STEM Occupational Intentions

Stability and Change Through High School

STATS IN BRIEF

June 2020

NCES 2020-167

U.S. DEPARTMENT OF EDUCATION

A Publication of the National Center for Education Statistics at IES

AUTHORS

Laura Holian

Emily Kelly

AnLar, LLC

PROJECT OFFICER

Elise Christopher

National Center for Education Statistics

Statistics in Brief publications present descriptive data 

in tabular formats to provide useful information to a 

broad audience, including members of the general public. 

They address simple and topical issues and questions. 

They do not investigate more complex hypotheses, 

account for interrelationships among variables, or 

support causal inferences. We encourage readers who 

are interested in more complex questions and in-depth 

analysis to explore other National Center for Education 

Statistics (NCES) resources, including publications, online 

data tools, and public- and restricted-use datasets. See 

nces.ed.gov and references noted in the body of this 

document for more information.

Actual and projected growth

in the science, technology, 

engineering, and mathematics 

(STEM) economy has led to an 

emphasis on STEM education as a 

strategy for increasing the supply of 

STEM workers (Atkinson and Mayo 

2010). Between 2005 and 2015, 

employment in STEM occupations 

grew faster than in non-STEM 

occupations. In 2015, approximately 

6 percent of all U.S. workers were in 

STEM occupations (Noonan 2017). 

Additionally, job openings in STEM 

and health care are projected to 

grow the fastest among occupational 

clusters (Carnevale, Smith, and 

Strohl 2013). 

Because of the anticipated 

demand for STEM occupations, 

researchers and policymakers 

have been studying and trying 

to address attrition from STEM 

fields as students move through 

the education pipeline (Metcalf 

2010). For example, 48 percent of 

bachelor’s degree students who 

declared a STEM major left their 

initially chosen STEM major within 

6 years of entering postsecondary 

education (Chen 2013). Attrition from 

STEM majors at the postsecondary 

level is associated with academic 

performance, coursetaking patterns, 

and the sex and race/ethnicity of 

students (Chen 2013). To increase 

the supply of students interested in 

STEM fields at the postsecondary 

level, educators and policymakers 

have focused on increasing student 

interest and engagement in K–12 

STEM education. 

Previous reports from the U.S. 

Department of Education’s NCES 

within the Institute of Education 

Sciences have presented findings 

regarding postsecondary majors, 

STEM participation, and 2013 

change in college major (Chen 2013; 

Leu 2017). While such postsecondary 

information is critical, information 

on high school students’ changing 

occupational intentions can 

also provide insights into their 

postsecondary choices.

Many studies have examined the 

relationship between student 

characteristics and STEM interest, 

occupations, and coursetaking. 

Using a nationally representative 

sample of over 6,000 students to 

examine how interest in STEM fields 

changed throughout high school, 

Sadler et al. (2012) found that female 

interest in STEM decreased by the 

end of high school, while male 

interest remained relatively stable. 

In general, females are less likely 

than males to be interested in a 

STEM major (Chen 2009; Moakler 

and Kim 2014). Family members 

can influence students’ academic 

and occupational pursuits (Oymack 

2018). For example, having at least 

one parent in a STEM occupation 

is related to students’ STEM career 

aspirations (Holmes et al. 2017). 

Additionally, parent attitudes during 

students’ high school years and 

parents’ expectations for the length 

of their children’s education are 

related to success in a STEM major in 

postsecondary education (Hinojosa 

et al. 2016). Further, exposure to 

occupations of family members may 

influence students’ expectations and 

intentions for future jobs (Hinojosa 

et al. 2016; Holmes et al. 2017).

Using data from a cohort of 2009 

high school freshmen, this brief 

presents data on occupational 

intentions of students and changes 

in intentions over the first 3 years 

of high school, as students are 

preparing to make decisions about 

postsecondary education. The brief 

includes information on student, 

family, and school-level factors 

associated with changes in STEM 

occupational intentions over time 

in high school. It also compares 
 2 

STEM coursetaking of students who 

consistently throughout high school 

intended later to be employed in 

a STEM field, students who never 

intended to be employed in a STEM 

field, and students who changed 

intentions during high school. This 

brief complements other studies 

by NCES that examine recruitment 

and retention of students in STEM 

fields during and after college (Chen 

2013). It builds on the work of Mangu 

et al. (2015) who used the NCES 

High School Longitudinal Study of 

2009 (HSLS:09) baseline and first 

follow-up data on students’ declared 

occupational intentions in STEM 

fields to classify them as Intenders, 

Not intenders, Newcomers, or 

Leavers. Mangu et al.’s definition of 

STEM included health occupations. 

The definition of STEM fields used in 

this brief does not include health or 

health sciences.

While the relationship between 

interest and intention for future 

careers and student, family, and 

school factors is complex, this report 

provides only simple descriptive 

statistics. It does not investigate more 

complex hypotheses, account for 

interrelationships among variables, 

or support causal inferences. The 

analyses are limited to considering 

one factor at a time, rather than 

looking at the patterns by gender 

and race/ethnicity or the pattern by 

gender and race/ethnicity by family 

background characteristics. 

Data, Methods, and 

Structure of the Report

This Statistics in Brief presents data 

from the NCES HSLS:09. HSLS:09 is a 

longitudinal dataset that is nationally 

representative of high school 

freshmen in the United States in 

2009. Students who participated in 

the HSLS:09 were followed through 

2016, with intermediate survey 

follow-ups in 2012 and 2013. The 

base-year data collection in 2009 

included interviews with parents, 

students, and school staff. 

The analyses in this brief rely on 

multiple sources of information from 

HSLS:09. Student data are used to 

gauge STEM occupational intentions, 

interest in mathematics and science, 

engagement in school, academic 

performance, and coursetaking. 

Parent information is used to 

establish parents’ highest level of 

educational attainment and parent 

STEM occupation. 

Students were asked, “As things 

stand now, what is the job or 

occupation that you expect or 

plan to have at age 30?” Their 

responses were coded on the data 

file into the corresponding 6-digit 

Occupational Information Network 

(O*NET) codes and then into the 

following categories: not a STEM 

occupation; life and physical science, 

engineering, mathematics, and 

information technology occupations; 

and health occupations. Overall, 

71 percent of students (approximately 

15,000) had responses to the 

questions about job or occupational 

expectations at both time points, 

2009 and 2012. 

This brief provides information about 

the students in the fall of their ninthgrade year in 2009 and again from 

the spring of 2012, when most were 

in 11th grade. It defines STEM as life 

and physical science, engineering, 

mathematics, and information 

technology. This definition of STEM 

has been used in previous NCES 

reports. Reports using this definition 

of STEM have covered topics such 

as STEM degree outcomes, students 

who major in STEM, and attrition 

in STEM within postsecondary 

education (Chen 2009; Chen 2013; 

Hinz and Chen 2018).

Background Information

At some point in high school, 

14 percent of students expected or 

planned to have a job at age 30 that 

could be classified as STEM (figure 

1). The distribution of occupational 

intentions at age 30 was similar 

in both the 2009 and 2012 survey 

follow-up, but there were changes 

within occupational intention 

categories. Some of the students 

who reported intentions for a 

STEM occupation at age 30 in 2009 

reported intentions for an occupation 

in a field other than STEM in 2012. 

