A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

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A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity Michael F. Middaugh Assistant Vice President for Institutional. Research and Planning University of Delaware National Director Delaware Study of Instructional Costs and Productivity

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A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity. Michael F. Middaugh Assistant Vice President for Institutional. Research and Planning University of Delaware National Director Delaware Study of Instructional Costs and Productivity. - PowerPoint PPT Presentation

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Page 1: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

A Data-Centered Approach to ManagingInstructional Costs and Enhancing

Faculty Productivity

Michael F. MiddaughAssistant Vice President for Institutional. Research

and Planning

University of Delaware

National Director

Delaware Study of Instructional Costs and Productivity

Page 2: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• Over the past decade has grown and matured from small beginnings into a major data-sharing consortium of close to 400 colleges and universities that have elected to participate since its inception.

• It is the tool of choice for benchmarking data on faculty teaching loads, instructional costs, and externally funded research and service activity, all at the academic discipline level of analysis.

Page 3: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• Begun in 1992 with initial participant pool of 15 research universities, 16 doctoral universities, and 65 comprehensive and baccalaureate institution.

• Today, the participant pool in any given year embraces 50+ research universities, 30+ doctoral universities, 60+ comprehensive institutions, and 30+ baccalaureate colleges. (Note that the Delaware Study continues to employ the 1995 Carnegie Institutional Taxonomy).

Page 4: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• The evolution of the Delaware Study was financially supported by TIAA/CREF in 1995, and by two major grants from the Fund for Improvement of Post Secondary Education (FIPSE) in 1996-99 and 2001-04.

• The core activity supported by these grants has been the Delaware Study Advisory Committee which designed the instrumentation, data definitions, collection methodology, and calculation conventions.

Page 5: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• The seminal question that drives the Delaware Study is “Who is teaching what to whom, and at what cost?” This question can be answered satisfactorily only by looking at data at the academic discipline level of analysis.

• The Data Collection Form from the teaching load/cost portion of the Delaware Study underscores this emphasis.

Page 6: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• Among Delaware Study benchmarks that are generated annually from Part A of the Data Collection Form are:- Lower division and upper division student credit hours and

organized class sections taught per FTE faculty (for each faculty category)

- Total undergraduate student credit hours and organized class sections taught per FTE faculty

- Total graduate student credit hours and organized class sections taught per FTE faculty

- FTE students taught per FTE faculty

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The Delaware Study

• Among Delaware Study benchmarks that are generated annually from Part B of the Data Collection Form are:

- Direct instructional expense per student credit hour

taught

- Direct instructional expense per FTE student taught

- Personnel costs as a percentage of direct instructional

expense

- Separately budgeted research and service expenditures

per FTE tenured and tenure track faculty

Page 8: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• National benchmarks are produced for each discipline for which a minimum of 5 institutions submit data. Benchmarks are arrayed

- By Carnegie Institution Type

- By highest Degree Offered

- By Relative Emphasis on Undergraduate versus

Graduate Instruction

Page 9: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study

• In addition to receiving the National Benchmark Reports, participating institutions may request peer group analyses that mirror the format of the national reports, but contain data only from specified peers (institutional identities masked).

• Participating institutions have access to the Delaware Study secure server, containing the data set from which national benchmarks are generated, and are welcome to develop their own customized analyses.

Page 10: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Using Delaware Study Data at the Institutional Level

• From its inception, the Delaware Study has had as its primary function that of being a management tool for provosts, deans, and department chairs to assess the relative position of their academic departments and programs vis-à-vis those at appropriate comparator institutions.

• The Delaware Study is not intended to be used as a tool to reward or penalize programs, but rather to focus on strategies for program improvement.

Page 11: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

My Provost chooses to focus on tenured/tenure track faculty when examining data from the Delaware Study

• Direct instructional costs are 85% to 90% on average driven by faculty salaries.

• Tenured and tenure track faculty are “fixed costs.” They are essentially with us until retirement.

• Tenured and tenure track faculty are the most visible of faculty categories.

• What is the return on investment?

Page 12: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

• We provide the Provost with data from multiple years of the Delaware Study, looking at the University indicators as a percentage of the national benchmark for research universities.

