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INSTRUCTIONAL SERVICE IN
ACADEMIC DEPARTMENTS:
AN EXPLORATORY STUDY

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ABSTRACT

INSTRUCTIONAL SERVICE IN ACADEMIC DEPARTMENTS:
AN EXPLORATORY STUDY

BY

Lou Anna Kimsey Simon

This study was an investigation of the instructional service com-
ponent of academic departments. This examination is part of a broader!
project funded by a grant from the Exxon Education Foundation and
centered at the Office of Institutional Research at Michigan State Uni-
versity under the direction of Dr. Paul L. Dressel. One of the foci of
this the third phase of the Exxon Departmental Study Project is the
development of a budgeting model for academic departments based on
clusters of departments with similar intrinsic characteristics and insti-
tutional roles. The selection of instructional service as a focus of
study was predicated on the possibility of its inclusion as a dimension
of the clustering framework. However, the concept of instructional
service has been brought to the forefront at Michigan State University
because the newly established medical schools subsidize certain depart-
ments for the service instruction given the medical students in "shared"
departments. In lieu of a formalized pricing system for service instruc-
tion, this study identified the amount of service instruction in each
academic department and sought to determine how the extent of instruc-
tional service was reflected in other data about the department (i.e.,

level of funding and staffing patterns).

 

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Purposes

This study was exploratory in nature and was designed to identify
the relationships between measures of instructional service and the
other available data about academic departments. Specifically, the
purposes of this study were to 1) develop appropriate measures of the
instructional service component of academic departments; 2) identify
relationships among these measures and between these instructional
service measures and other departmental characteristics; and 3) classify
departments according to each undergraduate and graduate instructional
service measure and determine which variables discriminate among the

categories of the instructional service measures.

Instructional Service Measures

Two sets of instructional service measures were constructed to
represent the instructional service component of academic departments.
The department-based instructional service measures represented the
relative amount of the total instructional load of each department who
were service students (nondmajors) while the university-based instruc-
tional service measures reflected the relative amount of the total
instructional service load of the institution (instruction to nondmajors)
which was assumed by each department. Within each of these two set of
measures, six measures representing various aggregates of courses within

the departments were also constructed.

 

 

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Research Design

The research design developed for this study centered around ten
questions about the relationships among the twelve instructional service
measures and between each of these measures and departmental descriptor
variables. In this study, two hundred fifty—two Spearman rank correla-
tions and eight chi-square tests for independence were used to analyze
the relationships among the twelve instructional service measures and
between each of these measures and variables representing funding,
faculty rank distributions, average salary, number of graduate assis-
tants, prestige of graduate programs/faculty, and level of students
served in undergraduate courses. In addition, the multiple discriminant
analyses identified factors (generated from the principal axes factor
analysis) which discriminated among the levels of eight of the instruc-

tional service measures.

Findings

The analyses of the data on instructional service revealed that sig-
nificant relationships existed between 1) undergraduate and total
instructional service measures, 2) department—based and university-based
instructional service measures, and 3) unadjusted and adjusted instruc—
tional service measures. The results of the chi-square tests for inde-
pendence indicated that l) departments that service predominately lower
division students tended to have high adjusted, and unadjusted, under-
graduate university—based measures and 2) departments with prestige

graduate programs/faculty tended to be classified as medium for the

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department-based graduate instructional service measures while the

rated departments were primarily distributed between the medium and

high categories for the university-based graduate measures. In addition,
of the one hundred eighty Spearman rank correlations between the instruc-
tional service measures and the descriptor variables representing fund-
ing, faculty rank distributions, number of graduate assistants, and
average salary, sixty-four (35.6%) were statistically significant, but
only twenty-two of these correlations (12.2%) were strong (greater than
.50) and, therefore, meaningful. Finally, the results of the principal
axes factor analysis with a varimax rotation and the multiple discrimi-
nant analyses were unusually decisive. In the factor analysis six
factors were defined which were good representations of the original
data (explained 82% of the variance) and were highly internally consis—
tent (alphas greater than .90). For seven of the eight instructional
service measures used in the multiple discriminant analyses, only one of
the two discriminant functions was significant. For the adjusted
graduate department-based instructional service measure, no discriminant
function was significant. Three factors emerged which discriminated
among the categories of the seven instructional service measures.

Factor 1 (undergraduate instructional load) was the dominant variable in
the analyses of the unadjusted and adjusted undergraduate university-
based instructional service measures. Factor 2 (graduate instructional
load) was the dominant variable for the adjusted graduate department-
based instructional service measure and the unadjusted and adjusted grad-

uate university-based instructional service measures. Factor 3

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(undergraduate instructional output) was the dominant variable for the
unadjusted and adjusted undergraduate department-based instructional

service measures.

Conclusions

The findings indicated that overlap among the instructional service
measures existed. The results of this study suggested that in any fur-
ther analysis which included instructional service only the unadjusted
undergraduate and graduate department-based are needed to represent the
instructional service component of academic departments. Further, the
lack of meaningful relationships between the department-based instruc-
tional service measures and the descriptor variables indicated that the
funding and staffing of departments are not related to the level of
instructional service in these departments. Instructional volume rather
than the parameters of the instructional process in academic departments
tended to be the primary determinant of departmental funding and staff-
ing. Finally, though the results of the multiple discriminant analyses
were unusually decisive, the use of factors instead of variables greatly
complicated the interpretation of the results. Further research which
clarifies the interactions of variables within these dominant factors
is needed before a clear understanding of the relationships between the
level of instructional service and variables representing instructional
load and instructional output emerges. However, such further research
must also be related to the realities of departmental organization and

budgetary process.

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INSTRUCTIONAL SERVICE IN ACADEMIC DEPARTMENTS:

AN EXPLORATORY STUDY

By

Lou Anna Kimsey Simon

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Administration and Higher Education

1974

© Copyright by
LOU ANNA KIMSEY SIMON
1974

To My Family
This study is dedicated to my fwnily.

Their encouragement, understanding, and
love are the cornerstone of my efforts.

iii

all?

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ACKNOWLEDGMENTS

This writer wishes to express her sincere appreciation to
Dr. Paul L. Dressel for his guidance and support in preparing this
dissertation and for the excellent experience derived while working in
the Office of Institutional Research as a graduate assistant and as
the Assistant Director of the Exxon Departmental Study Project.

This writer also wishes to thank the members of her committee--
Dr. Maryellen McSweeney, Dr. Philip Marcus, and Dr. Vandel Johnson.
Their advice and criticism have greatly improved the quality of this
'work and the quality of the educational experience which surrounded
this effort.

Grateful acknowledgment is extended to all members of the Institu-
tional Research staff for their constant support and encouragement.
A special word of appreciation is extended to Dr. Mary Thompson and
Dr. William.Faricy who assisted in the final preparation of this manu-
script.

Finally, this writer wishes to thank Christina Traines who dis-

played outstanding competence and patience in typing manuscript drafts.

 

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Overview

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II.

III.

IV.

V.

TABLE OF CONTENTS

LI S T OF TABLES I O O O O O O O O O O 0

LIST OF FIGURES. . . . . . . . . . . .

 

RATIONALE FOR THE STUDY. . . . . . . .

Introduction. . . . . . . . . . . .
Purpose of the Study. . . . . . . .
Assumptions of the Study. . . . . .
Limitations of the Study. . . . . .
Definitions of Terms. . . . . . . .
Overview of the Dissertation. . . .

CONCEPTUAL FRAMEWORK FOR INSTRUCTIONAL
smary O C O O O O O O O O O O O O
OTHER DEPARTMENTAL LITERATURE. . . . .

Background. . . . . . . . . . . . .
Departmental Organization . . . . .
Empirical Studies . . . . . . . . .
Summary . . . . . . . . . . . . . .

RESEMCH DESIGN 0 O O O O O O O O O O 0

Instructional Service Measures. . .
Data. . . . . . . . . . . . . . . .
Research Questions. . . . . . . . .
Methodology . . . . . . . . . . .

Summary . . . . . . . . . . . . . .

THE RESULTS 0 O O O O O O O O O O O O 0

Instructional Service Measures. . .
Relationships Between Instructional

and Descriptive Data . . . . . .
Discriminatory Variables. . . . . .
Summary . . . . . . . . . . . . . .

Measures

Page

vii

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CHAPTER
VI. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS FOR
STIJDY O O O O O O O O O O C O O O O O O O
OverView Of the Study 0 O O O O O O O O O
smry Of Findings 0 C O O O O O O O O 0
Conclusions . . . . . . . . . . . . . . .
Recommendations for Further Study . . . .
APPENDICES
A. DEPARTMENTS IN STUDY . . . . . . . . . . . .
B. LIST OF MSU DEPARTMENT DESCRIPTOR VARIABLES.

C. TABLES OF DATA USED IN THIS STUDY. . . . . .

BIBLIOGRAPHY I O O O C O O O O O O O O O O O O O O 0

vi

Page

106
106
114

116
125

128
131
135

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LIST OF TABLES

Table

10.

ll.

12.

13.

14.

15.

16L

Summary Measures. . . . . . . . . . . . . . . . . . . . . .
Instructional Service Students by Course Level, Fall 1971 .
Enrollment by Course Level, Fall 1971 . . . . . . . . . . .
Equations for Instructional Service Measures. . . . . . . .
Department-based Instructional Service Measures, Fall 1971.
University-based Instructional Service Measures, Fall 1971.

Extreme Departments--Unadjusted and Adjusted Department-
based Instructional Service Measures. . . . . . . . . . . .

Descriptive Data--Department-based Instructional Service
Measures 0 O O O O I O O O O O O O O O O O O O O O O O O O 0

Descriptive Data-—University-based Instructional Service
Measures 0 O O O C O O C O O O O O O O O O O O O O O O O O O

Spearman Rank Correlations Among Instructional Service
Measures 0 O O O O O O O O O O O O O O O O O O O O O O O O 0

Departments with Predominately Lower Division Instructional
Service Students in Undergraduate Courses . . . . . . . . .

Chi-square Tests of Independence-:Level of Instructional
Service Students in Undergraduate Courses . . . . . . . . .

Departments with Prestige Graduate Faculty/Programs . . . .

Chi-square Tests of Independence-—Prestige of Graduate
FaCUItYIPrOgramS O O O O O O O O O O I O O O O O O O O O 0 O

Spearman Rank Correlations Between Instructional Service
Measures and Descriptive Data . . . . . . . . . . . . . . .

Descriptor Variables with Moderate and Strong Relationships
to Instructional Service.Measures . . . . . . . . . . . . .

vii

Page

38
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62
64
65

67

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73

75

79

80

82

83

85

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LIST OF TABLES--Continued

Table

17.

18.

19.
20.
21.
22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

Categories of Department—based Instructional Service
Depar men t 8 O O O O O O O O O O O O O O O I O O O O O O O 0

Categories of University-based Instructional Service
Deparmenta O O C O O C C O O O O O O O O C I O O I O O O 0

Factors and Their Loadings. . . . . . . . . . . . . . . . .
Descriptive Data--Factors and Their Loadings. . . . . . . .
Standardized Discriminant Functions . . . . . . . . . . . .
Group Means on Standardized Functions . . . . . . . . . . .

List of Departments with Disparate Unadjusted and Adjusted
Department-based Instructional Service Measures . . . . . .

Departmental Rankings on Department-based Instructional
Service Measures. . . . . . . . . . . . . . . . . . . . . .

Departmental Rankings on University-based Instructional
Service Measures. . . . . . . . . . . . . . . . . . . . . .

Rank Ordering of Departments According to Unadjusted Under-
graduate Department-based Instructional Service . . . . . .

Rank Ordering of Departments According to Unadjusted Gradu-
ate Department-based Instructional Service. . . . . . . . .

Rank Ordering of Departments According to Unadjusted Total
Department-based Instructional Service. . . . . . . . . . .

Rank Ordering of Departments According to Adjusted Under—
graduate Department-based Instructional Service . . . . . .

Rank Ordering of Departments According to Adjusted Graduate
Department-based Instructional semiceo o o o o o o o o o 0

Rank Ordering of Departments According to Adjusted Total
Department-based Instructional Service. . . . . . . . . . .

Rank Ordering of Departments According to Unadjusted Under-
graduate University-based Instructional Service . . . . . .

Rank Ordering of Departments According to Unadjusted Gradu-
ate University-based Instructional Service. . . . . . . . .

viii

Page

91

92
94
95
100

101

136

137

139

141

142

143

144

145

146

147

148

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Table

34.

35.

36.

37.

38.

39.

40.
41.

42.

43.

44.

45.

Rank Ordering of Departments According to Unadjusted Total
University-based Instructional Service . . . . . . . . . .

Rank Ordering of Departments According to Adjusted Under—
graduate University-based Instructional Service. . . . . .

Rank Ordering of Departments According to Adjusted Gradu-
ate University-based Instructional Service . . . . . . . .

Rank Ordering of Departments According to Adjusted Total
University-based Instructional Service . . . . . . . . . .

Departmental Rankings on General Fund Expenditures,
1971-72 0 O C O O I I O O O O O O O O O O O O O O O O O O 0

Departmental Rankings on Research Grant and Contract
Expenditures, 1971-72 0 o o o o o o o o o o o o o o o o o 0

Faculty Rank Distribution Indices. . . . . . . . . . . . .
Graduate ASSiStantS, 19 71-72 0 o o o o o o o o o o o o o 0

Rank Ordering of Departments According to Average 10~month
Equated salary, 19 71-72 0 O O O O O O O O O O O O O O O O 0

Percentage Distribution of Instructional Service Students
by Student Level--Unadjusted Data. . . . . . . . . . . . .

Percentage Distribution of Instructional Service Students
by StUdent Level--Adj 113th Data. 0 o o o o o o o o o o o 0

Factor scores 0 O O O O O O O O O O O O O O O O O O O O O O

Page

149

150

151

152

153

155

157

159

161

162

165

168

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1. Group Means——DBIS—-UU and DBIS—UG . . . . . . . . . . . . . 102
2. Group Means—~DBIS—AU and DBIS—AG . . . . . . . . . . . . . 102
3. Group Means-w-UBIS—UU and UBIS—UG . . . . . . . . . . . . . 104

4. Group Means__UBIS-AU and UBIS—AG o o o o o o o o o o o o o 104

 

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Chapter I

RATIONAL FOR THE STUDY

Introduction

As university operations have come under close scrutiny by
legislative and fiscal agencies and the taxpaying public, growing
disillusionment with higher education has amplified the cry for more
managerial and financial accountability. In an article by Grassell,
‘Whitter--speaking for the Council for the Advancement of Small
Colleges--stated that

The crisis in which higher education finds itself today demands

nothing less than our institutions being operated on the basis

of sound management principles, keeping in mind, of course, that

college and university purposes and characteristics are differ-

ent from those of business and government.1

In addition to being under public suspicion, higher education
also finds itself in financial difficulty. The "dollar squeeze" has
been intensified by declining revenues from tuition, increasing oper-
ating costs, and diminishing soft monies. As Cheit points out

In short, due to inflation and growing demands on schools for

more service, for broader access, for academic innovation and
for more quality, costs were rapidly rising. But income has not.2

 

1E. M. Grassell, "The President Needs Training in Management,"
College Management, 6 (August, 1971), p. 29.

2E. F. Cheit, The New Depression in Higher Education (New York:
McGraw-Hill, 1971), p. l.

("”1" 5}

 

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Thus, less costly techniques must be found for meeting institutional
responsibilities while retaining acceptable levels of quality. The
development of efficient and effective methods of resource allocation
compatible with institutional organization, goals, and needs has
become of primary importance.

Many states have developed techniques of formula or program
budgeting for appropriating funds to institutions. Yet, once institu—
tions have these funds in their possession, they tend to divide these
funds among operating units in traditional ways. This allocation
procedure often takes the form of across-the-board percentage increases
or decreases. Such uniform percentage changes across operating units
reinforce the relative position of units and indirectly establish
institutional priorities. The "fat" programs and departments remain,
and some even grow fatter. But this type of system.maintenance cannot
respond to changes in societal goals and public needs and to altera-
tions in assigned or implied institutional responsibilities. Simple
maintenance or reinforcement of existing structures and priorities is
no longer tenable for institutions of higher education.

Sound planning and management require that institutional priori-
ties become operational through the budget. Within each institution,
the key to sounder financial management lies at the level of the basic
budget unit or cost center. In academic areas this basic unit is
usually the department. In spite of debates about the appropriateness
of the departmental structure for higher education, especially under-

graduate education, departments remain the predominant organizational

f1

 

arrives to the
1;; 55.51:- pattern.

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elements of colleges and universities around the world. Furthermore,
alternatives to the departmental structure tend over time to regress to
this basic pattern. At the departmental level inputs are translated
into various outputs with contrasting degrees of efficiency. The
aggregate of these departmental data reflects the overall level of
institutional efficiency. A redefinition of efficiency at the insti-
tutional level does not imply greater effectiveness or efficiency for
all departments. (This change could reflect a shift of mean which was
accompanied by greater departmental variation.) Thus, departments
represent viable units around which to develop a budget methodology.
Some would argue as McConnell does in the following passage that
each department is unique and that separate criteria must be developed
for the evaluation of each department.
The nature of departments varies so greatly, not only among
institutions, but within particular institutions, that it is very
difficult to make valid general statements about departmental
organization and administration.3
On the other hand, a complete departmental self-study for each unit at
a large institution is prohibitive, especially if such a self-study
were to become necessary as an annual basis for resource allocation.
Furthermore, the budgetary process for any single department always
takes place in the context of the needs and aspirations of other

departments. Departmental comparisons are inevitable. Procedures

should be developed and tested by which departments could be grouped

 

3T. R. McConnell, Notes for a Table on Departmental Organization,
Monograph 5 (Blouder, Colorado: Western Interstate Commission for
Higher Education, 1969), p. l.

