the persistence of the gender gap in introductory physics lauren kost steven pollock, noah...
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The Persistence of the Gender Gap in Introductory Physics
Lauren Kost
Steven Pollock, Noah Finkelstein
Department of Physics,
University of Colorado at Boulder
July 21, 2008
Acknowledgments• Physics faculty:
Michael DubsonNoah FinkelsteinKathy PerkinsSteven PollockCarl Wieman
• Ph. D. students:Charles BailyLauren KostBenjamin SpikeChandra Turpen
• Postdocs:Stephanie ChasteenSteven GoldhaberLaurel MayhewSam McKaganArchie PaulsonNoah Podolefsky
• School of Ed members:Valerie OteroKara GrayBud Talbott III
This material is based upon work supported by the National Science Foundation under Grant No. REC 0448176, CAREER: Physics Education and Contexts of Student Learning. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the NSF
MotivationAIP Statistics:
50% of physics students in HS are female22% of bachelors in physics go to females10% of faculty in physics are female
Lorenzo et. al. Am. J. Phys. 74, 118 (2006)
Harvard Claim:Fully interactive courses eliminate the gender gap.
Interactive Engagement techniques better than Traditional Lecture
Hake, Am. J. Phys. 66, 64 (1998)
Gender Gaps at CU Boulder
0
2
4
6
8
10
12
14
16
18
20
Partial Partial Partial
Level of Engagement
FM
CE
<S
>M
- <
S>
F (
%)
Pretest Posttest
Gender Gaps at CU Boulder
0
2
4
6
8
10
12
14
16
18
20
Partial Partial Partial Full Full Full Full
Level of Engagement
FM
CE
<S
>M
- <
S>
F (
%)
Pretest Posttest
Gender Gaps at CU Boulder
0
2
4
6
8
10
12
14
16
18
20
Partial Partial Partial Full Full Full Full All
Level of Engagement
FM
CE
<S
>M
- <
S>
F (
%)
Pretest Posttest
Conclusions (I)
• Despite fully interactive techniques, gender gap persists at our institution
• Harvard claims results independent of instructor, we see otherwise
• Where does the gender gap come from? Why does it exist?– Do gender differences exist in other
aspects of the introductory course?
Gender Gaps in Course Grades
-10 -5 0 5 10
Course Grade
Exams
Participation
Homework
<S>M - <S>F (%)
Females higher Males higher
Gender Gaps in CLASS Shifts
Gender Gaps in BackgroundEffect Size
HS GPA * 0.47
SAT – Math * 0.33
ACT – Math * 0.14
Females Males1 year HS Physics * 80% 89%
1 year HS Calculus 70% 67%
* = statistically significant difference
0
10
20
30
40
50
60
70
80
90
100
0 <= S <= 12 12 < S <= 18 18 < S <= 27 27 < S <= 45 45 < S <= 100
FMCE Pretest score (%)
Av
g. F
MC
E P
os
tte
st
sc
ore
(%
)
Females Males
Impact of Pretest on Post Test
rpre,post = 0.56
37% 19%
8% 22%
21% 16%
14% 22%20% 21%
Regression Analyses
• Control for prior physics and math knowledge and incoming attitudes and beliefs
• Multiple Regression– The average posttest gender difference is 3%
(reduced from the observed difference of 10%).
– 70% of the gender gap is accounted for by background differences.