Likewise, some of the students who 

reported intentions for a job in a field 

other than STEM in 2009 reported 

intentions for a STEM occupation in 

2012. Health occupations and health 

science are considered non-STEM 

fields in this brief.

The analyses presented throughout 

the brief use the following four 

categories of STEM occupational 

FIGURE 1. Distribution of fall 2009 ninth-graders in spring 2012, by 

occupational intention at age 30 in 2009 and 2012

STEM occupational intention in either 2009 or 2012, or both

Not a STEM occupational intention in either 2009 or 2012

14%

86%

NOTE: Students wrote in their expected occupation at age 30 in both 2009 and 2012. STEM 

occupations include life and physical science, engineering, mathematics, and information 

technology. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 3 

intentions: STEM Intenders, STEM 

Newcomers, STEM Leavers, and 

Non-STEM Intenders (figure 2). 

STEM Intenders are students 

who, as high school freshmen in 

2009, expected to be in a STEM 

occupational field at age 30 and 

maintained that intention when 

surveyed again in 2012. STEM 

Intenders represent 3 percent of the 

population. STEM Intenders include 

those who changed from one STEM 

career to another within STEM.

STEM Newcomers are students 

who, as high school freshmen in 

2009, expected to be in a non-STEM 

occupational field at age 30 but in 

2012 changed their occupational 

expectation to a STEM field. STEM 

Newcomers represent 5 percent of 

the population. 

STEM Leavers are students 

who, as high school freshmen in 

2009, expected to be in a STEM 

occupational field at age 30 but in 

2012 changed their occupational 

expectation to a non-STEM field. 

STEM Leavers represent 6 percent 

of the population.

Non-STEM Intenders are students 

who, as high school freshmen 

in 2009, expected to be in an 

occupation in a field other than 

STEM, and in 2012 reported 

expectations for an occupation in a 

field other than STEM at age 30. 

Non-STEM Intenders represent 

86 percent of the population.

Thus, by spring 2012, 8 percent 

of students who were high school 

freshmen in 2009 expected to 

pursue a STEM career (i.e., STEM 

Intenders, STEM Newcomers); 

92 percent did not (i.e., STEM 

Leavers, Non-STEM Intenders). 

The comparisons highlighted in the 

text are statistically significant at 

the p < .05 level. Only statistically 

significant differences are described 

in the text of the report. No 

adjustments were made for multiple 

comparisons. For additional 

information about p values and the 

data or methods used in this study, 

see the Technical Notes at the end of 

the report. 

FIGURE 2. Distribution of fall 2009 ninth-graders in spring 2012, by 

STEM occupational intention categories

STEM

Newcomer

STEM occupational intention category

STEM

Intender

Percent

STEM

Leaver

Non-STEM

Intender

0

20

40

60

80

100

3 5 6

86

NOTE: Students wrote in their expected occupation at age 30 in both 2009 and 2012. STEM 

occupations include life and physical science, engineering, mathematics, and information 

technology. STEM Intenders include students who wrote in any STEM occupation in both 

2009 and 2012. STEM Newcomers include students who wrote in a non-STEM occupation in 

2009 and a STEM occupation in 2012. STEM Leavers include students who wrote in a STEM 

occupation in 2009 and a non-STEM occupation in 2012. Non-STEM Intenders include 

students who wrote in a non-STEM occupation in both 2009 and 2012. Students with 

missing data at either time were not included. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 4 

STUDY QUESTIONS

1 What are the student 

characteristics of 

STEM Intenders, STEM 

Newcomers, STEM 

Leavers, and NonSTEM Intenders?

2 What are the 

family and school 

characteristics of 

STEM Intenders, STEM 

Newcomers, STEM 

Leavers, and NonSTEM Intenders?

3 What are the 

similarities and 

differences in 

high school STEM 

coursetaking of STEM 

Intenders, STEM 

Newcomers, STEM 

Leavers, and NonSTEM Intenders?

Key Findings

• Among STEM Intenders, a 

higher percentage were male

(77 percent) than female

(23 percent). Among Non-STEM 

Intenders, a higher percentage 

were female (54 percent) than 

male (46 percent) (figure 3). 

• A higher percentage of STEM 

Intenders than Non-STEM 

Intenders were White (60 percent 

compared to 51 percent), and a 

lower percentage were Black 

(9 percent compared to 

14 percent) (figure 4).

• Among STEM Intenders, STEM 

Newcomers, and STEM Leavers, 

a higher percentage had a 

parent whose highest degree 

was an associate’s or bachelor’s 

degree compared to all students 

(45 percent compared to 

39 percent) (figure 5). 

• A higher percentage of STEM 

Intenders compared to NonSTEM Intenders had a parent 

with an occupation in a STEM 

field (18 percent compared to 

9 percent) (figure 6). 

• A higher percentage of STEM 

Intenders compared to 

Non-STEM Intenders took a 

mathematics course higher than 

algebra I by the end of ninth 

grade (57 percent compared to 

34 percent) (figure 7). 

• A higher percentage of STEM 

Intenders compared to NonSTEM Intenders were on an 

academic track (55 percent 

compared to 34 percent) 

(figure 8). 
 5 

1 What are the student characteristics of STEM Intenders, STEM Newcomers, STEM Leavers, and Non-STEM Intenders?

Approximately half of 2009 ninthgraders in 2012 were male and 

half were female, but 77 percent 

of STEM Intenders were male and 

23 percent were female. Similar to 

STEM Intenders, 78 percent of STEM 

Newcomers were male and 

22 percent were female (figure 3). 

While a small percentage of ninthgraders reported intentions to 

pursue STEM, there was significant 

variation by race/ethnicity (figure 4).

Approximately half of the fall 2009 

ninth-graders in spring 2012 were 

White (52 percent), 14 percent were 

Black, 22 percent were Hispanic, 

4 percent were Asian, and 9 percent 

were Other/Two or more races. 

By comparison, the racial/ethnic 

distribution of STEM Intenders was 

60 percent White, 9 percent Black, 

14 percent Hispanic, 5 percent 

Asian, and 12 percent Other/Two

or more races.

FIGURE 3. Percentage distribution of fall 2009 ninth-graders in spring 

2012 in each STEM occupational intention category, by sex

All STEM

Intender

STEM occupational intention category

STEM

Newcomer

STEM

Leaver

Non-STEM

Intender

0

20

40

60

80

100

Percent

50

50

77

23

78

22

61

39

46

54

Male Female

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 

FIGURE 4. Percentage distribution of fall 2009 ninth-graders in 

spring 2012 for each STEM occupational intention category, by student’s 

race/ethnicity

All

Percent

STEM

Intender

STEM

Newcomer 

STEM occupational intention category

STEM

Leaver

Non-STEM 

Intender

0

20

40

60

80

100

52

14

22

9

60

9

14

12

57

12

17

10

57

10

17

12

51

14

22

9

4 5 4 4 4

White Black Hispanic Asian Other/Two or more races

NOTE: Detail may not sum to 100 because of rounding. Black includes African American, 

Hispanic includes Latino, Other/Two or more races includes American Indian, Alaska Native, 

Pacific Islander, Native Hawaiian, and respondents having origins in more than one race.

