Carteret Community College Title III Grant

December 2, 2009

Numbers Talk…No.4: How are we doing?

Filed under: Cindy Schersching's white papers — cynthea1 @ 2:44 pm

It is frequently useful to benchmark key metrics to a known universe of similar organizations.

Benchmarking can tell us if we are moving in the right direction, how much ‘head room’ we have to grow, and, alternatively, whether there are areas that need more resource to bring performance up to par.
A second benefit of using benchmarks is that – with some assumptions – we can infer performance numbers that we are unable to generate.
For this exercise, we will use summary numbers published by Noel-Levitz, a respected agency with known expertise in educational/institutional research, and compare them to similar numbers generated for Carteret Community College (CCC). We will begin with the comparison of retention and the percent of hours completed relative to the number attempted. CCC metrics are run on the same sample definition and time frame as the benchmark numbers.

Retention Rates and Percentage of Hours Completed
Base: Cohorts, first time, full time, degree seeking

Retention Rates Percentage of Hours Completed divided by Total Hours Attempted
Noel-Levitz 2-Year Public Institutions Carteret Community College Index:

Noel-Levitz 2-Year Public Institutions Carteret Community College Index:


2007-2008 55.8% 59.3% 106 75.0% 77.6% 103

CCC compares quite favorably with these key national numbers; we are in the top half of the sample distribution of 2-year public institutions.

Noel-Levitz also generates a persistence rate for 2-year public institutions. For this time period and sample definition, it is 71.3%. For a variety of reasons, we are unable to get a comparable number for CCC.

The response to the last blog regarding persistence and retention rates suggests the relationship between these two metrics is likely a strong – though not perfect – positive one. Noel-Levitz also concludes that ’ term-to-term persistence benchmarks within a given academic year are natural predictors of year-to-year retention rates for a cohort of students. As such, these benchmarks serve as early indicators of attrition, facilitating intervention’ (2009 Noel-Levitz, Inc. • Benchmark Research Study Conducted Fall 2008—Mid-Year Retention Indicators Report).

Using these assumptions, a conservative reasonable estimate of persistence suggests CCC is also in the top half of the distribution.

When 2008-2009 estimates of these same metrics become available, we will be able to re-apply/re-test our assumptions and update these comparisons.

Submitted by Cindy Schersching, PhD, December 2, 2009


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