,‘ 1,115

 

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or clustered on variables or parameters which provide an equitable
basis for departmental funding. These dimensions should recognize

the inherent differences in disciplines and their concomitant instruc-
tional methodologies which affect input and output properties. This
clustering strategy is predicated on the assumption that the budgetary
procedure for departments with similar characteristics and missions
should utilize the same funding principles and variables. When this
strategy is applied, each department is compared only with other
departments in its cluster and not with the entire university commun-
ity. This approach permits variability among departmental clusters
while stressing the development of uniform funding criteria within
clusters.

The fundamental question is what dimensions or variables should
be used as a basis for departmental clustering. By employing factor
analytic techniques almost any set of variables could be used to group
departments. Yet, implicit in the above discussion is the assumption
that these clustering dimensions should have inherent implications for
departmental resource allocation. This stipulation requires a clear
understanding of each of the dimensions chosen as a basis for cluster-
ing departments. Simply manipulating the cost data on academic
departments reflects only past budgeting practices about which little
rationale is available. Thus, clustering dimensions must be identified
in the context of a conceptual model of resource allocation, and these
dimensions should be explored in light of present departmental data so

that relationships in the data can be identified and redundancies

 

. ‘ ~
Sal-neg. 0D-y ‘1
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“ct the azaLySLS C

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eliminated. Only after intensive study should these dimensions be
included in the departmental clustering methodology. This study under-
took the analysis of one possible dimension--the instructional service

component of academic departments.

Purpose of the Study

This study was exploratory in nature and designed to identify
relationships and patterns between the aspects of instructional service
and other available data on academic departments. This examination of
instructional service in academic departments is part of a broader
project funded by a grant from the Exxon Education Foundation and
centered at the Office of Institutional Research at Michigan State Uni-
versity under the direction of Dr. Paul L. Dressel. One of the foci
of this third phase of the Exxon Departmental Study Project“ is the
development of the cluster-oriented budgetary schema alluded to in the
introduction of this chapter. Using eighty-two academic departments
at Michigan State University as the study population, the specific pur-
poses of this study were to:

1. Develop appropriate measures of the instructional service com-

ponent of academic departments. These measures represent both

the amount of instructional service in a department and the

 

I*The two previous projects are summarized in The Confidence Crisis
(1970) by Dressel, Johnson, and Marcus and Return to Responsibility
(1972) by Dressel and Faricy. Journal articles and dissertations have
also been written from the data of these projects.

 

contributic

serv'ce loe

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contribution of a department to the overall instructional

service load of the institution.

2. Identify relationships among_the instructional service
measures, among_phese measures and other departmental charac-
teristics. These departmental characteristics include funding
level, faculty rank distribution, and levels of students

served.

3. Classify departments on the basis of instructional service
and determine which variables serve to discriminate among
catggories of service. Through various analyses, variable and
variable sets emerge which are related to the amount of instruc-

tional service in academic departments.

Assumptions of the Study

Three basic assumptions are the premises for this study. First,
departments are the basic organizational units in institutions of
higher education and are, thus, an appropriate analysis unit. The
development of departments can be traced to nineteenth century Harvard
and the University of Virginia.5 While the rationale for the establish-
ment of departments is unclear, the expansion of knowledge and the

elective system fostered the development of departments as organizational

 

5J. S. Brubacher and W. Rudy, Higher Education in Transition
(New York: Harper and Brothers Publishers, 1958), p. 354.

 

cities.s 188315:

2:25, tepattaeats

 

.41

the faculty

Li
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raiaxlty and a1:
'zgreseat status

3 :eaffimed in t.

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education and
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6 Regardless of the initial organizational intent of depart-

entities.
ments, departments have evolved as the professional and intellectual
home of the faculty, providing peer social-psychological support for
the faculty and also serving as a vehicle for academic governance.
The present status of departments as the "heart of the multiversity"7
is reaffirmed in the following passage from the Michigan State Univer-
sity faculty bylaws:

The department or school is the basic administrative unit of
education and research within the university.8

Second, departments can be described by dimensions that transcend
traditional collegial structure and disciplinary lines. Further,
these dimensions are identifiable, measurable, and can be explicated
in objective terms. Thus, the teaching load of each department,
regardless of affiliated college or subject matter, can be expressed
in a countable unit such as teaching credits. The existence of such
dimensions, not the homogeneity of departments on these dimensions, was
postulated in this study.

The third assumption implicit in this research was that the

instructional service aspect of academic departments is a viable

 

6J. A. Perkins (Ed.), The University as an Organization
(New York: McGraw-Hill Book Company, 1973), p. 25.

7R. Hutchins, "The University and the Multiversity," The New
Republic, April 1, 1967, p. 17.

8Michigan State University, Bylaws for Faculty Governance
(East Lansing: Michigan State University, 1971), p. 7.

4+?

 

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dimension for study. In this study departmental activity was parti-
tioned into two basic analysis units--a core unit and a service unit.
The core unit consists of those inputs, resources, and outputs which

are related to the education of students (graduate as well as under-
graduate) who are majors in programs in a department. This departmental
aspect includes the research and public service activities which are
integrally related to the instructional programs within the department.
The service aspect consists of those inputs, resources, and outputs
which are related to the education of students who are not majors in
programs offered by the department. This service component includes
instruction to nondmajors as well as research and public service activi-
ties that are tangential to the main thrust of the department and the
disciplines within the department. Thus, using the core-service
dichotomy, the service component of academic departments is defined as
an extension of activity beyond that which is required for the educa-
tion of students majoring in fields within the department.

Part of the utility of this dichotomy for resource allocation
rests on cost differentials between service and non-service instruction.
Service instruction tends, by nature, to be introductory, thus lending
itself to large class size and reduced cost per unit. In addition,
introductory courses are usually taught by junior faculty whose salar-
ies are lower than senior faculty. Finally, the addition of service
students to primarily major—oriented classes can be viewed as affecting
marginal cost rather than fixed cost. Thus, while exact cost differen-
tials are unknown, available evidence supports the proposition that

these differentials exist.

 

Recent organ

are indicated tn

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Recent organizational developments at Michigan State University
have indicated the need for a better understanding of the service
aspect of academic departments. The addition of two medical schools9
triggered the proliferation of multi—administered and multi-financed
departments. These "shared" departments received operating funds from
each medical school as well as from the university's general fund.

This multiple funding occurred because the medical schools each re-
ceived a line budget from the legislature. Through the funding of
these "shared" departments, the medical schools were providing a sub-
sidy for the service rendered to their students by the "shared" depart—
ment. This type of subsidy was heretofore hidden in the general fund
appropriations since each department provides some service to the
university community. While neither the medical schools nor the
"shared" departments were the focus for this research, these units did
provide the impetus for studying the service aspect of academic depart-

ments within a conceptual framework based on economic theory.

Limitations of the Study.

This study was limited to analyses related only to the instruc-
tional service aspect of academic departments. Thus, the service
aspect was considered only in terms of course offerings. This view of
service neglected such faculty activities as advising and sitting on
graduate committees of non-majors. Hence, the qualifier "instructional"

has been used throughout this study. In addition, the generalizability

 

9The College of Human Medicine was established in 1966, and the
College of Osteopathic Medicine was established in 1970.

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10

of the results of the study was limited by the inclusion of only
departments from.Michigan State University. However, the exploratory
and descriptive nature of the research lends itself to an institutional-
based in-depth study with the economic model providing the conceptual

framework for similar work in other institutions.

Definitions of Terms

As noted previously, one of the purposes of this study was to
develop appropriate measures of the instructional service component
of academic departments. Two constructs were created for this purpose.
One set of measures was developed to reflect the relative amount of
instructional service in each academic department. These department-
based instructional service measures (DBIS) represented the proportion
of the total number of students enrolled in a department during Fall
term 1971 who were service students (nondmajors). As the percentage
of service students increased, the value of these department-based
instructional service measures also increased, with higher values
representing departments whose instruction was primarily service. The
second set of measures was developed to reflect the relative amount of
the total instructional service load of the university (instruction to
nondmajors) which was assumed by each academic department. These
university-based instructional service measures (UBIS) represented the
proportion of the total number of service students taught during Fall
term 1971 who received instruction in each academic department.
Similarly, high values on these universityebased instructional service

measures represented departments that processed many service students

 

 

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11

and, therefore, assumed a large share of the university's non—major
instruction. Both constructs are discussed in greater detail in

Chapter IV.

Overview of the Dissertation

Chapter I has presented a rationale for the study of instruc-
tional service. Chapter II presents ideas and literature related to
a conceptual framework for resource allocations of which instructional
service is a part. Chapter III presents other relevant literature
about the department and its operations. Chapter IV describes the
nature of the data, the specific research questions in this study, and
the analysis methodologies. Chapter V presents the results of the
various analyses. Chapter VI presents a summary and conclusions of

the study along with suggestions of areas for further study.

 

 

 

 

 

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Chapter II

CONCEPTUAL FRAMEWORK FOR INSTRUCTIONAL SERVICE

As mentioned in Chapter I, the validity of instructional service
as a dimension of a departmental budgeting schema and, hence, as a
topic for study was predicated on the efficacy of this concept in
resource allocation. The fiduciary relationships between the basic
science departments and the medical schools at Michigan State Univer«
sity provided an example of the purchase of service by units within
the same umbrella organization. This situation evolved because the
medical programs were line-budgeted by the legislature and because
the "shared" pattern which evolved helped facilitate the integration
of the medical schools into the university community. Yet, no system-
atic method of exchange has evolved for determining what activities of
the departments are actually being purchased and what relative value,
"price," is associated with each of these activities. The amount of
the departmental subsidy has been separately negotiated for each fund-
ing source. In turn, department chairmen have tried to allocate their
departmental activities in a manner commensurate with the subsidy.
However, with a growing cry for more accountability, this allocation
by bargaining must give way to a more quantitative input-output model
in which the commodities purchased from these basic science departments

are identified and their rates of exchange are clearly established.

12

 

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13

While actual dollar subsidies occur between the medical schools and
the basic sciences, a hypothetical service subsidy schema could be
developed which provides part of the basis for the funding of all
academic departments. In this study only the instructional service
aspect of academic departments was analyzed. Yet, a service subsidy
schema could extend to all the activities of the department which are
not associated with the education of department majors. For example,
academic advising, doctoral committee assignments and administrative
assignments in other departments, i.e., curriculum committees, could
also be included.

In a RAND publication, economist Martin Shubik proposed eight
basic mechanisms for resource allocation: "(1) the economic model with
a price system, (2) voting procedures, (3) bidding, (4) bargaining,
(5) allocation by high authority, (6) allocation by force, (7) alloca-

1 The current trend in

tion by custom, and (8) allocation by chance."
institutions of higher education is away from mechanisms 2-8 which have
been historically dominant and towards a flexible system which provides
not only incentives for adapting to changing educational needs and for
improving the educational quality by reducing costs, but also a format
for assessing the efficiency and effectiveness concerns of an account-

ability model. These types of incentives are present in an economic

model with a price system. However, higher education when examined

 

1M. Shubik, On Different Methods of Allocatinijesources, as
quoted in D. W. Breneman, Internal Pricinngithin the Universipye-
A Conference Report (Berkeley, Calif.: University of California,
1971), pp. 3-4.

 

     
 

it: at economic j.

",1 fi' ‘I5cs.Zdtlt
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3:: purchase it
3 these who fin.
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14

from an economic perspective, is an extremely unique industry. Unlike
other organizations whose operations are governed by a market model,

in institutions of higher education, "(1) those who consume its product
do not purchase it; (2) those who produce it do not sell it; and

(3) those who finance it do not control it."2

Thus, the selection of
the type, quantity and quality of an educational output is governed by
the producers (faculty within each department) and is not determined
by the consumer (the student) since he has no buying power. Within
this type of framework, no incentives for adapting to changing educa-
tional needs exist. Further, since the producers have no investments
in the product (not the financiers), little incentive exists for
improving quality and reducing costs.

The above assessment of the uniqueness of higher education indi-
cates that organizational behavior in educational institutions is
diametrically opposed to the price-driven tenets of a market model.

In its polar characteristics it represents a nondmarket economy

in which (a) non-price variables, non-profit goods, and non-

divisible resources (inputs and outputs) are prominently present;

(b) non-tatonnement exchanges and resource transfers are very

important due to transaction and information costs; (c) price

signals and output quotas may be replaced by other organizational
procedures ...; and solutions may be attempted by central direc-
tives and informal organizational procedures.

Thus, the interaction of departments for scarce resources within the

umbrella organization of the institution simulates a nondmarket model

 

2J. M. Buchanan and N. E. Develetoglou, Academia in Anarchy
(New York: Basic Books, Inc. Publishers, 1970), p. 8.

 

3K. A. Fox (Ed.), Economic Analysis for Educational Planning
(Baltimore: The Johns Hopkins University Press, 1972), p. 20.

 

52:5 this intera;
tyne-price (cua'.
fixation with:

:gtizization of a
:tgrization and t
kaiiiticn, t'ne :
ti: can occur.

31*é-r‘set model

etzznics. The e

 

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15

since this interaction represents an internal market which is governed
by non-price (quality and prestige) variables. Techniques for resource
allocation within a non-market model require the optimization or sub-
optimization of a policy function which reflects the objectives of the
organization and the set of activities which relate inputs to outputs.
In addition, the relative price of each must be known before Optimiza-
tion can occur. Plessnar, Fox and Sanyal have developed a policy-based
nonemarket model for the allocation of resources in a department of
economics. The economic part of the model was represented by a
programming objective function which consists of the capitaliza-
tion of expected lifetime income earned by students who graduate
from the department in all its programs less departmental expenses
on new faculty and other expenditures associated with the teaching
program.“
Fox has also described problems and approaches for comparing work loads
and performance among departments within a university, developing work
load, cost, and quality measures for a given department, and comparing

5 However, all

departments in the same discipline across institutions.
these techniques which apply the postulates of non-market models to
higher education are theoretical manipulation rather than practical
realities upon which resource allocation can be based.

If departments are viewed using the core-service dichotomy

described in Chapter I, a more practical application of an economic

 

l’Y. Plessnar, K. A. Fox, and B. C. Sanyal, "On the Allocation of
Resources in a University Department," Metroeconomica,2M)(September,
1968), p. 259.

 

5K. A. Fox (Ed.), Economic Analysis for Educational Plannipg
(Baltimore: The Johns Hopkins University Press, 1972), pp. 258-295.

 

 

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theory for resource allocation emerges. The decentralized market

model advocated by Hoenack and Norman6

in a recent journal article
could be applied to only the service aspect of each department, and
more subjective allocation techniques like bargaining or bidding

could be used as a basis for the subsidy of the core areav-teaching,
research, and public related to the education of majors. This pro—
cedure theoretically divides the department into a major coalition

and a service unit in a manner which parallels Hirschleifer's model

of a divisionalized firm.7 Under this allocation procedure, depart—
ments would first be funded in terms of their major coalition-reore--
activities. Thus, funding from external agencies for research or
instruction would become part of the pool for the core activities.
Funding for the service aspect would be generated from fees paid by
nondmajors in exchange for instruction or other activities provided by
the department. "Theoretically, under this system, each department
has an incentive to reduce costs while maximizing output since it
naturally wishes to maintain or increase its operating budget."8
In addition, the separation of funding for service and non-service

students would provide non—service students with buying power which

theoretically should make the department more responsive to the needs

 

6S. A. Hoenack and A. L. Norman, "Incentives and Resource Alloca-
tion in Universities," Journal of Higher Education, 45 (January,

7J. Hirschleifer, "Economics of the Divisionalized Firm,"
Journal of Business, 30 (April, 1957).

8J. F. Minahan, "Administrative Cost Accounting: Whose Cost and
Whose Accounting," Journal of Higher Education, 45 (January, 1974),
p. 25.

 

 

"'"se students

rather than requi
2:: be reizburse
asigzents, anc

rte of model is

arts-eaten oetu

Hoenack a“:

el\

Smite fees 5*

6“
1:5: .
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T33 SEI’Vi;
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17

of these students and should increase the quality of service instruc-
tion. This is especially true if the students purchased elective
rather than required instruction. Similarly, the department could
also be reimbursed for activities such as advising, doctoral committee
assignments, and committee assignments outside the department. This
type of model is presently approximated by the "shared” department
arrangement between the medical schools and the basic science depart-
ment.

Hoenack and Norman advocated the position that instructional
service fees should be set by each department and that these fees could
differ substantially by department and by teaching methodology. Thus,

The service unit sets the prices of all its services, including

instruction. The expansion or contraction of a service unit

depends solely on its market performance because service units
receive payment directly from their clients and budgets are not

granted automatically by the institution.... In establishing a

schedule of prices for alternative types of services, it is

assumed that academics will seek to maximize a utility function

of which prestige is an important component.9
In a market model with such an internal pricing schema, each department
accrues part of its operating budget on the basis of the value of its
output (measured by a schedule of internal prices) and uses this portion
of its budget to purchase resources, internally priced at opportunity
cost. Thus, "the central administration can influence departmental

behavior by altering the values placed on outputs, while maintaining

the advantages of decentralization in resource use through the system

 

9S. A. Hoenack and A. L. Norman, "Incentives and Resource Alloca-
tion in Universities," Journal of Higher Education, 45 (January, 1974),
p. 25.

