Promoting Equality and Inclusion in Graduate Education at US - - PowerPoint PPT Presentation

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Promoting Equality and Inclusion in Graduate Education at US - - PowerPoint PPT Presentation

Jun 19, 2023 10 likes •524 views

Promoting Equality and Inclusion in Graduate Education at US Research Universities: Structures and Practices in the Mathematical, Physical, Environmental Sciences & Engineering Colette Patt, PhD Asst. Dean, for Diversity, Equity and

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Promoting Equality and Inclusion in Graduate Education at US Research Universities: Structures and Practices in the Mathematical, Physical, Environmental Sciences & Engineering

Colette Patt, PhD

  • Asst. Dean, for Diversity, Equity and Inclusion,

Mathematical and Physical Sciences, UC Berkeley) Mark Richards (Provost and Executive Vice President, University of Washington) Rodolfo Mendoza-Denton (Professor of Psychology, Richard &Rhoda Goldman Distinguished Professor, UC Berkeley) and our colleagues at the UC Berkeley MPS Dean’s Diversity Office, The California Alliance Research Team, and the Research Exchange

Supported by the National Science Foundation– Alliance for Graduate Education and the Professoriate This material is based upon work supported by the grants: 1647273, 1742065, 1306595, 1306683, 1306747, 1306760. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Ensuring equitable access to academic careers in STEM is vital to the long term health of science and also is a matter of fairness, and justice

  • Research universities’ STEM doctoral programs produce most of the US’s advanced

research workforce (FFRCs, industry, gvt)

  • STEM fields lead to some of the most lucrative careers in all sectors
  • At large research universities, such as University of California’s 10 campus system,

more than 50% of all tenure and tenure-track faculty are in STEM, this influences academic culture

  • Among research universities, top research universities disproportionately produce

the US professoriate– these institutions have an exponential impact on STEM.

Clauset A, Arbesman S, Larremore D (2015) Systematic inequality and hierarchy in faculty hiring networks. Science Advances 1:e1400005-e1400005. UCOP 2017 Accountability Report

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US STEM faces a serio ious challenge:

  • At each level of the Science, Technology, Engineering and Mathematics (STEM)

educational and career path, there is less representation of US minorities (URMS) -- Hispanics, Latinx, Chicanx, African Americans, Indigenous Peoples of the US.

  • Despite approx. $2.9 billion/year in federal funds, the situation has remained mostly

stagnant for 50 years.

  • Most severe UR is in Mathematical, Physical, Environmental Science &Engineering

(MPESE). Problem is most severe at major research universities.

  • Since 2000, URM share of MPESE PhDs has increased from 5% to 10%, but this has

not yet resulted in diversification of the faculty, esp. the tenure-track faculty

  • URM share is~6%-7% domestic postdocs, ~2% of all US (domestic + international)

postdocs.

  • Absolute number of postdoc & faculty positions has increased substantially, but URM

share has not kept pace.

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US Population ~30% URM

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US Population ~30% URM

US STEM BA/BS: ~20% URM

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Mathematical, Physical, Environmental Sciences and Engineering (MPESE) PhDs: ~10% URM

US Population ~30% URM

US STEM BA/BS: ~20% URM

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MPESE PhDs: ~10% URM

US Population ~30% URM

MPESE Postdocs: ~6-7% URM US STEM BA/BS: ~20% URM MPESE Tenure/te nure track Faculty: ~6% URM

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MPESE PhDs: ~10% URM

US Population ~30% URM

MPESE Postdocs: ~6-7% URM US STEM BA/BS: ~20% URM Missing URM MPESE Faculty: ~24%

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MPESE PhDs: ~10% URM

US Population ~30% URM

MPESE Postdocs: ~6-7% URM US STEM BA/BS: ~20% URM Missing URM MPESE Faculty: ~24%

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MPESE PhDs: ~10% URM

US Population ~30% URM

MPESE Postdocs: ~6-7% URM US STEM BA/BS: ~20% URM Missing URM MPESE Faculty: ~24%

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What accounts for the persistence of inequitable access from the doctoral to the postdoc level and the professoriate for URMs? What can we do to address this? The US population demographics are changing rapidly –so stagnation means we are actually losing ground.

