examining interventions to reduce stereotype threat in undergraduate mathematics
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Examining Interventions to Reduce Stereotype Threat in Undergraduate Mathematics. Dr. Jessica M. Deshler Department of Mathematics West Virginia University, USA. Randomised Controlled Trials in the Social Sciences, 9 th Annual Conference University of York, UK, September 2014. - PowerPoint PPT PresentationTRANSCRIPT
Examining Interventions to Reduce Stereotype Threat in Undergraduate Mathematics
Dr. Jessica M. DeshlerDepartment of Mathematics
West Virginia University, USA
Randomised Controlled Trials in the Social Sciences, 9th Annual Conference
University of York, UK, September 2014
Context for the Study
My background: B.S., M.S. & Ph.D. in Mathematics
Research: applied mathematics mathematics education
Approaching studies in the undergraduate classroom as both a researcher (mathematics, education) and an instructor.
West Virginia University
Research Intensive, public, land-grant university
Morgantown, West Virginia
Fall 2013 Enrollment ~ 23,000 Undergraduate students
~ 5,000 Graduate students
Stereotype Threat
Being at risk of confirming, as self-characteristic, a negative stereotype about one’s group. (Steele & Aronson, 1995)
Has been shown to reduce the performance of individuals who belong to negatively stereotyped groups. (Steele, 1997).
Women & Mathematics
“When women perform math, unlike men, they risk being judged by the negative stereotype that women have weaker math ability.”
-(Spencer, Steele & Quinn, 1999)
Why do we need to support women/girls in mathematics?
Diverse populations bring diverse perspectives –
Diversity Trumps Ability (Page, 2008)
If all of our students (employees, coworkers, etc.) have the same backgrounds (experiences, perspectives), they can’t work as efficiently to solve problems.
In US, 31% of PhDs in Mathematics (NSF, 2012) are women, but only 21% of tenure track faculty in mathematics departments.
Our Study
Interventions have been shown to reduce stereotype threat in a laboratory setting.
Research Question: Would the interventions work in an actual undergraduate mathematics classroom?
Our implementation: Use two laboratory interventions in a college calculus class.
Does the data support the laboratory findings?
Values Affirmation Intervention
Students ranked 5 personal characteristics Creativity, Humor, Physical Attractiveness, Social
Skills & Relationships with friends/family
Describe importance of highest ranked characteristic
Describe a time in life this was important
Control: Rank same 5 characteristics but write about his/her least valuable attribute & why it’s important to others.
Role Model Intervention
A reading on a fictitious female WVU student majoring in mathematics (and education) who has been successful in mathematics, college, etc….
Picture
Control: A reading about business/industry, not focused on specific people.
Participants
Calculus I class - two sectionsStudents were not mathematics majors48 women, 76 menOne class period (not at the institution where these were used in the lab)
Randomly Assigned to one of: Control (no interventions)Values Affirmation intervention ONLYRole Model intervention ONLYBOTH Interventions
Design
Randomly assigned, blocked by gender, to one of two conditions, both conditions, or neither condition.
Neither
Values Affirmatio
n
Role Model Both Total
Female 12 14 9 13 48
Male 18 15 24 19 76
Plots by Intervention & Gender
0
2
4
6
8
10
12
14
16
Role Model Both ControlValues Affirmation
Means by Treatment: Female
Means by Treatment: Male
Procedural Results
Female Male
Conceptual Results
Female Male
Is this a real effect?
Concern about self-selection into the course
Sample size too small to detect the effects we saw (first time using an authentic measure)
Sample was chosen based on what worked in the lab – where the math test was GRE-like
Characteristics of Participants
0 20 40 60 80 100 120 1401.5
2
2.5
3
3.5
4
4.5
GPA by Gender
FemaleMale
Participant
GP
A
Results – Continued
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Role Model Intervention
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
2
4
6
8
10
12
14
16
18
Values Affirmation
FemaleMale
GPA
Calc
ulu
s S
core
Results - Continued
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Both
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Control
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Role Model Intervention
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20Values Affirmation
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Both
FemaleMale
GPA
Calc
ulu
s S
core
1.75 2.25 2.75 3.25 3.75 4.250
5
10
15
20
Control
FemaleMale
GPA
Calc
ulu
s S
core
Next Steps
Now that we have a sense of real performance on this assessment, run the experiment with a reasonable sample size.
Pay more careful attention to the randomization procedures, rather than having to fix problems later through the model
The experiment is cheap, relatively speaking (cost is in time)
Advice?
References
National Science Foundation. 2012. Women, Minorities, and Persons with Disabilities in Science and Engineering .
Page, S. (2008). The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools and Societies Steele, C. (1997). A threat in the air: How stereotypes shape intellectual identity and performance, American Psychologist, 52 (6)
Steele, C.M. & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans, Journal of Personality and Social Psychology 69 (5)
Spencer, S.J., Steele, C.M. & Quinn, D.M., (1999). Stereotype Threat and Women’s Math Performance, Journal of Experimental Social Psychology, 35 (1)
Acknowledgements
Research Team:
Elizabeth Burroughs, Mathematics, Montana State University (Visiting at University of York)
Jessi Smith, Psychology, Montana State University
Rachel Matsumoto, Graduate student, Psychology, Montana State University