 

:5 internal res;
otter: 1.2.3.8163

l. Toe abse
of colle

2. The lat}:

OL'CP'JZS;

w

Toe prev

o..,.; l ‘
maritime 112:1.

3e outputs of 1

 

18

of internal resource prices."1°

Yet, several problems prohibit the
current implementation of a complete pricing system:

1. The absence of a complete, well-defined and measurable set
of college and university outputs;

2. The lack of systematic methods for evaluating university
outputs;

3. The prevalence of single year budgets;

4. Lack of knowledge regarding the educational production func-
tion; and

5. Inflexibility in staffing created by tenure positions.11
Therefore, until research which identifies and measures adequately
the outputs of higher education and research which characterizes the
decisiondmaking processes within institutions have been completed,
internal pricing--like the non-market approach--will remain theoretical
exercises. Until these methodological problems are solved, the inclu-
sion of the instructional service measures as a dimension of the
departmental clustering and budgeting schema serves to identify depart-
ments whose funding base would be contingent largely on money acquired
from service instruction.

A review of the annotated bibliographies of the Association for
Institutional Research for the last four years revealed no reference

to service instruction. Thus, measures of instructional service have

not become part of the regular reporting schema for academic departments.

 

10D. W. Breneman, Internal Pricing Within the Universipy--A Con-
ference Report (Berkeley, Calif.: University of California, 1971),
p. 30.

11Ibid.

 

 

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19

However, probably the most prominent examples of the use of the concept
of instructional service in a management system are the induced course
load and the induced work load matrices which are an integral part of
the Resource Requirements Prediction Model (RRPM) developed by the
National Center for Higher Education Management Systems at the Western
Interstate Commission for Higher Education. From the data in these
matrices, the number of credits taken in each discipline by the average
student enrolled in each program and the total number of credits each
discipline must generate in order to satisfy the demand placed on it

by all students enrolled in each program for a given period can be
determined.‘12 Since the dimensions of these matrices are in terms of
programs and disciplines, further aggregation is necessary to generate
work load information for each department. On the basis of this in—
formation the effect of a decrease or increase in enrollment in any
other sector of the institution can be calculated in terms of the
resource needs of each department. Unfortunately, the construction of
induced course load and work load matrices is a difficult task which
requires large manpower and hardware commitments. However, the measures
of instructional service developed in this study do identify departments
whose resource requirements are very sensitive to change in the enroll—
ments within the institution. For example, the department—based
instructional service measures reflected the relative proportion of the

department's instructional load which are service students. Thus,

12National Center for Higher Education Management Systems, A Blue—

2rint for RRPM, 1.6 Application (Boulder, Colo.: Western Interstate
Commission for Higher Education, 1973), p. 19.

 

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20

departments with high department-based instructional service measures
have instructional loads and, thus, resource requirements which are

sensitive to changes in student enrollments or enrollment patterns.

Summapy

The preceding discussion provided evidence that the concept of
instructional service can be incorporated in resource allocation and
projective techniques, and within these frameworks this concept can
produce greater clarity and refinement in management models. Yet, the
operation of this concept in the framework presented above is prac-
tically impossible. The instructional service measures developed for
this study and the eventual use of these measures in a departmental
clustering and budgetary schema are important because they provide a
method of incorporating instructional service into a management model
before all the methodological problems mentioned above have been

solved.

o—A
yd:

 

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Chapter III

OTHER DEPARTMENTAL LITERATURE

While the instructional service component of academic departments
was of primary interest in the study, a brief review of the literature
about the establishment and organization of the department provides a
general framework from which to view academic departments and their
management. It was evident from the review of available literature
that most articles about academic departments were based on speculation
rather than empirical data. However, in this chapter some of the
empirical works on academic departments are presented. Again, their
relevance is in terms of a general understanding of academic depart—
ments, and these works had little direct bearing on the analyses in this

study.

Backgppund

The evolution of the department to its present position as the
basic organizational unit in institutions of higher education closely
paralleled the growth and specialization of knowledge. Yet, the estab-
lishment of the elective system in the early nineteenth century provided
the catalyst for the reorganization of college faculties on the basis

of subject matter rather than individual chairs of instruction.1

 

JJ. Brubacher and W. Rudy, Higher Education in Transition
(New York: Harper and Brothers, Publishers, 1958), p. 114.

 

21

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22

The emergence of the department pattern as an organizational reality
occurred in the "second quarter of the nineteenth century at both

2 While forces such as

Harvard and the University of Virginia."
specialization and the elective system have been identified as con«
tributors to the development of the departmental structure, the exact
rationale used by men such as Eliot at Harvard for this reorganization
is only speculation. Veysey states the problem thus:
Indeed one may find the date on which such and such a depart—
ment was established at such and such a university; one may
even uncover a spirited debate over the details of certain of
the new arrangements. But exceedingly little direct evidence
may be found on decisions involving the basic shape of the
rapidly emerging academic structures.3
As the complexity of American life continued to change from a rural,
agricultural society to highly industrialized, urban society aS*a
result of the Industrial Revolution, new specializations were intro-
duced as viable areas of advanced study. These specializations grew
into departments such as engineering, management, and architecture.
In the‘new technological society educational institutions are
expanded not only to exercise research functions but also to
play a central role in the economy and the system of stratifi—

catiod as agencies of selection, training, and occupational
placement of individuals.“

 

2Ibid., p. 354.

. 3L. R. Veysey, The Emergence of the American University (Chicago:
The University of Chicago Press, 1965), p. 267.

1’A. H. Halsey, "The Changing Functions of Universities," in A. H.
Halsey, J. Floud, and C. A. Anderson (Eds.), Education,gEconomy, and
Society (Glencoe, 111.: The Free Press, 1961), pp. 456-465.

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23

With the space age also came widening commitments on the part of insti-
tutions of higher education to the study of societal issues. Depart-
ments of resource development, racial and ethnic studies, and urban
development began to appear on university campuses in addition to
departments representing new specializations such as biophysics and
packaging.

Through its evolution the department "has become the potent force
both in determining the stature of the university and in hampering
the attempts of the university to improve its effectiveness and adapt

5 This increase in

to changing social and economic requirements."
departmental autonomy was a function of the rapid growth and increased
specialization of academic departments and the decentralization of
authority which resulted because the central administrative personnel
could not deal with all the complexities of an evolving multiversity.
Yet, this autonomy which has allowed departments to grow and prosper
poses a threat to departments today because of growing presses for
accountability at all institutional levels. Indeed, Freeman in a recent
article calls departments "a fallacy of misplaced abstraction."6
Freeman further contends that "like credit hours, departments seem use-
ful only in documenting where one has been and not at all useful in

7

imagining where he might go." While perpetuation of the organizational

 

5P. L. Dressel and D. Reichard, "The University Department: Retro-
spect and Prospect," Journal of Higher Education, 41 (May, 1970),
p. 387.

6L. D. Freeman, "The Management of Knowledge," Journal of Higher
Education, 45 (February, 1974), p. 86.

71bid., p. 92.

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24

integrity of the department, rather than the development and transmis—
sion of knowledge, may have become the primary thrust of departments
in today's institutions, departments are still the basic organizational

unit and the "heart" of the institution.

Departmental Organization

Though.McConnell has indicated that the great diversity among
departments makes generalizations about departmental organization and
administration very difficult, the recent studies by Hobbs and Anderson
and by Dressel gpnal, provide some insight into the organization of
academic departments. Though faculty members were described by Millett

as "individual practitioners of scholarship,"8

they do have responsibil-
ity for some administrative matters. These activities generally fall
under the major heading of governance. The primary foci of faculty
efforts in governance at the department level are curriculum review
and control and personnel concerns. Hobbs and Anderson indicated that
the organizational modes for dealing with these two areas were differ-
ent. Curriculum review and control decisions were handled in a demo-
cratic manner while personnel decisions were relegated to a group of
senior faculty.
The most widely applicable model of academic departmental organi—
zation is a composite of (l) a division of labor among peers for
administrative activities, (2) an oligarchy of the senior pro-
fessional ranks for decisiondmaking with respect to professional
concerns, and (3) a collegium, i.e., a democracy, for decision-
making with respect to curricular affairs. But given (a) depart—

ments with varying degrees of activities requiring coordination,
and, hence, varying extents of the divisions of administrative

 

8J. D. Millett, The Academic Community (New York: McGraw—Hill
Book Company, 1962), p. 102.

 

labor, 0))
in profess:
ntal mail
:zinistra’:
if not nos:i
enjoy in CT-
1:atorial p:

CESCIID a:

 

.fi'.

9.

'.':e organic

the role of the

atinistratit'e
Eran: and cont
225. On the
tion in detemii

. 0L
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1 «J5, 3;?98

 

“qultative p

I155 are introd

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uns‘bafiles

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.... could ma.-
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\

25

labor, (b) several possible structures for governance, whether

in professional or curricular concerns, (c) numerous depart-

mental matters which fall in the areas of intersect between

administration and governance, and (d) the inclination of many,

if not most, individuals to exploit whatever power they may

enjoy in one context when participating in another--the combi-

natorial possibilities of organizational models with which to

describe any given academic department are legion.9

The organization of academic departments is further complicated by
the role of the department chairman or head in the decision-making
within the department. There is some debate in the literature as to
whether an elected chairman or an appointed head should be the chief
administrative officer of the department. Porter indicated that if
prompt and confident administration is important then a head is indi-
cated. On the other hand, a chairman is indicated if faculty participa-
tion in determining departmental policy is of paramount concern.10
It, thus, appears that the appointed department head occupies a more
authoritative position than does an elected chairman. Further complexi-
ties are introduced into the organization of departments by past
inadequacies of definition because "for the most part ... the chairman's
role was so poorly defined that there wasn't anything they could do

which could make much difference."11 Euwema indicated that the head

should be personally responsible for recruiting, faculty evaluation,

 

9W. C. Hobbs and L. G. Anderson, "The Operation of Academic Depart-
ments," Management Science, 15 (December, 1971), pp. B-142—l43.

1°K. Porter, "Department Head or Chairman?" AAUP Bulletin, 47
(December, 1961), p. 339.

 

11W. Key, The Department Chairman: One Man's Viewpoint (Boulder,
(blo.: Western Interstate Commission for Higher Education, 1970),
p. 2.

 

:xticultzz, and t
aetything else. '
Toe departs:
#2.: supervisor.
tse faculty to ;
12 ‘.'.dustry has

tile tne cnair:

,,_

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26

curriculum, and ceremonial functions and that he should delegate
everything else.12

The department chairman's position is similar to that of a first-
line supervisor. He represents the administration to the faculty and
the faculty to the administration. However, the first-line supervisor
in industry has two advantages over the department chairman. First,
while the chairman's decisions are primarily in policy execution, the
supervisor makes many decisions of policy formulation as well as execu-
tion. Second, the supervisor's relationship to his subordinates is
usually hierarchical while the chairman is both a leader and a profes-
sional colleague and, thus, has shared power with his colleagues.13
McKeachie summarizes the organizational problems of the chairmanship
thus:

Although the department chairmen in most colleges and universi-

ties are the key individuals in determining the educational

process of the institution, they are generally ill-prepared,

inadequately supported, and more to be pitied than censored.
The chairman's role as well as the formal and informal aspects of the

departmental organization need to be more closely studied so that an

effective management model for academic departments can be developed.

 

123. Euwema, "The Organization of the Department," Educational
Record, 23 (January, 1953), p. 42.

13J. J. Corson, Governance of Colleggs and Universities (New York:
McGraw~Hill Book Company, 1960), p. 89.

1"W. J. McKeachie, "Memo to a New Department Chairman," Educational
Record, 42 (Spring, 1968), p. 221.

 

. .
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dd .35 CEPart
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27

Empirical Studies

Beginning in 1918, Committee T, on Academic Freedom and Tenure,
of the American Association of University Professors has studied the
various procedures in departmental and institutional administration.
At periodic intervals questionnaires were mailed to several hundred
AAUP chapter offices throughout the United States. The 1948 survey was
summarized in Doyle,15 and this survey showed that the major functions
of the department chairman included budgeting and curriculum control
and review. However, Doyle's own study of 107 departments in 33
liberal arts colleges for the academic year 1950-51 is one of the most
intensive works done on the role and functions of the department chair-
man. In this study Doyle conducted interviews about the actual prac-
tice in each department and also studied faculty handbooks, regulations,
resolutions, and minutes. In addition to delineating the functions of
these chairmen, Doyle indicated that these chairmen spent most of their
time in educationally rather than administratively related activities.
Doyle also reported that previous teaching experience, teaching ability,
and administrative ability were the three criteria used in the selec-
tion of a chairman.

Gunter surveyed the department chairmen in ten state universities
during the 1963-64 academic year. He found that the size of the

institution (large or small) did not affect the principal functions of

 

15E. A. Doyle, The Status and Functions of the Department Chair-
man (Washington, D.C.: Catholic University of America Press, 1953) '
pp. 115-125.

 

32 5epartnent c.-

:.:;::an. 011 tit

 

arts toiiege, He

ttzride a criterl

:: tse cepartner.

;:si:i':e correl;

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5 state-support,

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Fftfessicnal Out'

a“ were Percei'

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28

the department chairman.” Hemphill in 1955 studied the relationship
between departmental reputation and the leadership behavior of the
chairman. On the basis of the data from 22 departments of a liberal
arts college, Hemphill concluded that, "It appears that reputation may

Provide a criterion of excellence."17

In an effort to study the power
of the department chairman, Hill and French sampled 375 professors in
5 state—supported four year colleges. Their findings indicated a
positive correlation between the faculty's perception of the power of
the department chairman and the level of the professor's satisfaction
and the productivity in terms of organizational goals. However, a
slight negative correlation existed between perceived power and the
professional output of the professors. In addition, department chair-
men were perceived to have less authority than other administrative

3 Finally, Patterson has reported that in a study of 338

groups.1
professors in 90 departments at 10 universities faculty members tended
to regard the ideal department chairman as a facilitator of their own

self—determined goals, an intermediary between themselves and the dean,

 

150. W. Gunter, "The Role of Department Chairmen in the Governance
of State Universities" (Unpublished Ed.D. dissertation, Washington
State University, 1964).

17J. K. Hemphill, "Leadership Behavior Associated with the Admin-
istrative Reputation of College Departments," in W. W. Charters, Jr.
and N. L. Gage (Eds.), Readings in the Social Psychology of Education
(Boston: Allyn and Bacon, 1963), p. 326.

18W. W. Hill and W. L. French, "Perceptions of Power of the Depart-
ment Chairman by Professors," Administrative Science Quarterly, 11
GMarch, 1967), pp. 548-574.

 

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29
as an information handler, and as a scheduler of time and space.19
Other research has focused on the faculty and students associated
with academic departments. Vreeland and Bidwell classified depart-
ments on the basis of departmental goals and means available for
achieving them. The findings of this research suggested that
the particular definition of undergraduate education by a depart-
ment faculty conditions teachers' affective responses to students
and the way in which they define and relate to the student role.
If so, it may be a faculty's conception of the instructional task
more than the content of the subject matter itself, that deter-
mines the social organization of the department's work with under-
graduates.2°
Currie £5 31. studied the relationship between the images of college
professors which are held by undergraduates and these students' inter-
est in becoming college professors. The results of this survey of
freshmen at the University of California indicated that the prevailing
image of the college professor (an occupational stereotype) is an
important factor in identifying students who are interested in certain
occupations. Also, the number of students "realistically considering"

becoming college professors varied from one area to another.21

 

19L. M. Patterson, "Preferences in Administrative Style Based on
an Inquiry Into the Perceptions of the Ideal Role of the Department
Chairman" (Unpublished Ph.D. dissertation, University of Texas, 1966).

20R. S. Vreeland and C. E. Bidwell, "Classifying University
Departments: An Approach to the Analysis of Their Effects," Sociology
of Education, 39 (Spring, 1966), p. 254.

211. D. Currie gt 31,, "Images of the Professors and Interest in
the Academic Profession," Sociology of Education, 39 (Fall, 1966),
pp. 301-323.

 

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23
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30

The theme of variability among departments and their students was
further documented by Gaff and Wilson whose research suggested that
areas of specialization--humanities, social sciences, natural sciences
and professional studies--represented four different faculty cultures
with different attitudes toward certain relevant educational topics.22
The concepts of local and cosmopolitan academic faculty were
described by Gouldner on the basis of his work at a small midwestern
college. While locals were characterized by their involvement on their
own campus and their general concern for the institution, cosmopolitans
were more discipline-oriented and had few ties to the institution at
which they were employed.23 Utilizing these concepts developed by
Gouldner, Hamblin and Smith surveyed graduate students about the
behavior and attitude patterns of professors in their department. On
the basis of their results, these researchers suggested that the primary
distinctions between those faculty members with local status and those
with professional status were their research publications and the fact
that these faculty members remained aloof (socially distant).2“

Finally, the research on departments as organizational units

which has been reported in the first two phases of the Exxon Departmental

 

22J. C. Gaff and R. C. Wilson, "Faculty Cultures and Interdisci-
plinary Studies," Journal of Higher Education, 43 (March, 1971), pp.
186-201.