• The Provost receives a single sheet for each academic department, with graphs reflecting the following indicators: Undergraduate Fall SCRH/FTE Faculty, Total Fall SCRH/FTE Faculty; Total AY SCRH/FTE Faculty (All); Fall Class Sections/FTE Faculty; Direct Cost/SCRH; External Funds/FTE faculty

Page 13: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Science Department

Undergraduate Student Credit Hours Taught per FTE T/TT Faculty

0

50

100

150

200

250

300

1994 1996 1997 1998 1999

UD

Nat'l

Total Student Credit Hours Taught per FTE T/TT Faculty

050

100150

200250

300350

1994 1996 1997 1998 1999

UD

Nat'l

Total Class Sections Taught per FTE T/TT Faculty

0.00.51.01.5

2.02.53.03.5

1994 1996 1997 1998 1999

UD

Nat'l

Total Student Credit Hours Taught per FTE Faculty (All Categories)

180190200210220230240250260

1994 1996 1997 1998 1999

UD

Nat'l

Direct Instructional Expenditures per Student Credit Hour

$0

$50

$100

$150

$200

$250

1994 1996 1997 1998 1999

UD

Nat'l

Separately Budgeted Research and Service Expenditures per FTE T/TT Faculty

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

FY95 FY97 FY98 FY99 FY00

UD

Nat'l

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Teaching Load Data

Undergraduate Student Credit Hours Taught per FTE T/TT Faculty

0

50

100

150

200

250

300

1994 1996 1997 1998 1999

UD

Nat'l

Total Student Credit Hours Taught per FTE T/TT Faculty

050

100150

200250

300350

1994 1996 1997 1998 1999

UD

Nat'l

Page 15: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

More Teaching Data…

Undergraduate Student Credit Hours Taught per FTE T/TT Faculty

0

50

100

150

200

250

300

1994 1996 1997 1998 1999

UD

Nat'l

Total Student Credit Hours Taught per FTE T/TT Faculty

050

100150

200250

300350

1994 1996 1997 1998 1999

UD

Nat'l

Total Class Sections Taught per FTE T/TT Faculty

0.00.51.01.5

2.02.53.03.5

1994 1996 1997 1998 1999

UD

Nat'l

Total Student Credit Hours Taught per FTE Faculty (All Categories)

180190200210220230240250260

1994 1996 1997 1998 1999

UD

Nat'l

Direct Instructional Expenditures per Student Credit Hour

$0

$50

$100

$150

$200

$250

1994 1996 1997 1998 1999

UD

Nat'l

Page 16: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Cost and Scholarly Productivity Data…

Total Student Credit Hours Taught per FTE Faculty (All Categories)

180190200210220230240250260

1994 1996 1997 1998 1999

UD

Nat'l

Direct Instructional Expenditures per Student Credit Hour

$0

$50

$100

$150

$200

$250

1994 1996 1997 1998 1999

UD

Nat'l

Separately Budgeted Research and Service Expenditures per FTE T/TT Faculty

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

FY95 FY97 FY98 FY99 FY00

UD

Nat'l

Page 17: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Using Delaware Study Data at the National Level

• Over the past several years, Delaware Study data have been used for policy discussions at the national level to describe how much faculty teach, and what constitutes the major factors contributing to the magnitude of instructional expenditures.

• A brief review of the findings is instructive.

Page 18: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

How Much Do Tenured and Tenure-Track Faculty Really Teach?

• In my book, Understanding Faculty Productivity: Standards and Benchmarks for Colleges and Universities (Jossey-Bass, 2001), I looked at four cycles of Delaware Study data to examine the validity of criticism that tenured and tenure-track faculty do little teaching and focus largely on their own specialized research interests.

• I looked at 24 disciplines typically found at most four year colleges and universities.

Page 19: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Disciplines Under Analysis

• Communications

• Computer & Info. Sciences

• Education

• Engineering

• Foreign Languages and Lit.

• English

• Biological Sciences

• Mathematics

• Philosophy

• Chemistry

• Geology

• Physics

• Psychology

• Anthropology

• Economics

• Geography

• History

• Political Science

• Sociology

• Visual and Performing Arts

• Nursing

• Business Administration

• Accounting

• Financial Management

Page 20: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

How Much Do Tenured and Tenure-Track Faculty Really Teach?

• Benchmark (refined mean ) data for each of the disciplines from the four cycles were arrayed and an average (i.e. “mean of the means”) was calculated.

• For example, the proportion of all undergraduate student credit hours that were taught by tenured and tenure track faculty was examined for each discipline, and a mean was calculated that reflected the average proportion across the 24 disciplines.

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How Much Do Tenured and Tenure-Track Faculty Really Teach?