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 6 

2 What are the family and school characteristics of 

STEM Intenders, STEM Newcomers, STEM Leavers, and 

Non-STEM Intenders?

Family Characteristics

For the sample, a “parent” could 

be a biological parent, adoptive 

parent, stepparent, other relative, or 

other guardian. Overall, 39 percent 

of 2009 ninth-graders in 2012 had 

a parent with an associate’s or 

bachelor’s degree, and 15 percent 

had a parent with a master’s degree 

or higher (figure 5). A higher 

percentage of STEM Intenders 

than Non-STEM Intenders had 

a parent whose highest degree 

was an associate’s or bachelor’s 

degree (45 percent compared to 

38 percent), and a higher percentage 

had a parent whose highest degree 

was a master’s degree or higher 

(25 percent compared to 14 percent). 

The percentage of students whose 

parent’s highest degree was an 

associate’s or bachelor’s degree 

was not different between STEM 

Intenders, STEM Newcomers, and 

STEM Leavers (45 percent each). 

FIGURE 5. Percentage distribution of fall 2009 ninth-graders in spring 

2012 for each STEM occupational intention category, by parent’s 

educational attainment

All

STEM occupational intention category

STEM

Intender

STEM

Newcomer 

STEM

Leaver

Non-STEM

Intender 

0

20

40

60

80

100

Percent

46

39

15

31

45

25

38

45

17

40

45

15

48

38

14

High school or less Associate’s or bachelor’s degree Master’s degree or higher

NOTE: Detail may not sum to 100 because of rounding. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 7 

This brief examines the most recent 

job or occupation of the adult in 

the student’s house acting in the 

role of parent (figure 6). Overall, 

approximately 10 percent of students 

had at least one parent in a STEM 

field when the student was in ninth 

grade. Compared to Non-STEM 

Intenders (9 percent), a higher 

percentage of STEM Intenders, STEM 

Newcomers, and STEM Leavers had 

at least one parent in a STEM field 

(18 percent, 13 percent, and 

13 percent, respectively). 

A higher percentage of STEM 

Intenders (38 percent) than STEM 

Leavers (28 percent) or Non-STEM 

Intenders (24 percent) had family 

income greater than $95,000. There 

was not a statistically significant 

difference between the percentage 

of STEM Intenders and STEM 

Newcomers whose family income 

was above $95,000 (table 1). 

School Characteristics

There was not a consistent pattern 

between school control (public 

versus private) or school urbanicity 

and students’ STEM occupational 

intentions (table A-1). For example, 

there were not statistically 

significant differences between 

public and private school students 

in the rate of STEM Intenders, STEM 

Newcomers, or STEM Leavers. 

Looking at urbanicity, a lower 

percentage of STEM Intenders 

(17 percent) attended rural schools 

compared to Non-STEM Intenders 

(23 percent) and STEM Leavers 

(26 percent). There were not 

statistically significant differences 

in rates of STEM Intenders or other 

occupational intention categories in 

schools classified as city, suburb, or 

town (table A-1). 

FIGURE 6. Percentage distribution of fall 2009 ninth-graders in 

spring 2012 for each STEM occupational intention category, by parent’s 

occupational field

STEM occupational intention category

Percent

Either parent in STEMfield Neither parent in STEM 

field

All STEM 

Intender

STEM

Newcomer

STEM

Leaver

Non-STEM

Intender

0

20

40

60

80

100

77 78

61

10

90

18

82

13

88

13

87

9

91

NOTE: Detail may not sum to 100 because of rounding. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 

Table 1. Percentage distribution of fall 2009 ninth-graders, by STEM occupational 

intention categories and total family income in 2008

Total family 

income in 2008

STEM

Intender

STEM 

Newcomer

STEM

Leaver

Non-STEM 

Intender

Less than or equal to 

$35,000 15 29 26 33

Between $35,000 

and $95,000 47 40 47 43

Greater than 

$95,000 38 31 28 24

NOTE: Detail may not sum to 100 because of rounding. Standard errors can be found in table B-1.

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for 

Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update and High School 

Transcript File.
 8 

3 What are the similarities and differences in high school 

STEM coursetaking of STEM Intenders, STEM Newcomers, 

STEM Leavers, and Non-STEM Intenders?

Which mathematics and science 

courses students take in ninth 

grade can lead them down different 

pathways. Algebra I is a prerequisite 

for higher level mathematics and 

science courses. Early or late 

completion of algebra I could lead a 

student to different college majors or 

career paths. 

A higher percentage of STEM 

Intenders than Non-STEM Intenders 

took a math course higher than 

algebra I by the end of ninth grade 

(57 percent compared to 34 percent) 

(figure 7). 

There was no difference in the 

percentage of STEM Intenders and 

Non-STEM Intenders who took either 

general or advanced science courses 

(table A-2). Advanced science courses 

include specialty courses (aerospace, 

anatomy, microbiology), advanced 

studies courses, Advanced Placement 

(AP) courses and International 

Baccalaureate (IB) courses.

Looking at completing specific 

mathematics and science courses, 

a greater percentage of STEM 

Intenders and STEM Newcomers 

took at least one credit in 

precalculus, calculus, or physics 

compared to STEM Leavers and NonSTEM Intenders (table A-2).

FIGURE 7. Percentage distribution of fall 2009 ninth-graders in spring 

2012 for each STEM occupational intention category, by student’s highest 

level of mathematics completed by the end of ninth grade

All STEM

Intender

STEM

Newcomer

STEM

Leaver

Non-STEM

Intender 

0

20

40

60

80

100

14

51

35

6

37

57

10

47

42

15

46

39

15

51

34

STEM occupational intention category

Percent

Less than algebra I Algebra I Higher than algebra I

NOTE: Details may not sum to 100 because of rounding. Courses less than algebra I include 

no math, basic math, other math, and prealgebra. Courses higher than algebra I include 

geometry, algebra II, trigonometry, other advanced math, and precalculus. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 9 

Many higher paying occupations—

both STEM and non-STEM—require 

college degrees. According to the 

National Science Board (2019), 

“S&E [science and engineering] 

occupations”—defined as life science, 

computer and mathematical science, 

physical science, social science, and 

engineering—are generally assumed 

to require at least a bachelor’s 

degree in an S&E field. Pursuing 

an academic track in high school 

can help ensure students’ access to 

postsecondary education. Students 

with interests and intentions 

outside of STEM fields may intend 

to pursue postsecondary education 

and take courses on an academic 

track. To be on an academic track, 

a student must earn four credits 

in English, three credits in math 

with one higher than algebra II, 

three credits in science with one 

higher than biology, three credits 

in social studies with one in U.S. 

or world history, and two credits 

in one foreign language. A higher 

percentage of STEM Intenders 

than Non-STEM Intenders were 

on an academic track (55 percent 

compared to 34 percent) (figure 8). 

In addition to differences between 

STEM Intenders and Non-STEM 

Intenders in courses taken and 

being on an academic track, there 

were also differences in their 

overall high school GPA scores. 

A higher percentage of STEM 

Intenders (74 percent) than STEM 

Newcomers (58 percent), STEM 

Leavers (55 percent), and Non-STEM 

Intenders (50 percent) had GPAs 

between 3.0 and 4.0 (figure 9). 