23A. W. Gouldner, "Cosmopolitans and Locals: Toward an Analysis
of Latent Social Roles," Administrative Science Quarterly, 2 (June, 1958),
pp. 444-480.

2"R. L. Hamblin and C. R. Smith, "Values, Status, and PrOfessors,"
Sociometry, 29 (September, 1966), pp. 183-196.

 

 

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31

Study Project merits attention. The Confidence Crisis represented a
study of selected university departments in fourteen universities.
Featherstone called this book a "basic text" and an excellent review
of the literature on departments as well as a report of research find-

ings.25

The basic question in this research was what roles do the
operation and function of departments in large universities play in
the achievement of the institution's goals? The results reported in
The Confidence Crisis indicated that departments with high national
standing, based on productivity research and doctoral degrees, were
characterized by more informal administrative organization and prac-
tices than departments of less stature. In addition, departments of
high national standing were found to be less involved in local institu—
tional matters and tended to shun institutional priorities. Further,
three of the tentative conclusions reached in this study were thus:
Autonomy is essential to effective departmental operation, but
autonomy is meaningless without adequate resources, which, in
turn, are dependent upon the existence of both departmental self—
confidence and confidence reciprocated among the department, the
dean, and the university.... The confidence game is a central

element in university relations.... The outcomes of the confi-

dence game are not always in best interest of higher education.26

The authors concluded by stating that the "university and the depart-

1.n27

ments within them are out of contro Reorganization of departments

 

25R. L. Featherstone, The Development of Management Systems for
the Academic Department (Boulder, Colo.: Western Interstate Commission
for Higher Education, 1972), p. 15.

 

26F. L. Dressel, F. C. Johnson, and P. M. Marcus, The Confidence
Crisis (San Francisco: Jossey-Bass, Inc., Publishers, 1970), p. 145.

27Ibid., p. 232.

 

:; the develc;
gazetted to t
'.‘;1': the prior:

:gerazzon mm

desigzed to b:
"Liversity. 1
izs cits is ;
.L‘é basis Cf .
25:19:: 5081'
tile MSI FE

"'rv-«uents f

r)
n
H-
D
(‘V
m

32

and the development of appropriate management informational systems
are needed to ensure that "resources are allocated and used in accord
with the priorities set for the university by the university in co-
operation with those who support it."28

In Return to Reaponsibility, a sequel to The Confidence Crisis,
Dressel and Faricy focus "on developments, self-generated or imposed,
designed to bring increased control over the uses of resources in the
university. The appropriate degree of autonomy of the university and
its units is a central issue ... through all the discussion."29 On
the basis of the responses to questionnaires sent to faculty, adminis-
tration, board members and legislators, the authors suggested that
while most people accept the need for departmental review, most
respondents felt that this review should be conducted by faculty or
administrators.

Efficiency, uniformity, a better "product"--these appear to be

major concerns in universities. But human concerns--personal

and intellectual welfare--are not neglected, especially on

particular issues.30
On new patterns of organization, the authors stated that

Departmental autonomy is generally decreased by innovative struc-

tures, but problems of autonomy--excessive or deficient-~are

merely shifted to other points in the structure. Furthermore, no
structure observed has been able to curb or satisfy the faculty's

 

28Ihid., p. 232.

29P. L. Dressel and W. H. Faricy, Return to Responsibility
(San Francisco: Jossey-Bass, Inc., Publishers, 1972) p. xii.

3°Ihid., p. 47.

 

it authors a
sat and ma:

1
recurce ail:

. I
...g.‘..

RCICGO

Indeed,
an the

ver ity
the pri
societ}
Sky is

'n.“
.‘mfi.?, on

33

desire for a disciplinary—based structure corresponding to their
graduate school preparation and their research interest.31

The authors also stressed the need for planning and coordination at the
state and national level so that some measure of congruence between
resource allocation, social needs and institutional roles can be

achieved.

Indeed, most faculty members and departments seem to have operated
on the principle that what is good for them is good for the uni—
versity; and in turn, the university seems to have operated on

the principle that what is good for the university is good for
society. But, in fact, what they perceive as good for the univer—
sity is not necessarily needed by, wanted by, or good for society.32

Finally, on the subject of constraints, the authors listed four types
of constraints that are reasonable and justifiable:

Generally, constraints are justifiable when they

(a) tend to make the students' educational experience more inter—
esting, challenging, and relevant to social needs;

(b) provide policies that are both necessary and fair as judged
by students and the general public;

(c) encourage or ensure more efficient use of resources;

(d) permit effectiveness and success to be judged by results and
costs, rather than by faculty or student preferences for
particular educational processes.

Summary

Fundamental organizational questions about the department and its
operations still remain even though the department structure has been in

existence for over 100 years. Much has been written about the department

 

311bid., p. 87.
321hid., p. 184.

331hid., p. 188.

 

 

[‘1

v. ' 1
3“ éabcts 0‘
. .: 3

33.31 systa
;::ev0 “ -r:
...-“.5 .6ch
2:5: : part:
’.'... .;
:uneatEu a:

'g-ng-n at... 1
but“ ' '
. on. .. d‘

34

and its members, but few facts have emerged. Systematic research on
all facets of departmental operations including the formal and informal
social systems is needed. In addition, the results of these research
efforts need to be coalesced into a theory of academic departments so
that departments on the same or different campuses can be adequately
evaluated and compared. Each effort to describe, measure, or report
departmental operations, like this study of the instructional service
aspect of academic departments, makes such a theory of departments

more possible.

 

E vucr"’.-Vm' ‘ V,"

the aforesa:
p:ia.e measures
i—zpattnents; 2)
easures and amc
tits, and 3) Cl;
:3 determine 1:
35 iZSEructiona

4" is fully c‘

«Partner.

Chapter IV

RESEARCH DESIGN

The aforesaid purposes of this study were to 1) develop appro-
priate measures of the instructional service component of academic
departments; 2) identify relationships among the instructional service
measures and among these measures and other departmental characteris-
tics, and 3) classify departments on the basis of instructional service
and determine which variables serve to discriminate among categories
of instructional service. The research design developed to meet these

aims is fully described in this chapter.

Instructional Service Measures

Departmental instructional service measures could have been based
on either the number of students majoring in other departments who were
enrolled in courses in a department or the number of student credit
hours (SCH) generated by these students. Since the number of student
credit hours generated by a department is a function of the enrollment
of that department, the use of both measures would have been redundant.
Thus, one set of measures was a sufficient representation of instruc-
tional service. Student-based measures were used as instructional
service indicators in this study because service—oriented, sub-program
courses existed which had enrollments but generated no student credit

hours.

35

0L8 Cd‘v'e

Tue enrollte:

cf stuients e

ia:a do not 1

36

One caveat should be given about the nature of enrollment data.
The enrollment data for each department are an aggregate of the number
of students enrolled in each course offered by the department. These
data do not represent the number of unique students enrolled in the
department. For example, if a student were enrolled in two courses in
a department during a term, this person would be reflected as two
students in the enrollment data for the department for that term.
However, this attribute of enrollment data did not adversely affect the
data structure of this study since the instructional service concept
was based on instructional activity or effort on the part of academic
departments. Though only one student was involved, this student
participated in two instructional activities provided by the department,
and both of these activities were reflected in the enrollment data for
the department.

In this study, the instructional service component of academic
departments was represented by two sets of measures——department-based
instructional service measures (DBIS) and university-based instructional
service measures (UBIS). The department—based instructional service
measures (DBIS) described the relative amount of instructional service
(instruction to nonemajors) in each academic department. These depart-
ment-based measures were defined as the percentage of the total number
of students enrolled in a department during Fall term 1971 who were
service students (nondmajors). Thus, DBIS - number of service students
in a department/total number of students in the department. This equa—

tion was applicable for all course levels. On the other hand,

37

university-based instructional service measures (UBIS) represented the
relative amount of the total instructional service load of the uni-
versity (an aggregate over all departments) which was assumed by each
academic department. Thus, UBIS - number of service students in a
department/total number of service students over all departments. This
equation was also applicable for all course levels. Since the level

of a course affects its cost, with more advanced level courses tending
to cost more,1 both department-based and university-based instructional
service measures were computed for each course level. Undergraduate
courses were initially subdivided into subprogram, lower level, and
upper level, while graduate courses were subdivided into graduate-
professional, masters level, and doctoral level. The six summary
measures constructed for each department for-both categories of instruc-
tional service measures are displayed in Table 1.

The three unadjusted measures (undergraduate, graduate, and total)
were based on all course levels applicable to each category. The
adjusted measures, as constructed, did not include subprogram and short
courses (undergraduate and total measures) and graduate-professional
courses (graduate and total measures). Subprogram courses are those
courses which are remedial in nature and whose credits do not count
toward a degree. Short courses are those courses that are associated
with the Agricultural Technology programs (usually granting two—year

certificates) and are taught by various departments in the institution.

 

1R. L. Williams, "The Cost of Educating One College Student,"
Educational Record, 42 (October, 1961), p. 233.

~m>m~ beau:

mumawwnmnmhca mnumzfitwcb .H

 

I‘ ...I I‘ll i“

 

 

oo¢IOCn

aoNIOOH ~o>o~ hm3c~

omolcoc nonusoo uhozm e Euhaoumczm
$152222 ”.2353; . n:._.~mfl_.:.z~ mafia: :3 dogma:

.....sz...::~.~.r. a: 1:252 23 awaréz .......~..:QZM|

 

 

 

 

In no:- n-‘uV-d: \fiirh on-nlunflum-t

t W adssz.\.

38

 

deduced

Hm>mH Honouoov

 

 

 

 

 

¢awloow Hm>oH m.uuumma
aaeuoom Hd>eH edema Hence peupefip< .e
mmNIOOH Hm>oH Hosea
mmmloom Hm>MH kuouoom
momloow Ho>oH m.uoumma muwsvmuw woumsfim< .n
mmqloom Ho>ma Home:
mmNIOOH Ho>oH Hosea mumsvmuwumvs: voumafivd .c
mmmloom Ho>oH Hmuouoov
mmmloom Hm>ma m.uoumma
mmoloom Honowmmomoumlouwsvmuw
mmcloom Hm>oH Home: HmuOu vmumsnmmaa .m
mmmlooa Hm>ma umsoa
mmOIooo mmmusou uuosm w amuwouansm
mmmloom Ho>mH Honouoov
mamloom Ho>oH m.umumma mumswmuw wounsmwmab .m
maoloom HmGOfimmomoumloumnmmuw
mmqloom Hm>mH Home:
mmNIooH Hm>mH umBoa mumscmeuomc: woumaficwas .H
maelooo mumusoo uuonn w sapwouansm

 

 

E ass

 

.JhIIIlIIlIIlIlIIIlIltlIIIIIlIIIIIlIIIllllllllllllllllllltlll
amooaozH

ease e 5% 11% ea “E

”amazon mo gm>mg

mwuammmz.%umaa=m .H manna

Eizall)‘: graduate'
nth the three Pr‘
egaEIedicine. 0
aijus-ted indicato
is :rre aPPlicabl
:rgdnized profess
xlcgy program.
One other p
service in aeade
szuients (non-ta
:curse level (ur
iii unadjusted c
25:15 serving p:

.‘.-.. .
“3:1

DCtiCn by 1

'l
...-
by:

. I
5 Increase

L: A .' -
audlthn,

on
“an undergradu
.31.:

“is: 3'1
.en d
ep-
E-Sures Her
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Irv:
“«
Urinatl
v.

39

Finally, graduate-professional courses are those courses associated
with the three professional programs at Michigan State University——
Human Medicine, Osteopathic Medicine, and Veterinary Medicine. The
adjusted indicators reflect a concept of instructional service which
is more applicable to other institutions that do not have similarly
organized professional programs or an equivalent Agricultural Tech-
nology program.

One other piece of information was collected about instructional
service in academic departments. A percentage distribution of service
students (nondmajors) by class level was generated for each aggregate
course level (undergraduate, graduate, and total) from both adjusted
and unadjusted data. These data were further aggregated, and depart-
ments serving primarily lower level students were identified. This
distinction by student level was prompted by research which found that
"costs increase with the advance in class level of the student."2
In addition, one of the questions of interest in this study was whether
high undergraduate instructional service-oriented departments taught
primarily lower division or upper division undergraduate students.
Thus, when department-based and university-based instructional service

measures were coupled with data about the level of student served, a

picture of the department's instructional service role began to emerge.

Data
Information gathered on eighty-two (82) academic departments at

Michigan State University formed the data base used in this study.

 

2Ibid., p. 232.

 

steriev of '
:i'er no depa
5:233. Tnis
for the C0111
flag-artzent.

:e:':s within
15:; presen

.j/ ».
fisher -Iln'

Wing of ti
‘~‘=C in this
“$131118 Sour.

The ser

40

A review of the list of these departments found in Appendix A reveals
that no department in the College of Education was included in this
study. This was a practical and not a conceptual omission. The data
for the College of Education are not reported nor aggregated by
department. Thus, no departmental data summaries exist for the depart—
ments within the College of Education. In addition, one other subh
tlety present in the data should be noted. Data for multi—administered
and/or -financed departments were aggregated and reported as represent-
ing a single department. For example, the Colleges of Human Medicine,
OsteOpathic Medicine, and Veterinary Medicine each contributed to the
funding of the Department of Anatomy. However, the data for Anatomy
used in this study reflected the total dollars for Anatomy from all
funding sources.

The service measures described above were computed for each depart—
ment in the study from enrollment data in the Analysis of Student
Enrollment in Courses by Student's Curriculum and Class (R7705) and
from tenth day class lists for Fall 1971, both of which were prepared
by the Registrar's Office. Class lists were used because they are the
only available source of enrollments by major for departments with non-
unique curriculum codes. For example, all departments in the College
of Agriculture and Natural Resources have the same curriculum code and
are aggregated in the R7705 report; hence. separation of majors in each
department in this college from other Agriculture students would have
been impossible using this report. Since the service loads of depart—
ments, not the instructional service load of colleges, were of interest

in this study, the major codes appearing on class lists for departments

Like those it
:2-urique c1
3: eajors a
Sunerou
various phas
L‘. '
..es are 115
pa: represe

routine iv e:

9‘

41

like those in the College of Agriculture and Natural Resources with
non—unique curriculum codes were used to discriminate between depart—
ment majors and service students.

Numerous departmental descriptor variables were also used in
various phases of the analyses conducted in this study. These varia—
bles are listed in Appendix B. These data for the l97l«72 academic
year represent objective data (empirical and externally observable)
routinely compiled by various offices athichigan State University.3
In addition, data representing the prestige of graduate education in
departments at.Michigan State was gleaned from reports published by

the American Council on Education.“

Thus, the twelve department—based
and university—based instructional service measures and these eighty-six

descriptor variables comprised the data base for this study.

Research_9uestions

This research was exploratory in nature and was designed to
identify relationships among the instructional service measures and
among these measures and other available data on academic departments.
The areas of inquiry central to this study and their attendant statis-

tical analysis are delineated in the following passages.

 

3These offices include the Registrar's Office, the Office of
Institutional Research, the Provost's Office, and the Office of the
Vice-President for Business and Finance.

‘'The American Council on Education published reports on graduate
education prestige compiled by Cartter in 1966 and by Roose and
Andersen in 1970.

 

L. Relationships be

iLStructional 5:

Do departm
undergraduate p
oriented gradug
this question i
service and de
Email? indep
used to assess

‘
5518.

. fliationships

E

The dep

«weal Servi
we prQCESs 4

‘.'7?’

«Htse level

9:“d8nt')

‘ adj- Us t
fiam COurs
‘.‘Erslty‘baq
“elatiODShj
lead

l.

42

Relationships between undergraduate and graduate department-based
instructional service measures.

Do departments with highly instructional service-oriented
undergraduate programs tend to have highly instructional service-
oriented graduate programs? The null hypothesis associated with
this question was that department-based undergraduate instructional
service and department-based graduate instructional service are
mutually independent. Spearman rank correlation coefficients were
used to assess this relationship for both unadjusted and adjusted

data.

Relationships between department-based instructional service
measures and university—based instructional service measures.

The department-based instructional service measures for each
department were defined in terms of the service students processed
by the department. On the other hand, the university-based instruc-
tional service measures reflected the department's contribution to
the processing of students at theinstitutional level. For each
course level (undergraduate, graduate and total), are the department-
based and university-based instructional service measures inde-
pendent? Spearman rank correlation coefficients for both unadjusted
and adjusted data were used to test the null hypothesis that for
each course level department-based instructional service and uni-

versity-based instructional service are mutually independent.

Relationships between adjusted instructional service measures and

unadjusted instructional service measures.

As
aéjusted
subprogra
the inst:
data on c

eighty- tr

2 ...-
* v s:
‘0
'.‘
":

43

As noted previously, the difference between unadjusted and
adjusted instructional service measures reflected the effect of
subprogram and short courses and graduate—professional courses on
the instructional service level of a department. A review of the
data on course offerings revealed that thirty—three (33) of the
eighty—two (82) departments had courses falling into at least one
of the above categories (see Appendix C, Table 23). The extent of
the relationships between unadjusted and adjusted measures for both
department—based and university—based instructional service was
determined using Spearman rank correlation coefficients. The null
hypotheses were that the unadjusted and adjusted department—based
instructional service measures for each course level are mutually
independent and that the unadjusted and adjusted university-based
instructional service measures for each course level are mutually

independent.

Relationships between the level of students served in undergraduate
courses and the undergraduate instructional service measures.

