Gary L. Bridges
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Hortensia Soto Johnson
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Roger Johnson
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Introduction Once again, the State of Colorado has formulated, legislated, and implemented a performance funding model for higher education without input from the group that is the closest to, and spends more time with, students than any other group in higher education – faculty. Higher education institutions are trying to abide by a legislative mandate, the provisions of which many do not fully understand, know how to apply, or know how to measure. This research project quantifies faculty members’ opinions of their degree of involvement in the initial selection of quality indicators, their degree of familiarity with the Quality Indicator System (QIS), their level of agreement with performance funding to effect quality improvement, and their level of agreement with the state’s goals for higher education. Definition Performance funding links some portion of higher education funding to achievement of pre-specified performance or productivity goals. Colorado’s Performance Funding Efforts The latest addition to Colorado’s quality improvement legislation is Senate Bill (SB) 99-229, signed into law June 2, 1999. Colorado House Bill (HB) 96-1219, the "Higher Education Quality Assurance Act", represented the second, albeit tentative, step toward a quality-enhancing budgeting formula for higher education in Colorado. Previously, Colorado higher education grappled with performance funding under HB 94-1110. This legislation was in effect during the period 1994-95 to 1997-98, although the legislature funded only the first three years. Bridges (1999) identified a number of problems inherent in Colorado’s performance funding model of HB 94-1110 and subsequently, HB 96-1219. These problems included: 1) HB 94-1110 directed the funding allocations for performance funding purposes to the institutions’ governing boards and did not require that the boards share the funding with the institutions, whose performance data were used to determine the original allocations, 2) The amount earmarked for performance funding purposes was well short of the national average of 2 to 5 % of base funding. Colorado identified approximately 0.2% (two tenths of one percent) of the base budget during the period 1994-95 to 1996-97 to be allocated for performance funding, 3) The "performance funding" model was actually administered as an enrollment funding model which meant that superior or enhanced performance was not rewarded to the same degree as was an increase in enrollment, 4) The Colorado State Legislature discontinued funding for HB 94-1110 before the legislation expired. Institutions were required to continue compiling and submitting performance funding data even though funding had been discontinued. Many of the performance indicators were changed during this period, creating confusion among the institutions, 5) All institutions were rewarded the same under HB 94-1110. Bridges’ research showed that research institutions attracted higher-achieving students (as defined by ACT scores) and that ACT scores significantly influenced students’ GRE scores (one of the performance indicators used under HB 94-1110). Yet the state’s performance funding model did not differentiate between the institutions. In other words, the research institutions would receive the same performance funding credit for their students’ higher GRE scores even though their students’ higher ACT scores may have virtually guaranteed that their GRE scores would be higher. Bridges noted other structural differences such as higher faculty salaries and different weekly faculty to student contact hours that could affect research institutions’ achievement toward certain performance indicators. This research project is intended to more closely identify some of the differences between the research institutions, non-research four-year institutions, and community colleges. The three institutions classified by CCHE as "Research I" universities (Colorado School of Mines/CSM, University of Colorado at Boulder/UCB, and Colorado State University/CSU) admitted higher-achieving students (as evidenced by index scores [ACT plus high school GPA/class standing]), delivered education differently (as evidenced by differences in their weekly contact hours with students), and paid higher faculty salaries (See Table 1). |
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Note. a Research institutions are shown in bold. CSM refers to Colorado School of Mines. UCB refers to University of Colorado at Boulder. CSU refers to Colorado State University. UCD refers to University of Colorado at Denver. UCCS refers to University of Colorado at Colorado Springs. UNC refers to University of Northern Colorado. SBA refers to the State Board of Agriculture system. Trustees refers to the Trustees of State Colleges system. b Index score consists of the student’s ACT score plus the better of their high school GPA or class standing index. c 1996 d 1995-96 e Student-Faculty weekly contact hours. |
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The Survey Researchers mailed the survey, "Faculty Opinion of the
Quality Indicator System in Colorado" (see the Attachment)
to 630 faculty members at 12 four-year colleges and universities
and 11 community colleges in Colorado. They randomly selected
names from the institutions’ faculty phone books and on-line
faculty directories. Respondents returned 118 (19 %) completed
surveys. The instrument consisted of 10 statements characterizing
faculty members’ familiarity with the Quality Indicator
System (QIS), the quality indicators, the state’s higher
education goals; their involvement in selecting their respective
institutions’ quality indicators; and their opinions on
the policy setting process in general. The survey also contained
25 performance measures (determined by the state) that serve
as action steps to help institutions achieve the state’s
five goals for higher education as articulated in Senate Bill
(SB) 99-299. The state’s five goals for higher education
are: 1. Provision of a high quality, efficient, and expeditious
undergraduate education, 2. Provide assistance to elementary
and secondary education to achieve systemic reform and creation
of appropriate linkages between elementary and secondary education
and higher education, 3. Provision of work force preparation
and training, 4. Use technology to lower institutions’ capital
and administrative costs and improve quality and delivery of
education, 5. Provide services with a high level of operational
productivity and effectiveness. Respondents used the following
five-point Likert scale to indicate their agreement or disagreement
with the 10 statements and the 25 performance measures:
Analysis Researchers used the statistical package MINITAB to analyze the responses by cross tabulating the responses to faculty rank and to type of institution (i.e., research, non-research, and community college). This research project identifies the nature of and the degree of differences between research faculty and non-research faculty’s understanding of and opinions of performance funding and the QIS in Colorado. The researchers hope that this information will be useful to policy makers as they grapple with the many variables inherent in performance funding policy. Figures 1 through 9 report the percent responses by institutional group (Research, Non-research, and Community College). Because of the similar nature of the first four statements, the researchers combined them into one response (familiarity) for reporting purposes. They also collapsed the responses to "Disagree", "Neutral", and "Agree" for a more readable report. Performance measure responses were grouped according to the appropriate state goals for reporting purposes. Figures 10 through 18 report the percent responses by faculty rank (Assistant, Associate, Professor, and Other). "Other" combines the responses from instructors, lecturers, and non-ranked faculty. Table 2 reports the percent of responses received by faculty rank compared to the percent of faculty rank for the state of Colorado. Table 3 shows the percent of responses received by institutional group compared to the percent of student full-time equivalent (SFTE) attending each institutional group in Colorado. Table 4 is a summary of the total "agree" and "disagree" responses. Summary Analysis As the data presented in Table 4 illustrate, the respondents overwhelmingly agreed with the performance measures selected by the state to serve as action steps for the state’s higher education goals. Sixty percent of the respondents, however, were generally unfamiliar with the CCHE’s quality indicators, their own institutions’ indicators, and the higher education goals for the state; 82 % of the respondents do not believe that CCHE adequately communicates with higher education faculty; 49 % did not believe that the state legislature is interested in improving higher education; and 62 % did not agree that linking funding to quality indicators is the best way to improve quality. There seems to be a general disconnect, highlighted by mistrust and lack of communication, between higher education faculty and the state’s policy makers. It is doubtful that the state will ever realize the full potential of performance funding without more fully engaging faculty in the total policy making process. |
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| Assistant |
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| Associate |
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| Other |
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| Research |
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| Non-research |
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| Community College |
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| Familiar with: QIS, CCHE’s statewide indicators, my institution’s indicators, the higher education goals in SB 99-299. |
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| CCHE adequately communicates with faculty. |
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| The legislature wants to improve higher education. |
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| Linking funding to indicators is best way to improve quality. |
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| High quality group of performance measures. |
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| K-12 group of performance measures. |
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| Work force group of performance measures. |
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| Technology group of performance measures. |
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| Productivity group of performance measures. |
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