Conclusions• Gender differences exist in several aspects
• Males and females are differently prepared
• Differences in male and female backgrounds account for about 70% of the gender gap
Thank You
• Find more info at:
http://per.colorado.edu
• Pollock, et al, PRST PER 3, 010107 (2007)
• Kost, et al, PERC Proceedings 2007, p. 137
• PRST PER paper in review
• Poster at PST4 from 5 – 6 PM on Tuesday
Courses, Student Population, and Data• 7 semesters introductory, calculus-based mechanics
– 3 semesters Partially Interactive (without Tutorials)– 4 semesters Fully Interactive (with Tutorials)
• Student population– 25% female– 50% engineering majors (6% physics majors)– 80% white
• Data sources– Matched FMCE pre/post data (N ~ 2100)– Matched CLASS pre/post data (N ~ 1900)– Course grades (N ~ 3600)– Demographic and background data (N ~ 3600)
Gender Gaps at CU Boulder
Pollock, et. al. Phys. Rev. ST PER, 3, 010107 (2007)
0
2
4
6
8
10
12
14
16
18
Partially Interactive Fully Interactive
<S
>M
- <
S>
F (
%)
Pretest Posttest
Multiple Regression
• What is the difference between a male’s and a female’s scores, after controlling for several important factors?
• Sample of 1027 students (30% of population)
Building the Model
Dependent Variable: FMCE Posttest
Independent Variables: Gender
FMCE Pretest
Math Score
CLASS Pre Overall Fav
Other Independent Variables:
HS GPA
HS Physics
HS Calculus
Ethnicity
Regression Model
PREFEMALEb
CLASSb
MATHbPREb
FEMALEbbPOST
5
4
32
10
Interaction: gender & pretest
Females
Males
Regression Model
PREFEMALEb
CLASSb
MATHbPREb
FEMALEbbPOST
5
4
32
10
Gender Effect
PREbb 51EffectGender
CLASSbMATHb
PREbbPOST
43
20 :M
CLASSbMATHb
PREbbbbPOST
43
5210 )( :F
Regression ResultsModel Summary
.650 .423 .420 21.10490Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
ANOVA
333098.7 5 66619.747 149.567 .000
454770.7 1021 445.417
787869.5 1026
Regression
Residual
Total
Model1
Sum ofSquares df Mean Square F Sig.
Coefficients
31.459 2.954 10.650 .000
-9.978 2.618 -.163 -3.811 .000
.585 .040 .426 14.663 .000
.225 .085 .112 2.659 .008
.242 .043 .140 5.617 .000
7.241 .871 .216 8.311 .000
(Constant)
GENDER2
FMCEPRE
GEND_FMCEPRE2
@1110_PRE_OV_FAV
MATHCOMBINED
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Regression Results
PREFEMALE
CLASSMATH
PREFEMALEPOST
2.0
2.07
6.01031
PRE 2.010EffectGender
Gender Effect
-10
-8
-6
-4
-2
0
2
4
6
8
10
0 10 20 30 40 50 60 70
FMCE Pretest (%)
Ge
nd
er
Eff
ec
t (M
-F)
Conclusions
• Even when controlling for physics background, math skills, and attitudes and beliefs, gender is still a significant factor in posttest score.
• Accounted for only 43% of variation in post test scores, other factors to consider
Normalized Gain
0
0.1
0.2
0.3
0.4
0.5
0.6
IE 1 IE 2
Avg
. N
orm
aliz
ed G
ain
Females Males
Normalized Gain by semester
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
SP 04 Tut
FA 04 Grps
SP 05 Trad
FA 05 Trad
SP 06 Tut
FA 06 Tut
SP 07 Tut
ALL
Av
g.
No
rma
lize
d G
ain
Females Males
Multiple Regression
Gender Gaps in Physics 2
0
5
10
15
20
25
Fall 04 Spring 05 Fall 05 Spring 06 Fall 06 Spring 07 All
<S
>M
- <
S>
F
0
5
10
15
20
25
30FMCE Posttest BEMA Pretest BEMA PosttestN
/A
Gender Gaps in Physics 2
0
5
10
15
20
25
Fall 04 Spring 05 Fall 05 Spring 06 Fall 06 Spring 07 All
<S
>M
- <
S>
F
0
5
10
15
20
25
30FMCE Posttest BEMA Pretest BEMA PosttestN
/A
Matched Analysis – 1110 Gain
rpre,gain = 0.281
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 <= S <= 12 12 < S <= 18 18 < S <= 27 27 < S <= 45 45 < S <= 100
Females Males