Gender and Educational and Occupational Choices Jacquelynne S. Eccles University of Michigan Paper presented at the Gender Role Conference San Francisco

Gender and Gender and Educational and Educational and

Occupational ChoicesOccupational ChoicesJacquelynne S. EcclesJacquelynne S. Eccles

University of MichiganUniversity of Michigan

Paper presented at the Gender Role ConferencePaper presented at the Gender Role ConferenceSan Francisco April 2004 San Francisco April 2004

and Chinese University of Hong Kong, February, 2004and Chinese University of Hong Kong, February, 2004

Acknowledgements: This research was funded by grants from NIMH, NSF, Acknowledgements: This research was funded by grants from NIMH, NSF, and NICHD to Eccles and by grants from NSF, Spencer Foundation and and NICHD to Eccles and by grants from NSF, Spencer Foundation and

W.T. Grant to Eccles and BarberW.T. Grant to Eccles and Barber

Why Do Women and Men Why Do Women and Men Make Such Different Make Such Different

Choices for Their Lives?Choices for Their Lives? In most cultures, women and men In most cultures, women and men

are concentrated in quite different are concentrated in quite different occupations and roles.occupations and roles.

Why?Why? My goal today is to provide one My goal today is to provide one

perspective on this quite complex perspective on this quite complex question – a perspective grounded in question – a perspective grounded in Expectancy –Value Models of Expectancy –Value Models of Achievement-related Choices Achievement-related Choices

OverviewOverview

I began my research work in this I began my research work in this area focused on one specific area focused on one specific question:question:

WHY ARE FEMALES LESS LIKELY WHY ARE FEMALES LESS LIKELY TO GO INTO MATH AND PHYSICAL TO GO INTO MATH AND PHYSICAL SCIENCE THAN MALES?SCIENCE THAN MALES?

Overview 2Overview 2 I became increasingly aware, however, I became increasingly aware, however,

that this question is a subset of two much that this question is a subset of two much more general questions:more general questions:

WHY DOES ANYONE DO ANYTHING?WHY DOES ANYONE DO ANYTHING?

WHAT PSYCHOLOGICAL, BIOLOGICAL, WHAT PSYCHOLOGICAL, BIOLOGICAL, AND SOCIAL FORCES INFLUENCE THE AND SOCIAL FORCES INFLUENCE THE CRITICAL CHOICES PEOPLE MAKE CRITICAL CHOICES PEOPLE MAKE ABOUT HOW TO SPEND THEIR TIME ABOUT HOW TO SPEND THEIR TIME AND THEIR LIVES?AND THEIR LIVES?

GoalsGoals

Provide an overview of gender Provide an overview of gender differences in occupational plans and differences in occupational plans and choiceschoices

Discuss alternative explanations for Discuss alternative explanations for these differences – focusing on my these differences – focusing on my Expectancy – Value Model of Expectancy – Value Model of Achievement-Related ChoicesAchievement-Related Choices

Summarize our research findings Summarize our research findings relevant to this question and this modelrelevant to this question and this model

Student responses to Student responses to The Job Picture StoryThe Job Picture Story and and Typical Typical Day When I’m ThirtyDay When I’m Thirty Essay Essay

0

40

80

120

160

200

240

280

320

NO

. OF

ST

UD

EN

TS

A B C D E F G H I J K L M N O

CAREER

K-12 CAREERS Females

Males

FEMALE MALE

A 5% 95%

B 14% 86%

C 13% 87%

D 27% 73%E 32% 68%

F 55% 45%G 48% 52%H 55% 45%I 61% 39%J 85% 15%K 98% 2%L 85% 15%M 87% 13%N 97% 3%O 42% 58%

N= 1987 N=1962

TOTAL N= 3949A TRUCKDRIVER, CARPENTER, MECHANIC F DOCTOR, LAWYER, ARCHITECT, ACCT’NT K NURSE

B PROFESSIONAL ATHLETE G ARTIST, ROCK STAR,SINGER, MUSICIAN L MODEL, DESIGNER, MOVIE STAR, DANCER

C POLICE, FIREFIGHTER, MILITARY, PILOT H REPORTER, WRITER, TV ANNOUNCER M SECRETAR, FLIGHT, ATT. SALES CLERK

D SCIENTIST. ENGINEER, COMPUTER SCI. I VETERINARIAN, FOREST RANGER, FARMER N UNPAID WORKER (HOMEMAKER, PARENT)

E EXECUTIVE, BUSINESSPERSON, BANKER J TEACHER 0 THER

Participation in M/S/E Participation in M/S/E careerscareers

In 1997, women In 1997, women representedrepresented

* 23% of all scientists * 23% of all scientists and engineersand engineers

* 63% of psychologists* 63% of psychologists

* 42% of biologists* 42% of biologists

* 10% of * 10% of physicists/astronomersphysicists/astronomers

* 9% of engineers* 9% of engineers

Source: National Science Source: National Science Foundation, 2000Foundation, 2000

Bachelor’s degrees in 2000Bachelor’s degrees in 2000

PercentsPercents WomenWomen MenMenTotal M/S/ETotal M/S/E 28.028.0 36.936.9PhysicalPhysical 0.80.8 1.61.6EngineerinEngineeringg

