Data Buddies Survey:
2022 Annual
Report
By: CERP Staff
Released: 7/14/2023
Introduction
About The Data Buddies Survey
The CRA Data Buddies Survey (DBS), managed by the CRA Center for Evaluating the Research Pipeline (CERP), is a rich data source providing important information to the community on the state of computing in higher education. After two years of piloting in 2011-2012, participating Data Buddy departments have been distributing the survey to undergraduate and graduate students in computing-related degree programs, as well as students completing non-degree programs, since 2013. In 2014, CERP added a longitudinal component to its data collection efforts and started recruiting cohorts of students to complete follow-up surveys on an annual basis. With this expansion, DBS also collects data from individuals who graduate from their degree program and enter the workforce.
About CERP
The Computing Research Association’s (CRA) Center for Evaluating the Research Pipeline (CERP) is a research and evaluation center whose mission is to promote diversity in computing. CERP serves as a resource for the computing community by supporting efforts to recruit and retain individuals considered underrepresented in computing or historically marginalized (i.e., women; people who are Black/African American, Hispanic/Latinx, Indigenous and First Nations, Native Americans, Alaska Natives, Native Hawaiians, and Pacific Islanders; persons with disabilities; persons from low-income backgrounds; first generation college students; LGBTQIA+ individuals; and veterans). More generally, CERP strives to inform the computing community about patterns of entry, subjective experiences, persistence, and success among individuals involved in academic programs and careers related to computing.
CERP was created by the Committee on the Status of Women in Computing Research (CRA-W)/Coalition to Diversify Computing (CDC) Alliance through a National Science Foundation grant to the Computing Research Association (CNS-1246649). For more information about CERP, visit https://cra.org/cerp/. You can reach CERP Staff at cerp@cra.org.
Important Definitions
Below are some definitions of abbreviations or terms that are used throughout the report:
General Terms
DBS: Data Buddies Survey
High Response Rate institutions: Institutions that had a response rate of 20% or greater, based on the number of students to whom they distributed the survey.
CRA member institutions: While participation in the Data Buddies Survey is not limited to CRA members, a majority of our participating institutions are CRA members.
MSIs: Minority Serving Institutions. From our participating institutions, this includes Historically Black Colleges and Universities (HBCUs), Hispanic-Serving Institutions (HSIs), Tribal Colleges and Universities (TCUs), and Asian American and Native American Pacific Islander Serving Institutions (AANAPISIs).
Student Terms
BHN: “African American/Black, Hispanic/Latino(a), and Native American/Alaskan Native.” In line with recent discussions about race and ethnicity within the computing community, we have followed recent recommendations to update how we refer to diverse groups of students, particularly students who are underrepresented in computing based on one or more of their identities. Click here to read more about why we updated our language.
AW: “Asian, White/Caucasian.” In line with recent discussions about race and ethnicity within the computing community, we have followed recent recommendations to update how we refer to diverse groups of students, particularly students who are underrepresented in computing. Click here to read more about why we updated our language.
Undergraduate students: Survey respondents who are enrolled in an undergraduate degree at the time of their response. This includes both Associate’s and Bachelor’s degree programs.
Graduate students: Survey respondents who are enrolled in a graduate degree at the time of their response. This includes both Master’s and Doctoral degree programs.
Non-degree students: Survey respondents who are enrolled in a non-degree program of study (e.g. certificate program) at the time of their response.
Non-students: Survey respondents who are not enrolled in any program of studies at the time of their response. This includes program graduates who are employed in contexts such as academia, government labs, and industry; or who are currently looking for work.
First generation college students: Students who report that they have parent(s) who have not earned at least a Bachelor’s degree.
Institutional Characteristics
The 2022 DBS survey collected responses from 169 institutions (182 unique departments) across the United States and Canada between October 2022 and February 2023.
Geographical Distribution
Institutional Category Summaries
Below are overall summary percentages of the data collected in fall 2022.
Number of Responses by Source
Distribution Channel
| Count | Percent | |
|---|---|---|
| Department distribution | 11781 | 89.18% |
| Prior participant (direct email) | 1429 | 10.82% |
| Total | 13210 | 100.00% |
Respondent Type
| Count | Percent | |
|---|---|---|
| Undergraduate Student | 9431 | 71.39% |
| Graduate Student | 2811 | 21.28% |
| Non-degree Student/Non-student | 968 | 7.33% |
| Total | 13210 | 100.00% |
Department Type (Highest Degree Granted)
| Count | Percent | |
|---|---|---|
| Bachelor’s | 986 | 8.38% |
| Doctorate | 10466 | 88.91% |
| Master’s | 319 | 2.71% |
| Total | 11771 | 100.00% |
Student Characteristics
DBS collects data from undergraduate, graduate, and non-degree seeking students, as well as non-student professionals. This section reports demographics and academic background of DBS respondents. There are three sets of tables for each section: undergraduate, graduate, and non-students/non-degree seeking students.
