Developing a Racial Diversity Index
for California Community Colleges
Alice van Ommeren
RP Group Conference – April 2011
Background
Increasing attention to reducing the
achievement gap (outcomes)
 Policymakers and administrators are
inquiring about the racial disparities
 Researchers are being tasked to
measure inequities and disparities
 Importance of capturing the racial
diversity of the student body (access)

Statement of the Problem
Aware that we have a diverse system
and been considerate in reporting
 Nature of the CCC’s racial composition
has been relatively unexamined
 The relationship between student
diversity as a covarariate or predictor
variable has not been explored

Purpose of the Study
Examine the empirical nature of racial
composition and diversity of the
student population across the
California community colleges
Study Objectives




Discuss types of diversity measures and
relevant studies in higher education
Develop racial diversity indices for each
of the community colleges
Describe the indices and potential use
as adjustment variables
Discuss application of the indices for
researchers and policymakers
Caution
Racial categories are constructs and do
not capture social, cultural, economic
and political issues surrounding racial
diversity
General Methodology
Datasets
 Early Racial Composition Measures
 Diversity Range and Variability
 Diversity Indices
Analysis
 Exploratory Data Analysis
 Correlations and Scatterplots
Specific Methodology




Measures and indices for 111 colleges
from Data Mart (Annual 2009-10)
Removed 3 of the 9 categories
(American Indian, 2 or more, unknown)
Descriptives, also used histograms and
boxplots to identify outliers
Relationship among the diversity
measures & indices
Racial Composition Measures

Percent White
Simplest measure, most common in early studies

Percent Minority
Alternative to % white, measure of racial minority

Percent Underrepresented Minority (URM)
Another alternative, historically underrepresented
in completing college.
For this study, defined as Hispanic, Black, Filipino
and Pacific Islander
Descriptives of Diversity Measures
Overall
Mean
Overall
Median
Highest
College
Lowest
College
% White
40%
37%
83%
1%
% Minority
59%
62%
99%
17%
% URM
48%
48%
97%
14%
% Black
9%
5%
58%
1%
% Hispanic
34%
32%
91%
11%
% Asian
11%
7%
45%
1%
Racial Composition (CCC) over Time




Percent of White has decreased over
time (55% in 1992 to 38% in 2010)
Percent of Black in CCC has stayed at
8% since 1992, Filipino and Pacific
Islander has also stayed the same
Hispanics increased from 21% to 36%
and Asian from 15% to 18%
All these patterns are consistent with
state population changes
Dimensional Diversity Measures

Diversity Range
Difference between the lowest and highest
Skewness = 100% - (% highest - % lowest)

Diversity Variability
Measures the spread, standard deviation
SqRt (1 – ((%white-m)2 + (%black-m)2 + ….)/k)
Descriptives of Dimensional Measures
Overall
Mean
Overall
Median
Highest
College
Lowest
College
Div. Range
49%
52%
76%
9%
Div. Variability
81%
81%
91%
67%
Diversity Index



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Sensitive to proportional differences,
takes into account all categories
Intended to measure how much “variety”
or “spread” a college or district has
among its racial groupings
Measures the probability that any two
randomly selected students will be in the
same racial grouping
Ranges from 0 (no diversity) to 1
(complete diversity)
The Use of Diversity Indices
Ecology
 Measure biodiversity in ecosystems
Economists
 Measure distribution of sectors
Demographers
 US Census Bureau
 USA TODAY Diversity Index
Diversity Indices in Education

U.S. New & World Report
– Utilized in their ranking

Edsource, Ethnic Diversity Index for CDE
– A characteristic of the school or district

CSU Dominguez Hills (2005)
– WASC Diversity Sub Committee

Educational benefits with diversity
– U.S. Supreme Court (UC in 1978), SLO’s
Types of Diversity Indices

Many different types of indices
– Specific to field of study and purpose

Simpson’s Diversity Index
– Origins in Ecology
– Sensitive to richness (number of categories) and
evenness (number of students in category)
– More weight to number of categories
– Ranges between 0 to 1
Simpson’s Diversity Index
DS= 1 - Sum1i [ni*(ni-1)]/[N*(N-1)]
Ds = 1 - 40(39) + 25(24) + 15(14)
80(79)
= 1 - 2370
6320
= 1 - 0.375
= 0.625
Descriptives of Diversity Indices
Overall
Mean
Overall
Median
Highest
College
Lowest
College
Simpson (6)
.60
.62
.79
.18
Simpson (5U)
.52
.54
.72
.17
*U/UMR – Combining Asian and White
Discussion of Distribution

High Diversity Indices
– Colleges with even spread among White, Black
and Asian (mostly Bay Area colleges)
– Using UMR, even balance with Black and
Hispanic groups (outside the Bay Area)

Low Diversity Indices
– Colleges with both high Hispanics (Imperial) and
high White (Shasta, Redwood, Siskiyous)
– This was consistent with UMR index
Thought from the Literature
The diversity index captures the idea that
the diversity of races matters but that which
race is in the majority and which in the
minority does not matter at all
Correlations with Outcome Measures
Progress
Rate
30 Units
Rate
Basic
Skills
Transfer
Rate
Simpson (6)
.242*
.106
.119
.221*
Simpson (5U)
-.119
-.184
-.079
-.116
Other Measures & Indices
Segregation Measures
 Dissimilarity Index
– Segregation between two social groupings

Exposure Index
– Measures a single groupings average
exposure to all groupings
Research Limitations


Index does not single out and give more
weight to one racial group over another
Does not incorporate other student
characteristics, such as the largest racial
group, percent English learners, etc.
Research Results

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California community colleges racial
composition is diverse across the system
This study lays the empirical groundwork
for explaining diverse student populations
Provides an important characteristic of the
campus, useful in describing the college
Relationship with diversity indices and
SPAR and Transfer Rate, needs exploring
Conclusions



California community colleges racial
composition is diverse across the system
Colleges with high diversity indices are in
the Bay Area with large Asian proportions
Relationship with high diversity indices
and SPAR and Transfer Rate
Further Research for Colleges




Track your college diversity measures
and indices over time
Compare college diversity index to
district, service area or peer group
Contrast student diversity index to
faculty diversity index
Create different types of college diversity
indices and evaluate
Further Research for System



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Explore the effect of the index in a
multivariate relationship
Develop service area indices and
compare with college indices
Explore other dimension of diversity,
such as age, gender, socioeconomics
And….
Handouts & Contact Information
References and Indices
 Alice van Ommeren at 916.327.5878
avanommeren@cccco.edu
