location ............

Urban ............................ 37.6 4.6 11.7 4.8 9.6 17.7 6.6 7.4

Rural .............................. 39.2 4.0 13.8 4.7 8.5 18.8 7.0 7.9

Any

program Characteristic

Mentoring Tech prep Job

shadowing

Career

major

Cooperative

education
48 Monthly Labor Review August 2001

School-to-Work Programs

tion in any work-based program, and participation in any

school-based program. Table 12 provides the odds ratios obtained from the logistic regressions.19

Findings from the logistic regression analysis confirm

many of the cross-tabulation results discussed previously.

Youths who work are more likely (about 1.3 times more

likely) to participate in any school-to-work program and any

work-based program. Youths who characterized their course

of study as general are less likely than college preparatory

students to participate in any school-to-work program and

any work-based program, whereas those who characterized

their course of study as vocational, technical, or businessoriented were more than twice as likely as college preparatory students to participate in any school-to-work program

and any school-based program.

In addition, black youths are more likely than white youths

to participate in any program, any work-based program, and

any school-based program. Students who attend private

schools are less likely to participate in any program, any

work-based program, and any school-based program than

were students who attend public school. Lastly, students

whose mothers are college graduates were slightly less likely

to participate in any program and any school-based program

than were students whose mothers are high school graduates.

HOW COMMON ARE SCHOOL-TO-WORK PROGRAMS? We have examined this question from two different perspectives—that

of the Nation’s high schools and that of its students. The

SAS96 data show that school-to-work programs are commonly

offered in U.S. high schools, with more than 60 percent of schools

providing at least one such program. The NLSY97 data show

that a fair number of high school students are participating in

school-to-work programs, with about 38 percent of students

reporting having participated in at least one program. However,

we have some concerns about the quality of these data because

sizable numbers of students in schools that supposedly do not

have school-to-work programs reported participating in

them.What kinds of schools offer school-to-work programs, and

what kinds of students participate in them? The data indicate

that private high schools and high schools with high graduation rates and college attendance rates are less likely to offer

school-to-work programs.

Regarding the likelihood of schools with disadvantaged

student populations offering school-to-work programs, our

findings are somewhat ambiguous—on the one hand, schools

with dropout prevention programs are more likely than other

schools to offer school-to-work programs, while on the

other hand, schools with high percentages of Hispanic

students (who are more likely to be disadvantaged) and

schools receiving Title I funding are less likely to offer

these programs. Students who work while going to school are

more likely to participate in school-to-work programs, as are

youths who reported their course of study in high school as

technical, vocational, or business-oriented. Also, blacks are more

likely than whites to participate in school-to-work programs,

whereas youths whose mothers are highly educated are less

likely to participate in these kinds of programs. 

Table 12.. Logistic regression results for probability of participating in school-to-work programs

Any Work-based School-based

 Worker-related characteristics

Low grades in 8th (Cs and/or Ds) ........................................................ 0.97 0.95 0.93

Medium grades in 8th (Cs and/or Bs) .................................................. 98 1.05 .90

Working .............................................................................................. 1

1.31 11.31 1.15

0 percent chance of completing 4-year college ................................ 1

.68 .77 .69

1 to 33 percent chance of completing 4-year college ....................... 1

.73 .72 .76

34 to 66 percent chance of completing 4-year college ..................... 1

80 73 190

General course of study in high school ............................................. 1

.81 1.75 .87

Vocational, technical, or business program ....................................... 1

2.26 1.26 12.70

...........................................................................................................

 Socio-economic status related characteristics ..........

Female ............................................................................................... .99 1.13 1

.82

Black .................................................................................................. 1

1.33 11.22 11.41

Other .................................................................................................. 1.06 1.24 .90

Hispanic .............................................................................................. .85 .76 .95

Log of annual household income ........................................................ 1.05 1.07 .99

Biological mother has less than high school degree .......................... .97 1.09 95

Biological mother has GED ............................................................................................ 1.07 1.13 .87

Biological mother has some college, no degree ................................. 1.10 1.21 .90

Biological mother has associates degree ........................................... .99 1.03 .99

Biological mother has college degree ................................................. 1.97 1.00 1.93

Private school .................................................................................... 1

.55 1.73 1.36

Other type of school.......................................................................... 1.36 1.18 1

1.68

Urban .................................................................................................. .97 1.03 .90

1

 Significantly different from 1 at 5-percent level.