1.71.7 8.88.8

Math/CSMath/CS 2.22.2 6.26.2EarthEarth 0.20.2 0.50.5BiologicalBiological 6.56.5 6.86.8SocialSocial 8.68.6 9.79.7PsychologyPsychology 8.08.0 3.33.3

Source:NSF 02-327

Differences on Academic Differences on Academic IndicatorsIndicators

Females Earn Better School Marks than Males Females Earn Better School Marks than Males in All Subjects Areas at All Grade Levelsin All Subjects Areas at All Grade Levels

Males Score Better than Females on Timed Males Score Better than Females on Timed Standardized Tests Scores on Many Subject Standardized Tests Scores on Many Subject AreasAreas

Females are Now More Likely than Males to Females are Now More Likely than Males to Pursue Many Forms of Advanced EducationPursue Many Forms of Advanced Education

Males are More Likely than Females to be Males are More Likely than Females to be Placed in Remedial Educational Programs, to Placed in Remedial Educational Programs, to be Expelled from School, and to Drop Out of be Expelled from School, and to Drop Out of School PrematurelySchool Prematurely

Common ExplanationsCommon Explanations Biological DifferencesBiological Differences

Brain differences –Brain differences – Hemispheric SpecializationHemispheric Specialization

May be linked to verbal and spatial skillsMay be linked to verbal and spatial skills Specialized Sensitivities for Learning and InterestsSpecialized Sensitivities for Learning and Interests

Such as preferences for speech input and faces versus Such as preferences for speech input and faces versus mechnical objectsmechnical objects

Do not know the actual mechanisms but genetic studies Do not know the actual mechanisms but genetic studies suggest these may be heritable and may be sex-likedsuggest these may be heritable and may be sex-liked

DisabilitiesDisabilities Learning particular types of materialsLearning particular types of materials Social intelligenceSocial intelligence AnxietiesAnxieties

Anxiety and PerformanceAnxiety and Performance

Anxiety

Performance

LevelMales

Females

Common ExplanationsCommon Explanations

HormonalHormonal PrenatalPrenatal

Linked to developing organizational Linked to developing organizational structure of brain and other hormonal structure of brain and other hormonal systemssystems

PostnatalPostnatal Right after birth hormonal peaksRight after birth hormonal peaks PubertyPuberty AdulthoodAdulthood Activational systemsActivational systems

Psychological Psychological DifferencesDifferences

Ability Self Concepts for Different Ability Self Concepts for Different Skill AreasSkill Areas

Domain Specific Interests and Domain Specific Interests and PreferencesPreferences

More General Differences in Values More General Differences in Values and Goalsand Goals

AnxietiesAnxieties

Social ExperiencesSocial Experiences

Family and PeersFamily and Peers Role ModelsRole Models ExpectationsExpectations Provision of Differential ExperiencesProvision of Differential Experiences

Schools and Larger SocietySchools and Larger Society Differential TreatmentDifferential Treatment Differential Teaching Practices for Differential Teaching Practices for

Different Subject AreasDifferent Subject Areas

Very Difficult to Distinguish These Very Difficult to Distinguish These Hypotheses Hypotheses

All are Likely InfluencesAll are Likely Influences

In Addition, People Self-Socialize In Addition, People Self-Socialize into the Culturally Approved Social into the Culturally Approved Social Roles and NichesRoles and Niches

One Way to Frame the One Way to Frame the QuestionQuestion

Do these differences exist even Do these differences exist even amongst a group of individuals who amongst a group of individuals who have sufficient intelligence to choose have sufficient intelligence to choose even the most demanding even the most demanding intellectual careers? For example intellectual careers? For example amongst people who are highly amongst people who are highly gifted in both the verbal and gifted in both the verbal and mathematical areas?mathematical areas?

DegreeN Percent N Percent

Master's (arts or science)

58 11% 76 18%

Ph.D. (or comparable doctorate)

60 11% 13 3%

Law 79 14% 3 <1%M.D. 47 8% 5 1%M.B.A. 19 3% 1 <1%Graduate engineering degree

14 2% 0

Graduate certificate in librarianship

1 <1% 13 3%

Graduate diploma in social work

0 8 2%

Other 5 1% 3 <1%

Note: Percentages based on total number of college graduates. Data derived from Terman and Oden, 1947]

Highest Graduate Degrees Obtained by 1945

------------------------------------------------------------------------------------------------------------

Men Women

Current Gifted ResearchCurrent Gifted Research

Similar differences emergeSimilar differences emerge Females now more likely to go on to Females now more likely to go on to

college but are still underrepresented in college but are still underrepresented in the physical sciences and engineeringthe physical sciences and engineering

Another ViewAnother View

Look at the proportion of women at Look at the proportion of women at each step along the pipelineeach step along the pipeline

Figure 1Figure 1

Proportion of Females in Each GroupProportion of Females in Each Group

0

10

20

30

40

Per

cen

t W

ho

are

Fem

ales

Math-SAT over 550 Freshman planningto major

BS Degrees PhD Degrees

Physical Sciences

0

10

20

30

40

Perc

ent W

ho a

re F

emal

es

Math-SATover 550

Freshmanplanning to

major

BS Degrees PhDDegrees

Engineering

Final ViewFinal View

Put the question into a larger Put the question into a larger perspective –perspective –

Why does anyone do anything?Why does anyone do anything?