FIGURE 8. Percentage distribution of fall 2009 ninth-graders in spring 

2012 for each STEM occupational intention category, by academic track

All STEM

Intender

STEM

Newcomer

STEM

Leaver

Non-STEM

Intender 

0

20

40

60

80

100

Percent

STEM occupational intention category

Academic Not an academic track

35

65

55

45

47

53

37

63

34

66

NOTE: Students on an academic track must earn four credits in English, three credits in 

math with one higher than algebra II, three credits in science with one higher than biology, 

three credits in social studies with one in U.S. or world history, and two credits in one 

foreign language. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 

FIGURE 9. Percentage distribution of fall 2009 ninth-graders in spring 

2012 for each occupational intention category, by overall unweighted 

high school GPA

All STEM

Intender

STEM

Newcomer

STEM

Leaver

Non-STEM

Intender 

0

20

40

60

80

100

Percent

STEM occupational intention category

Lower than C’s (GPA 1.9 or less)

B’s and C’s (GPA 2.0 to 2.9)

A’s and B’s (GPA 3.0 to 4.0)

12

36

52

5

21

74

11

31

58

8

37

55

13

37

50

NOTE: Detail may not sum to 100 because of rounding. 

SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center 

for Education Statistics, High School Longitudinal Study of 2009 (HSLS:09), 2013 Update 

and High School Transcript File. 
 10 

FIND OUT MORE

For questions about content, to download this Statistics in Brief, or to view it online, 

go to

https://nces.ed.gov/pub-search/pubsinfo.asp?pubid=2020167

Readers may also be interested in the following NCES products related to topics covered in 

this Statistics in Brief:

Health and STEM Career Expectations and Science

Literacy Achievement of U.S. 15-Year-Old Students 

(NCES 2020-034). https://nces.ed.gov/pubsearch/

pubsinfo.asp?pubid=2020034. 

High School Longitudinal Study of 2009 (HSLS:09)

2013 Update and High School Transcript Study: 

A First Look at Fall 2009 Ninth-Graders in 2013

(NCES 2015-037rev). http://nces.ed.gov/pubsearch/

pubsinfo.asp?pubid=2015037rev. 

High School Longitudinal Study of 2009 (HSLS:09) First 

Follow-up: A First Look at Fall 2009 Ninth-Graders 

in 2012 (NCES 2014-360). https://nces.ed.gov/

pubs2014/2014360.pdf.

High School Longitudinal Study of 2009 (HSLS:09): A First 

Look at Fall 2009 Ninth-Graders (NCES 2011-327). 

https://nces.ed.gov/pubs2011/2011327.pdf.

Male and Female High School Students’ Expectations

for Working in a Health-Related Field 

(NCES 2020-082). https://nces.ed.gov/pubsearch/

pubinfo.asp?pubid=2020082.
 11 

Technical Notes

Survey Methodology

Starting with a cohort of students 

who were in the ninth grade in fall 

2009, HSLS:09 follows students 

throughout their high school and 

early adult years to understand their 

trajectories from the beginning of 

high school into postsecondary 

education, the workforce, and 

beyond. The estimates provided 

in this Statistics in Brief are based 

on data collected in the base year 

(fall 2009), first follow-up study 

(spring 2012), and 2013 update 

(2013) of the HSLS:09. The HSLS:09 

base year and first follow-up study 

included a student questionnaire, 

and questionnaires administered to 

students’ parents, school counselors, 

and school administrators. The 

student questionnaire collected 

information such as expectations 

and aspirations; high school 

interests; grade progression; 

and demographics and family 

background. The 2013 update 

collected information on high school 

completion and postsecondary plans. 

High school transcripts were also 

collected. The update did not include 

new information about students’ 

STEM occupational intentions.

In the base-year HSLS:09, students 

were sampled through a two-stage 

process: schools were sampled 

first, followed by students within 

schools. The target population at the 

school level was defined as regular 

public schools (including public 

charter schools) and private schools 

in the 50 states and the District of 

Columbia that provided instruction 

in both ninth and eleventh grades. 

Stratified random sampling based on 

school type (public, private-Catholic, 

private-other), geographic region 

(Northeast, Midwest, South, West), 

and geographic location of the school 

(city, suburban, town, rural) resulted 

in the identification of 1,889 eligible 

schools. A total of 944 of these 

schools participated in the study, 

resulting in a 55 percent weighted 

response rate, or 50 percent 

unweighted response rate. 

In the second stage of sampling, 

students were randomly selected 

using a stratified systematic 

sampling procedure from baseyear enrollment lists provided 

by administrative contacts at the 

school. The second-stage sampling 

strata were defined by the students’ 

race/ethnicity (White, Black, 

Hispanic, Asian, Other) specified by 

the school, yielding approximately 

26,300 sampled students (or 

about 28 students per school). The 

target population of students was 

defined to include all ninth-grade 

students who attended the studyeligible schools in the fall 2009 

term. Students who were unable 

to directly participate in the study 

because of language barriers or 

severe disabilities were retained 

in the sample, and contextual data 

were sought for them. Their ability 

to complete the study instruments 

was reassessed in the first follow-up. 

Of the 26,300 sampled students, 

all 25,200 base-year, studyeligible students were eligible to 

participate in the assessment, 

with the exception of a few cases 

in which students passed away 

or were found to not have been 

in ninth grade during the base 

year. (Two exceptions to this are 

sample members who died or were 

removed as a result of base-year 

sampling errors discovered only in 

the first follow-up; e.g., the student 

was not a ninth-grader in 2009.) 

Approximately 20,600 students 

participated in the assessment, 

resulting in a weighted studentlevel response rate of 82 percent. 

Unlike prior NCES secondary 

studies, the HSLS:09 student sample 

was not freshened to include a 

representative later-grade cohort. 

As a result, first follow-up estimates 

from the sample are associated 

only with the ninth-grade cohort 

2.5 years later and not the universe 

of students attending the eleventh 

grade in the spring of 2012. 

Two broad categories of error 

occur in estimates generated from 

surveys: sampling and nonsampling 

errors. Sampling errors occur when 

observations are based on samples 

rather than on entire populations. 

The standard error of a sample 

statistic is a measure of the variation 

due to sampling and indicates the 

precision of the statistic, that is, how 

close to the population value the 

estimated statistic is likely to be. The 

complex sampling designs used in 

HSLS:09 must be taken into account 

when calculating such variance 

estimates as standard errors. The 

variance for the estimates in this 

Statistics in Brief was calculated 

using balanced repeated replication 

to accommodate the complex 

sample design. 

Nonsampling error can be 

attributed to several sources: 

incomplete information about all 

respondents (e.g., some students 

or schools refused to participate 

or students participated but 

answered only certain items); 

differences among respondents in 

question interpretation; mistakes in 

recording or coding data; and other 

errors in collecting, processing, and 

imputing missing data. Standard 

quality-control procedures were 

followed in the HSLS:09 data 

collection process in order to 

minimize nonsampling errors.

For more information on HSLS:09 

methodology, see the following: 

High School Longitudinal Study of 

2009 (HSLS:09): Base-Year Data File 

Documentation (NCES 2011-328). 

https://nces.ed.gov/pubsearch/

pubsinfo.asp?pubid=2011328.