Demographics
This section provides information on DBS respondents’ demographic background in terms of race/ethnicity, disability status, first generation status, and citizenship. All tables are broken down by gender.
Race/ethnicity
|
Women (%) [n = 2,642] |
Men (%) [n = 4,170] |
Non-binary (%) [n = 285] |
|
|---|---|---|---|
| Arab/Middle Eastern/Persian | 3.41% | 3.51% | 2.14% |
| Asian/Asian American | 45.00% | 66.78% | 37.97% |
| Black/African American | 8.33% | 3.51% | 9.63% |
| Hispanic/Latinx | 9.54% | 6.24% | 10.16% |
| Indigenous | 0.68% | 0.45% | 0.00% |
| Native American | 1.25% | 1.02% | 1.07% |
| Native Hawaiian/Pacific Islander | 0.61% | 0.23% | 0.53% |
| White/Caucasian | 43.57% | 23.24% | 45.45% |
| Something else | 3.22% | 2.61% | 2.14% |
|
Women (%) [n = 882] |
Men (%) [n = 1,542] |
Non-binary (%) [n = 82] |
|
|---|---|---|---|
| Arab/Middle Eastern/Persian | 3.55% | 2.85% | 3.23% |
| Asian/Asian American | 35.66% | 67.25% | 31.54% |
| Black/African American | 7.96% | 4.22% | 2.87% |
| Hispanic/Latinx | 12.06% | 7.13% | 11.47% |
| Indigenous | 0.72% | 0.65% | 0.72% |
| Native American | 1.89% | 0.97% | 0.72% |
| Native Hawaiian/Pacific Islander | 0.98% | 0.32% | 0.36% |
| White/Caucasian | 50.36% | 23.93% | 60.57% |
| Something else | 3.96% | 2.40% | 3.94% |
|
Women (%) [n = 164] |
Men (%) [n = 262] |
Non-binary (%) [n = 58] |
|
|---|---|---|---|
| Arab/Middle Eastern/Persian | 4.56% | 4.88% | 0.00% |
| Asian/Asian American | 28.42% | 31.71% | 14.75% |
| Black/African American | 4.56% | 6.10% | 1.64% |
| Hispanic/Latinx | 20.35% | 23.17% | 3.28% |
| Indigenous | 2.81% | 3.66% | 1.64% |
| Native American | 1.40% | 8.54% | 0.00% |
| Native Hawaiian/Pacific Islander | 2.81% | 10.98% | 0.00% |
| White/Caucasian | 57.89% | 41.46% | 50.82% |
| Something else | 5.26% | 8.54% | 1.64% |
Disability
|
Women (%) [n = 2,553] |
Men (%) [n = 4,005] |
Non-binary (%) [n = 267] |
|
|---|---|---|---|
| Attention deficit disorder | 7.83% | 9.36% | 31.84% |
| Auditory disability | 1.02% | 0.87% | 4.87% |
| Autism spectrum disorder | 1.84% | 2.40% | 19.10% |
| Blind or visually impaired | 0.63% | 0.77% | 1.87% |
| Health-related disability | 3.06% | 1.57% | 9.36% |
| Learning disability | 1.53% | 1.60% | 4.49% |
| Mental health disability | 13.00% | 5.24% | 36.70% |
| Mobility or orthopedic disability | 0.51% | 0.52% | 4.49% |
| Speech or language disorder | 0.27% | 0.67% | 1.12% |
| Something else | 1.65% | 1.75% | 4.49% |
| No disability reported | 77.56% | 81.57% | 38.95% |
|
Women (%) [n = 825] |
Men (%) [n = 1,478] |
Non-binary (%) [n = 76] |
|
|---|---|---|---|
| Attention deficit disorder | 7.15% | 5.55% | 17.11% |
| Auditory disability | 1.09% | 0.81% | 6.58% |
| Autism spectrum disorder | 1.45% | 2.37% | 14.47% |