Characteristic Odds ratio
Monthly Labor Review August 2001 49

The views expressed in this article are those of the authors and do

not necessarily reflect the views of the U.S. Department of Labor.

1

 The Act called for approximately $300 million to be appropriated for fiscal year 1995, with equal amounts being available for fiscal

years 1996–99. Federal funding for school-to-work programs is scheduled to end in 2001.

2

 Concise definitions of these three components were not provided in the Act. The definitions that follow were developed by

Mathematica Policy Research, Inc., an organization that has been

involved in a large-scale study to evaluate school-to-work grants. See

The First National Survey of Local School-to-Work Partnerships: Data

Summary, August 1997.

3

 A copy of the School-to-Work Act is available on the Internet at

www.stw.ed.gov/factsht/act.htm.

4

 The NLSY97 is an annual survey that, among other things, will

interview youths while they make their transition from school to the

workforce. When the present analysis was conducted, however, data

were available from only one interview with these youths, and most of

them were still attending school. Nonetheless, for an analysis of the

effects of school-to-work programs on early youth outcomes, see

David Neumark and Mary Joyce, “Evaluating School-To-Work Programs Using the New NLSY,” Working Paper 7719 (Cambridge, MA,

National Bureau of Economic Research, May 2000).

5

 Primary sampling units are geographical constructs consisting of

either a metropolitan area or a county.

6

 Or 5,295 responses out of 7,390. Among the respondents, another 42 failed to answer any of the first 11 questions in the schoolto-work section and thus were dropped from the analysis.

7

 “Title I” is short for “Part A of Title I of the Improving

America’s Schools Act of 1994, Reauthorization of the Elementary

and Secondary Education Act of 1965.” Title I is the largest Federal

aid program for our Nation’s schools and is aimed at providing educational services to children who are the furthest from meeting the

standards that each State has set for all children.

8

 Throughout this article, all estimates of means, proportions, and

percentages are sample-weighted. The logistic regression estimates

that appear later are not weighted.

9

 Or 4,484 out of 8,984. Actually, 4,489 were asked the school-towork questions, but 5 were dropped from the analysis due to missing or

ambiguous information on their current grade level.

10 Clearly, we will be able to examine this issue when data from later

waves of the survey are available.

11 To determine the number of respondents for which information

on a given characteristic is missing, simply add up the unweighted

numbers in the first column of table 2 and subtract the resulting sum

from 4,484.

12 There are, however, instances where this may be valid. In particular, in the NLSY97, the youth was asked whether they “ever”

participated in these programs and not whether they participated in

the programs at their current school, so it is possible that the youth

could have participated in the program at another school or through

an another organization (i.e. church, business group, or civic organization). However, we suspect that this is at most a minor part of the

problem, as the inconsistencies appear almost as severe for schoolbased as for work-based programs.

13 As mentioned previously, a nonresponse to the question on

whether the school offered a particular program was treated as a “no”

response. To the extent that this is not the case, the percent of

schools estimated to have these programs will be underestimated.

14 That is, we conducted a statistical test that incorporated the

standard error associated with each estimate and found that the hypothesis that the two estimates are equal could be rejected at the 5-

percent significance level.

15 The incidence rate for schools in which 25 to 75 percent of the

student body is black also was larger than the incidence rate for schools

in which more than 75 percent of the student body is black; however,

this difference, while similar in magnitude to the difference mentioned in the text, was not statistically significant.

16 Note that the odds ratios on a discrete variable should be interpreted relative to the excluded category. The excluded categories in

Table 7 are public schools, schools in suburban locations, schools with

graduation rates in quartiles 1 to 3, schools with college enrollment in

quartiles 1 to 3, schools without breakfast programs, schools without

Title I funding, and schools without dropout prevention programs.

