inequality in mathematics and science achievement - walter secada

Inequality in mathematics and science achievement

Walter G. SecadaProfessor and Chair, Department of Teaching and Learning

Senior Associate Dean, School of EducationUniversity of Miami, FL

Presentation made to STEM Summit 2010: Early Childhood through Higher Education, University of California-Irvine, February 18-19, 2010

Presentation Overview

• Why de we care about inequality?• Defining achievement• Defining social-demographic groups• Not all inequalities are equal• Defining goals• Malleable versus non-malleable

determinants• P-SELL

Why do we care about inequality?

• Socially enlightened self-interest• Meaningful participation in our democracy• Ideals of fair play• Remedy for historical injustices• Personal utilitarian worth• Part of our cultural background• Maintaining the disciplines

Defining Achievement

• Performance on standardized tests (most common): SAT, HSB, NELS, TIMSS, LSAY, NAEP, PISA (match of curriculum to test)

• Course grades• Course taking (tracks)• College majors and course taking• Careers requiring math and science• Careers as mathematicians and scientists

Defining Achievement, 2

• Interrelationships among: e.g. course taking predicts test performance; test performance constrains course taking

• High in one does not guarantee high in another

Defining Social-Demographic Groups

• Somewhere between the individual (and individual variation) and the population lies the group

• Dominant groupings: Gender (not sex), race and ethnicity, social class, language proficiency

• Secondary groupings: immigrant status, generational status

• Emerging grouping: special needs, sexuality

Defining Social-Demographic Groups, 2

• Differences based on groups have differential importance in social policy debates; for example, social class is an accepted characteristic that explains away group differences

• Groupings have had histories of being accepted as natural; now, among social scientists, they are seen as socially constructed

• Groupings are now seen as interacting (e.g., race-class-gender) or, better stated, people are seen as inhabiting multiple groups at the same time

Not all inequalities are equal

• According to PISA results:• In reading literacy, females do better in ALL

countries; in 11 countries, they are at least half a proficiency level above males; in the remaining 21 (which includes the United States) they are less than half a proficiency level ahead

• In mathematics, males do better in half the countries (no gender differences in the U.S.)

• In Science, males do better in three countries; females do better in three (no gender differences in the U.S.)

Not all inequalities are equal

• In the U.S., females now enroll in and complete post-secondary education in greater numbers than males; if they enter the sciences, it tends to be the life and/or social sciences

• Given PISA results: the real gender question is why are so few females entering other (non-life, non-social) sciences and why are so few females entering mathematics

• Need to look at other (structural) sources of inequality

Not all inequalities are equal

• The interactions of race (ethnicity) with gender and social class is more complex than one would believe based on looking at either single-groupings or at one or another grade or at one or another subject

• Consider the following 10th grade mathematics achievement scores, taken from ELS (NCES 2004-404; equated to NELS 1990 and HSB 10th grade)

Asian, Hawaiian, Pacific Islander Black or African American Hispanic, no race

Hispanic, race Multiracial, non-Hispanic White, non-Hispanic

Female

Male

gender

10th Grade Mathematics Achievement

By ethnicity, SES quartile, and gender

SOURCE: ELS public release data (NCES2004-404)

30.00

35.00

40.00

45.00

Eq

uat

ed t

o N

EL

S 1

990

and

HS

B 1

0th

gra

de

12

34

mean

SES quartile

30.00

35.00

40.00

45.00

Eq

uat

ed t

o N

EL

S 1

990

and

HS

B 1

0th

gra

de

12

34

mean

SES quartile

12

34

mean

SES quartile

10th Grade Mathematics Achievement

American Indians and Alaska NativesBy SES quartile

SOURCE: ELS public release data (NCES2004-404)

1 2 3 4 Mean

SES quartile

36.00

38.00

40.00

42.00

Defining Goals

• Is your goal to close one (or more) achievement gap(s)? If so, along which lines?

• Is your goal to improve achievement of an underperforming or under-represented group?

• Improvement of achievement by the lower end of a distribution may, sometimes, result in exacerbating the gap (Sesame Street revisited).

• Innovations targeted for the lower end often are restricted from it (Montessori Schools)

Malleable versus non-malleable determinants

• By the time a child enters school, it is too late for him/ her to chose her/his parents more wisely.