| Blind or visually impaired | 0.85% | 0.61% | 3.95% |
| Health-related disability | 2.55% | 1.76% | 11.84% |
| Learning disability | 0.61% | 1.08% | 15.79% |
| Mental health disability | 6.18% | 3.92% | 27.63% |
| Mobility or orthopedic disability | 0.12% | 0.47% | 5.26% |
| Speech or language disorder | 0.12% | 0.54% | 1.32% |
| Something else | 1.82% | 1.83% | 6.58% |
| No disability reported | 84.12% | 86.40% | 38.16% |
|
Women (%) [n = 146] |
Men (%) [n = 251] |
Non-binary (%) [n = 37] |
|
|---|---|---|---|
| Attention deficit disorder | 10.65% | 10.07% | 28.21% |
| Auditory disability | 1.18% | 0.75% | 7.69% |
| Autism spectrum disorder | 7.69% | 4.10% | 15.38% |
| Blind or visually impaired | 0.59% | 1.12% | 0.00% |
| Health-related disability | 5.92% | 3.73% | 17.95% |
| Learning disability | 1.18% | 0.00% | 10.26% |
| Mental health disability | 16.57% | 8.58% | 53.85% |
| Mobility or orthopedic disability | 0.59% | 1.49% | 2.56% |
| Speech or language disorder | 0.00% | 0.37% | 2.56% |
| Something else | 0.59% | 2.61% | 10.26% |
| No disability reported | 68.64% | 76.49% | 28.21% |
First generation
|
Women (%) [n = 2,535] |
Men (%) [n = 3,933] |
Non-binary (%) [n = 271] |
|
|---|---|---|---|
| Continuing generation | 75.70% | 74.55% | 73.06% |
| First generation | 24.30% | 25.45% | 26.94% |
|
Women (%) [n = 832] |
Men (%) [n = 1,460] |
Non-binary (%) [n = 73] |
|
|---|---|---|---|
| Continuing generation | 74.88% | 71.44% | 79.45% |
| First generation | 25.12% | 28.56% | 20.55% |
|
Women (%) [n = 159] |
Men (%) [n = 252] |
Non-binary (%) [n = 58] |
|
|---|---|---|---|
| Continuing generation | 80.56% | 75.84% | 88.52% |
| First generation | 19.44% | 24.16% | 11.48% |
Citizenship
|
Women (%) [n = 2,617] |
Men (%) [n = 4,129] |
Non-binary (%) [n = 281] |
|
|---|---|---|---|
| U.S. citizen or permanent resident | 85.52% | 85.42% | 87.90% |
| Non-U.S. citizen with temporary visa | 10.70% | 11.43% | 8.90% |
| Other non-U.S. citizen | 3.78% | 3.15% | 3.20% |
|
Women (%) [n = 863] |
Men (%) [n = 1,523] |
Non-binary (%) [n = 79] |
|
|---|---|---|---|
| U.S. citizen or permanent resident | 33.72% | 33.55% | 64.56% |
| Non-U.S. citizen with temporary visa | 60.02% | 61.13% | 31.65% |
| Other non-U.S. citizen | 6.26% | 5.32% | 3.80% |
|
Women (%) [n = 153] |
Men (%) [n = 254] |
Non-binary (%) [n = 32] |
|
|---|---|---|---|
| U.S. citizen or permanent resident | 76.14% | 80.44% | 91.18% |
| Non-U.S. citizen with temporary visa | 18.18% | 12.92% | 2.94% |
| Other non-U.S. citizen | 5.68% | 6.64% | 5.88% |
Academic Background
This section provides information on DBS respondents’ respondents’ computer science (CS) and math backgrounds prior to starting an undergraduate degree. All tables are broken down by gender.
