Data

Who We Are

The Research team believes students' experiences and aspirations should be at the center of every decision. We transform data into knowledge that includes and honors every student. This knowledge is continuously improved by the college through critical inquiry and reflection, and it serves as the foundation for all college plans and actions.

We support the mission of City College of San Francisco by partnering with college constituents to transform inquiries into insights. We leverage student data, domain expertise, and our data analysis skills to guide the college toward student-focused decisions at all levels.

What We Do

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Tableau Dashboards
Fact Sheets

CCSF Students & Enrollment Data 2017-2020

Regional Data

Older Data

Reports and Briefs

Four student retention programs, CalWORKs, EOPS, Guardian Scholars, and HARTS, collaborated with the Office of Research and Planning to assess their shared Student Services Outcome: program provides students a welcoming space and community that will serve to encourage persistence. In this qualitative research study, the Office of Research and Planning facilitated focus groups with students from the four retention programs. We found similar themes related to program space needs were often largely shared within a program, and each program shared similarities with other programs related to the goals of students, but each program appears to have overall different space needs. We also found that students value community they find within these programs, actively building community through their interactions with each other both organically and through program facilitated events.

Building a welcoming community: A qualitative assessment of students’ sense of belonging - September 2020

This set of charts and tables describes CTE at City College from AY 2016-17 through AY 2018-19. Data include credit and noncredit total FTES, awards, course success, hours of attendance, and department contribution to FTES -- disaggregated by CTE and non-CTE. Students are compared across CTE and non-CTE for credit and noncredit, disaggregated by age, ethnicity, and residency.

Additional CTE data includes the CTE Employment Outcomes Survey (CTEOS) results for 2019, as well as reports for CTE trends at CCSF.

Data slides: Career and Technical Education (CTE) at CCSF - November 2019 (updated February 2020)

Brief: Career and Technical Education (CTE) at CCSF Overview, AY 2016-17 to AY 2018-19

LMI FAQ: Resource to help CTE programs navigate self service labor market information (LMI) data. LMI FAQ.

CTEOS (Employment Outcomes Survey):  San Francisco Outcomes Report 2019 - CreditSan Francisco Outcomes Report 2019 - Noncredit, and Statewide Outcomes Report 2019

CTE Trends at CCSF (January 2020): CTE Trends - Annual HeadcountCTE Trends - Course SuccessCTE Trends - Degrees and CertificatesCTE Trends - Productivity

This annually produced set of charts and tables describe student enrollments in noncredit courses at CCSF over a ten year period. Student demographics for students enrolled in noncredit and credit are compared, including ethnicity and age, along with other characteristics such as enrollment by department and center.

Noncredit Numbers (Summary data: Noncredit classes and students) - October 2020

Noncredit Numbers (Summary data: Noncredit classes and students) - October 2019

Noncredit Numbers (Summary data: Noncredit classes and students) - August 2018

Noncredit Numbers (Summary data: Noncredit classes and students) - April 2017

This brief examines noncredit course-taking behaviors and subsequent credit enrollments for first-time noncredit ESL students in three cohorts, disaggregated by age, ethnicity, sex, ESLN level, and location of coursework. Students who begin noncredit coursework at higher ESLN levels transition to credit at higher rates than do those beginning at lower ESLN levels, female students transition at a higher rate than male students, Asian students transition at a higher rate than Latino/a students, and younger students transition at higher rates than older students. This analysis helps inform our understanding of students who transition from noncredit ESL to credit coursework.

First-time noncredit ESL students and transitions to credit - April 2020

This annual report contains disaggregated data used to review equity gaps, assess progress, and plan for improvement. Measures include course success; progress through the math, English and ESL sequence; completion data (i.e. transfer, degrees, certificates); matriculation services and more for credit, as well as for noncredit where applicable. Data are disaggregated by race/ethnicity, gender, and other demographic groups such as foster youth, veterans and students with disabilities.  

Student Equity and Achievement Data - September 2019 

This study incorporates ten years of Positive Attendance Roster Sheet (PARS) data. Open enrollment allows for students to enter at any time in the semester. However, after the semester's halfway point relatively few new students entered into noncredit classes. Enrollment generally peaked at the end of the first month, then slowly declined, with a sharp drop off in the last week or two of the semester. Analysis for the entire college, by department, and by center showed little variation among departments or centers; however, programs with cohorts showed more consistent enrollment across the semester. Individual department or campus reports available upon request.

PARS Attendance Study (Fall 2008 to Spring 2018) - May 2019

To better understand the impact of credit class cancellations on overall student enrollment at City College of San Francisco (CCSF), we analyzed enrollment records for students who were dropped from a credit class due to the class’ cancellation in Fall 2016, Fall 2017, and Fall 2018 semesters. In addition, we analyzed demographic characteristics of students enrolled in canceled class sections for Fall 2018, and compared results to those from a similar study completed in Fall 2016.

Re-enrollment Patterns Among Students Who Were Dropped Due to Credit Class Cancellations - October 2018