Whereas, To increase transfer completion, the California legislature has prioritized data-informed reforms, such as AB 1705 (Irwin, 2022) [1], with the goal of achieving equitable outcomes;
Whereas, The current throughput model [2] uses all students enrolled in a prerequisite class in the calculation of the gateway course’s success rate, regardless of whether those students passed the prerequisite or enrolled in the gateway course and thereby ignoring any confounding variables, with throughput only counting relative growth in pass rates, neglecting to account for disproportionate fail rates, particularly among students of color [3];
Whereas, Conditional throughput measures success rates exclusively for those students who enroll in and complete a gateway course and, according to the Research and Planning group’s pre-calculus/business calculus research [4], shows maximized completion for those taking the prerequisite; and
Whereas, AB 1705 (Irwin, 2022) [5] does not mandate methodology for local data validation of the efficacy of prerequisite courses [6], thus allowing for local flexibility given the vast differences in math proficiency across districts [7];
Resolved, That the Academic Senate for California Community Colleges request open and public collaboration with the California Community Colleges Chancellor’s Office to enhance the use of data to define and measure equitable outcomes with the goal of developing meaningful metrics;
Resolved, That the Academic Senate for California Community Colleges express its concern regarding the limitations of relying exclusively on throughput to ensure data-informed approaches to increasing equitable outcomes;
Resolved, That the Academic Senate for California Community Colleges research and assess conditional throughput as an acceptable metric for data validation and its impact on closing equity gaps, providing feedback to colleges by the fall 2024 Plenary; and
Resolved, That the Academic Senate for California Community Colleges call for allowing local districts to include any data validation metrics that allow local districts to work with system partners to determine how conditional throughput maximizes the probability of students completing math and English in the first year, better addressing their unique needs, particularly as the data validation metrics apply to equity.
MSC
1. https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202120220AB1705
2. See slide 3: https://rpgroup.org/Portals/0/Documents/Projects/MultipleMeasures/Presentations/ValidatingPlacementSystems.pdf
3. See pages 8-9: https://rpgroup.org/Portals/0/Documents/Projects/MultipleMeasures/AB705_Workshops/MaximizingCalcCompletionForBusinessAdminDegree_May2023.pdf?ver=2023-05-16-072731-540
4. See 1:02:36 – 2:31:15 https://www.youtube.com/watch?v=whQsv4PeeDY
5. https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202120220AB1705
6. https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202120220AB1705
7. https://caaspp-elpac.ets.org/caaspp/CompareReportSB?ps=true&lstTestYear=2023&lstTestType=B&lstGroup=1&lstGrade=13&lstSchoolType=A&lstCds1=19000000000000&lstCds2=21000000000000&lstCds3=15000000000000&lstNav=srch