Subjective Task ValueSubjective Task Value

1.1. Interest Value – Enjoyment one Interest Value – Enjoyment one gets from doing the activity itselfgets from doing the activity itself

Similar to Intrinsic ValueSimilar to Intrinsic Value

2.2. Utility Value – Relation of the Utility Value – Relation of the activity to one’s short and long activity to one’s short and long range goalsrange goals

Similar in some ways to Extrinsic Similar in some ways to Extrinsic ValueValue

Subjective Task Value Subjective Task Value ContinuedContinued

3. 3. Attainment Value:Attainment Value: Extent to which engaging in the Extent to which engaging in the activity confirms an important component on one’s self-activity confirms an important component on one’s self-schema or increases the likelihood of obtaining a desired schema or increases the likelihood of obtaining a desired future self or avoiding an undesired future self.future self or avoiding an undesired future self.

a.a. Individuals seek to confirm their possession of Individuals seek to confirm their possession of characteristics central to their self-schema.characteristics central to their self-schema.

b.b. Various tasks provide differential opportunities for Various tasks provide differential opportunities for such confirmation.such confirmation.

c.c. Individuals will place more value on those tasks Individuals will place more value on those tasks that provide the opportunities for this confirmation.that provide the opportunities for this confirmation.

d.d. Individuals will be more likely to choice those Individuals will be more likely to choice those activities that have high attainment value.activities that have high attainment value.

Subjective Task Value Subjective Task Value ContinuedContinued

4.4. CCost –ost –Psychological CostsPsychological Costs

Fear of Success, Fear of Fear of Success, Fear of Failure,Failure, AnxietyAnxiety

Financial CostsFinancial CostsLost Opportunities to Fulfill Other Lost Opportunities to Fulfill Other GoalsGoals

or to do Other Activitiesor to do Other Activities

Key Features of ModelKey Features of Model

1.1. Focuses on Focuses on ChoiceChoice not on not on DeficitsDeficits

2.2. Points Out Importance of Studying the Points Out Importance of Studying the Origins of Individuals’ Perception of Origins of Individuals’ Perception of the Range of Possible Optionsthe Range of Possible Options

3.3. Focuses on the Fact that Choices are Focuses on the Fact that Choices are made from a Wide Range of Positive made from a Wide Range of Positive OptionsOptions

How Does This Relate To Gender?How Does This Relate To Gender?

PersonalExperiences

Subcultural Scripts,Beliefs, andStereotypes

Societal Beliefs, Images, andStereotypes

Personal IdentitiesSelf Concepts

Personal Values

Personal Goals

Social IdentitiesSalience

Content

Perception of BarriersAnd Benefits

Due to One’s GroupMembership

SuccessExpectations

SubjectiveTaskValue

Life Choices

Gender-Roles and Ability Gender-Roles and Ability Self Concepts and Personal Self Concepts and Personal

ExpectationsExpectations

Cultural Stereotypes about Which Cultural Stereotypes about Which Gender is Supposed to be Good at Gender is Supposed to be Good at Which SkillsWhich Skills

Extensive Socialization Pressures to Extensive Socialization Pressures to Make Sure These Stereotypes are Make Sure These Stereotypes are FulfilledFulfilled

Gender-Roles and Gender-Roles and Subjective Task ValueSubjective Task Value

1.1. Different Hierarchies of Core Personal ValuesDifferent Hierarchies of Core Personal Values

a.a. Concern with Social Goals versus Concern with Power Concern with Social Goals versus Concern with Power or Achievement Goals;or Achievement Goals;

b.b. Concern with Social Relationships versus concern with Concern with Social Relationships versus concern with Individual Achievement and Status.Individual Achievement and Status.

c.c. Interest in Things versus Interest in People.Interest in Things versus Interest in People.

d.d. Interest in Cooperation versus Interest in CompetitionInterest in Cooperation versus Interest in Competition

2.2. Density of HierarchyDensity of Hierarchy

a.a. Single-mindedness versus Diverse InterestsSingle-mindedness versus Diverse Interests

Gender-Roles and Gender-Roles and Subjective Task Value Subjective Task Value

ContinuedContinued3.3. Different Long Range GoalsDifferent Long Range Goals

4.4. Different Definitions of Success in Various Goals Different Definitions of Success in Various Goals and Roles.and Roles.

a.a. What does it take to be a successful father What does it take to be a successful father versus a successful mother?versus a successful mother?

b.b. What does it take to be a successful What does it take to be a successful professional?professional?

c.c. What does it take to be a successful human What does it take to be a successful human being?being?

Gender Differences in Gender Differences in Values Among Gifted Values Among Gifted Children and YouthChildren and Youth

1.1. Activity InterestsActivity Interests

a.a. Females less interested than males in Females less interested than males in physics, chemistryphysics, chemistry

b.b. Females more interested in English, foreign Females more interested in English, foreign languages, music, drama, medical-related languages, music, drama, medical-related majors, and biological sciencesmajors, and biological sciences

c.c. Females more interested in reading, writing Females more interested in reading, writing and domestic activities and arts and craftsand domestic activities and arts and crafts

d.d. Females less interested in sports, working Females less interested in sports, working with machines, tools, and electronic with machines, tools, and electronic equipmentequipment

Gender Differences in Values Gender Differences in Values Among Gifted Children and Youth Among Gifted Children and Youth

ContinuedContinued2.2. Personal ValuesPersonal Values

a.a. Females score higher on social and aesthetic Females score higher on social and aesthetic valuesvalues

b.b. Females score lower on theoretical, economic Females score lower on theoretical, economic and political valuesand political values

3.3. Density of ValuesDensity of Values

a.a. Females tend to rate a broader range of Females tend to rate a broader range of activities and future roles as important than do activities and future roles as important than do males.males.

b.b. Males are more likely to rate a few activities Males are more likely to rate a few activities very high and the remaining activities very low.very high and the remaining activities very low.