• Social policy is often unable (or unwilling) to tackle (let alone) change long-standing practices

• We may not have developed the technologies that allow us to change determinants of achievement (de-tracking)

Malleable versus non-malleable determinants, 2

• We know a lot on how to improve achievement at the lower end of the distribution

• We do not know how efforts focused at one kind of achievement interact with other forms of achievement or (more seriously) with other efforts

Malleable versus non-malleable determinants, 3

• We know very little – maybe next to nothing – about CLOSING any of the aforementioned gaps

• Issues of defining interventions, bringing them to scale, costs involved, avoiding the math and science wars

• Inclusion and improvement of performance is often set in opposition to excellence

Malleable versus non-malleable determinants, 4

• Valerie E. Lee with Julia Smith (2001). Restructuring high schools for equity and excellence: What works. New York: Teachers College Press

• Secondary schools, between 500 and 1500 students, which provide a limited and focused math/science curriculum, whose teachers accept responsibility for student achievement, and where teaching focuses on depth and understanding (over superficial coverage) begin to close the SES-based achievement gap between 8th and 10th grade and between 10th and 12th in mathematics and science (NELS:88 data)

Promoting Science among English Language Learners (P-SELL)

• DIRECTED BY OKHEE LEE• Five year research and development project• Inquiry based science: “hands-on” (but really more lab-

base), math applications (e.g., metric measurement), writing (of hypotheses, methods and results)

• Addresses the Sunshine State Science Standards in grades 3-5

• Includes language-based supports• Goes from very teacher directive (3rd grade) to more

student driven (5th grade) across its three years• Professional development focused on implementation

P-SELL: Data Gathering

• FCAT student achievement in 3rd-grade math (n = 4,500 P-SELL), 4th-grade math & writing (3,100), 5th-grade math & science (n = 2,500)

• P-SELL test of Student science-achievement (growth), P-SELL writing assessment

• Teacher surveys• Classroom observation based on CORS scales• Student reasoning tasks; teacher discussion of

student reasoning• School-level interviews

P-SELL Results: 3rd grade math

2004

- Bas

eline

2005

- P-S

ELL Y

ear 1

2006

- P-S

ELL Y

ear 2

2007

- P-S

ELL Y

ear 3

2008

- Sus

taini

ng Y

ear 1

2009

- Sus

taini

ng Y

ear 2

270

280

290

300

310

320

330

340

350

Statewide

P-SELL Schools

Comparison Schools

P-SELL Results: 4th grade math

2005 - Baseline Year 2006 - P-SELL Year 1

2007 - P-SELL Year 2

2008 - P-SELL Year 3

2009 - Sustaining Year 1

280

290

300

310

320

330

340

Statewide

P-SELL Schools

Comparison Schools

P-SELL Results: 5th-grade math

2006 - Baseline Year 2007 - P-SELL Year 1 2008 - P_SELL Year 2 2009 - P-SELL Year 3300

305

310

315

320

325

330

335

340

Statewide

P-SELL Schools

Comparison Schools

P-SELL results: 4th-grade writing

2005 - Baseline 2006 - PSELL Year 1

2007 - PSELL Year 2

2008 - PSELL Year 3

2009 - Sustain Year 1

3.4

3.5

3.6

3.7

3.8

3.9

4

4.1

State

P-SELL Schools

Comparison Schools

P-SELL results: 5th-grade science

2006 - Baseline 2007 - PSELL Year 1 2008 - PSELL Year 2 2009 - PSELL Year 3240

250

260

270

280

290

300

310

320

State

P-SELL Schools

Comparison Schools

Questions and Answers

Appendix A

• Science Achievement figures (following the mathematics achievement figures used above) from NELS 1990 (10th grade)

Asian and Pacific Islander

10th grade Science Scores

SES

4.003.002.001.00

Me

an

SC

IST

D

64

62

60

58

56

54

52

50

48

46

GENDER

1.00

2.00

Hispanics

10th grade Science Scores

SES

4.003.002.001.00

Me

an

SC

IST

D

56

54

52

50

48

46

GENDER

1.00

2.00

African Americans

10th grade Science Scores

Non-Hispanics

SES

4.003.002.001.00

Me

an

SC

IST

D

56

54

52

50

48

46

44

GENDER

1.00

2.00

Whites

10th grade Science Scores

Non-Hispanics

SES

4.003.002.001.00

Me

an

SC

IST

D

62

60

58

56

54

52

50

48

GENDER

1.00

2.00

American Indian

10th grade Science Scores

SES

4.003.002.001.00

Me

an

SC

IST

D

54

52

50

48

46

44

GENDER

1.00

2.00