• It is important to look at faculty teaching activity in this way. If one simply looked at the proportion of all undergraduate credit hours taught by tenured and tenure track faculty at an institution, large volume departments such as English, Foreign Languages, and Mathematics – all of which frequently make extensive use of graduate teaching assistants – would exert undue influence on the overall proportion.

• But students take courses in multiple disciplines, and the focus should be on the likelihood that they will encounter tenured and tenure track faculty across those disciplines, hence the averaging of Delaware Study benchmarks.

Page 22: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

How Much Do Tenured and Tenure-Track Faculty Really Teach?

• On average, across the disciplines, one of every two lower division undergraduate student credit hours at research and doctoral universities are taught by tenured and tenure track faculty. The proportion is two of every three lower division credit hours at comprehensive institutions, and three of four lower division credit hours at baccalaureate institutions.

• On average, across the disciplines, nearly two of every three undergraduate student credit hours at research and doctoral universities are taught by tenured and tenure track faculty, with the proportion being three in four at comprehensive and baccalaureate institutions.

Page 23: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

What constitutes the major factors contributing to the magnitude of instructional expenditures?

• Delaware Study data were the basis for the recent National Center for Education Statistics Research and Development Report (NCES 2003-161), A Study of Higher Education Instructional Expenditures: The Delaware Study of Instructional Costs and Productivity (Middaugh et al, 2003).

• The report is part of the NCES response to a Congressional mandate for an analysis of higher education costs.

Page 24: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• Focuses solely on the issue of direct instructional expenditures.

• Examines factors associated with the magnitude of direct instructional expenditures at 4-year colleges and universities in the United States.

• As will become clear, factors associated with instructional expenditures are very different from those associated with tuition rates, as identified in earlier NCES Studies.

• Cost and price are not interchangeable constructs, and a strong statistical relationship between them has not been found.

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Study of Higher Education Instructional Expenditures

• Multiple data cycles of the Delaware Study of Instructional Costs and Productivity.

• Delaware Study was started in 1992, and has matured into a data sharing consortium embracing over 300 participant colleges and universities.

• Focus of data collection activity includes detailed information on teaching loads by faculty category, instructional costs, and externally funded scholarship.

• All analysis is done at the level of the academic discipline.

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Limitations of the Study

• Participation in Delaware Study is voluntary, and is restricted to 4-year, Title IV-eligible institutions only. The issue of non-response bias must be addressed.

• Because the population for this study is self-selecting, it is not a random sample. Descriptive statistics are applied to the data to describe expenditure patterns, but cannot be inferentially generalized to a larger population. The descriptive information is nonetheless valuable.

• The data reflect direct instructional expense only, and does not constitute a full cost model.

Page 27: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• Study focuses primarily on data from 1998, 2000, and 2001 Delaware Study data collection cycles.

• Direct instructional cost per student credit hour taught is focal dependent variable. Patterns of dispersion and differences in cost across disciplines are examined against factors such as Carnegie institution type, highest degree offered in the discipline, relative emphasis on undergraduate versus graduate instruction, etc.

• Also examined is relationship of cost to factors such as department size, tenure rate, teaching volume, personnel intensiveness of cost, etc.

Page 28: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• The key finding from analysis of multiple years of Delaware Study data is that most of the variance in instructional cost across institutions, as measured by direct expense per student credit hour taught, is associated with the disciplinary mix within an institution.

• While an institution’s Carnegie classification is associated with some of the variation in direct instructional expense, it accounts for less of the cost differential across institutions than the disciplinary mix factor.

Page 29: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Direct Expense per Student Credit Hour Taught:Institution Type Within Discipline, 2001

264

140

171

379

124

233

116131

316

106

181

112

147

342

100

242

132

202

138

0

50

100

150

200

250

300

350

400

Chemistry English Foreign Languages MechanicalEngineering

Sociology

Do

lla

rs

Research

Doctoral

Comprehensive

Baccalaureate

Page 30: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Direct Expense per Student Credit Hour Taught:Discipline Within Institution Type, 2001

264

233

181

242

140 140

112132

171

131147

202

379

316

342

138124

106 100

0

50

100

150

200

250

300

350

400

Research Doctoral Comprehensive Baccalaureate

Do

lla

rs

ChemistryEnglishForeign LanguagesMechanical EngineeringSociology

Page 31: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• Overarching question: In describing the cost of instruction in higher education institutions, which is the more important factor – the designation as research, doctoral, comprehensive, or baccalaureate, or the configuration of disciplines that comprise that institution?