Michigan Study of Adolescent Life TransitionsMichigan Study of Adolescent Life Transitions(MSALT)(MSALT)

U of M Affiliated Investigators:U of M Affiliated Investigators:

Waves 1-4Waves 1-4Jacque EcclesJacque EcclesCarol MidgleyCarol MidgleyAllan WigfieldAllan Wigfield

Jan JacobsJan JacobsConnie FlanaganConnie Flanagan

Harriet FeldlauferHarriet FeldlauferDavid ReumanDavid ReumanDoug MacIverDoug MacIverDave KlingelDave Klingel

Doris YeeDoris YeeChristy Miller BuchananChristy Miller Buchanan

Waves 5-8Waves 5-8Jacque EcclesJacque EcclesBonnie BarberBonnie BarberLisa ColarossiLisa Colarossi

Deborah JozefowiczDeborah JozefowiczPam FromePam FromeSarah LordSarah LordMina VidaMina Vida

Robert RoeserRobert RoeserLaurie MeschkeLaurie Meschke

OVERVIEW OF DESIGN AND SAMPLE:OVERVIEW OF DESIGN AND SAMPLE:MICHIGAN STUDY OF ADOLESCENT LIFE MICHIGAN STUDY OF ADOLESCENT LIFE

TRANSITIONS – MSALTTRANSITIONS – MSALT

DESIGN: DESIGN: On-going Longitudinal Study of On-going Longitudinal Study of One One Birth Cohort Birth Cohort

Data Collected in Grades 6, 7, 10, Data Collected in Grades 6, 7, 10, 12; 12; and again at Ages 20 and 25and again at Ages 20 and 25

Data Collected from Adolescents, Data Collected from Adolescents, Parents, and Parents, and School – School –

Most Most Using Survey Using Survey FormsForms

SAMPLE:SAMPLE: Nine School DistrictsNine School DistrictsApproximately 1,200 AdolescentsApproximately 1,200 AdolescentsApproximately 90% WhiteApproximately 90% WhiteApproximately 51% FemaleApproximately 51% FemaleWorking/Middle Class BackgroundWorking/Middle Class Background

Michigan Study of Adolescent/Adult Life Transitions: MSALT

Time 1 Time 2 Time 3

YEAR Fall 1983

Spring 1984

Fall 1984

SPRING 1985

1988 1990 1992 1996 2000

GRADE 6th 6th 7th 7th 10th 12th 2 years after H.S.

6 years after H.S.

9 years after H.S.

WAVE

1 2 3 4 5 6 7 8 9

YOUTH SURVEY

PARENTS SURVEY

TEACHER QUESTIONNAIRE

RECORD DATA

FACE TO FACE INTERVIEW

+

MSALT Sample General MSALT Sample General CharacteristicsCharacteristics

School based sample drawn from 10 School based sample drawn from 10 school districts in the small city school districts in the small city communities surrounding Detroit.communities surrounding Detroit.

Predominantly White, working and middle Predominantly White, working and middle class familiesclass families

Approximately 50% of sample of youth Approximately 50% of sample of youth went on to some form of tertiary went on to some form of tertiary educationeducation

Downsizing of automobile industry caused Downsizing of automobile industry caused major economic problems while the youth major economic problems while the youth were in secondary schoolwere in secondary school

BELIEFS AND GENDERED

STEREOTYPES ABOUT MATH-RELATED PROFESSIONS

PERCEPTIONS OF SOCIALIZERS

ATTITUDES AND EXPECTATIONS

GENDERED STEREOTYPES

ABOUT MATH SKILLS APPROPRIATENESS

INTERPRETATION OF PAST MATH EVENTS

GOALS AND GENERAL SELF-SCHEMATA

1. Personal Identity

2. Gender Role Identity

3. Career and Other Life Goals/Values

4. Minimum Standards for Achievement

SELF-CONCEPT OF MATH ABILITY

PERCEPTIONS OF THE DIFFICULTY OF

MATH

PERCEPTION OF TASK VALUE

1. Liking of math

2. Perceived usefulness of math

3. Importance of doing well in math

4. Worth of the amount of effort needed to do well

EXPECTANCIES

1. Current

2. Future

ACHIEVEMENT BEHVAIOR

1. Enroll in advanced courses

2. Aspire to math-related careers

Two Basic QuestionsTwo Basic Questions

ARE THERE GENDER DIFFERENCES ARE THERE GENDER DIFFERENCES ON ON

THESE SELF-RELATED BELIEFS? THESE SELF-RELATED BELIEFS? DO THE GENDER DIFFERENCES IN DO THE GENDER DIFFERENCES IN

THESE SELF-RELATED BELIEFS THESE SELF-RELATED BELIEFS MEDIATE THE GENDER MEDIATE THE GENDER DIFFERENCES IN INVOVLEMENT?DIFFERENCES IN INVOVLEMENT?