CS Background
|
Women (%) [n = 2,620] |
Men (%) [n = 4,139] |
Non-binary (%) [n = 278] |
|
|---|---|---|---|
| Took AP Computer Science A | 24.85% | 30.68% | 34.89% |
| Took AP Computer Science Principles | 16.03% | 18.05% | 23.74% |
| Took AP Computer Science AB | 2.37% | 2.90% | 3.96% |
| Took other AP courses | 45.27% | 40.47% | 50.00% |
| Took dual enrollment courses | 20.42% | 17.73% | 17.63% |
| Learned a computer programming language | 40.00% | 49.92% | 56.12% |
| Engaged in software or hardware related projects | 21.26% | 34.89% | 42.09% |
| Took part in student groups related to computing | 18.89% | 20.78% | 27.70% |
| Completed an online course related to computing (e.g., MOOC) | 10.95% | 15.39% | 12.59% |
| Attended a workshop or other training in computing (e.g., through your local library, community center, etc.) | 13.74% | 12.71% | 20.14% |
| None of the above | 21.64% | 18.43% | 12.59% |
|
Women (%) [n = 836] |
Men (%) [n = 1,486] |
Non-binary (%) [n = 71] |
|
|---|---|---|---|
| Took AP Computer Science A | 18.18% | 18.10% | 23.94% |
| Took AP Computer Science Principles | 5.98% | 5.65% | 7.04% |
| Took AP Computer Science AB | 4.67% | 6.93% | 5.63% |
| Took other AP courses | 21.65% | 23.15% | 40.85% |
| Took dual enrollment courses | 7.66% | 6.53% | 15.49% |
| Learned a computer programming language | 49.16% | 56.46% | 45.07% |
| Engaged in software or hardware related projects | 29.19% | 34.66% | 30.99% |
| Took part in student groups related to computing | 19.14% | 20.52% | 19.72% |
| Completed an online course related to computing (e.g., MOOC) | 16.87% | 20.12% | 21.13% |
| Attended a workshop or other training in computing (e.g., through your local library, community center, etc.) | 17.58% | 17.83% | 16.90% |
| None of the above | 26.08% | 22.61% | 16.90% |
|
Women (%) [n = 79] |
Men (%) [n = 132] |
Non-binary (%) [n = 11] |
|
|---|---|---|---|
| Took AP Computer Science A | 14.00% | 17.57% | 23.08% |
| Took AP Computer Science Principles | 8.00% | 5.41% | 7.69% |
| Took AP Computer Science AB | 5.00% | 10.14% | 0.00% |
| Took other AP courses | 44.00% | 47.30% | 69.23% |
| Took dual enrollment courses | 17.00% | 15.54% | 23.08% |
| Learned a computer programming language | 36.00% | 56.76% | 46.15% |
| Engaged in software or hardware related projects | 27.00% | 46.62% | 38.46% |
| Took part in student groups related to computing | 17.00% | 22.30% | 30.77% |
| Completed an online course related to computing (e.g., MOOC) | 5.00% | 14.86% | 15.38% |
| Attended a workshop or other training in computing (e.g., through your local library, community center, etc.) | 12.00% | 14.86% | 7.69% |
| None of the above | 27.00% | 21.62% | 23.08% |
Math Background
|
Women (%) [n = 2,627] |
Men (%) [n = 4,140] |
Non-binary (%) [n = 278] |
|
|---|---|---|---|
| Algebra I | 90.45% | 88.07% | 91.37% |
| Algebra II | 87.78% | 85.70% | 88.13% |
| Trigonometry | 66.88% | 70.43% | 75.54% |
| Pre-calculus | 84.81% | 82.58% | 84.17% |
| Calculus | 68.75% | 68.21% | 75.18% |
| Statistics | 44.04% | 43.65% | 38.85% |
| None of the above | 1.71% | 1.91% | 4.68% |
|
Women (%) [n = 838] |
Men (%) [n = 1,479] |
Non-binary (%) [n = 70] |
|
|---|---|---|---|
| Algebra I | 82.46% | 82.96% | 64.29% |
| Algebra II | 71.48% | 72.21% | 68.57% |
| Trigonometry | 71.96% | 77.08% | 55.71% |
| Pre-calculus | 67.78% | 72.75% | 67.14% |
| Calculus | 71.72% | 71.47% | 65.71% |
| Statistics | 62.29% | 58.62% | 51.43% |
| None of the above | 6.68% | 6.15% | 2.86% |
|
Women (%) [n = 79] |
Men (%) [n = 133] |
Non-binary (%) [n = 11] |
|
|---|---|---|---|
| Algebra I | 81.00% | 87.92% | 92.31% |
| Algebra II | 77.00% | 84.56% | 92.31% |
| Trigonometry | 68.00% | 76.51% | 69.23% |
| Pre-calculus | 79.00% | 79.87% | 84.62% |
| Calculus | 67.00% | 76.51% | 61.54% |
| Statistics | 38.00% | 39.60% | 30.77% |
| None of the above | 9.00% | 3.36% | 0.00% |
Acknowledgements
DBS is currently supported through the National Science Foundation (NSF) awards CNS-1840724, CNS-2036717, DUE-1821136, subawards and contracts, and direct CRA contributions. Previous NSF awards that supported DBS include CNS-1246649 and DUE-1431112.
Suggested Citation
Center for Evaluating the Research Pipeline (2023). “Data Buddies Survey 2022 Annual Report”. Computing Research Association, Washington, D.C.