Dr. Estela Zarate, CSUF Department of Educational Leadership; Dr. Adriana Ruiz Alvarado, UCLA Higher Education Research Institute; Dr. Alessandra Pantano, UCI

1. PERSISTENCE IN MATH: THE ROLE
OF INITIAL MATH PLACEMENT
MARIA ESTELA ZARATE
ADRIANA RUIZ ALVARADO
ALESSANDRA PANTANO

2. EXISTING LITERATURE
• URM representation among mathematics and statistics majors
has decreased in the past decade (NSF, 2015).
• To date, existing research on STEM major persistence has
identified several predictors of success:
• pre- college
• psycho-social factors
• institutional support
• first year math achievement

3. RESEARFCH QUESTIONS
1. How does initial math course level effect math major
persistence after 5 years?
• What is the association between initial math course level
and first year math GPA?
2. Do the effects of initial math course level vary for
underrepresented minorities (URM) and women?

4. SETTING
• Southern California
• Researdch institution
• >30,000 undergraduate students
• Highly selective

5. SAMPLE (N=598)
• 9 entering cohorts (2001-2009)
• First-time freshmen
• 55% Female
• 48% first-generation college students
• 51% Asian/Asian American
• 28% White
• URM
• 20% Hispanic/Latino Chicano
• 2% Black/African American
• Median income <$60,000

6. CALCULUS PLACEMENT
Math
2A
Math
2B
AP credit
AB ≥3
Or
SAT≥600
AP credit
AB ≥4
Or
BC=3
AP
credit
BC>3
No Precalculus
in HS
or SAT<600
Math
1A
Math
1B
Math
2D
(remedial)
Precalculus
in HS and
SAT<600

7. Math
2A
Math
2B
Math
2J
Math
3A
Math
3D
Math
2D
Math
2E
Math
8
Teaching
Othertracks
After F13
All
Math
13
LOWER DIVISION
COURSES
Prior F13
Math
2C Prior F01
All
Math
6A
From S06 to
SS10

8. TWO REGRESSION MODELS
OUTCOME VARIABLES
1. Multinomial Logistic Regressions
• Math Degree
• Non-Math Degree
• Left institution prior to completing a degree
2. Binary Logistic Regressions
• Math Degree
• Non-Math Degree

9. INDEPENDENT VARIABLES
Controls
• URM
• Race
• Gender: Female
• First Generation
• Family Income
• High School GPA
Variables of Interest
• SAT (Verbal + Math)
• First Year Math GPA
• Started: PreCalculus
• Started: Higher than Calc
• Started: Level of Math Class

10. FIRST MATH COURSE TAKEN IN COLLEGE,

11. RESULTS
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
How many completed Math Degrees in 5+ years?
Left no degree Non-Math Degree Math Degree

12. Table 1. Results of Logistic Regression Model for Completing a Math Degree, Relative to Leaving the University (n=375)
All Students URM Asian White Male Female
b sig b sig b sig b sig b sig b sig
URM .529 -- -- -- 1.082 .209
Asian 1.353 *** -- -- -- 1.714 ** 1.121 *
Gender: Female .645 * .794 .620 .840 -- --
First Generation .243 .542 .439 -.337 -.472 .816
Family Income .050 -.052 .087 .066 .065 .047
High School GPA 1.104 1.226 .782 1.900 1.222 1.083
SAT (Verbal + Math) -.001 -.002 -.002 .002 -.001 -.002
First Year Math GPA 1.258 *** 1.698 *** 1.928 *** .471 1.242 *** 1.221 ***
Started: PreCalculus -1.366 * -- -- -- -.677 -1.754 *
Started: Higher than Calc 2.253 *** -- -- -- 2.667 ** 1.639
Started: Level^
-- 1.913 ** 1.609 * 1.846 ** -- --
*p<.05, **p<.01, ***p<.001 ^Ordinal variable was used instead of dichotomous measures due to small cell sizes in
disaggregated data
RESULTS: MATH DEGREE VS. LEAVING

13. RESULTS
Table 2. Results of Logistic Regression Model for Completing a non-Math Degree, Relative to Leaving the University (n=328)
Non-Math Degree
All Students URM Asian White Male Female
b sig b sig b sig b sig b sig b sig
URM -.292 -- -- -- -.086 -.428
Asian .888 * -- -- -- 1.128 * .782
Gender: Female .657 * .858 .671 .715 -- --
First Generation .022 -.386 .159 -.111 -.062 .139
Family Income .046 -.102 .063 .077 .073 .025
High School GPA .843 .705 1.215 .798 .544 1.194
SAT (Verbal + Math) -.001 -.001 .001 -.002 .000 -.001
First Year Math GPA .498 ** .670 * .920 ** .303 .615 ** .298
Started: PreCalculus .133 -- -- -- 1.015 -.315
Started: Higher than Calc .945 -- -- -- 1.660 * -.114
Started: Level^ -- .316 .200 .384 -- --
*p<.05, **p<.01, ***p<.001 ^Ordinal variable was used instead of dichotomous measures due to small cell sizes in
disaggregated data

14. Table 3. Results of Logistic Regression Model for Completing a Math Degree, Relative to Completing a Non-Math Degree (n=493)
All Students URM Asian White Male Female
b sig b sig b sig b sig b sig b sig
URM .788 * -- -- -- 1.058 .639
Asian .408 -- -- -- .476 .330
Gender: Female .017 -.152 .026 .073
First Generation .138 .654 .230 -.368 -.437 .555
Family Income .007 .036 .026 -.012 -.005 .026
High School GPA .225 .555 -.461 1.514 .601 -.221
SAT (Verbal + Math) -.001 .001 -.003 .005 -.001 -.001
First Year Math GPA .823 *** 1.434 ** 1.041 *** .068 .652 ** 1.027 ***
Started: PreCalculus -1.455 ** -1.586 -1.433 *
Started: Higher than Calc 1.318 *** -- -- -- .974 * 1.830 ***
Started: Level^ 1.652 ** 1.357 *** 1.322 ** --
*p<.05, **p<.01, ***p<.001 ^Ordinal variable was used instead of dichotomous measures due to small cell sizes in disaggregated
data
RESULTS

15. INITIAL PLACEMENT MATTERS BECAUSE IT
INFLUENCES GRADES IN SUBSEQUENT COURSES
First Term GPA

16. INITIAL PLACEMENT MATTERS BECAUSE IT
INFLUENCES GRADES IN SUBSEQUENT COURSES
Table 4. Results of Dunnet T3 Post-Hoc Tests Comparing Math GPA in First Term and First Year, by Starting Level
First-Term Math GPA First-Year Math GPA
First Group Second Group
1st Group
Mean
2nd Group
Mean
Mean
Diff.
1st Group
Mean
2nd Group
Mean
Mean
Diff.
Precalculus Calculus 2.78 3.01 -0.23 2.33 2.82 -0.49 **
Precalculus Higher than Calculus 2.78 3.17 -0.38 2.33 3.07 -0.74 ***
Calculus Higher than Calculus 3.01 3.17 -0.16 2.82 3.07 -0.25 **
**p<.01, ***p<.001