BUT FIRST, ARE THERE GENDER BUT FIRST, ARE THERE GENDER DIFFERENCES IN LONG TERM DIFFERENCES IN LONG TERM OCCUPATIONAL PLANS?OCCUPATIONAL PLANS?

Gender Differences in Gender Differences in Ability Self Concepts – 7Ability Self Concepts – 7thth

GradeGrade

3

3.5

4

4.5

5

5.5

6

Math English Sports

GirlsBoys

Gender Differences in Gender Differences in Subjective Task Value – 7Subjective Task Value – 7thth

GradeGrade

3

3.5

4

4.5

5

5.5

6

6.5

Math English Sports

GirlsBoys

How Young Do These How Young Do These Differences EmergeDifferences Emerge

Childhood and Beyond StudyChildhood and Beyond Study Similar MeasuresSimilar Measures Similar Population in Southeastern Similar Population in Southeastern

Michigan Michigan 4 Middle Class School Districts4 Middle Class School Districts Primarily WhitePrimarily White 3 Cohorts Beginning in 13 Cohorts Beginning in 1stst, 2, 2ndnd, and 4, and 4thth

gradesgrades Followed Longitudinally until age 22Followed Longitudinally until age 22

Gender Differences in Ability Self-Gender Differences in Ability Self-Concepts: 1Concepts: 1stst, 2, 2ndnd, & 4, & 4thth Graders Graders

4

5

6

7

Mea

n R

atin

gs

GeneralSports

Throw Tumble Music Read Math

Ability Self-Concepts

Girls

Boys

WORRY ABOUT WORRY ABOUT PERFOMANCE ACROSS PERFOMANCE ACROSS

DOMAINSDOMAINS

2.5

3.0

3.5

4.0

4.5

5.0

5.5

Me

an

Ra

tin

g f

or

Wo

rry

Math Reading Sports Not beliked

Hurt oth.Feel.

Domain

Girls

Boys

IMPORTANCE OF ABILITY IMPORTANCE OF ABILITY IN DIFFERENT DOMAINSIN DIFFERENT DOMAINS

4.0

4.5

5.0

5.5

6.0

6.5

Mea

n R

atin

g o

f Im

po

rtan

ce

Math Reading Sports Music Social

Domain

Girls

Boys

Enjoyment of Different Enjoyment of Different DomainsDomains

4

4.5

5

5.5

6

6.5

Mea

n R

atin

g f

or

Lik

ing

Math Reading Sports Music

Domain

Girls

Boys

ConclusionConclusion

Gender Differences Occur across Gender Differences Occur across Several Domains for Both Ability Self Several Domains for Both Ability Self Concepts and Subjective Task ValuesConcepts and Subjective Task Values

Gender Differences Emerge Quite Gender Differences Emerge Quite YoungYoung

Do These Differences Mediate Gender Do These Differences Mediate Gender Differences in Course Taking and Differences in Course Taking and Activity Involvement?Activity Involvement?

Predicting Number of Honors Math Classes (sex, DAT) Predicting Number of Honors Math Classes (sex, DAT) N = 223 (honors students)N = 223 (honors students)

Gender

Math Aptitude

Number of Honors Math

Courses (R² = .08)

.15

.22

Predicting Number of Honors Math ClassesPredicting Number of Honors Math ClassesN = 223 (honors students)N = 223 (honors students)

Gender

Math Aptitude

Self-Concept of Ability in

Math

(R² = .06)

Interest in Math

(R² = .02)

Utility of Math

(R² = .04)

Number of Honors Math

Courses

(R² = .19)

.15

.12

.14.18

.14

.13

.25

Predicting # of Physical Science Predicting # of Physical Science Classes (sex, DAT)Classes (sex, DAT)

Number ofPhysicalScienceCourses

(R2 = .15)

Number ofPhysicalScienceCourses

(R2 = .15)

GenderGender

MathAptitude

MathAptitude

.34

.16

Predicting # of Physics Predicting # of Physics ClassesClasses

Gender

Math Aptitude

Utility Of P.S. (R2=.05)

Linking P.S.

(R2=.03)

Self-Concept of Ability in P.S.

(R2=.06)

Number of

Physical Sciences Courses (R2=.34)

.20

.19

.48

.09

.09

.17

.13

.16

.09

Predicting Team SportsPredicting Team Sports

Gender

Self-Concept of Ability in Sports (R² = .09)

Utility of Sports (R² = .08)

Liking Sports (R² = .05)

Team Sports 10th grade (R² = .29)

Team Sports 12th grade (R² = .21)

.31

.04

.29

.23

.15

.13.24

.27

.18

Ability Self-Concept

Sex Utility Value

Importance Value

Free Time Spent

.28

.21

.19

.11 (.46)

.36 (.53)

.17 (.46)

R² = 8%

R² = 5%

R² = 4%

R² = 32%

Correlation: Sex – Time Spent = .14

Partial Correlation: Sex – Time Spent = .002

(controlling mediating variables)

ConclusionConclusion In this sample, the gender differences in In this sample, the gender differences in

Utility Value were the strongest mediators Utility Value were the strongest mediators of gender differences in math and physical of gender differences in math and physical science course enrollments.science course enrollments.

A slightly different pattern is emerging for A slightly different pattern is emerging for math in the CAB study: Math Ability Self math in the CAB study: Math Ability Self Concept is having a stronger effect. Concept is having a stronger effect.