Do high undergraduate instructional service—oriented depart—
ments serve primarily lower division or upper division students?
Similarly, do departments which assume a large part of the institu—
tional service load serve predominately lower division or upper
division undergraduate students? A chi—square test for independence
was used to test the hypothesis that the level of department—based
undergraduate instructional service and the level of students served

in undergraduate courses are statistically independent and the

 

.-

bit-othesis
tional sen
keepeflden'
$553le ti
variables'
$333035}:
instruct“
:EPErment

30 de

44

hypothesis that the level of university-based undergraduate instruc-
tional service and the level of students served are statistically
independent. The correlation coefficient phi (O) was used to
describe the strength of the relationships between these qualitative

variables.

Relationships between the department-based and university-based
instructional service measures and the faculty rank distribution of
departments.

Do departments with similar department-based or university-based
instructional service measures have similar faculty rank distributions?
Are the department-based or the university-based instructional service
measures reflective of the faculty rank distributions within depart-
ments? These relationships were of interest since, theoretically,
the type of instructional load in academic departments should affect
staffing. Three faculty rank indices--one based on faculty headcount,
one based on full-time equivalent faculty (FTE), and one based on
the percentage distribution of faculty and ranks-dwere constructed by
weighting each rank. Spearman rank correlation coefficients were
used to assess the relationships between these faculty rank distribu-
tion indices and undergraduate and graduate, adjusted and unadjusted
department-based and university-based instructional service measures.
The general form of the null hypothesis was that the faculty rank
distribution index and the instructional service measure are mutually

independent.

 

' 4035;".
:l :‘Lt‘

”3:181 ser

instructic

assistants

Spearman r
:i-zzships

deg-at :ten:
These rel:

3385821:

be
533:1 and
thESe this
Qi‘versit
average 5
:‘epartthan
tam; of t

‘mrUCti

45

6. Relationships between department-based and university—based instruc—
tional service measures and the number of graduate assistants
employed in academic departments.

Do departments with similar department—based or university—based
instructional service measures employ a similar number of graduate
assistants? Two measures of the number of graduate assistants in a
department——headcount and FTE's-dwere developed for each department.
Spearman rank correlation coefficients were used to assess the rela—
tionships between these measures and the undergraduate and graduate,
department—based and university—based instructional service measures.
These relationships were calculated for both adjusted and unadjusted
instructional service measures. The general form of the null hypothe—
sis was that the measure of the number of graduate assistants and

the instructional service measure are mutually independent.

7. Relationships between department-based and university—based instruc-
tional service measures and the funding level and average salary in
academic departments.

The two major sources of departmental funding are the general
fund and research grants and contracts. Is the level of funding from
these two sources independent of the level of department-based and
university—based instructional service in the department? Is the
average salary of faculty in a department related to the level of
department-based or university-based instructional service? The ex—
tent of these relationships among funding, average salary, and

instructional service measures was assessed using Spearman rank

46

correlation coefficients. The null hypothesis tested stated the

mutual independence of each pair of variables.

Relationships between the prestige of graduate education in depart-
ments and the department-based or universityebased graduate instruc-
tional service measures.

Do departments with prestigious graduate programs have relative-
ly high or low department-based and university-based instructional
service measures? A chi-square test for independence was used to
test the hypothesis that the level of department—based graduate
instructional service and level of prestige of the department's
graduate program are statistically independent and the hypothesis
that the level of university-based graduate instructional service
and the level of prestige are statistically independent. The corre-
lation coefficient phi (¢) was used to describe the strength of the

relationships between these qualitative variables.

Classification of departments on the basis of instructional service.
Using the rankings of departments on undergraduate and graduate
instructional service data, four two-dimensional arrays of the
following form were constructed.
Graduate

Low Medium_ High

 

Low
Underggaduate Medium
High

These four arrays represented the rankings on unadjusted department-

based, adjusted department-based, unadjusted university-based, and

gar; U35

tely

ta

instruct

‘
32 SC]

9.‘
L.

.3
...:

v

. ..
‘ 9
“

e d

.-
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a
N

.
“a
{ti-1‘

.

O,

C

lo.

47

adjusted university-based instructional service measures. Each cate-
gory was constructed on the basis of rankings and represented approx-
imately one-third of the departments. This stratification was based
on ranking to ensure approximately equal cell sizes for the multiple
discriminant analysis discussed in the next passage. In addition,
since departments tended to cluster around the extremes of the
instructional service measures, especially the department-based

measures, the ranks provided the best representation of the data.

Identification of descriptor variables reflective of the classifica-
tion schema.

For each dimension, undergraduate and graduate, of the four
instructional service arrays, what descriptor variables discriminate
among the categories of undergraduate and graduate instructional
service? That is, what linear combination of variables will maximize
the differences among groups? Multiple discriminant analysis was the
technique used to study the relationships among the categories of
undergraduate and graduate instructional service in terms of the
many descriptor variables available for each department. The selec-
tion of the input variables for the multiple discriminant analyses
was facilitated by the use of principal axes factor analysis. In
principal axes factor analysis, redundancies in the data are elimi-
nated by the generation of n statistically independent linear combi-
nations called factors. These factors were, in turn, used as the

input variables for the discriminant analysis.

 

A review of tht
statistical techniq
trues—rank correl
aes factor analysi

i: the following pa

Spearman Ran'

basic questions: 1
tat is the extent
it was used as a

‘.‘.szructional sen

"‘21P“! Variabl

a.
VI.

4':

u

‘.'E * a .
°~ pOSltlve

a“,
“-G.’

IECEPQndEnC

33's:-

Si‘fv' I
:3: '.‘F‘ a

“syn COmpu
2:5,

.ed in thl
"is t?

48

Methodology

_"

A review of the preceding sectién reveals that four types of
statistical techniques were used in this study. Each of these tech-
niques--rank correlation, chi-square test for independence, principal
axes factor analysis, and multiple discriminant analysis--are described
in the following paragraphs.

Spearman Rank Correlations--Correlation analysis deals with two
basic questions: does a relationship exist between two variables and
what is the extent of this relationship? In this study, Spearman's
rho was used as a measure of the relationships among the ranks of the
instructional service measures and the ranks of the other departmental
descriptor variables. As with other measures of relationships, the
values of rho vary from -1, a perfect negative correlation, to +1, a
perfect positive correlation, with a value of zero indicating statis-
tical,independence. Since departments tended to cluster around the
extremes of the instructional service measures, correlation coefficients
based on ranks rather than raw data were most appropriate in this
study. In order to correct for the many ties which were present in the
instructional service data, correlation coefficients were calculated
using the ranks on these service data as the input into a computer pro-

5 The correlation coefficients

gram which computed Pearson's r.
generated in this manner were then interpreted as Spearman's rho's.

This type of manipulation was possible since "Pearson's r reduces to

 

5W. J. Conover, Practical Nonparametric Statistics (New York:
John Wiley & Sons Inc., 1971), p. 246.

 

Sgertan's r'no
:pstheses of m
ratatistic, t
Chi-spare
Esience tests
:x : continge
Stiiirfour ba
.. ”four based

353:}. tables \

49

Spearman's rho if the data are replaced by their ranks."6 The null
hypotheses of mutual independence (E (rs) - 0) were tested using a
t-statistic, t - rs VN:2— / /l:;2;, with N-2 degrees of freedom.7
Chi-square Test for Independence--The chi-square test for inde-
pendence tests statistical independence within the framework of an
r x c contingency table. Eight chi-square tests were conducted on this
study--four based on level of student served in undergraduate courses
and four based on the prestige of graduate programs. The 2 x 3 contin-

gency tables which provided the basis for the analyses are diagramed as

Underggaduate Instructional Service

 

Low Medium High
Predominately Lower
Student Division
L222; Predominately Upper
Division
Graduate Instruction Service
LOW’ Medium High
Ranked
Prestige
Unranked

In order to test the hypothesis of the general form, the level of quali-

tative variable A is independent of the level of qualitative variable B,

 

61hid., p. 247.

7L. A” Marascuilo, Statistical Methods for Behavioral Science
Research (New York: McGraw—Hill Book Company, 1971), p. 457.

‘)
the
R is

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3318:

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50

r c (0. - E )2

the statistic T = Z Z le ii

11

region for the null hypothesis correspond to values of T greater than

was computed.8 The rejection

5.991, the .95 percentile of the chi—square random variable with

9

(r-l)(c-l) = 2 degrees of freedom. The strength of the association

between the dimension of the contingency table was computed using
the phi coefficient. The range of g is from 0 to l, where zero is
uncorrelated while one represents a perfect relationship. The rela—
tionship between the phi coefficient and Karl Pearson's chi—square is
expressed for a r x c contingency tables by the formula: 3 = MET7NM
where N is the sample size and M is the minimum of (r—l) and (c—l).1°
Principal Axes Factor Analysis-—Factor analysis was described by
Overall and Klett as
a powerful method of statistical analysis that has as its aim
the explanation of relationships among numerous correlated vari-
ables in terms of a relatively few underlying factor variables.11
In this study one of the main analysis problems was the selection of
variables for use in the multiple discriminant analyses. Since the
number of departmental descriptor variables exceeds the number of de-
partments in each instructional service category, criteria for variable

selection were needed. Yet, no §_priori variable selection strategy

which accounted for possible correlations within the descriptor

 

8W. J. Conover, Practical Nonparametric Statistics (New York:
John Wiley & Sons Inc., 1971), p. 155.

9Ibid., p. 156.

10L. At Marasciulo, Statistical Methods for Behavioral Science
Research (New York: McGraw—Hill Book Company, 1971), p. 406.

ilJ. E. Overall and C. J. Klett, Applied Multivariate Analysis
(New York: McGraw—Hill Book Company, 1972), p. 89.

.-~'

263';

.l

. ' ' -.
snake”
V

In
any

a
no.

 

‘4.

an
vi

51

variables and which weighted the variables accordingly existed.
Principal axes factor analysis with a varimax rotation provided a tool
for reducing the data into smaller set of orthogonal (statistically
independent) factors which account for a maximum amount of the total
variability among departments on all the descriptor variables.
Principal axes factor analysis is one of the multifactor tech—
niques described by Rummel and characterized by the following attributes:
l. The approach is one of reducing the data to the minimum number

of common factors or factor—dimensions necessary to reproduce
the original data.

2. The complexity of the variables may be one (as in the multiple-
group technique), two, or greater.
3. The complexity of the factors may consist of general, group,
or specific factors.
4. Communalities must be estimated if the common factor model is
involved.12
The general steps of most factor analytic techniques as delineated by
Comrey are "(a) selecting the variables; (b) computing the matrix of
correlations among the variables; (c) extracting the unrotated factors;
(d) rotating the factors; and (e) interpreting the rotated factors."13
In this study thirty-five (35) departmental descriptor variables
were used in the factor analysis conducted in this study. The remain-
ing descriptor variables listed in Appendix B were used in other analy-

ses conducted in this study. Steps b, c, and d were accomplished

through the use of two computer programs, PACKAGE and FACTRB, which were

 

12R. J. Rummel, Applied Factor Analysis (Evanston, 111.: North-
western University Press, 1970), p. 333.

13A. L. Comrey, A First Course in Factor Analysis (New York:
Academic Press, 1973), p. 4.

 

:21 065E

I",
,‘ ;.

52

available at the Michigan State University Computer Center. First, a
product-moment correlation matrix was computed with estimates of the
communalities substituted in the diagonal of this matrix. This neces-
sary substitution causes an inherent weakness in the common factor
analytic model--a basic indeterminacy or circularity in calculation.
Rummel describes the problem thus:

The communalitieslu, hz, cannot be known until the common factors

are defined. The delineation of these factors, however, depends

on the correlation matrix.... The traditional procedure for

dealing with this indeterminacy—-this communality problemr-is to

insert in the principal diagonal of the correlation matrix some

estimates of the communality values.15
Two types of estimates of the communalities are commonly used; the upper
bound which is unity or the lower bound which is the squared multiple
correlation (SMC) of a variable with all the other variables in the data
set. In the absence of other relevant studies that could serve as a
guide for the choice of communality estimates for this study, the squared
multiple correlations were used since Rummel described them as "the best
estimate on theoretical and empirical grounds."16

As previously noted, the unrotated factors were extracted using

principal axes factor analysis. The principal axes technique was

 

1"Communalities are defined as the "sum of the squares of the factor
loadings over all the factors," and they give the proportion of the
variance of the variables that can be accounted for by scores in the
factor." (Comrey, 1973, p. 12)

15R. J. Rummel, Applied Factor Analysis (Evanston, 111.: North-
western University Press, 1970), p. 312.

16Ihid., p. 320.

:s: of the
b33:::el e
rs: ince I
Izzgutatio:
ent: opera

.

23221265 I.

extant t0
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aha-1;»;
«C

53

described by Cattell as the preferred technique "notably_for its

mathematical properties and for practical reasons such as yielding a

"17

test of the number of factors.... The principal axes were defined

by Rummel as the "minimum orthogonal dimensions required to linearly
reproduce (define, generate, explain) the original data."18
Computationally, principal axes factor analysis is an iterative method
which operates on the correlation matrix and successive residual
matrices to generate principal axes factor loadings based on principal
components. These coefficients (factor loadings) represent the
"extent to which variables are related to the hypothetical factor."19
FACTRB extracts successive principal components and factors until the
eigenvalue of a factor is less than or equal to one or until a default
limit of twenty factors is reached. However, this program constraint
did not affect the analysis in this study. Some of the characteristics
of the factors which are derived using principal axes factor analysis
include
1. Both factor loadings and factor scores are orthogonal.
2. The variance contributions of the factors are decreasing.
The first factor measures the most variance and successive
factors will account for decreasing proportions of variance.
3. Sensitivity to random error or communality estimates appears

low relative to other techniques.
4. The geometrical fit of all factors is ellipsoidal.20

 

17R. B. Cattell, Handbook of Multivarate Experimental Psyghology.
(Chicago: Rand McNally & Company, 1966), p. 176.

18R. J. Rummel, Applied Factor Analysis (Evanston, Ill.: North-
western University Press, 1970), p. 338.

 

19A. L. Comrey, A First Course in Factor Analysis (New York:
Academic Press, 1973), p. 7.

20R. J. Rummel, Applied Factor Analysis (Evanston, Ill.: North-
western University Press, l970), pp. 344-45.

 

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“'6" York. 0“”

54

As previously mentioned, factor analytic methods are characterized
by a basic indeterminacy. That is, some data when factor analyzed by
different methods produces different factor loading matrices. In addi-
tion, "although principal axes factors are statistically orthogonal and
account for maximum possible variance, they tend to be complex and dif-

"21 Rotational transformations of the factors

ficult to interpret.
around the origin of an n—dimensional space have been used by factor
analysts "to obtain meaningful factors that are consistent (invariant)

as possible from analysis to analysis."22

In the factor loading matrix
that results from a principal axes factor analysis, the first factor
accounts for the largest amount of variance and subsequent factors
account for decreasing amounts of variance. In the matrix of rotated
factors, the variance is distributed more evenly across all the factors;
thus, the first rotated factors which are extracted do not have loadings
on almost all of the variables. In addition, in the rotated factor
matrix the variables are usually highly loaded on a few factors instead
of these variables being highly loaded on many factors as occurs in the
unrotated matrix. Thus, the rotation process can produce a matrix
improved in both parsimony and clarity.

Kaiser's varimax rotation procedure was used in this study to

generate the rotated factor matrix. The varimax method is an orthogonal

rotation technique which maximizes the variance of the squared factor

 

21J. E. Overall and C. J. Klett, Applied Multivariate Analysis
(New York: McGraw—Hill Book Company, 1972), p. 114.

223. Fruchter, Introduction to Factor Analyses (New York:
Van Nostrand, 1954), p. 106.

31:35 by column.
zero the same clust
1:: of other varie
rehlique rotatior
:i;aliy independen
:::ation are simpl
tel clarity, and
2' Saar?» a prir
‘es used to gener.
factors 'w‘xich are
:58 linear c0111:

Elites were used

.
\
n

3".

 

55

loadings by column. "A strong feature of varimax is its ability to dis-
cern the same cluster of variables regardless of the number or combina-

tion of other variables in the process."23

An orthogonal rather than
an oblique rotation method was chosen because the factors remain statis-
tically independent. In addition, "the chief grounds for orthogonal
rotation are simplicity, a mathematical elegance of the result, concep-
tual clarity, and amenability to subsequent manipulation and analysis."2“
In summary, a principal axes factor analysis with a varimax rotation
was used to generate n weighted linear combinations of variables called
factors which are statistically independent. Factor scores based on
these linear combinations were computed for each department, and these
scores were used as variables in the multiple discriminant analyses.
Multiple Discriminant Analysis--Multiple discriminant analysis is
a generalized form of regression in which the dependent variable repre-

sents group membership.25

In the case of two groups the dependent
variable assumes the values of 0 and 1. Since the number of discrimi-
nent functions (linear combinations of variables which serve to maximally
discriminate among groups) is equal to one less than the number of

groups,26 only one discriminant function, similar in form to a

 

23R: J. Rummel, Applied Factor Analysis (Evanston, Ill.: North-
western University Press, 1970), p. 392.

?“lhid., p. 388.
25F. N. Kerlinger and E. J. Pedhazur, Multiple Regression in
Behavioral Research (New York: Holt, Rinehart and Winston, Inc.,

1973), p. 337.

