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Headcount Unduplicated): The unduplicated/actual count of individual students enrolled in a specific term/year. Students may be enrolled in multiple courses but are counted only once for the term/year.
Enrollment: The duplicated count of students enrolled in a specific class/term/etc. Students that are enrolled in multiple courses are counted for each course.
Retention Rate: The number of enrollments with a grade of A, B, C, D, F, P, NP divided by the number of enrollments at census (receiving any grade). It is the percent of students retained out of the total enrolled. For example, in a class of 40 students where 8 students withdraw after census, the retention rate is 80%.
Success Rate: The Number of students who successfully complete the course (with a grade of A, B, C, P) divided by the number of enrollments at census (receiving any grade). The success rate is the percent of students successful in courses out of the total enrolled. (EW, RD, IP are not included in the denominator)
Persistence Rate: The percentage of students who re-enrolled in the following term/year. One Term/Term-to-Term Persistence is measured Fall to Spring or Spring to Fall. One Year Persistence is measured Fall to Fall.
Full-Time Equivalent (FTES): An enrolled student who attends 15 hours each week during the semester (or a group of students who, together, attend 15 hours each week). In an academic year, this hypothetical full-time student generates 525 student contact hours.
Disproportionate Impact (DI): Disproportionate Impact is when the percentage of persons from a particular racial, ethnic, gender, age, or disability group outcome measure is significantly different from the representation of that group in the population of students. DI is calculated using the Percentage Point Gap Minus One (PPG-1) methodology, in which the outcome rate of the primary subgroup is compared to the outcome rate of all OTHER students in the cohort.
Equity Gap: The systemic differences in outcomes that vary across student groups
Download a PDF of the IERP Glossary (here)
The value of data as it relates to advancing equity depends on how we make meaning of the data through the process of critical reflection and meaning making. The Center of Urban Education (CUE) describes this process as equity-minded sensemaking, which goes beyond noticing equity gaps in outcomes to interpreting equity gaps as an indicator that current practices are not working and asking equity-minded questions about how/why current processes are failing to serve students experiencing these inequities (McNair, Bensimon, Malcolm-Piquex, 2020, p. 61).
When looking at data disaggregated by race/ethnicity, consider the following:
What patterns do you see in the data?
Which racial groups are experiencing inequities?
What might be contributing to the equity gaps?
What additional information is needed to better understand equity gaps?
What questions might you ask for deeper understanding?
How might you use this information to inform goal setting?
For more information, please visit the IERP Dashboards page.