In this sample, the gender differences in all In this sample, the gender differences in all three expectancy – value beliefs mediated three expectancy – value beliefs mediated the gender differences in involvement in the gender differences in involvement in sports.sports.

What about College Course What about College Course Choices?Choices?

Wave 1,2 3,4 5 6 7 8 9

Grade 6 7 10 12 12+2 12+6 12+9

Age 12 13 16 18 20 24 27

Year 83-'84 84-'85 88 90 92 96 99

MSALT DESIGN

Specific Sample Specific Sample Characteristics for Analyses Characteristics for Analyses

Reported TodayReported Today

Those who participated at Wave 8 Those who participated at Wave 8 (age 25)(age 25) Female N = 791 Male N = 575Female N = 791 Male N = 575

Those who completed a college Those who completed a college degree bydegree by

Wave 8Wave 8 Female N = 515 Male N = 377Female N = 515 Male N = 377

Analyses: Within SexAnalyses: Within SexDiscriminant Function Discriminant Function

AnalysesAnalyses Use 12Use 12thth grade Domain Specific grade Domain Specific

Ability SCs and Values to predict Ability SCs and Values to predict College Major at age 25College Major at age 25

Use age 20 General Ability SCs and Use age 20 General Ability SCs and Occupational Values to predict Occupational Values to predict College Major at age 25College Major at age 25

Analyses 2: Between SexAnalyses 2: Between Sex

Logistic regression to test for Logistic regression to test for mediators of sex differences in mediators of sex differences in college Math/Engineering/Physical college Math/Engineering/Physical Science majorsScience majors

Time 1 Measures: 12Time 1 Measures: 12thth GradeGrade

Math/Physical Science Self-Math/Physical Science Self-Concept of AbilityConcept of Ability

Math/PS Value and UsefulnessMath/PS Value and Usefulness Biology Self-Concept of AbilityBiology Self-Concept of Ability Biology Value and UsefulnessBiology Value and Usefulness English Self-Concept of AbilityEnglish Self-Concept of Ability English Value and UsefulnessEnglish Value and Usefulness High School Grade Point AverageHigh School Grade Point Average

Sex Differences in Domain Sex Differences in Domain Specific Self Concepts and Specific Self Concepts and

Values Values

2

2.5

3

3.5

4

4.5

5

5.5M

ean

Val

ue

Self Concept and Value at Age 18 by Sex

Female

Male

Time 2 Measures: Age 20Time 2 Measures: Age 20Ability-RelatedAbility-Related

Math/Science General Ability Self Math/Science General Ability Self ConceptConcept Efficacy for jobs requiring math/scienceEfficacy for jobs requiring math/science

Intellectual Ability Self ConceptIntellectual Ability Self Concept Relative ability in logical and analytical Relative ability in logical and analytical

thinkingthinking High School Grade Point AverageHigh School Grade Point Average

Time 2 Measures: Time 2 Measures: Occupational ValuesOccupational Values

Job FlexibilityJob Flexibility Does not require being away from Does not require being away from

family family Mental ChallengeMental Challenge

Opportunity to be creative and learn Opportunity to be creative and learn new thingsnew things

Working with PeopleWorking with People Working with othersWorking with others

AutonomyAutonomy Own BossOwn Boss

Time 2 Measures: Comfort Time 2 Measures: Comfort with Job Characteristicswith Job Characteristics

Business Orientation: Comfort with Business Orientation: Comfort with tasks associated with being a tasks associated with being a supervisorsupervisor

People Orientation: Comfort working People Orientation: Comfort working with people and childrenwith people and children

Sex Differences in General Sex Differences in General Self Concepts and ValuesSelf Concepts and Values

2.5

3

3.5

4

4.5

5

5.5

6

Me

an

Va

lue

Female

Male

Time 3 Measures: Age 25Time 3 Measures: Age 25

Final College MajorFinal College Major

Occupation at Age 25: Coded into Occupation at Age 25: Coded into Global Categories based on Census Global Categories based on Census Classification CriteriaClassification Criteria

Sex Differences in College Sex Differences in College MajorsMajors

0

20

40

60

80

100

120F

req

uen

cy

Math/Science Biology Business Social Science

Female

Male

Sex Differences in Sex Differences in OccupationsOccupations

0

20

40

60

80

100

120

140

160

Fre

qu

ency

Math/Science Biology Business

Occupation at Age 25 by Sex

Female

Male

Domain Specific Attractors: + Self Concepts and Values

Domain Specific

Detractors: Anxieties

Non-Domain Detractors: + Values and Self Concepts

Non-Domain Attractors: General Achievement

Academic Choice

+

-

-

+

Predicting Women’s Math/Engineering/Physical Predicting Women’s Math/Engineering/Physical Science (M/E/PS) and Biological Science College Science (M/E/PS) and Biological Science College

Major from Domain Specific SCs Major from Domain Specific SCs and Values at 18and Values at 18

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Discriminant Function Coefficient

Value Biology

Biology selfconcept

Math/Sci Value

English value

Predicting Biology vs. Other College Major 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/sei selfconcept

Math/sci value

Final GPA

Predicting Science vs. Other College Major

Predicting Women’s M/E/PS and Predicting Women’s M/E/PS and Biological Science College Major from Biological Science College Major from