26J. E. Overall and c. J. Klett, Applied Multivariate Analysis
(New'York: McGraw—Hill Book Company, 1972), p. 281.

regression

sizes use:

the dizzere

 

56

regression equation, emerges. With the three group classification
schema used in this study, two discriminant functions which "maximize
the difference between groups relative to the differences within the
groups"27 were generated. These discriminant functions were linear
combinations of the composite variables and not the original descriptor
variables--a fact which complicated the interpretation of the discrimi-
nant functions. As was the case in principal axes factor analysis,
the two discriminant functions are orthogonal (statistically independ-
ent) to each other.
The first discriminant function is that single weighted combina-
tion of measurements which has maximum variance between groups
relative to the variance within groups.28
The second discriminant function is that weighted combination
of the p variables which of all possible weighted combinations
independent of the first discriminant function accounts for a
maximum of the remaining group differences.29
The computer program DISCRIM2 available at the Michigan State University
Computer Center was used to generate the two discriminant functions.
Since only three groups were used, the constraints of the program did
not affect the analysis. Eight separate discriminant analyses of the

instructional service measures were conducted in this study: department-

based unadjusted undergraduate, department-based unadjusted graduate,

 

27F. N. Kerlinger and E. J. Pedhazur, Multiple Regression in
Behavioral Research (New York: Holt, Rinehart and Winston, Inc.,
1973), p. 340.

 

28J. E. Overall and C. J. Klett, Applied Multivariate Analysis
(New York: McGraw—Hill Book Company, 1972), p. 281.

29Ibid., p. 282.

 

irartnent-ba
traiua’te, uni
adjusted gr

:ivers;ty-oa

In this
73E instruct:
italating 1

-::ire data 1

57

department-based adjusted undergraduate, department-based adjusted
graduate, university-based unadjusted undergraduate, university-based
unadjusted graduate, university-based adjusted undergraduate, and

university-based adjusted graduate.

Summagy

In this chapter the research design of the study was presented.
The instructional service measures were defined, and the procedure for
calculating these measures identified. Also, the parameters of the
entire data base for the study were described. While the purposes of
the study have been mentioned in previous chapters, the focus in this
chapter was on the specific areas of inquiry and their attendant
statistical techniques. The discussion of these techniques--rank
correlation, chi—square test for independence, principal axes factor

analysis, and multiple discriminant analysis--completed the chapter.

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Chapter V

THE RESULTS

This study was exploratory in nature and was designed to identify
relationships among the aspects of instructional service and other
available data on academic departments. The purposes of this study
were to 1) develop appropriate measures of the instructional service
component of academic departments; 2) identify relationships among the
instructional service measures and other departmental characteristics;
and 3) classify departments on the basis of instructional service and
determine which variables serve to discriminate among categories of
instructional service. In the preceding chapter the ten areas of
inquiry related to these research objectives were identified, and their
attendant statistical strategies and techniques were described. The

results of these statistical procedures are discussed in this chapter.

Instructional Service Measures

 

As noted above, one of the tasks in this study was the development
of appropriate measures of the instructional service component of aca-
demic departments. Two constructs were developed which reflected
aspects of instructional service. Department-based instructional service
measures represented the relative amount of the total enrollment in each

department who were service students (non-majors). Therefore, these

58

LJ

 

assures reflected
finishing of eac':
:structional servi

:::al institutional

 

 

 

'.as responsible.
iegartnent's contr
istitution.

For each cat!
Lied and univers

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fl)

displayed in

C3:
.Qted f
%
“killed -
c
“
lush
f
‘.i‘. a

59

measures reflected the role of instructional service in the internal
functioning of each department. On the other hand, universityebased
instructional service measures represented the relative amount of the
total institutional instructional service load for which each department
was responsible. Thus, these university-based measures reflected the
department's contribution to the total service instruction within the
institution.

For each category of instructional service measures--department-
based and university-based--six summary measures were calculated based
on the number of instructional service students for Fall 1971, which
are displayed in Table 2 and the total enrollments in each department
for Fall 1971 which are displayed in Table 3. These six summary
measures were described in Table l in the preceding chapter. The three
unadjusted measures (undergraduate, graduate and total) were based on
service and total enrollments in all courses applicable to each cate-
gory. The adjusted measures, as constructed, did not include subprogram
and short courses (undergraduate and total measures) and graduate-
professional courses (graduate and total measures). The equations used
to calculate these twelve measures of instructional service are reported
in Table 4. The six department-based instructional service measures and
the six university-based instructional service measures which were
computed for Fall 1971 are displayed in Tables 5 and 6 respectively.

Extreme Departments-—In this study, extreme departments were
defined as those departments with instructional service measures of 0.0
(no instructional service students; a non-service department) or 100.0

(all students were service students; a total service department).

 

 

 

 

 

 

 

 

 

 

 

 

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NOO.O OOO.n nO nO N nO OO NHO.O nNO.n nNn OOO.O OOn nnHOssasOn:
OnO OnO OH OH O OH OO HOO HOO HOH OOO OO OOOHeaO
HOO OOO ON ON ON OO OO HOO. OOO OOO OO nH nOansoOeO
OnN.O OnN.O On On OH OO OO OON.O OON.O OnO NON.O OO nsnannOO
nOO NON nO nO ON NH OO NOn OON OON OO nHH .OOOO annHO O.OOO
O O O O OO O OO OO OO OO OO OO nanOOOoHO
Nnn OnO NO NO O nN OO ONO Onn Onn OO OHH NuOandsnoHO
NOn NOn OO OO OO OO OO NOn NOn NH nOn OO neononan<
OH OO OH OO OO OO OH OO OO OO OO OO ONOOHOOOOO
N OO N OO OO OO N OO OO OO OO OO. . HOOO neHnHOnz
H OO H OO OO OO H OO OO OO OO OO OnuanansnO sass:
ONO ONO O O OO O OO nNO nNO HNH OOn OO ..on O .uHseO .ss:
HHO HHO n n OO n OO OOO OOO ON OOn OO nOenN O .nnsz .eOO
OOO OOO HN HN H ON OO NNO NNO NOO Onn OO .HnO OHHOO O .enn
HOn HOn Nn Nn O ON OO ONn ONn ONN On OO OOOHOOO OHHesO
.CquH H950“. HnuOH HMuOH dchOuUOQ mMOumwi AID HPJOH HGUOP H0>3 H0)?“ gumouq ucmfiubwdwa
magma—.3. weaving , cones—.42 home: uo33 loam
OHONON OO<OO<OO ONOOOOOOOOOzO

 

 

 

id

OOOOHOOOO--N OHOOH

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

II . lll‘llllll . be
O- ... c ...; Z M .2. ::
OON ...:n N... 2. N cc NOON OOO . . H. r: .
HO 3.. Z I O O . .n c: NN NO NO .. . ..N
N , . m... .3; .\~ It CC H O CO aka EL~ECEC.O.& N <
we: NCA . . v C ONn CC CC
HCN ex ex ex OH x... C
I I K r - rill :1 .: llllllli -\-i||l\l....- -.lulll‘llliu Ill ..1.. 9N ..-.NOIJMH -
«since 11.....arnw'll......ucie..|\-_u....n:w_.. 1:51.... arenas: .Tullill His... :23 7:1: 7;: 2. Land. O at . .c
-11 it . ....” ......— _,.< f... ...:— ..< .1: NtHHM UV‘NHHWWS! il 1.. .333: hi...”
:3... <3... :1... . .1 I11! 1...: ... <1fiw:rlfi\m. MO . . OH .H. 1< : a. z c z ...N NH 2 N.
~\ 3 a N NH:— O u n.>.-.~ 32.-:33 \AC d—-.ON.: ~ Din-N: a... ..O s CTR.

 

 

 

 

 

 

 

 

 

 

62

 

 

 

 

 

 

NnN NnN nOH nOH OH OO OO OnO OnO NON NOO OO .2 .z .x
OHn . OHn nO nO ON nN OO NOO NOO ONO NO OO .OnO HOanuOuez
OHn.H OHn.H HnN HnN On NOH OO NON.H NON.H NON.H OO OO .OnO HOOHNOOOHO
an.H an.H nO nO nN OO OO OnO.H OnO.H OHO HnO OO .HOO unssnanu
OnO OnO ON ON nN On OO Onn Onn NON NHH OO .OnO .nnn O HH>HO
NNN NNN On On OH NO OO OOH OOH nnH Hn OO .OnO HanHasOO
OOO OOO nO nO NH ON OO OnO OnO ONN OHN OO Openers
OON OON HO HO NH OO OO nOO nOO ONN NOO OO OHOOO O ON
nON nON nO nO H OO OO OON OON nOn nnn OO anHHnnnsen
HOO.H HOO.H OnN OnN Nn HON OO nON.H nON.H HOn NOn.H OO nneHOnnHesssnO
Nnn nnn OO OO nn nO OO OnO nnO NnN nON O .eenn O nOnHoHOOO
OOO ONO OH OH OO OH OO OOO OnO NHO OOO OH OanHnns>O<
OHO.H nOn.H ONO ONO On NOn OO OOH.H nOH.H nOH.H OO nn .nnuus O OeHnexnnz
HnO.H HnO.H ONO ONO ON OnO OO nNH.H nNH.H ONO.H OOH OO OnsssOnnnz
NHO NHO ON ON OO ON OO nOn nOn OON nnn OO .H .O .O
OON.n OON.n OOn OOn Hn OHn OO HHN.n HHN.n NNn.H OnO.H OO neHsnnonO
ONn.H OON.H nH nH OO nH OO nOn.H OnN.H nOO HnN HN .ae<.OOOOsOO.naO
OOn.N nOn.N OOO OOO On OOO OO NOO.N ONO.H nnO.H OOO nnH senanHO O .OOOO
OOO.N OOO.N OOH OOH nN nO OO Onn.N Onn.N ONO OHO.H OO .OnnH nonsseO
OnO OnO O O OO O OO OnO OnO nNN nnn OO nnHOHHsO
OnO.H OnO.H OO OO NH Nn OO ONN.H ONN.H HOO.H ONN OO OOOOOOHHOO
nO0.0 nOO.O nON nON nn ONH OO NON.O NON.O HHO Hnn.n OO ansz
HNN HNN On On O HO OO HNN HNN nHH OOH OO OnHOOHsOnHH
HOO.O HOO.O OnN OnN On OOH OO nON.O nON.O OOn.N nOO.H OO OOOOOHO
HnH.H HnH.H OO OO NN NO OO NOO.H NOO.H HNN HOO OO nuHOnaO O assume.
NHO.O NON.O OHn OHn OHH HOH OO NO0.0 NNO.n nON.N NOO.H OnO OOHHOnO
nON.N nON.N OOH OOH OO OOH OO NnO.N NnO.N NON nON.H OO OOO
OHO HOn NOH NOH O ONH OO NnO OOn OOn OO On .HuseO nonsense
On NN NH NH O O OO NN nH nH OO N .onnsHeO OOOHOOO
ONO ONO HN HN OO HN OO OOO OOO OOO OO OO .nnO .esO O sens
OOn OOn OH OH OO OH OO nON nON OON ON OO OnHOOOnON
ONO nOn On On NH NO OO HOn ONn NOH ONH nnN onsOHanOOOO
OOO nnO OO OO O On OO OnO OOn OOn OON HO nunssnnn
nOn NOn ON ON Hn nN OO OOn HON nnH OnH .OH .z.O O .Hnn Ones
OON OON HO HO nH OO OO NNN NNN NNN OO OO OOHHOHHO O .OOHO
nNO ONn nN nN OH O OO OOn Hnn nO OnN NO ONHOO
OON nOn On On nN On OO nOO Onn OO NNN OOn .Hnn HHOO O nose
NHn NON nH nH n O OO OON OON nH OnN On Nnnnnnasz HaeHOO
nOO NON NO NO OH OO OO HOn ONH NN nO HOO OannnnHOsO .OO
nON OO OO OO On On OO ONH OO OO OO ONH nanenonO .O<
kuOH dragon. HmuOH H.308 HMMOuUOG mhvumfl: mic HnuOH HGUOH H0>3 d0>3 Bands“ u=08uhwqwn
“Sum: 22 noun: :3 nouns—Hz non—N5 no.5..— scam
OO<NON ON<OO<OO ON<OO<OOOOO2O
Hmoa Hash .Ho>mq omuooo hp unoaanounm .m enema

H .... ...OH.

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cc N

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CC
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cc
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cc cc
cc cc
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unbeccnz>ec caE::
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(53

 

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O¢~.-H omo.HH ano.o~ ome.~ aka.” Haa.~ «no.n- H¢H.NH~ aou.~e ~on.os nne.n casuoa gnu-Hagan»
#5 es en oo co co as oo cc cc co co “soc unauaeu:
on .oo on co co co on co co cc cc co .eu: .nuou a .aam
Nee mg Nee ma co ma “Ne co co co cc oo .uox a.u:m.-a:<.am
mam was nNN on an n~ nod ~¢o New oNn NNM oo amoaouoanm
new Hm“ aha em on e oHH so so so cc co hmoflouuaungm
cow cow «AN mad «H ”ca ca Na Na ~o oo cc cwofioauum
mmm mfih 90H om an an cog «as mac ooe wm~ «a amofiofiaouuaz
eaH cod oo co co oo oo oafi cm” «5 «NH co .zuoa Hagan»:
.mNN N mNN N oo N o- oo oo oc oe oo. .vu: a.u=m.s«=<.ma
“Na man man me n me “am can ca“ can cc oo aaouaq<
n¢m.¢ nom.e co oo oo oo oo nan.o nan.c Hm ~en.e co oucufiom Hnfiuom
~o~.m ~o~.m co co co co co ~o~.n ~o~.n mm ~c~.n oo ouauaom Hausumz
Noe.n ~mo.n oo oo co co co Noo.n ~mo.n HA Hmo.n oc mafiuucaesm
Hum.o eq~.e co co co oo oo ana.o eeh.o oN wa~.o NNN .uauq a .unp .uoa<
mom oq¢ and oma co onH co Nam man one man ma .< .A .m .=
Ned.n ncfi.n Nam «an «ma emu co mmm.~ nmm.~ “no.“ m¢~.~ co h€338
oNo.H o~o.~ umq ”me e nae co nod.” neH.fi mmu «me co sues Hafiuom
Nae.” «we.» cc“ oqfi man -¢ oo New.“ ~qa.~ no~.n -o.e oo awofionummm
mo~.~ ao~.~ mm nm em an ac c~o.~ c~o.~ coe.a owe.” oo ooaufium Hooduaflom
mm~ mmH mmfi and q «ma oo co. co cc oo oo .Hoa .vafi a “can;
Noe.” hoc.a “ma “ma “n co“ co own.” oom.~ moo “an co anaaumooo .
mHo.~ mHo.~ mnH mnH 00 had co ema.~ «mm.a nHH.” co“ co ouguaan Hmacaduo .
Ham.~ Ham.~ q¢ em mm ac oo ~H~.~ ~H~.~ awe mo~.a co awofioaouzua<
NHe.H ~H0.H aNH aNH c: on oo nae.” mac.” noe.~ oo cc xmofloon
omq.~ eNc.H mcfi mod mm «NH oo -~.H -~.H so“ can oo aufiumfiumum
~eo.n noo.n NON ~o~ sh nNfi co new.“ mom.~ no~ ooo.~ oo auwazgm
o- oNN co co oo oo oo cNN oNN had an ac animus:
ohm.“ mNR.o «ac cm¢ NHH NNn co cmo.¢ an.o med.” as“.n nan moguasusumx
How How mm mm 0H so co as“ as“ noN nae oo awoaomu
Nqn Nan mm no cc 5 so «we a~e mug co ma honosoucm
mam.n mam.n “on “an nqm Qqfl oo ~na.e Hmo.¢ nae oan.¢ oo auumfiamsu
omn ouq cc” QQH an ac oo man NwN New co «Ha .nuum uaaam a.uon
mm mm mm an m mm 00 oo oo co co co aUfimaaaofin
oqm NnN Nmm NmN ONH we“ co «on one onc oo cad huuafiamsuoda
can me co co co co co can can cm w¢n co aeocouum<
ma oo mH oo oo oo ma co co co co co auuafizuamm
No as 5 co co co 5 co co cc co co Axuc ocaofluuz
Ho oo Ho oe oo oo as oo oo oc cc co ago-ao~u>ua cues:
HH¢.H HHG.H em on co em co “no.” ~na.~ gas oc~.H ca ..09 a .u«>=m .23:
NNn Nun aH a“ n oH co man man NNH c~c co .voou a .uuaz .a==
N-.~ NNN.“ «h «n m oo oo mc~.~ m¢H.H as“ Nun co .«um cacao a .eam
«no one ch cm a“ no co man man aon as oo muoaouu hauaam
.233. 138. H309 H30“. 133909 933m: .70 ~38. H.308 H354 H95..— EauMouN wag
$39.23 35m: «.3 vouaanz puma: .333 145m
mg<pce up<=a<au my<=n<¢oxuaz=

 

 

I'D‘iub O

cwzcfiuaocnum magma

64

 

 

 

 

 

 

 

 

 

 

 

 

 

[J

 