High School Longitudinal Study of 

2009 (HSLS:09) Base Year to First 

Follow-Up Data File Documentation 

(NCES 2014-361). https://nces.ed.gov/

pubs2014/2014361.pdf.

High School Longitudinal Study of 

2009 (HSLS:09) 2013 Update and 

High School Transcript Data File 

Documentation (NCES 2015-036). 

https://nces.ed.gov/pubs2015/

2015036.pdf.
 12 

Response Rates, Weighting, 

and Variables Used in 

the Analysis

NCES requires that for any stage of 

data collection yielding a response 

rate below 85 percent, the data 

must be evaluated for nonresponse 

bias (Seastrom 2014). For this brief, 

this requirement pertains to unit 

response rates—the percentage of 

students completing the student 

questionnaire—and item response 

rates for each of the questionnaire 

items used in this analysis. 

The overall student response rates 

for the fall 2009, spring 2012, and 

2013 Update student questionnaires 

were 86 percent, 82 percent, and 

79 percent, respectively. The unit 

weighted response rate for students 

with response in the 2013 Update, 

base year, and first follow-up was 

62.5 percent. 

A total of 18 variables were used for 

the student base-year to first followup to 2013 Update longitudinal 

unit nonresponse bias analysis. 

These 18 variables resulted in 

67 comparisons (tests). Bias was 

detected for 41.8 percent of the 

67 tests implemented with the 

student base-year to first follow-up 

to 2013 Update longitudinal weight 

(W3W1W2STU). After applying the 

nonresponse adjustments, no bias 

was statistically significant in any of 

the 67 tests. Details are available in 

Ingels et al. 2015. Estimates in this 

brief were weighted to adjust for the 

unequal probability of selection and 

enable the production of national 

estimates. Because this brief uses 

variables from the base year, first 

follow-up, and 2013 Update, the 

student weight, W3W1W2STU, 

was used to account for base-year 

school nonresponse and student 

nonresponse in the base year, first 

follow-up, and 2013 Update. 

The variables used and weighted 

response rate are displayed in 

exhibit 1.
 13 

Exhibit 1: Variables used in this brief and response rates 

Variable label Variable name 

Nonresponse adjusted 

weighted response rate 

Student’s expected occupation at age 30: STEM code 1 in 

base year X1STU30OCC_STEM1 98 

Student’s expected occupation at age 30: STEM code 1 in 

frst follow-up  X2STU30OCC_STEM1 98 

Student’s sex  X2SEX 100 

Student’s race/ethnicity composite  X2RACE 100 

Student’s interest in mathematics course in ninth grade  X1MTHINT  96 

Student’s interest in science course in ninth grade  X1SCIINT 96 

Student’s engagement in school in ninth grade  X1SCHOOLENG 97 

Student’s fnal grade in most advanced eighth-grade 

mathematics course  S1M8GRADE  98 

Student’s fnal grade in most advanced eighth-grade 

science course S1S8GRADE 97 

Parents’/guardians’ highest level of education  X1PAREDU  83 

Parent 1’s current/most recent occupation: STEM code 1 

(subdomain) X1PAR1OCC_STEM1 83 

Parent 2’s current/most recent occupation: STEM code 1 

(subdomain) X1PAR2OCC_STEM1 83 

Total family income from all sources in 2008 X1FAMINCOME 83 

School locale (urbanicity)  X1LOCALE 100 

School control  X1CONTROL 100 

Student’s highest level of math completed by the end of 

ninth grade  X3THIMATH9 92 

Student’s highest level of science completed by the end of 

ninth grade  X3THISCI9  92 

At least one credit earned in: algebra II X3T1CREDALG2 95 

At least one credit earned in: precalculus X3T1CREDPREC 95 

At least one credit earned in: calculus X3T1CREDCALC 95 

At least one credit earned in: statistics X3T1CREDSTAT 95 

Credits earned in computer/information sciences  X3TCREDCOMPSCI 95 

At least one credit earned in: chemistry X3T1CREDCHEM 95 

At least one credit earned in: physics X3T1CREDPHYS 95 

Academic track/concentrator  X3TACADTRCK 95 

Occupational concentrator  X3TOCCUCON 95 

Overall computed GPA  X3TGPATOT  95 

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Survey, Base Year, First Follow-Up, and 

2013 Update. 
 14 

The four variables related to family 

characteristics, taken from the 

parent sample, had response rates 

below 85 percent. 

Additional detail on constructs and 

scales follow.

Occupational Intention

In the base-year and first followup surveys, students were asked 

what job they expect or plan to 

have at age 30. The jobs written 

in by students were classified into 

the corresponding Occupational 

Information Network (O*NET) 

code, and then classified into 

Not a STEM occupation; Life and 

Physical Science, Engineering, 

Mathematics, and Information 

Technology Occupations; and 

Health Occupations. In this 

brief, the analyses of STEM 

occupational intentions treated 

Health Occupations as Not a STEM 

occupation. The occupational 

intention variables used in the 

analyses were created from 

X1STU30OCC_STEM1 (base year) 

and X2STU30OCC_STEM1 (first 

follow-up). For STEM occupational 

intentions, students whose jobs 

were classified as Life and Physical 

Science, Engineering, Mathematics, 

and Information Technology 

Occupations in both X1STU30OCC_

STEM1 and X2STU30OCC_STEM1 

were coded as “STEM Intenders”; 

students whose jobs were classified 

as either Not a STEM occupation or 

Health Occupations in X1STU30OCC_

STEM1 and Life and Physical Science, 

Engineering, Mathematics, and 

Information Technology Occupations 

in X2STU30OCC_STEM1 were coded 

as “STEM Newcomers”; students 

whose jobs were classified as Life 

and Physical Science, Engineering, 

Mathematics, and Information 

Technology Occupations in 

X1STU30OCC_STEM1 and Not a 

STEM occupation or Health 

Occupations in X2STU30OCC_STEM1 

were coded as “STEM Leavers”; 

and students whose jobs were 

classified as either Not a STEM 

Occupation or Health Occupations 

in both X1STU30OCC_STEM1 and 

X2STU30OCC_STEM1 were coded as 

“Non-STEM Intenders.”

Responses that were split across 

O*NET subdomains, did not have 

a specified O*NET subdomain, or 

were uncodeable were treated as 

missing. As a result, 8 percent of 

students who provided occupational 

intentions data in both fall 2009 and 

spring 2012 were coded as missing. 

Overall, data were available for 

71 percent of respondents. Because 

of the amount of missing data from 

nonresponse (21 percent) and other 

missing data, respondents were 

compared to nonrespondents on 

their sex, race, socioeconomic 

status quintile, school locale, 

and school institutional control. 

Differences between respondents 

and nonrespondents were tested for 

statistical significance using an 

alpha of .05. Respondents did not 

differ from nonrespondents on 

these characteristics.

Interest in Science or 

Mathematics, and School 

Engagement

Interest. Students’ interest in their 

base-year mathematics and science 

courses was measured as a scale of 

six variables that asked students the 

degree to which a student enjoyed 

the subject, felt the course was a 

waste of time, rated the course as 

their favorite subject, and rated 

the course as their least favorite 

subject. The variables X1MTHINT 

and X1SCIINT are scales constructed 

through principal components 

analysis, with a mean of 0 and 

standard deviation of 1. Higher scale 

values represent greater interest. 