General Self-Concepts and Values at 20General Self-Concepts and Values at 20

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/sci SelfConcept

People Oriented

Value workingwith people

Pridicting Biology vs. Other College Major

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1


Math/Sci SelfConcept

Intellectual SelfConcept

Final GPA

Working withpeople

Predicting Math /Science vs. Other College Major

Predicting Men’s M/E/PS and Biological Predicting Men’s M/E/PS and Biological Science College Major from Domain Science College Major from Domain

Specific SCs and Values at 18Specific SCs and Values at 18

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9


Biology Value

Biology selfconcept

Final Gpa

Predicting Biology vs. Other College Major 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/sci value

Math self concept

Final GPA

Predicting Science vs. Other College Major

Predicting Men’s M/E/PS and Biological Predicting Men’s M/E/PS and Biological Science College Major from General Self-Science College Major from General Self-

Concepts and Values at 20Concepts and Values at 20

-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5


Business Oriented

People Oriented

Final GPA

Value mental challenge

Value working with people

Math/Sci Self Concept

Value flexibility

Predicting Biology vs. Other College Major

-0.4 -0.2 0 0.2 0.4 0.6 0.8

Discriminant Function Coefficients

Math/Sci

Final GPA

Value Working withPeople

People oriented

Predicting Math/Science vs Other College Major

Mediation of Sex Mediation of Sex DifferencesDifferences

Used logistic regression to assess Used logistic regression to assess the extent to which the Time 1 and the extent to which the Time 1 and Time 2 predictors explained the sex Time 2 predictors explained the sex difference in majoring in difference in majoring in Math/Engineering/Physical ScienceMath/Engineering/Physical Science

Step 1: Sex onlyStep 1: Sex only Step 2: Sex plus all of Time 1 or Step 2: Sex plus all of Time 1 or

Time predictorsTime predictors

Time 1 Predictors of Time 1 Predictors of Science College MajorScience College Major

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Coefficient B

Time 2 Predictors of Time 2 Predictors of Science College MajorScience College Major

0 0.1 0.2 0.3 0.4 0.5 0.6

Coefficient B

Gender

Math/SC

Final GPA

Conclusions 1:Conclusions 1:

Strong support for the predictive power of Strong support for the predictive power of constructs linked to the Expectancy Value constructs linked to the Expectancy Value Model.Model. Domain Specific SCs and Values push both Domain Specific SCs and Values push both

women and men towards the related majorswomen and men towards the related majors Some evidence that more general values can Some evidence that more general values can

also push people away from M/S/PS majors also push people away from M/S/PS majors and towards Biology-Related majorsand towards Biology-Related majors

Sex differences in selection of M/E/PS Sex differences in selection of M/E/PS college major are accounted for by college major are accounted for by Expectancy Value ModelExpectancy Value Model

Predicting M/E/PS vs. Biology Predicting M/E/PS vs. Biology Major From General Self-Major From General Self-Concepts and Values at 20Concepts and Values at 20

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

Discriminant Function Coefficient for Females

Value working withPeople

Math/Sci self concept

People Oriented


Final Gpa

Business Oriented

-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3

Discriminant Function Coefficient for Males

Value Work With People

People Oriented

Business Oriented

Value Flexibility

Final GPA

Math/Science Self -Concept

Intellectual Self Concept

Predicting M/E/PS vs. Social Predicting M/E/PS vs. Social Science Major From Self-Concepts Science Major From Self-Concepts

and Values at 18and Values at 18

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8


Math/Sci selfconcept

Math/Sci Value

English SelfConcept

English Value

Final GPA-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8


Math/Sci Value

English SelfConcept

English Value

Final GPA


Predicting M/E/PS vs. Social Predicting M/E/PS vs. Social Science Major From General Self-Science Major From General Self-

Concepts and Values at 20Concepts and Values at 20

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/Sci Value


Final GPA

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Intellectual Self-Concept

Math/Sci Value

Final Gpa

Conclusions 2Conclusions 2

Even stronger support for both the Even stronger support for both the push and pull aspects of the Eccles push and pull aspects of the Eccles et al. Expectancy Value Modelet al. Expectancy Value Model

Strong evidence that valuing having Strong evidence that valuing having a job that allows one to work with a job that allows one to work with and for people pushes individuals and for people pushes individuals away from M/E/PS majors and pulls away from M/E/PS majors and pulls them toward the Biological Sciencesthem toward the Biological Sciences

Analyses 3Analyses 3

Now lets shift to the second set of Now lets shift to the second set of analyses: those linking self concepts analyses: those linking self concepts and values from ages 18 and 20 to and values from ages 18 and 20 to occupational plans at age 20 and occupational plans at age 20 and actual occupations at age 25actual occupations at age 25

Predicting M/E/PS vs Biology Predicting M/E/PS vs Biology Occupations at 25 from Self Occupations at 25 from Self Concepts and Values at 18Concepts and Values at 18

-0.4 -0.2 0 0.2 0.4 0.6 0.8



Final GPA

Value Biology

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/sci value

Math/sci selfconcept

Final GPA

Predicting M/E/PS vs Biology Predicting M/E/PS vs Biology Occupation at 25 from General Occupation at 25 from General Self Concepts and Values at 20Self Concepts and Values at 20

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6


People Oriented

Value Working with People

Value Math/Sci

Value Flexibility

Final GPA

-0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0


Value Working withPeople

Value Autonomy

Predicting M/E/PS vs Business Predicting M/E/PS vs Business Occupations at 25 From Self Occupations at 25 From Self Concepts and Values at 18Concepts and Values at 18