• Hierarchical linear modeling (HLM) is a statistical tool that provides the capability to disaggregate total variance in cost by institution, and by discipline within the institution. HLM helps to explore and describe the dispersion of instructional costs across institutions, and to identify those factors associated with the dispersion.

Page 32: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• The hierarchical linear model constructed in this study demonstrates that most of the variance in cost is at the discipline level within an institution, ranging from 76.0 percent in the 1998 data collection cycle to 82.6 percent in the 2000 cycle.

• When Carnegie institutional classification is taken into account in the hierarchical linear model, the dispersion in cost across institutions decreased, and the relative variance due to disciplines within an institution ranges from 81.0 to 88.0 percent.

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Study of Higher Education Instructional Expenditures

• These findings underscore that the disciplines that comprise a college or university curriculum – not its Carnegie designation – are associated with the dispersion of costs among institutions.

• This further highlights the distinction between cost and price. Stated plainly, price is a constant for all undergraduates at most institutions. Chemistry and engineering students pay the same tuition rate as English and sociology majors. However, the cost of delivering instruction in those disciplines varies widely.

Page 34: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• The study also focused on those factors that impact direct instructional expenditures within a discipline.

• In The Economics of American Universities, Paul Brinkman suggested that the behavior of marginal and average costs can be associated with four dimensions: size (i.e., quantity of activity or output), scope of services offered, level of instruction, and discipline.

• The analyses in this study determined that 60 to 75 percent of the variation in cost within a discipline or group of disciplines is associated with specific cost factors consistent with those identified by Brinkman.

Page 35: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• Volume of teaching activity, as measured by total student credit hours taught, is a major factor. Cost decreases as volume increases.

• Department size, as measured in terms of total number of faculty, is a consistent cost indicator. The larger the department, the higher the cost.

• The proportion of faculty holding tenure is a cost factor. The higher the proportion of tenured faculty, the higher the cost.

Page 36: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures

• The presence of graduate instruction in a discipline increases costs, although the measured effect of this variable on direct instructional expense in this study is smaller than teaching volume, department size, and faculty tenure rate.

• The extent to which expense is associated with personnel costs, as opposed to equipment costs, has less impact on total direct instructional expenditures within a discipline than do teaching volume, department size, and tenure rate.

Page 37: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Study of Higher Education Instructional Expenditures - Conclusions

• Earlier studies found no clear relationship between the cost of delivering a college education and the price charged for that education.

• Tuition rates were found to be influenced by the level of state appropriations at public institutions, and by market competition, endowment returns, and internal budget constraints at private institutions.

• Instructional expenditures are associated with entirely different factors – the disciplinary mix at an institution, and within the discipline, teaching volume, department size, tenure rates, etc.

• Cost and prices are not interchangeable constructs.

Page 38: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study – Next Steps

• As useful as Delaware Study teaching load/cost benchmarks are, they do not address the non-classroom dimensions of faculty activity in an institution and its academic programs.

• It is possible that quantitative productivity and cost indicators for a given program/discipline may differ significantly from other institutional, peer, and national benchmarks for wholly justifiable reasons of quality that can be reflected in what faculty do outside of the classroom.

• However, this cannot be determined unless measurable, proxy indicators of quality are collected.

Page 39: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

The Delaware Study – Next Steps

• In Fall of 2001, the University of Delaware was awarded a second three-year FIPSE grant.

• This grant underwrites the cost of developing data collection instruments and protocols for assessing out-of-classroom facets of faculty activity.

• Once again, the grant is supporting an Advisory Committee charged with responsibility for refining and enhancing data collection instrumentation, data definitions, and study methodology.

Page 40: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

Measures of Out-of-Classroom Faculty Activity:

The Data Collection Instrument

Page 41: A Data-Centered Approach to Managing Instructional Costs and Enhancing Faculty Productivity

ResourcesMiddaugh, M.F. Understanding Faculty Productivity: Standards and

Benchmarks for Colleges and Universities. San Francisco: Jossey-Bass, 2001.

Middaugh, M.F., Graham, R., Shahid, A. National Study of Higher Education Instructional Expenditures: The Delaware Study of Instructional Costs and Productivity (NCES 2003-161) Washington DC: US Department of Education, National Center for Education Statistics, 2003.

Middaugh, M.F. “Managing Instructional Costs and Enhancing Faculty Productivity,” in Journal for Higher Education Strategists, Vol. 1, Number 3, Fall 2003.

Delaware Study (Teaching Loads/Cost): http://www.udel.edu/ir/cost

Delaware Study (Out of Classroom Faculty Activity): www.udel.edu/ir/fipse