For the analyses in this brief, scale 

scores greater than 1 were recoded as 

high interest, scale scores between 

negative 1 and positive 1 were 

recoded as moderate interest, and 

scale scores lower than negative 1 

were recoded as low interest. 

School engagement. Students’ 

engagement in their school during 

the base year was measured as a 

scale of four variables that measured 

how often the ninth graders went 

to class without completing their 

homework, went to class without 

pencil or paper, went to class 

without books, and went to class 

late. The variable X1SCHOOLENG 

was created through principal 

factor components analysis of four 

variables and standardized to a 

mean of 0 and standard deviation 

of 1, where higher values represent 

greater engagement. For the 

analyses in this brief, scale scores 

greater than 1 were recoded as high 

school engagement, scale scores 

between negative 1 and positive 1 

were recoded as moderate school 

engagement, and scale scores lower 

than negative 1 were recoded as low 

school engagement. 

Coursetaking

Highest level. Students’ highest 

level of math and science taken by 

the end of their ninth-grade year 

was taken from their transcript 

data. Categories for highest level of 

mathematics taken in ninth grade 

included no math, basic math, 

other math, prealgebra I, algebra I, 

geometry, algebra II, trigonometry, 

other advanced math (including 

probability and statistics and other 

AP/IB math), and precalculus. 

These categories were recoded into 

less than algebra I (no math, basic 

math, other math, prealgebra I), 

algebra I, and higher than algebra I 

(geometry, algebra II, trigonometry, 

other advanced math, and 

precalculus). Categories for highest 

level of science taken in ninth grade 

included no science, general science, 

specialty science, advanced science, 

and AP/IB science. These categories 

were recoded into no science, 

general science, and advanced 

science (specialty science, advanced 

science, or AP/IB science). 

Credits earned. Transcript data 

were used to determine if at least one 

Carnegie unit of various courses was 

earned. A Carnegie unit is equivalent 

to a 1-year academic course taken 

1 period a day, 5 days a week. For 

each course, algebra I, algebra II, 

precalculus, calculus, geometry, 

statistics/probability, trigonometry, 

chemistry, physics, a student was 

coded as either yes, at least one 

credit earned, or no. 

Academic track. Being on an 

academic track is defined by both 

number of credits earned and 

specific levels attained for math, 

science, and social studies. Students 

are flagged as having been on an 
 15 

academic track if they earned at 

least four credits in English, three 

credits in math with one higher than 

algebra II, three credits in science 

with one higher than biology, three 

credits in social studies with one 

in U.S. or world history, and two in 

one foreign language. Only credits 

accrued in ninth through twelfth 

grade are included. 

Occupational concentrator. Being 

an occupational concentrator 

is defined as completing three 

credits in a particular occupational 

concentration. 

Statistical Procedures

Comparisons of proportions were 

tested using Student’s t statistic. 

Differences between estimates were 

tested against the probability of a 

Type 1 error or significance level. 

The statistical significance of each 

comparison was determined by 

calculating the Student’s t value 

for the difference between each 

pair of proportions and comparing 

the t value with published tables 

of significance levels for two-tailed 

hypothesis testing. Student’s t values 

were computed to test differences 

between independent estimates 

using the following formula:

Where E1 and E2 are the estimates to 

be compared and se1 and se2 are 

their corresponding standard errors. 

All comparisons highlighted in the 

text are statistically significant at the 

p < .05 level. 

Some tests, however, compared 

estimates from related groups (STEM 

Intenders compared to all students). 

To account for sample dependency, 

the t statistic for dependent samples 

was computed using the following 

formula,

where p is the proportion of the 

subgroup to the total group.

No adjustments were made for 

multiple comparisons. It is 

important to note that many of the 

variables examined in this report 

may be related to one another and 

to other variables not included in 

the analyses. Complex relationships 

should be fully explored and 

warrant further analysis. Readers 

are cautioned against drawing 

causal inferences based on the 

results presented.
 16 

References

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Economy: Fresh Approaches to 

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Strohl, J. (2013). Recovery: 

Job Growth and Education 

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and the Workforce.

Chen, X. (2009). Students Who 

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Education (NCES 2009-161). 

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Chen, X. (2013). STEM Attrition: 

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Hinojosa, T., Rapaport, A., Jaciw, A., 

LiCalsi, C., and Zacamy, J. (2016). 

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the Future STEM Workforce: 

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STEM Success. U.S. Department 

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Evaluation and Regional 

Assistance. 

Hinz, S., and Chen, X. (2018). 

Science, Technology, Engineering, 

and Mathematics (STEM) 

Graduates: Where are They 4 

Years After Receiving a Bachelor’s 

Degree? (NCES 2018-423). U.S. 

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Washington, DC: National 

Center for Education Statistics. 

Holmes, K., Gore, J., Smith, M., and 

Lloyd, A. (2017). An Integrated 

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Which Student and School 

Factors are Most Predictive? 

International Journal of Science 

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655–675. 

Ingels, S.J., Pratt, D.J., Herget, 

D., Bryan, M., Fritch, L.B., 

Ottem, R., Rogers, J.E., and 

Wilson, D. (2015). High School 

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and Nelson, J. (2015). 

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update.pdf. 

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 17 

APPENDIX A. DATA TABLES 

Table A-1. Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM occupational intention categories and 

student, family, and school characteristics 

Characteristics and Coursetaking All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Total 100.0 3.4 4.9 5.7 86.1 

Sex 

Male 50.2 77.2 77.9 60.7 46.5 

Female 49.8 22.8 22.1 39.4 53.5 

Race/ethnicity1 

White 52.0 59.8 56.9 57.1 51.1 

Black 13.7 8.9 12.1 10.2 14.2 

Hispanic 21.6 14.3 17.2 16.8 22.4 

Asian 3.6 5.1 3.8 4.3 3.5 

Other/Two or more races 9.1 12.0 10.1 11.7 8.7 

Interest in mathematics course in ninth grade2 

Not taking mathematics course 9.9 4.6 10.2 8.6 10.2 

Low interest 14.7 8.2 13.6 14.9 15.0 

Moderate interest 60.8 53.6 58.3 59.9 61.3 

High interest 14.6 33.6 17.9 16.7 13.5 

Interest in science course in ninth grade3 

Not taking science course 17.4 9.9 16.5 14.5 17.9 

Low interest 12.8 7.4 14.2 11.6 13.0 

Moderate interest 58.1 60.6 55.9 55.2 58.4 

High interest 11.7 22.1 13.4 18.8 10.7 

Engagement in school in ninth grade4 

Low engagement 15.9 8.9 17.9 11.6 16.3 

Moderate engagement 62.9 64.3 59.5 64.9 62.9 

High engagement 21.2 26.8 22.7 23.4 20.8 

Grade in eighth-grade mathematics course 

A 34.7 55.5 41.9 37.2 33.4 

B 38.1 29.8 34.3 39.2 38.6 

C 18.9 10.2 15.4 19.4 19.4 

D or below 8.2 4.6 8.3 4.2 8.6 

See notes at end of table. 
 18 

Table A-1. Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM occupational intention categories and 

student, family, and school characteristics—Continued 

Characteristics and Coursetaking All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Grade in eighth-grade science course 

