Post on 14-Dec-2015
A History of STEM Participation
• Spotty before WWII
• Women’s wartime opportunities (the first “computers”— “Men built the machines, but women made them work”)
• Access to education for minorities (separate and unequal; not “science material”)
STEM Education for All: Why Doesn’t this Yet Compute?
The Post-Sputnik Push
• NDEA and financial support for STEM study
• Teacher preparation
• New curricula
• Science experiences
• “Incidental inclusion”
STEM Education for All: Why Doesn’t this Yet Compute?
Structural Barriers in STEM Education
• Segregation of schools and under-resourcing of schools serving URM students- Barriers to students w/ disabilities in schools
- Curricular options
• Cultural assumptions re: capacity and/or interest
• Program segregation (home ec vs. shop; “Girls High)
STEM Education for All: Why Doesn’t this Yet Compute?
The Legal and Judicial Battles for Access
• Brown vs. Board of Education of Topeka, Kansas (1954)
• Titles VI and VII (1964)
• Executive Order 11246 (1965)
• Title IX (1972)
• Section 504 (1973)
• DeFunis vs. Odegaard (1974)
• Regents of the University of California vs. Bakke
STEM Education for All: Why Doesn’t this Yet Compute?
The Legal and Judicial Battles for Access (cont’d)
• Science and Engineering Equal Opportunities Act (1980)
• Americans with Disabilities Act (1990)
• Adarand Contractors vs. Peña (1995)
• Grutter vs. Bollinger; Gratz vs. Bollinger (2003)
• Fisher vs. University of Texas-Austin (pending)
• Various state ballot initiatives
STEM Education for All: Why Doesn’t this Yet Compute?
Cultural Battles for Access
• Civil rights movement
• Women’s movement
• Disability rights movement
• More “nuanced” movements within education (First Gen, minority males)
STEM Education for All: Why Doesn’t this Yet Compute?
Historical Approaches and Interventions in the Out of School Space
• Mathematics as a “critical filter” 1973
• Overcoming Math Anxiety 1978
• Expanding Your Horizons (Math/Science Network) 1974
• MESA 1970; MEP 1973
• National Advisory Council on Minorities in Engineering 1974
• Minorities in Engineering: A Blueprint for Action
• AAAS Project on the Handicapped in Science 1975
STEM Education for All: Why Doesn’t this Yet Compute?
What We Learned about STEM Education for All from Out of School Programs (from Equity and Excellence: Compatible Goals)
• Strong academic component in math, science, communications
• Highly qualified teachers who believe students can learn
• Emphasis on applications and career connections
• Interdisciplinary with hands-on opportunities, incorporation of computing
• Multi-year involvement
• Strong leadership with stable, committed staff
STEM Education for All: Why Doesn’t this Yet Compute?
What We Learned from Out of School Programs (cont’d)
• Stable funding base, multiple sources
• Broad recruitment
• Multi-sector cooperation
• Opportunities for in-and out-of-school learning
• Parental involvement/community support
• Specific attention to race/gender related inequalities
• Professionals and staff who look like students
• Peer support systems/ no “tokens”
• Evaluation, follow-up, data collection
• “Mainstreaming” into institutional programs
STEM Education for All: Why Doesn’t this Yet Compute?
What’s Needed In School and Out of School?
• A systems approach
• A clear vision
• Evidence-based strategies
• Content, Context, Culture and Community
STEM Education for All: Why Doesn’t this Yet Compute?
STEM Education for All: Why Doesn’t this Yet Compute?
A System of Solutions
For want of a nail the shoe was lost.
For want of a shoe the horse was lost.
For want of a horse the rider was lost.
For want of a rider the battle was lost.
For want of a battle the kingdom was lost.
And all for the want of a horseshoe nail.
Why Doesn’t this Yet Compute?
• Schools that don’t work for all students (Belief, behavior, practice, policy)
• Accountability without support,using imperfect standards (e.g., teaching to bad tests) (Policy)
• College level programs that don’t work even for the students who get there-- Talking About Leaving
• “Weeding, not cultivating” (Belief)
• Teacher –centered rather than learner centered (Behavior)
• Disciplinary culture (“Hyper-competitiveness” of many STEM fields)
STEM Education for All: Why Doesn’t this Yet Compute?
Framing the Problems
• Attrition
• Interest
• Preparation
• Hard work
STEM Education for All: Why Doesn’t this Yet Compute?