Anoo.HoV nouuaou Haney .nvc cu .Haouco ouw>uo¢ H-uou H< noouaou AnuOu .nvu aw .Haouco .uaov h< H-uOu
anonusou AnuOu .Hfla cw aucovsu- oua>uou we .lscMocH man: Amuuuaoo HnuOu .nwt :« aucovsuo ouu>uuu no .asavoca I name vouonnva
Amma.nv nomuaou .vuuw .wcn ea .Haouco moa>uua Hugo» u< noouaoo .vqum .nvo ca .Haouco .uuuv o< ouaavaum
mucousoo .vmwwwqfivc cu aucuvzuo cowbuoo mo .Escvoca mun: newnu300 .vouw.wfiwc cu nucovsun ouu>uoo uo .BanMcc~ I mama vounahvo
Anno.~ov nonuaoo .vuuwuovc: .nvu aw .HHOHco ovavuua Hquu p< noouaou .vnuuuovca .qva ca .Haouau .uaov =< ouosvaumuovca
Anomu300 .vumwuovca .fivx cu oucovauu uuw>hoa uo .aacvcca mun: nomusou .vuuwuovcs «fivn cw uuaovsuo ovu>hou mo .EacvcoH I mama vouuanv-
AnNH.omv nomuaou aqua“ .fivac: ca .aHouco oua>pon Houou ab munuaou Hugo» .finmca ca .HHOucu .unov ab 9 Hanan
Amouuaoo nauOu .fivrcs cu aucovsun ouw>huo no .anmvcca mfinc Hummusou Aqua» .fivac: c“ rucovvun ouw>uom no .25: ooH I mum vouusnvoc:
A<n~.cv nomuaou .caum .nvnc: a“ .aaouco uua>uua HQUOu o: mouuaou .vaum .flvmc: :« .«Houco .uaov u: «unavauu
Aaoauaou .vouw .flvucs cw mucuvsun ou~>uoo uo .sacvoca was: dmwnuaou .ccuw .fivuca Cu masovauu ovu>hum mo .adcvoo~ I mama vouonnvucn
Acmm.mov nouusou .vaumuovc: .avcc: ca .HAOuao ouw>hoa aduOu a: unannou .vauwuavaa .fivoc: :« .Huouco .unuv Db ounavauwuovc:
mnoousou .vcumuovca .dvuc: c“ mucuvuuu oou>huo uo .ssmvco~ mun: ‘Nmunuaou .vnuMuocc: «fives: c«-nucov:uo uuu>uen no .achcoa I mama vuunamcnc:
quaauoz uuw>uum Hunowuuahuwcw vuawmnhuwnuo>acb ¢ou=auux ouw>Lom anneauoauumcn cucumnucoauuaqoo nouzmmax

huwanam

 

 

nousnao: oua>uom Hdnowuoauuaan

uou unowuqsvu

.o canah

 

Table 5. Depart::

P

eIartzent
LJ_____~——-————

Agricultural Eco-.2.
kriudtural Eng_.
63:41 Husbandry
€GC 3 Soil Scicr.
Dairy

Fisheries 8 Uildi
F001 Sci. 3 Hut...
Forestry
Ecrticulture
Ringing

Park & Rec. Resen-
EMIX’)’ Science
Resource Barclay:
Art

English

Gem-m ‘ Russian
Fistory
Linil‘uistics

5351c
Philomphy
Religion
I‘m-ace La

figuage.
Acct. ; F

inance J
gas. Lav S Otfic.
Licnnics
EstelIRES.& I
Eminent

 

65

Table 5. Department-based Instructional Service Measures, Fall 1971

 

 

 

 

 

Unadjgsted Adjusted

QQQartment Undergraduate Graduate Total Undergraduate Graduate Total
Agricultural Economics 100.0 4.8 69.6 0.0 4.8 4.8
Agricultural Engineering 94.8 52.4 89.4 75.8 52.4 66.3
Animal Husbandry 83.9 7.7 80.8 80.7 7.7 77.1
CrOp 8 Soil Science 94.6 32.2 89.7 89.0 32.2 80.5
Dairy 92.5 4.0 87.2 91.5 4.0 85.6
Fisheries 8 Wildlife 64.8 4.9 52.1 64.8 4.9 52.1
Food Sci. 8 Hum. Nutr. 68.0 17.1 57.9 66.0 17.1 55.9
Forestry 46.2 39.1 45.7 40.6 39.1 40.5
Horticulture 83.6 11.9 76.8 71.8 11.9 62.6
Packaging 22.1 10.5 21.4 22.1 10.5 21.4
Park 8 Rec. Resources 49.5 47.9 49.3 49.5 47.9 49.3
Poultry Science 50.0 0.0 32.4 26.7 0.0 14.8
Resource Deve10pment 83.8 36.3 69.8 82.2 36.3 67.8
Art 44.0 4.7 41.4 44.0 4.7 41.4
English 76.2 22.9 72.8 72.4 22.9 68.8
German 8 Russian 85.5 4.3 80.6 85.5 a 4.3 80.6
History 86.1 15.3 82.3 86.1 15.3 82.3
Linguistics , 89.6 20.0 76.8 89.6 20.0 76.8
Music 35.8 0.5 34.2 35.8 0.5 34.2
Philosophy 93.2 36.2 91.0 93.2 36.2 91.0
Religion 96.6 100.0 96.6 96.6 100.0 96.6
Romance Languages 80.9 6.6 77.9 80.9 6.6 77.9
Acct. 8 Finance Adm. 70.3 58.6 68.2 68.0 58.6 66.1
Bus. Law 8 Office Adm. 73.9 100.0 74.2 72.4 100.0 72.7
Economics 86.5 69.6 83.9 86.5 69.6 83.

Hote1,Res.8 Inst. Mgt. 18.5 10.3 18.1 18.5 10.3 18.1
Management 88.4 72.7 82.7 88.4 72.7 82.7
Marketing 8 Trans. Adm. 83.9 45.7 73.9 83.4 45.7 73.4
Advertising 62.9 68.8 63.0 62.5 68.8 62.5
Audiology 8 Speech Sci. 53.4 1.0 44.2 53.0 1.0 43.8
Communications 73.6 50.4 70.8 73.6 50.4 70.8
Journalism 41.0 22.2 39.9 41.0 22.2 39.9
TV 8 Radio 32.8 8.6 30.2 32.8 8.6 30.2
Theatre. 44.4 2.2 40.5 44.4 2.2 40.5
Chemical Engineering 5.5 15.5 8.1 5.5 15.5 8.1
Civil 8 Sanitary Eng. 35.4 10.1 30.8 35.4 10.1 30.8
Computer Science 74.7 16.9 72.2 74.7 16.9 72.2
Electrical Engineering 12.4 33.9 15.9 12.4 33.9 15.9
Mechanical Engineering 14.8 11.6 14.5 14.8 11.6 14.5
Meta1., Mech, 8 Mat.Sci. 90.5 34.0 82.8 90.5 34.0 82.8
Family Ecology 56.4 42.1 54.8 56.4~ 42.1 54.8
Family 8 Child Science 72.0 28.4 69.4 72.0 28.4 69.4
Human Nutr. 8 Foods 73.8 15.8 71.9 73.8 15.8 71.9
Human Envir. 8 Design 22.9 7.4 22.4 22.9 7.4 22.4
Human Development 0.0 100.0 100.0 0.0 0.0 0.0
Medicine 0.0 100.0 100.0 0.0 0.0 0.0
Psychiatry 0.0 100.0 100.0 0.0 0.0 0.0

Idle $-~Coatinuod

. .

 

'9‘“;

‘, "t
"vh‘s uhkqd

951mm
5:43:35“,
licfiysits
5°13? 8 Plant Path,
C‘. .istry

E2212mm“
Secltjy
Hazhezatics
Surging

th-‘sics

Staziszicg

tricgy
53:33:0le
31112.31 Justice
gaffe;hy

lat-3r & Indust. R91.
~¢lit1ca1 Scien

 

u w-
“ ..tal LEChnelcgy
~~rcbxozogy
:E23Llo
rz‘v‘icl
.- .0 .
t... g)

Table 5--Continued

66

 

 

 

 

Unadiusted Adjusted
QgQartment Undergraduate Graduate Total Undergraduate Graduate Total
Astronomy 94.3 0.0 94.3 94.3 0.0 94.3
Biochemistry 83.3 29.1 65.2 79.1 29.1 59.8
BiOphysics 0.0 24.2 24.2 0.0 24.2 24.2
Botany 8 Plant Path. 91.6 29.9 75.1 88.3 29.9 68.5
Chemistry 95.3 15.0 89.5 95.3 15.0 89.5
Entomology 93.3 37.7 87.9 93.1 37.7 87.6
Geology 82.4 21.7 76.5 82.4 21.7 76.5
Mathematics 86.8 10.4 82.3 85.5 10.4 80.7
Nursing 2.5 0.0 2.5 2.5 0.0 2.5
Physics 94.8 10.4 89.2 94.8 10.4 89.2
Statistics 99.8 52.3 94.9 99.8 52.3 94.9
Zoology 73.0 17.1 68.5 73.0 17.1 68.5
Anthropology 91.0 21.3 88.1 91.0 21.3 88.1
Criminal Justice 30.9 13.3 29.8 30.9 13.3 29.8
Geography 84.8 8.8 77.8 84.8 8.8 77.8
Labor 8 Indust. Rel. 0.0 34.2 34.2 0.0 34.2 34.2
Political Science 81.4 30.6 79.8 '81.4 30.6 79.8
Psychology 80.6 23.1 75.7 80.6 23.1 75.7
Social Work 43.0 10.5 33.8 43.0 10.5 33.8
Sociology 91.0 42.9 86.3 91.0 42.9 86.3
Urban Plan. 8 Land. Arch. 28.6 10.3 26.0 26.9 V 10.3 24.6
Amer. Thought 8 Lang. 100.0 0.0 100.0 100.0 0.0 100.0
Humanities 100.0 0.0 100.0 100.0 0.0 100.0
Natural Science 100.0 0.0 100.0 100.0 0.0 100.0
Social Science 100.0 0.0 100.0 100.0 0.0 100.0
Anatomy 99.8 95.5 98.3 99.8 72.9 97.8
Lg. Anim. Surg. 8 Med. 0.0 99.1 99.1 0.0 0.0 0.0
Medical Technology 19.4 0.0 19.4 19.4 0.0 19.4
Microbiology 90.3 .60.7 84.1 89.7 15.6 81.1
Pathology 100.0 86.0 89.9 100.0 75.4 85.5
Pharmacology 100.0 66.5 78.7 100.0 0.0 64.2
Physiology 96.1 74.4 89.6 96.1 18.4 87.9
Sm. Anim. Surg. 8 Med. 0.0 97.5 97.5 0.0 26.7 26.7
Family 8 Community Med. 0.0 100.0 100.0 0.0 0.0 0.0
Medicine (0M) 0.0 100.0 100.0 0.0 0.0 0.0

 

Table 6. University-based Instructional Service Measures, Fall 1971

67

 

 

 

 

 

Unadjusted Adjusted
Department Undergraduate Graduate ‘ Total Undergraduate Graduate Total
Agricultural Economics .196 .084 .190 .000 .127 .004
Agricultural Engineering .582 .908 .598 .103 1.362 .147
Animal Husbandry .275 .021 I .262 .229 .032 .222
Crop 8 Soil Science .709 .401 .694 .340 .602 .349
Dairy .403 .021 .384 .365 . .032 .353
Fisheries 8 Wildlife .161 .063 .156 .167 .095 .165
Food Sci. 8 Hum. Nutr. .230 .275 .232 .218 .412 .225
Forestry .328 .380 .331 .272 .570 .282
Horticulture .513 .148 .495 .266 .222 .265
Packaging .069 .042 .068 .072 .063 .071
Park 8 Rec. Resources .221 .718 .246 .230 1.077 .259
Poultry Science '.012 .000 .011 .005 .000 .004
Resource Development .400 1.394 .449 .373 2.090 .433
Art .991 .148 .950 1.030 .222 1.002
English 3.840 1.500~ 3.724 3.274 2.248 3.238
German 8 Russian 1.012 .063 .965 1.052 .095 1.019
History 3.998 .760 3.839 4.155 1.140 4.051
Linguistics .217 .211 .216 .225 .317 .228
Music 1.671 .021 1.590 1.736 .032 1.677
Philosophy 1.804 .528 1.742 1.875 .792 1.838
Religion .878 .085 .839 .912 .127 .885
Romance Languages 2.246 .148 2.143 2.335 .222 2.261
Acct. 8 Finance Adm. 1.602 5.767 1.807 1.491 8.645 1.739
Bus. Law 8 Office Adm. 1.055 .317 1.018 1.015 .475 .997
Economics 3.039 8.365 3.301 3.158 12.540 3.483
Hote1,Res.8 Inst. Mgt. .118 .063 .115 .123 .095 .122
Management 1.135 10.414 1.592 1.179 15.611' 1.680
Marketing 8 Trans. Adm. 1.098 4.056 1.243 1.103 6.080 1.276
Advertising .597 .232 .579 .610 .348 .600
Audiology 8 Speech Sci. .268 .021 .256 .274 .032 .266
Communications 1.403 2.535 1.459 1.458 3.800 1.539
Journalism .314 .211 .309 .326 .317 .326
TV'8 Radio .245 .148 .240 .255 .222 .254
Theatre .213 .021 .204 .222 .032 .215
Chemical Engineering .010 .190 .019 .010 .285 .020
Civil 8 Sanitary Eng. .139 .169 .140 .144 .253 .148
Computer Science 1.185 .232 1.138 1.232 .348 1.201
Electrical Engineering .172 1.796 .252 .179 2.692 .266
Mechanical Engineering .076 .106 .077 .078 .158 .081
Metal., Mech, 8 Mat.Sci. .648 .739 .652 .673 1.108 .688
Family Ecology .360 .676 .376 .374 1.013 .396
Family 8 Child Science .905 .444 .882 .940 .665 .931
. Human Nutr. 8 Foods .446 .063 .428 .464 .095 .451
Human Envir. 8 Design .465 .084 .446 .483 .127 .471
Human Development .000 .021 .001 -.000 .000 .000
Medicine (HM) .000 .148 .007 .000 .000 .000
Psychiatry .000 .380 .019 .000 .000 .000

Table 6--Continued

68

 

 

 

 

 

__ Unagjysted Adjusted
Department Undergraduate Graduate Total Undeggraduate Graduate Total
Astronomy ‘. 396 . ooo . 377 .412 .000 . 397
Biochemistry .514 1.732 .574 .405 2.597 .481
Biophysics .000' .169 .008 .000 .253 .009
Botany 8 Plant Path. .396 .908 .421 .283 ‘1.362 .321
Chemistry 5.143 1.225 4.950 5.345 1.834 5.223
Entomology .504 .422 .500 .507 .633 .512
Geology .701 .380 .686 .729 .570 .723
Mathematics 6.584 .951 6.307 6.167 1.425 6.003
Nursing .008 .000 .007 .008 .000 .008
Physics 2.972 .444 2.847 3.089 .665 3.005
Statistics 1.395. 1.648 1.408 1.450 2.470 1.485
Zoology 1.184 .465 1.149 1.230 .697 1.212
AnthrOpology 2.207 .422 2.119 2.294 .633 2.236
Criminal Justice .638 .380 ‘ .625 .663 .570 .660
Geography 1.262 .253 1.212 1.311 .380 1.279
Labor 8 Indust. Rel. .000 1.141 .056 .000 1.710 .059
Political Science 2.337 .549 2.249 2.429 .823 2.373
Psychology 7.005 3.612 6.838 7.280 5.415 7.216
Social Work .547 1.104 .570 .569 -1.520 .602
Sociology 2.843 2.831 2.842 2.954 4.243 2.999
Urban Plan. 8 Land. Arch. .260 .296 .262 .249 .443 .256
Amer. Thought 8 Lang. 7.628 .000 7.252 7.669 .000 7.403
Humanities 6.228 .000 5.922 6.473 .000 6.248
Natural Science 5.692 .000 5.412 5.916 .000 5.711
Social Science 5.026 .000 4.778 5.223 .000 5.042
Anatomy .644 6.760 .946 .670 1.108 .685
Lg. Anim. Surg. 8 Med. .000 4.774 .235 .000 .000 .000
Medical Technology .042 .000 .040 .043 .000 .042
Microbiology .723 2.514 .811 .702 .443 .693
Pathology .090 ,3.887' .277 .093 2.818 .188
Pharmacology .106 2.387 .218 .110 .000 .106
Physiology .675 4.288 .853 .702 .443 .693
Sm. Anim. Surg. 8 Med. .000 9.104 .448 .000 .127 .004
Family 8 Community Med. .000 .760 .037 .000 .000 .000
Medicine (CM) .000 1.563 .077 .000 .000 .000

 

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69

A review of the data in Tables 5 and 6 revealed that departments at both
extremes appeared on the department—based instructional service measures
while only non—service departments were identified on the university“
based instructional service measures. In addition, the noneservice

1 These extreme

departments were identical on both sets of measures.
departments (non—service and total service) are listed in Table 7.
In general, these departments are classified as extreme because they did
not have any undergraduate or graduate courses. However, there were two
exceptions to the above for both the department—based and the university—
based instructional service measures. For both the unadjusted and
adjusted data, Poultry Science was classified as a graduate, nonvservice
department; Pharmacology was classified as a graduate, nonvservice
department on only the adjusted measure. Yet, both these departments
offered graduate courses and had graduate—level majors. Thus, these
deviations were engendered by student course selection for Fall 1971 and
could not have been predicted from such departmental characteristics as
number of majors and course offerings.