A 38.7 65.2 48.3 46.1 36.6 

B 37.7 25.7 31.8 34.7 38.7 

C 17.8 6.6 15.3 16.1 18.5 

D or below 5.8 2.5 4.5! 3.1! 6.2 

Parents’ highest degree 

High school diploma or less 46.2 30.7 38.2 40.2 47.8 

Associate’s degree or bachelor’s degree 38.9 44.7 44.6 44.6 37.9 

Master’s degree or higher 14.9 24.6 17.2 15.2 14.3 

Either parent’s occupation in a STEM feld 

Yes 9.5 17.7 12.6 13.3 8.7 

No 90.5 82.3 87.8 86.8 91.3 

Total family income in 2008 

Less than $35,000 31.8 15.5 29.4 25.6 33.1 

Between $35,000 and $95,000 43.4 46.5 40.0 46.5 43.3 

Greater than $95,000 24.8 38.0 30.6 27.9 23.7 

School locale 

City 31.8 37.4 31.3 30.1 31.7 

Suburb 33.4 36.2 37.1 34.7 32.9 

Town 11.9 9.8 11.5 9.0 12.2 

Rural 23.0 16.7 20.2 26.3 23.3 

School control 

Public 92.9 91.4 91.5 92.1 93.0 

Private 7.1 8.6 8.5 7.9 7.0 

See notes at end of table. 
 19 

 

 

 

 

Table A-1. Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM occupational intention categories and 

student, family, and school characteristics—Continued 

! Interpret data with caution. Estimate is unstable because the standard error represents more than 30 percent of the estimate. 

1 Black includes African American, Hispanic includes Latino, Other/Two or more races includes American Indian, Alaska Native, Pacifc Islander, Native 

Hawaiian, and respondents having origins in more than one race. 

2

 Interest in mathematics was constructed from a scale of the sample member’s interest in his/her base-year math course; higher values represent greater 

interest in his/her base-year math course. The scale was created through principal components factor analysis and standardized to a mean of 0 and 

standard deviation of 1. The inputs to this scale were S1MENJOYING, S1MWASTE, S1MBORING, S1FAVSUBJ, S1LEASTSUBJ, and S1MENJOYS. Students with a 

scale score lower than -1 were classifed as low interest, students with a scale score between -1 and 1 were classifed as moderate interest, and students with a 

scale score greater than 1 were classifed as high interest. 

3

 Interest in science was constructed from a scale of the sample member’s interest in his/her base-year science course; higher values represent greater 

interest in his/her base-year science course. Variable was created through principal components factor analysis and standardized to a mean of 0 and 

standard deviation of 1. The inputs to this scale were S1SENJOYING, S1SWASTE, S1SBORING, S1FAVSUBJ, S1LEASTSUBJ, and S1SENJOYS. Students with a scale 

score lower than -1 were classifed as low interest, students with a scale score between -1 and 1 were classifed as moderate interest, and students with a scale 

score greater than 1 were classifed as high interest. 

4

 Engagement in school in ninth grade was constructed from a scale of the sample member’s school engagement; higher values represent greater school 

engagement. Variable was created through principal factor components analysis and standardized to a mean of 0 and standard deviation of 1. The inputs 

to this scale were S1NOHWDN, S1NOPAPER, S1NOBOOKS, and S1LATE. Students with a scale score lower than -1 were classifed as low engagement, 

students with a scale score between -1 and 1 were classifed as moderate engagement, and students with a scale score greater than 1 were classifed as 

high engagement. 

NOTE: Detail may not sum to 100 because of rounding. STEM Intenders are students who, as high school freshmen in 2009, expected to be in a STEM 

occupational feld at age 30 and maintained that intention when surveyed again in 2012. STEM Newcomers are students who, as high school freshmen in 

2009, expected to be in a non-STEM occupational feld at age 30 but in 2012 changed their occupational expectation to a STEM feld. STEM Leavers are 

students who, as high school freshmen in 2009, expected to be in a STEM occupational feld at age 30 but in 2012 changed to a non-STEM feld. Non-STEM 

intenders are students who did not expect to be in a STEM occupational feld at age 30 at either time point.  

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Survey, Base Year, First Follow-Up, and 

2013 Update.  
 20 

Table A-2. Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM occupational intention categories and 

high school coursetaking 

Coursetaking All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Total 100.0 3.4 4.9 5.7 86.1 

Student’s highest level of mathematics completed by end of ninth grade 

Less than algebra I 14.4 5.7 10.4 15.0 14.9 

Algebra I 50.5 37.2 47.5 46.4 51.5 

Higher than algebra I 35.1 57.0 42.1 38.6 33.6 

Student’s highest level of science taken in ninth grade1 

No science 8.9 4.2! 6.8! 6.5 9.3 

General science 86.1 90.4 88.6 89.3 85.6 

Advanced science (specialty, IB, AP) 5.0 5.5! 4.6 4.2 5.0 

Took at least one credit in algebra II 

Yes 59.4 67.4 64.0 61.0 58.7 

No 40.6 32.6 36.0 39.0 41.3 

Took at least one credit in precalculus 

Yes 27.9 49.1 42.2 29.4 26.2 

No 72.1 50.9 57.8 70.6 73.8 

Took at least one credit in calculus 

Yes 13.7 39.1 28.8 14.7 11.8 

No 86.3 60.9 71.2 85.3 88.2 

Took at least one credit in statistics 

Yes 10.1 17.7 9.9 11.9 9.6 

No 90.0 82.3 90.1 88.1 90.4 

Took at least one credit in geometry 

Yes 77.6 82.3 79.4 77.9 77.3 

No 22.4 17.7 20.6 22.1 22.7 

Took at least one credit in trigonometry 

Yes 14.2 23.3 16.5 17.0 13.6 

No 85.8 76.7 83.5 83.0 86.4 

Took at least one credit in chemistry 

Yes 63.2 82.8 67.7 69.8 61.8 

No 36.8 17.2 32.3 30.2 38.2 

See notes at end of table. 
 21 

Table A-2. Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM occupational intention categories and 

high school coursetaking—Continued 

Coursetaking All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Took at least one credit in physics 

Yes 34.0 63.5 51.2 38.0 31.6 

No 66.0 36.5 48.8 62.0 68.4 

Took at least one credit in biology 

Yes 88.0 93.6 91.7 89.3 87.5 

No 12.0 6.4 8.3 10.7 12.5 

Took at least one credit in computer science/information technology 

Yes 30.4 35.1 38.3 36.0 29.5 

No 69.6 64.9 61.7 64.0 70.5 

Took an academic track 

Yes 35.3 54.6 46.9 37.3 33.7 

No 64.7 45.4 53.1 62.7 66.3 

Overall unweighted high school GPA 

A’s and B’s (GPA 3.0 to 4.0) 51.6 73.6 58.3 54.7 50.1 

B’s and C’s (GPA 2.0 to 2.9) 36.2 21.4 31.1 36.9 37.1 

C’s and below (GPA 1.9 and below) 12.2 5.1 10.6 8.4 12.8 

! Interpret data with caution. Estimate is unstable because the standard error represents more than 30 percent of the estimate. 