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Final GPA

Math/Sci SelfConcept

Math/sciValue

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8


Math/Sci Value


Value Biology

Final GPA

Biology Self Concept

Predicting M/E/PS vs Business Predicting M/E/PS vs Business Occupation at 25 from General Occupation at 25 from General Self Concepts and Values at 20Self Concepts and Values at 20

-0.4 -0.2 0 0.2 0.4 0.6 0.8 1


Math/Sci Value


Value Working with People

Value Mental Challenge

Value Flexibility

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8


Final GPA


Value flexibility

Value Working People


People Oriented

Conclusions Conclusions

Expectancy Value Model provides a Expectancy Value Model provides a good explanatory framework for good explanatory framework for understanding both individual understanding both individual differences and sex differences in differences and sex differences in educational and occupational educational and occupational choiceschoices

What about Gender Roles?What about Gender Roles?Role of Traditionality in Terms of Role of Traditionality in Terms of FamilyFamily

Role of Gender Role Stereotypes Role of Gender Role Stereotypes of Achievement Domainof Achievement Domain

The Impact of Girls’ Gender-Role Beliefs on their Educational The Impact of Girls’ Gender-Role Beliefs on their Educational and Occupational Decisionsand Occupational Decisions..

Gender-Role Beliefs

•Gender stereotypes of ability and value

•Belief that women’s domain is in the home

Self-Concept of Abilities

Values

Expectations for Adult Responsibilities

Achievement-Related Decisions

Content

•High school courses taken

•Occupational aspirations

•College major

•Occupation at age 20

Status and Expected Labor Force Participation

•Aspire to a family flexible job

•Status of educational and occupational aspirations

Figure 7Figure 7. Traditionality, Values, Expectations of Adult Responsibilities, and Aspirations – . Traditionality, Values, Expectations of Adult Responsibilities, and Aspirations – Theoretical Model.Theoretical Model.

GPA

SES

Traditionality

Importance of Children

Importance of career

Degree of Responsibility for Income

Degree of Responsibility for Childcare and Household

Status/Family Flexible Achievement Choices

•Value of family flexible occupation

•Status of occupational aspiration

•Status of age 20 occupation

•Status of age 20 salary

What About Gender Role What About Gender Role Stereotypes?Stereotypes?

Figure 3Figure 3.Gender Stereotypes of Math, Self-Concept, Values & Math/Physical Science .Gender Stereotypes of Math, Self-Concept, Values & Math/Physical Science Outcomes – Theoretical Model.Outcomes – Theoretical Model.

Note: The paths between the stereotype variables and the outcomes are free.

Math Ability Stereotype

Math Value Stereotype

7th Grade Math Self-Concept of Ability

7th Grade Math Value

10th Grade Math Self-Concept of Ability

10th Grade Physical Science Self-Concept of Ability

10th Grade Math Value

10th Grade Physical Science Value

Math and Physical Science Achievement Choices

•Number of high school courses taken

•Occupational aspirations

•College major

•Current occupation

CONCLUSIONSCONCLUSIONS General psychological model works very well General psychological model works very well

across domainsacross domains Values are key and yet they are often neglected in Values are key and yet they are often neglected in

studies of gender differences while efficacy/ability studies of gender differences while efficacy/ability self-concepts and over emphasizedself-concepts and over emphasized

Gender-role ideology is central to acquisition of Gender-role ideology is central to acquisition of gendered valuesgendered values

Gendered values help predict both sex differences Gendered values help predict both sex differences and individual differences within sex in activity and individual differences within sex in activity choicechoice

Anticipated costs may be critical in long term Anticipated costs may be critical in long term choiceschoices

ApplicationsApplications

Interventions to increase the Interventions to increase the participation of females in M/E/PS participation of females in M/E/PS need to focus on increasing women’s need to focus on increasing women’s understanding that M/E/PS and understanding that M/E/PS and Informational Technology jobs can Informational Technology jobs can help people and do involve working help people and do involve working with people as well as increasing with people as well as increasing their confidence in their ability to their confidence in their ability to succeed in these fields.succeed in these fields.

Characteristics of Effective ClassroomsCharacteristics of Effective Classrooms

Frequent Use of Cooperative Learning Frequent Use of Cooperative Learning OpportunitiesOpportunities

Frequent Use of Individualized Learning Frequent Use of Individualized Learning OpportunitiesOpportunities

Infrequent Use of Competitive Motivational Infrequent Use of Competitive Motivational Strategies Strategies

Frequent Use of Hands-On Learning Frequent Use of Hands-On Learning OpportunitiesOpportunities

Frequent Use of Practical Problems as Frequent Use of Practical Problems as AssignmentsAssignments

Active Career and Educational Guidance Aimed Active Career and Educational Guidance Aimed at Broadening Students’ View of Math and at Broadening Students’ View of Math and Physical SciencesPhysical Sciences

Frequent Use of Strategies Designed to Create Frequent Use of Strategies Designed to Create Full Class Participation Full Class Participation

Thank YouThank You

More details and copies can be More details and copies can be found at found at

www.rcgd.isr.umich.edu/garp/www.rcgd.isr.umich.edu/garp/

The EndThe End

Documents

Gender and Educational and Occupational Choices Jacquelynne S. Eccles University of Michigan Paper presented at the Gender Role Conference San Francisco