Re-framing the Problems
• Retention
• Attraction
• Support
• Working smart
STEM Education for All: Why Doesn’t this Yet Compute?
Challenges
• Messaging matters
• Money matters
• Where the learning environment is problematic
• The quality of the learning experience
• The culture of STEM
• Reward structure of the academy
STEM Education for All: Why Doesn’t this Yet Compute?
Takeaway Lessons
• Learning from fields with large and consistent increases
• Looking at interventions within fields that share your challenges
• Looking at experiments/interventions in computer science
STEM Education for All: Why Doesn’t this Yet Compute?
Life sciences
• Near universal course taking in high school
• High percentage of in-field teachers
• High percentage of female teachers
• Compelling topics
• “Connection to self/community”
• Critical mass
STEM Education for All: Why Doesn’t this Yet Compute?
Medicine
• Removal of “informal’ barriers via legal remedy
• Perception of openness/fairness more applications from women
• More application more admissions
• Med schools in MSIs
• Compelling topics and strong attraction
• Socially attractive (image and visibility)
• Strong undergrad advisory infrastructure
• Clear pathway
• BUT…….
STEM Education for All: Why Doesn’t this Yet Compute?
Institutions/Departments/Programs that Stand Out for Success
• STC’s vs. regular departments
• Physics vs. Applied Physics at Michigan
• Kati Haycock’s examples http://www.edtrust.org/dc/presentation/access-to-success-in-america-where-are-we-what-can-we-do-1
STEM Education for All: Why Doesn’t this Yet Compute?
Lessons Learned from Successful Efforts
• Un-stack the K-12 deck (A’s are C’s; teacher assignment; course availability; remedial focus)
• Leadership- Student success a priority
• Tap into institutional culture to achieve student success
• “Faculty as problem solvers not problems to be solved”
• Data (disaggregated) for action
• Make mandatory the things that work
STEM Education for All: Why Doesn’t this Yet Compute?
Lessons Learned (cont’d)
• Evaluate programs and make adjustments based on what is learned
• Develop and monitor retention plans
• Highlight the clear pathways to success (Rein in choices)
• Focus on course improvement of introductory and developmental courses
• Use effective advising models
STEM Education for All: Why Doesn’t this Yet Compute?
Unpacking the Data
• Males and females
• Different URMs
• Different disabilities
• Males and females within each URM or disability group
STEM Education for All: Why Doesn’t this Yet Compute?
% Women Bachelor’s Degrees, disaggregated by race/ethnicity in select “High Performance” STEM Fields, 2010
STEM Education for All: Why Doesn’t this Yet Compute?
Agricultural sciences
48% Male
52% Female
42% Male
58% Female
Biological sciences Psychology
23% Male
77% Female
Source: Calculated from NSF, NCES 2010, Table 5.2
% Women Bachelor’s Degrees, disaggregated by race/ethnicity in select “Average Performance STEM Fields, 2010
STEM Education for All: Why Doesn’t this Yet Compute?
Earth, atmospheric, and ocean sciences
39% Female
61% Male
Source: Calculated from NSF, NCES 2010, Table 5.2
42% Female
Mathematics and Statistics
42% Male
58% Male
% Women Bachelor’s Degrees, disaggregated by race/ethnicity in select “Average Performance STEM Fields, 2010
STEM Education for All: Why Doesn’t this Yet Compute?
Chemistry
49% Female 51%
Male
Source: Calculated from NSF, NCES 2010, Table 5.2
30% Female
Chemical engineering
42% Male
70% Male
% Women Bachelor’s Degrees, disaggregated by race/ethnicity in select “Low Performance” STEM Fields, 2010
STEM Education for All: Why Doesn’t this Yet Compute?
Physics
80% Male
20% Female
91% Male
9% Female
Electrical engineering Mechanical engineering
89% Male
11% Female
Source: Calculated from NSF, NCES 2010, Table 5.2
% Bachelor’s Degrees, disaggregated by race/ethnicity in “Low Performance” Computer Science, 2010
STEM Education for All: Why Doesn’t this Yet Compute?
18% Female
82% Male
Source: Calculated from NSF, NCES 2010, Table 5.2
Computer sciences
The Way Forward
• Single-sex education in low performance fields? (Smith College and Picker Engineering)
• Critical mass
• Teacher preparation
• New curricula (more applications, cultural links, career connection)
• Experiences and career exploration (e.g., AAAS Entry Point!)
• “Deliberate inclusion” and questioning absence
STEM Education for All: Why Doesn’t this Yet Compute?