1

 General science courses include courses such as earth science, life science, physical science, technological inquiry, biology, chemistry, and physics. 

Advanced science courses include specialty courses (aerospace, anatomy, microbiology), advanced studies courses, Advanced Placement (AP) courses, and 

International Baccalaureate (IB) courses. 

NOTE: Detail may not sum to 100 because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Survey, Base Year, First Follow-Up, and 

2013 Update. 
 22 

APPENDIX B. STANDARD ERROR TABLES 

Table B-1. Standard errors for table A-1: Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM 

occupational intention categories and student, family, and school characteristics 

Student characteristics All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Total 0.25 0.35 0.31 0.49 

Sex 

Male 0.78 3.05 2.61 2.95 0.78 

Female 0.78 3.05 2.61 2.95 0.78 

Race/ethnicity 

White 1.24 3.66 3.42 3.95 1.26 

Black 0.92 2.07 2.42 2.24 0.99 

Hispanic 1.09 3.35 3.39 3.01 1.12 

Asian 0.40 1.68 0.86 0.97 0.46 

Other/Two or more races 0.46 2.83 1.56 2.46 0.43 

Interest in mathematics course in ninth grade 

Not taking mathematics course 0.64 1.20 2.29 1.47 0.69 

Low interest 0.51 1.68 2.02 2.96 0.57 

Moderate interest 0.77 3.78 2.96 3.08 0.79 

High interest 0.53 3.74 1.87 2.04 0.59 

Interest in science course in ninth grade 

Not taking science course 1.16 2.11 2.39 2.35 1.22 

Low interest 0.64 1.77 2.34 2.57 0.73 

Moderate interest 0.99 3.08 2.97 2.92 1.11 

High interest 0.49 2.73 2.06 2.47 0.55 

Engagement in school in ninth grade 

Low engagement 0.59 1.94 2.39 1.67 0.63 

Moderate engagement 0.69 4.06 2.83 2.88 0.78 

High engagement 0.59 3.38 2.53 2.65 0.65 

Grade in eighth-grade mathematics course 

A 0.94 3.76 3.44 2.97 0.98 

B 0.76 3.38 2.98 2.53 0.83 

C 0.58 2.24 2.54 2.61 0.64 

D or below 0.51 1.85 2.57 1.02 0.56 

See notes at end of table. 
 23 

 

 

Table B-1. Standard errors for table A-1: Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM 

occupational intention categories and student, family, and school characteristics—Continued 

Student characteristics All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Grade in eighth-grade science course 

A 0.97 3.39 3.67 2.60 1.00 

B 0.82 3.10 3.12 2.65 0.83 

C 0.76 1.49 2.41 2.80 0.85 

D or below 0.41 1.27 1.35 1.09 0.44 

Parents’ highest degree 

High school diploma or less 1.08 3.22 2.98 3.27 1.15 

Associate’s degree or bachelor’s degree 0.84 3.28 2.85 3.34 0.88 

Master’s degree or higher 0.58 2.57 1.95 2.05 0.65 

Either parent’s occupation in a STEM feld 

Yes 0.48 2.77 1.76 2.23 0.48 

No 0.48 2.77 1.76 2.23 0.48 

Total family income in 2008 

Less than $35,000 1.19 3.41 3.04 3.09 1.32 

Between $35,000 and $95,000 0.88 4.41 3.18 3.33 0.98 

Greater than $95,000 0.90 3.38 2.69 2.95 0.97 

School locale 

City 0.34 3.53 3.50 2.77 0.41 

Suburb 0.24 3.12 2.98 2.45 0.34 

Town 0.17 1.73 1.96 1.74 0.20 

Rural 0.22 2.37 3.19 2.41 0.28 

School control 

Public 0.09 1.46 1.13 0.96 0.13 

Private 0.09 1.46 1.13 0.96 0.13 

# Not applicable. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Survey, Base Year, First Follow-Up, and 

2013 Update. 
 24 

Table B-2. Standard errors for table A-2: Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM 

occupational intention categories and high school coursetaking 

Student characteristics All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Total 0.25 0.35 0.31 0.49 

Student’s highest level of mathematics completed by end of ninth grade 

Less than algebra I 0.98 1.55 2.36 2.53 1.06 

Algebra I 1.15 3.32 3.14 3.07 1.23 

Higher than algebra I 1.06 3.61 3.30 2.89 1.14 

Student’s highest level of science taken in ninth grade 

No science 0.96 1.62 1.99 1.85 1.04 

General science 1.14 2.75 2.56 1.93 1.22 

Advanced science (specialty, IB, AP) 0.61 1.76 1.37 0.92 0.63 

Took at least one credit in algebra II 

Yes 1.57 3.82 3.51 3.89 1.55 

No 1.57 3.82 3.51 3.89 1.55 

Took at least one credit in precalculus 

Yes 0.87 3.46 3.57 2.62 0.87 

No 0.87 3.46 3.57 2.62 0.87 

Took at least one credit in calculus 

Yes 0.72 3.39 3.35 1.85 0.71 

No 0.72 3.39 3.35 1.85 0.71 

Took at least one credit in statistics 

Yes 0.76 2.45 2.42 1.76 0.77 

No 0.76 2.45 2.42 1.76 0.77 

Took at least one credit in geometry 

Yes 1.08 2.93 2.94 2.27 1.09 

No 1.08 2.93 2.94 2.27 1.09 

Took at least one credit in trigonometry 

Yes 1.08 3.17 2.50 2.52 1.09 

No 1.08 3.17 2.50 2.52 1.09 

Took at least one credit in chemistry 

Yes 1.15 2.72 2.99 2.89 1.18 

No 1.15 2.72 2.99 2.89 1.18 

See notes at end of table. 
 25 

Table B-2. Standard errors for table A-2: Percentage distribution of fall 2009 ninth-graders in spring 2012, by STEM 

occupational intention categories and high school coursetaking—Continued 

Student characteristics All 

STEM 

Intender 

STEM 

Newcomer 

STEM 

Leaver 

Non-STEM 

Intender 

Took at least one credit in physics 

Yes 1.2 3.1 3.6 3.1 1.2 

No 1.2 3.1 3.6 3.1 1.2 

Took at least one credit in biology 

Yes 0.85 1.75 1.65 1.86 0.89 

No 0.85 1.75 1.65 1.86 0.89 

Took at least one credit in computer science/information technology 

Yes 1.46 3.31 3.64 3.79 1.44 

No 1.46 3.31 3.64 3.79 1.44 

Took an academic track 

Yes 0.99 3.76 3.28 2.74 1.06 

No 0.99 3.76 3.28 2.74 1.06 

Overall unweighted high school GPA 

A’s and B’s (GPA 3.0 to 4.0) 1.02 3.56 3.43 3.47 1.10 

B’s and C’s (GPA 2.0 to 2.9) 0.79 3.27 2.86 3.54 0.83 

C’s and below (GPA 1.9 and below) 0.69 1.83 2.18 1.76 0.75 

NOTE: Advanced science courses include Advanced Placement (AP) courses and International Baccalaureate (IB) courses. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School Longitudinal Survey, Base Year, First Follow-Up, and 

2013 Update. 
 26 

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