  • Preparation?
  • Sense of belonging?
  • Advising?
  • Mentorship?
  • Bias?
  • Exclusion, intentional or unintentional?
  • Finances?
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Berkeley Life in Science Survey (BLISS) Study Graduate Student Progress (Winter-Spring 2013) Survey of MPESE UC Berkeley doctoral students asked about wide range of experiences and perceptions at each stage of the path to the PhD

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Total Completers Percent Non-URM men 555 218 39% Women 383 204 53% URM 109 55 50% M&PS 398 165 41% EECS 234 88 38% Chemistry 381 199 52%

Participation rates (graduate students)

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Won a fellowship or grant

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Urm Female Male, Non-URM

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Passed Qualifying Exams

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Urm Female Male, Non-URM

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Submitted a Paper for Publication

0% 10% 20% 30% 40% 50% 60%

URM Female Male, non-URM

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0% 20% 40% 60% 80% 100% Chemistry EECS+MPS All Underrepresented Minority Women Non-URM Men

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0% 20% 40% 60% 80% 100% Chemistry EECS+MPS All Underrepresented Minority Women Non-URM Men

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0% 20% 40% 60% 80% 100% Chemistry EECS+MPS All Underrepresented Minority Women Non-URM Men

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PhD Exit Survey Findings

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PhD Exit Survey (1998-2013)

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Respondent Headcount: PhD Exit Survey Division Total Non-URM Men Women URM Bio 1,563 690 812 103 Chemistry 1,273 814 415 66 EECS 692 559 107 22 MPS 1,242 939 244 59 Mathematics 377 298 55 26 Physics 502 408 65 23 All 4,770 3,002 1,578 250

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Respondent Headcount: PhD Exit Survey Division Total Non-URM Men Women URM Bio 1,563 690 812 103 Chemistry 1,273 814 415 66 EECS 692 559 107 22 MPS 1,242 939 244 59 Mathematics 377 298 55 26 Physics 502 408 65 23 All 4,770 3,002 1,578 250

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PhD Exit Survey Questions

  • “Did you deliver any papers at national scholarly meetings?”
  • “Were you encouraged by faculty in your department to

publish?”

PhD Exit Survey Findings 24

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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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0% 20% 40% 60% 80% 100% Mathematics Physics Bio Chemistry EECS MPS All Underrepresented Minority Women Non-URM Men

  • Fig. 2. Papers presented at national scholarly meetings (Ph.D. exit survey). Note: Error bars represent 1 SE.
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We published the results: Mendoza-Denton, R., Patt, C., Fisher, A., Eppig, A., Young, I., Smith, A., & Richards, M. A. (2017). Differences in STEM doctoral publication by ethnicity, gender and academic field at a large public research university. PLoS One, 12(4), e0174296. doi: 10.1371/journal.pone.0174296.

We wanted to understand: What’s happening in Chemistry at Berkeley?

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NSF-California Alliance for Graduate Education and the Professoriate (Berkeley, UCLA, Caltech, Stanford)

Fisher AJ, Mendoza-Denton R, Patt C, Young I, Eppig A, Garrell RL, et al. (2019) Structure and belonging: Pathways to success for underrepresented minority and women PhD students in STEM fields. PLoS ONE 14(1): e0209279.

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NSF-California Alliance for Graduate Education and the Professoriate (Berkeley, UCLA, Caltech, Stanford)

Cross-institutional study to:

  • Examine pathways to success among a larger group of students (Total: 435;

URM: 232; Asian: 54; White:149)

  • Survey included: publication rates, subjective well-being and distress,

student experience in PhD program, relationships with peers, progress in doctoral program, psychological factors. The selected measures enabled us to focus on our specific interest in sense

  • f belonging and publication success.

Chemistry did not stand out as it had at Berkeley, We found some of the same differences for women and minorities, especially African Americans.

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Female Students URM Students Prepared for Grad Classes Prepared for UG Classes Feel Insignificant in STEM Perceived Success (vs. peers) Level of Distress Clear Expectations Clear Perform. Standards Feel Accepted in STEM

  • .25
  • .17
  • .12
  • .15

.24

  • .30

.14 .25

  • .24

.39 .25

  • .15
  • .30
  • .16
  • .22

*Not pictured: direct effect of Female Students on Distress, β = .19

Path Modeling

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Relevant Results

  • There is a relationship between publication and graduate student distress

that disproportionately effects women and URMs

  • Clear departmental expectations mitigate distress (total effect = -.11)
  • As do clear departmental performance standards, -.22
  • Taken together, clear expectations and standards have a combined effect
  • f -.33
  • 11% of the total variance

Does Chemistry have clearer expectations and performance standards, especially related to publication?