17 Meaning that we conducted statistical tests incorporating the

standard errors associated with each estimate and found that the hypothesis that the two estimates are equal could be rejected at the 5-

percent significance level.

18 We also examined the relationship between school-to-work programs and two alternative measures of working that may signal a different level of attachment to the labor force than holding a job during the

survey week. The first was an indicator variable for whether or not the

youth worked for an employer at any time during the 1996–97 school

year or following summer. The second was an indicator variable for

whether or not the youth worked for an employer during the 1996–97

school year. The results using the first work variable were very similar to

those discussed in the text. The second work variable also was positively

related to participation in school-to-work programs, but the association

was not statistically significant.

19 The excluded categories in Table 12 are youths whose grades in 8th

grade were in the “A” to “B” range, youths not working, youths who said

their chance of completing college was greater than 66 percent, youths

in college preparatory course of study, male youths, nonblack and nonHispanic youths, youths whose biological mother has a high school education, youths in public schools, and youths in rural areas.

NOTES

Appendix: Definitions of school-to-work programs in NLSY97 and SAS96

The NLSY97 interviewers were instructed to show the respondents a card with the school-to-work programs and their definitions. The interviewers then asked, “Here is a list of some

of the kinds of programs schools offer to help students prepare for the world of work. Have you ever participated in any

of these programs through your school?” The following is

the list of programs and their definitions (listed in the order in

which they were asked):

• Career major program, which is a defined sequence of

courses based upon an occupational goal;

• Job shadowing, which is to spend time following workers

at a work site;

• Mentoring, which involves being matched with an individual in an occupation;

• Cooperative education, which combines academic and
50 Monthly Labor Review August 2001

School-to-Work Programs

vocational studies with a job in a related field;

• School-sponsored enterprise, which involves the production of goods or services by students for sale to or use

by others;

• Tech prep, which is a planned program of study with a

defined career focus that links secondary and post-secondary education;

• Internship or apprenticeship, which involves working for

an employer to learn about a particular occupation or

industry.

The SAS96 was administered by a paper questionnaire that

was filled out by school administrators and mailed back to

the National Opinion Research Center. The specific schoolto-work programs were asked about in a grid-style questionnaire with each column pertaining to a different program.

The grid was preceded by the following instructions and definitions of terms:

The questions on the following pages are about work-based

and career-oriented activities offered at your school. Please

refer to the glossary that follows for definitions of activities and terms referenced in this section.

• Apprenticeship: Typically, multiyear programs that

combine school- and work-based learning in specific

occupational areas or occupational clusters and are designed to lead directly into either a related postsecondary

program, entry-level job, or registered apprenticeship program. May or may not include paid work experiences.

• Career major: A coherent sequence of courses based upon

an occupational goal.

• Cooperative education: A method of instruction whereby

students alternate or parallel their academic and vocational studies with a job in a related field. May or may not

include paid work experiences.

• Internship: For a specified period of time, students work

for an employer to learn about a particular industry or

occupation. Students’ workplace activities may include

special projects, a sample of tasks from different jobs, or

tasks from a single occupation. May or may not include

paid work experiences.

• Job shadowing: Typically as part of career exploration

activities in early high school, a student follows an employee for one or more days to learn about a particular

occupation or industry. Job shadowing is intended to

help students hone their career objectives and select a

career major for the latter part of high school.

• Mentoring: Pairing a student with an employee over an

extended period of time during which the employee helps

the student master certain skills and knowledge the employee possesses, models workplace behavior, challenges the student to perform well, and assesses the

student’s performance. Mentoring may be combined with

other work-based learning activities, such as internships

or on-the-job training.

• School-sponsored enterprise: The production of goods

or services by students for sale to or use by others.

School-sponsored enterprises typically involve students

in the management of the project. Enterprises may be

undertaken on or off the school site.

• Tech prep: A planned program of study with a defined

career focus that links secondary and post-secondary

education.