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63
salary, which may result from costs differences due to geographic region. By using a
single MSA, salary adjustments among districts will not be necessary.
In addition to MSAs, other methods of creating a homogeneous peer group of
comparable colleges must also be incorporated. Unlike the study by Rose and
Sengupta, The Kansas Study focused on community colleges across the country,
though none were in California. That study disaggregated data according to whether
the districts were multi-campus or single campus districts. In addition, they collected
data on the size of the districts based on the number of students, but not FTES. The
size of the school is an important factor given that Rose and Sengupta highlighted the
benefits of an “economies of scale” effect when fixed costs are spread out among
many students at large schools. One notable factor of the Kansas Study is that the
schools in the sample were self-selected; the schools studied willingly participated and
volunteered information. In this study of the CCC, the sample is not self selected, but
instead selected based on characteristics that are designed to create a homogeneous
peer group for the purposes of comparative analysis.
Within the funding mechanism of the CCC system, districts are distinguished
by size based on FTES. Small districts are those that have less than 10,000 FTES,
medium districts have an FTES of 10,000 to 20,000; large districts are those with over
20,000 FTES. Since the funding of the CCC takes into account FTES, it is logical to
also measure expenditures by the same measure. Disaggregating districts by FTES
also addresses economies of scale, which occurs in large districts, but not in small
Object Description
| Title | Finance in the California community college: Comparative analysis and benchmarking of instructional expenditures |
| Author | Karamian, Martin |
| Author email | martinsfsu@netzero.com; karamim@piercecollege.edu |
| Degree | Doctor of Education |
| Document type | Dissertation |
| Degree program | Education (Leadership) |
| School | Rossier School of Education |
| Date defended/completed | 2011-03-17 |
| Date submitted | 2011 |
| Restricted until | Unrestricted |
| Date published | 2011-04-26 |
| Advisor (committee chair) | Picus, Lawrence O. |
| Advisor (committee member) |
Melguizo, Tatiana Vega, William |
| Abstract | The goals of this empirical study of community colleges are to 1) create a benchmark for per student instructional expenditures; and 2) account for variations in instructional expenditures among a peer group of community colleges in Southern California. The peer group sample included 22 single campus community college districts in the Los Angeles area. Using data for three fiscal years a refined mean benchmark value for instructional expenditures of $2,676.71 per full-time equivalent student (FTES) was estimated with a standard deviation of $326.54. Using Pearson product-moment correlation coefficient, 11 variables were correlated with instructional costs per FTES. The largest and only statistically significant determinant included the number of part-time instructors (-0.424). While other variables were correlated, none were statistically significant at the 95% confidence interval. The results from the sample suggest that larger colleges have lower instructional costs per FTES despite higher faculty pay. Expanding credit student enrollment within the funding growth limits set by the State, along with additional part-time instruction within the limits set by the State will likely result in lower instructional costs per FTES and an economy of scale effect. The effect of increased institutional size on quality of education was not assessed. |
| Keyword | finance; California; community college; comparative analysis; benchmarking; instructional expenditures; economics; higher education; spending; instruction; education; economy of scale |
| Geographic subject (state) | California |
| Geographic subject (country) | USA |
| Coverage date | 1990/2010 |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3775 |
| Contributing entity | University of Southern California |
| Rights | Karamian, Martin |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Karamian-4454 |
| Archival file | uscthesesreloadpub_Volume23/etd-Karamian-4454.pdf |
Description
| Title | Page 71 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 63 salary, which may result from costs differences due to geographic region. By using a single MSA, salary adjustments among districts will not be necessary. In addition to MSAs, other methods of creating a homogeneous peer group of comparable colleges must also be incorporated. Unlike the study by Rose and Sengupta, The Kansas Study focused on community colleges across the country, though none were in California. That study disaggregated data according to whether the districts were multi-campus or single campus districts. In addition, they collected data on the size of the districts based on the number of students, but not FTES. The size of the school is an important factor given that Rose and Sengupta highlighted the benefits of an “economies of scale” effect when fixed costs are spread out among many students at large schools. One notable factor of the Kansas Study is that the schools in the sample were self-selected; the schools studied willingly participated and volunteered information. In this study of the CCC, the sample is not self selected, but instead selected based on characteristics that are designed to create a homogeneous peer group for the purposes of comparative analysis. Within the funding mechanism of the CCC system, districts are distinguished by size based on FTES. Small districts are those that have less than 10,000 FTES, medium districts have an FTES of 10,000 to 20,000; large districts are those with over 20,000 FTES. Since the funding of the CCC takes into account FTES, it is logical to also measure expenditures by the same measure. Disaggregating districts by FTES also addresses economies of scale, which occurs in large districts, but not in small |