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Please return form to the Graduate Assistant in 419 Latimer Hall. Please indicate whether you would like this evaluation to become a part of the Graduate Student Record, which is completely accessible to the graduate student. Otherwise this evaluation will be returned to you at the conclusion of the examination. I would like this evaluation to become a part of the Graduate Student Record. Yes / No (circle one) PRE-QUALIFYING EXAM GRADUATE STUDENT EVALUATION Student Name:

Research Director:

Please evaluate the above student in the following areas with regard to research capability (a possible scale might be superior, excellent, good, average, below average). Address your comments to the Chair of the Qualifying Exam committee. Probable Creativity: Innate Scientific Curiosity and Motivation: Research Progress to Date: Technical Ability: Major Strengths: Major Weaknesses: Roughly when would you expect this student to submit a paper for publication? Please rank this student (from 1.0 to 4.0, 1.0 being “the best”) at this stage in their career: Signature: Date:

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From other studies we know that :

  • Ambiguity provides fertile ground for the expression of prejudice

(Dovidio & Gaertner, 2000)

  • Unclear expectations and ambiguous judgments are common in

graduate education and include “expectations of brilliance” (I’ll know it when I see it) (Leslie, Cimpian, Meyer, & Freeland, 2015)

  • Virtually all steps leading to publication involve judging ambiguous

stimuli:

  • Ideas
  • Methods
  • Findings
  • Write-ups
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Preliminary diagnosis: All students benefit from an appropriate balance of Structure

(inconsistent in STEM: costs very little to address!!!)

+ Support and Belonging

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Berkeley-University of Washington 3 year qualitative study to understand how Berkeley Chemistry is achieving equitable outcomes We plan to identify other departments achieving equitable outcomes, identify the key features of departments that have equitable outcomes, then develop a publicly-available standardized measure for departments to use to assess their own program structure, culture and belonging.

& Collaborative interventions with key partner universities with the California Alliance for Graduate Education and the Professoriate, with support from the National Science Foundation and the Washington Research Foundation

Next steps: Qualitative Research

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Research Exchange

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The Cali lifornia All lliance Project (NSF/AGEP)

  • Who? Berkeley, Stanford, Caltech, UCLA

++ Michigan, Harvard, Georgia Tech, UT Austin, UW

  • Why these institutions? collective prestige and desire to win
  • What?

Focus on Mathematical, Physical, Computer and Engineering Sciences (MPCES) (advanced PhD students and postdocs) Program elements: postdoctoral fellowship competition professional development and retreats [research] The Research Exchange (RE)

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Research Exchange

  • Brief, carefully-mentored, and structured inter-institutional visits

(advanced PhD students and postdocs)

  • Basically hacking the existing ”old-boy” network → structural visibility
  • Although relatively new, already have placed about 90 participants
  • Results include new research collaborations, co-authored papers, postdoc

and faculty job offers, increased interest in faculty jobs

  • Our ambition:
  • Expand the RE to include top 25 URM PhD-producing institutions, capture about 50%
  • f all URM PhD students and postdocs
  • Double the number of URM faculty in the MPCES fields at American Research

universities in the next 5-10 year

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Research Exchange

  • Brief, carefully-mentored, and structured inter-institutional visits

(advanced PhD students and postdocs)

  • Basically hacking the existing ”old-boy” network → structural visibility
  • Although relatively new, already have placed about 90 participants
  • Results include new research collaborations, co-authored papers, postdoc

and faculty job offers

  • Our ambition:
  • Expand the RE to include top 25 URM PhD-producing institutions, capture about 50%
  • f all URM PhD students and postdocs
  • Double the number of URM faculty in the MPCES fields at American Research

universities in the next 5-10 year

“Hey Joe, I’ve got this great student….”.

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Retreats and Professional Develo lopment

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Thank You!

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Extra slides

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Path Modeling

  • Extension of regression
  • Paths represent directional effects
  • Change in X predicts change in Y
  • Strength of relationship expressed as a coefficient between -1

and 1 (like a correlation)

  • Path model allows concurrent and successive estimations that

connect variables

  • Different models are fitted to the data and the best one is

chosen based on model estimates

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Percentage of people recommending a job candidate for hire based on candidate race and strength of resume

10 20 30 40 50 60 70 80 90 100

strong ambiguous weak White candidate Black candidate % recommending Resume strength Dovidio & Gaertner, 2000

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