Two additional points should be made about the data in Table 7.
When the total instructional efforts of the department was considered

(unadjusted total instructional service measures), every department in.

the study provided instruction to service students (nondmajors) in either

 

1The definition of the university-based measures required that the
sum of the departmental values for each measure equal 100. Thus, no
total service departments existed on the university-based measures.

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71

undergraduate or graduate courses. Thus, the degree of both under-
graduate and graduate instructional service, not the presence or absence
of instructional service, should be used to differentiate the role of
instructional service in academic departments. Second, a comparison

of the list of unadjusted and adjusted extreme departments revealed
that some departments (Psychiatry, Human Development, etc.) shifted
from.graduate, total service departments (unadjusted) to graduate, non-
service departments (adjusted). This exchange occurred because all of
the courses offered in these departments were graduate-professional
courses, and enrollments in these courses were not part of the adjusted
data base. Similarly, Agricultural Economics was classified as an
undergraduate, total service department (unadjusted) and an undergradu-
ate, non-service department. In this case, the deletion of enrollments
of sub-program and short courses to form the adjusted data base elimi-
nated all undergraduate enrollment in Agricultural Economics. This,

in turn, changed the value of the undergraduate instructional service
measure from 100.0 to 0.0.

Descriptive Data--The department-based instructional service
measures ranged from 0.0 (non-service) to 100.0 (total service) for all
measures except the unadjusted total which ranged from 2.50 to 100.0.
The range, mean, median, and standard deviations of these six measures
are presented in Table 8. These data in Table 8 indicated that means
and medians for the undergraduate and total instructional service
measures were substantially higher than the means and medians for the
graduate service measures. Thus, generally, the level of graduate

service instruction is less than the level of undergraduate service

72

Table 8. Descriptive Data--Department-based Instructional Service

 

 

 

Measures

Standard
Summary Measures Range Median Mean Deviation
unadjusted undergraduate 0.0 - 100.0 75.45 62.73 34.47
unadjusted graduate 0.0 - 100.0 21.95 33.26 32.12
unadjusted total 2.5 - 100.0 76.10 67.64 27.46
adjusted undergraduate 0.0 - 100.0 73.30 60.37 34.68
adjusted graduate 0.0 - 100.0 15.55 22.65 23.57

 

instruction in academic departments. However, the obvious exceptions
were those departments which had no undergraduate service or instruc-
tional load (i.e., Labor and Industrial Relations and Psychiatry). The
distributions of the undergraduate and total department-based instruc-
tional service measures were negatively skewed (median > mean) for both
unadjusted and adjusted data while the distributions of the graduate
measures were positively skewed (median < mean). Finally, when the
unadjusted and adjusted department-based measures for each instructional
level were compared, the difference scores indicated that the means of
the unadjusted and adjusted, graduate and total measures were meaning-
fully different (10.61 and 10.51 respectively).

Parallel data for the university-based instructional service
measures are presented in Table 9. While both the upper and lower limits
of the ranges of the department-based measures with relatively constant
(0.0 and 100.0), only the lower limits of the ranges of the university-

based measures exhibited this stability. All measures except the

73

Table 9. Descriptive Data--University-based Instructional Service

 

 

 

Measures
Standard
Summary Measures Range Medium Mean Deviation
unadjusted undergraduate 0 - 7.628 .514 1.220 1.774
unadjusted graduate 0 - 10.414 .380 1.221 2.103
unadjusted total .001 - 7.252 .535 1.219 1.694
adjusted undergraduate 0 - 7.669 .438 1.220 1.808
adjusted graduate 0 - 15.611 .364 1.220 2.527
adjusted total 0 - 7.403 .461 1.220 1.763

 

unadjusted total (.001) had lower limits of 0.0. The upper bounds of
the range varied from 7.403 (adjusted total) to 15.611 (adjusted gradu-
ate). Also, the upper limits of the graduate measures were larger than
their undergraduate and total counterparts. The data in Table 9 indi-
cated that the means of the six university-based instructional service
measures were identical when rounded to the nearest hundredth. Further,
the medians, though exhibiting more variance than the means across
measures, were less than the means which indicated that the distribu-
tions of all of the university-based instructional service measures were
positively skewed.

Correlational Data2—-Three of the ten sets of research questions

outlined in Chapter IV focused on the relationships among the twelve

 

2Throughout the discussions in Chapter V and VI "relationship"
implies the relationship of the rank order of the variables as computed
by Spearman's rho.

74

instructional service measures defined in this study. Spearman rank
correlation coefficients were computed based on the ranking of the
departments on each instructional service measure. A composite of the
rankings for each department and the rankings for each measure are shown
in Appendix C, Tables 24-37. The correlation coefficients relevant to
all three questions are presented in Table 10.

The first set of research questions dealt with the relationships
among the undergraduate, graduate, and total instructional service
measures. For the unadjusted department-based instructional service
measures, the relationship between the undergraduate and graduate
instructional service measures was extremely weak3 (-.07) while the
relationships between the undergraduate and total (.53) and the graduate
and total measures were statistically significant but moderate and weak
respectively. A similar pattern emerged for the adjusted department-
based measures for which the relationship between the undergraduate
and graduate measures was very weak (.26) while the relationships between
the undergraduate and total (.96) and the graduate and total (.32)
measures were statistically significant and very strong and weak respec-
tively. Thus, for the adjusted department-based instructional service
measures, the null hypothesis of mutual independence was not rejected

for the relationship between undergraduate and graduate measures and

 

3Qualitative descriptions of the correlation coefficients (weak,
moderate, strong) were based on guidelines presented by Marascuilo.
(L. Marascuilo, Statistical Methods for Behavioral Science Research
(New York: McGraw-Hill Book Company, 1971), p. 433.)

75

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76

was rejected for the relationship between undergraduate and total and
graduate and total measures. Parallel results were found for the
unadjusted university-based instructional service measures. However,
for the adjusted university—based instructional service measures, the
relationship between the undergraduate and the graduate measures (.41)
was weak but statistically significant.

The second set of research questions focused on the relationships
between department—based and university-based instructional service
measures. The Spearman rank correlation coefficients for these rela—
tionships are also found in Table 10. In this analysis, the relation—
ships between each department—based summary measure and its university—
based counterpart were of interest. The null hypothesis of mutual
independence was rejected for all six summary measures. However, the
strength of the relationships varied from .38 (unadjusted total) to .82
(adjusted graduate).

Finally, the third set of research questions were developed to
assess the relationship between the unadjusted and adjusted instruc—
tional service measures at each level (undergraduate, graduate and
total). An analysis of these six correlation coefficients revealed that
on the basis of these Spearman rho's the null hypothesis of mutual
independence for each pair of unadjusted and adjusted measures was
rejected. In addition, the strengths of the relationships for the uni—
versity-based measures (.98, undergraduate; .75, graduate; .97, total)
were greater than those for the department-based measures (.93, .57,

and .55 respectively).

77

Summary-~The analyses of the data on instructional service revealed
that significant relationships existed between 1) undergraduate and
total instructional service measures, 2) undergraduate and graduate
adjusted, university-based measures, 3) department-based and university-
based instructional service measures, and 4) adjusted and unadjusted
instructional service measures. Only the relationships between the
undergraduate and graduate unadjusted department-based, adjusted depart-
ment-based, and unadjusted university-based instructional service

measures were not significant.

Relationships Between Instructional Service
Measures and Descriptive Data

Five of the areas of inquiry delineated in Chapter IV focused on
the relationships of the twelve instructional service measures with
other descriptive data about the academic departments. These descrip-
tive data included funding, faculty rank distributions, graduate assis-
tants, prestige of graduate programs and level of instructional service
students. The relationships with funding, faculty rank distributions,
graduate assistants and average salary, were assessed by Spearman rank
correlations based on the rankings on the instructional service measures,
Appendix B, Tables 24-37 and the rankings on the descriptor variables,
Appendix C, Tables 38-42. The relationships with prestige and level of
instructional service were measured through a chi-square test for inde-
pendence. A discussion of the results of each type of analysis is pre-

sented in this section of Chapter V.

78

Chi-square Tests of Independence--Four chi-square tests were used
to assess the relationship between the level of instructional service
students in undergraduate courses and the level of undergraduate instruc-
tional service based on unadjusted and adjusted, department-based and
university-based instructional service measures. Departments were
first classified into predominately lower division or predominately
upper division instruction service on the basis of the percentage dis-
tributions of students by level presented in Appendix C, Tables 43-44.
The departments which provided instructional service in undergraduate
courses to primarily lower division undergraduate students are listed
in Table 11. The departments were then classified into low, medium, and
high instructional service departments. The classification procedure
and its results are discussed fully in a subsequent section of this
chapter. The observed and expected cell frequencies and the results
of the analyses of the contingency tables for each test are presented
in Table 12. A review of the results of these four chi-square tests
for independence revealed that the level of department-based instruc-
tional service in undergraduate courses was independent of the predomi-
nate level of instructional service students in undergraduate courses.
The values of chi-square and phi were 4.29 and .24 for the unadjusted
data and 2.69 and .18 for the adjusted data. Conversely, the computed
values of chi-square for the university-based.measures were sig-
nificant at the .05 level. Therefore, the null hypotheses were rejected
and significant relationships existed between the unadjusted and
adjusted university-based instructional service measures and the level

of instructional service students in undergraduate courses.

Table 11.

79

Departments with Predominately Lower Division Instructional

Service Students in Undergraduate Courses

 

 

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F‘F‘
pic:
0 O

12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.

Based on Unadjusted Data

 

Agricultural Economics
Agricultural Engineering
Animal Husbandry

Crap and Soil Science
Dairy

Horticulture

Poultry Science

German and Russian

Music

Romance Languages
Communications

Human Environment and Design
Chemistry

Mathematics

Physics

Criminal Justice
Psychology

American Thought and Language
Humanities

Natural Science

Social Science

Medical Technology

 

......q'. —- .—

H
OWCDVO‘UIbUJNl-J
O O

p.»
H
O

12.
13.
14.
15.
16.
17.
18.

Based on Adjusted Data

Animal Husbandry

Dairy

Poultry Science

German and Russian

Music

Romance Langauges
Communications

Human Environment and Design
Chemistry

Mathematics

Physics

Criminal Justice

Psychology

American Thought and Language
Humanities

Natural Science

Social Science

Medical Technology

 

80

Table 12. Chi-square Tests of Independence--Level of Instructional
Service Students in Undergraduate Courses

 

 

Lower Division
Upper Division

Lower Division
Upper Division

Lower Division
Upper Division

Lower Division
Upper Division

*Significant; alpha

Department-Based-—Unadjusted Undergraduate

Low Medium High
4 (7.24) 7 (7.51) 11 (7.24)
23 (19.76) 21 (20.49) 16 (19.76)
x2 = 4.69 6 = .24

Department-Based--Adjusted Undergraduate

Low Medium High
5 (5.93) 4 (5.93) 9 (6.15)
22 (21.07) 23 (21.07) 19 (21.85)
x2 = 2.69 3 = .13

University-Based--Unadjusted Undergraduate

Low Medium High
3 (7.24) 7 (7.51) 12 (7.24)
24 (19.76) 21 (20.49) 15 (19.76)
2 A.
X = 7.71* 0 = .31

University-Based-—Adjusted Undergraduate

Low Medium High
3 (5.93) 3 (6.14) 12 (5.93)
24 (21.07) 25 (21.85) 15 (21.07)
x2 = 11.89* 3'- .38

.05

81

The strengths of these relationships were .31 for the unadjusted data
and .38 for the adjusted data. Finally, an inspection of the con—
tingency tables indicated that departments that served predominately
lower division students in undergraduate courses tended to have high
university—based instructional measures.

A second set of four chi-square tests for independence was used
to assess the relationship between the prestige of graduate programs
and the level of instructional service in graduate courses. The
reports on the prestige of graduate education by Cartter (1966) and
Roose and Andersen (1970) published by the American Council on Educa-
tion were used to identify departments with prestige graduate programs.
Both reports rated departments on the quality of their faculty and the
quality of their graduate program. A composite of those two ratings was
used to identify the ”ranked" departments listed in Table 13. Six
departments appeared in the Roose-Andersen report which were not rated
in the Cartter report. These departments which are designated with
asterisks in Table 13 were included in the analyses as rated depart-
ments. The categories of graduate instructional service were based on
the rankings of departments on each measure and are discussed in a sub-
sequent section. The observed and expected frequencies and the results
of the chi-square tests on each contingency table are presented in
Table 14. The null hypothesis that the level of graduate instructional
service and the prestige rating of graduate education are statistically
independent was rejected for all four measures of graduate instructional

service. The strengths of these relationships as described by the phi

82

Table 13. Departments with Prestige Graduate Faculty/Programs

 

 

*Anthropology History
*Biochemistry ‘ Mathematics

Botany Mechanical Engineering
*Chemical Engineering A Microbiology
Chemistry *Music,\

Civil and Sanitary Engineering Philosophy
Economics Physics

Electrical Engineering * Physiology

English Political Science
Entomology Psychology
Geography * *Romance Languages‘
Geology Sociology

*German and Russian x Zoology

 

*Rated by Roose and Andersen (1970) but not by Cartter (1966).
N - 26 (31.7%)

coefficient were .31, unadjusted department-based; .38, adjusted
department-based; .27, unadjusted university-based, and .35 adjusted
university-based. A comparison of the observed and expected values in
each contingency table disclosed that for the department—based graduate
instructional service measures the ranked departments tended to have
medium unadjusted and adjusted measures. However, for the university-
based graduate instructional service measures, the rank departments were
primarily distributed in the medium and high categories for the unad-
justed and adjusted measures.

Correlational Data--As previously noted, Spearman rank correlation
coefficients were used to measure the strengths of the relationships
between the twelve instructional service measures and descriptive data

such as funding, faculty rank distributions, graduate assistants and

83

 

 

Table 14. Chi-square Tests of Independence Prestige of Graduate
Faculty/Programs
Department-Based--Unadjusted Graduate
Low Medium High
Ranked 7 (8.88) 14 (8.56) 5 (8.56)
Unranked 21 (19.12) 13 (18.44) 22 (18.44)
x2 = 7.81* 0= .31
Department-Based——Adjusted Graduate
Low Medium High
Ranked 3 (8.56) 15 (8.88) 8 (8.56)
Unranked 24 (18.44) 13 (19.12) 19 (18.44)
2
X = 11.53* 6- .38
University-Based-—Unadjusted Graduate
Low Medium High
Ranked 4 (8.88) 10 (8.24) 12 (8.88)
Unranked 24 (19.12) 16 (17.76) 16 (19.12)
2
X = 6.09* 6= .27
University-Based--Adjusted Graduate
Low Medium. High
Ranked 2 (7.93) 11 (9.51) 13 (8.56)
Unranked 23 (17.07) 19 (20.49) 14 (18.44)
X2 = 10.20 6= .35

*Significant; alpha = .05

84

average salary. The correlation coefficients are presented in Table 15.
This array is a table of correlations, not a correlation matrix, because
only the correlations of the descriptor variables with the twelve
instructional service measures are displayed.

One of the sets of relationships under study was the relationships
between the instructional service measures and funding. Ten variables
were identified which represented three aspects of funding in each
department. Five variables (total, salary, labor, supplies and services
and equipment) described the general fund expenditures for the 1971-72
academic year; four variables (total, salary, equipment, and other)
described the research grant and contract expenditures for 1971-72, and
one variable (average salary) described the lOdmonth equated average
salary for each department. The data in Table 15 indicated that signifi-
cant but weak relationships existed between general fund total and
salary expenditures and the unadjusted and adjusted, undergraduate and
total department-based instructional service measures. However, the
relationships between these general fund variables and the comparable
university-based instructional service measures were strong and statis-
tically significant. Three other significant relationships were found
in the general fund data: general fund labor and unadjusted total
department-based measure, general fund supplies and services and unad-
justed total department-based measure, and general fund supplies and
services and unadjusted university-based measure. While no significant
relationships occurred between the department-based instructional

service measures and the four research grant and contract variables,

85

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. nH manna.

86

four significant, but weak, relationships were evidenced between the
university-based instructional service measures and these four funding
variables. These relationships were between the following pairs of
variables: unadjusted graduate and total; unadjusted graduate and
salary; unadjusted graduate and other; and adjusted undergraduate and
equipment. Finally, only three significant relationshipsv—unadjusted
and adjusted graduate university-based instructional service measures
and unadjusted graduate department-based measure-dwith average salary
were present in the data. Interestingly, most of the non-significant
relationships with average salary were negative.

The second set of relationships which was analyzed in this study
included the twelve instructional service measures and indicators of
the faculty distribution by ranks in each department. These relation-
ships were of interest because, theoretically, the type of instruc-
tional load in academic departments should affect staffing. Three
faculty rank indices—-one based on faculty headcount, one based on
full-time equivalent faculty (FTE), and one based on the percentage
distribution of faculty over ranks-dwere constructed by weighting each
rank (4-professor, 3-associate professor, 2—assistant professor, and
l-instructor) and summing across ranks. These indices and ranking of
the deparUments on each are displayed in Appendix C, Table 40. The
evidence in Table 15 suggested that both the headcount and FTE faculty
indices were significantly related to eight of the twelve instructional
service measures--department—based unadjusted and adjusted undergraduate

and adjusted total; university-based unadjusted and adjusted

87

undergraduate and total and adjusted graduate. In addition, the head-
count index is significantly related to the unadjusted total department-
based measure while the FTE index is significantly related to the unad-
justed graduate university—based measure. On the other hand, the
faculty rank index based on the percentage distribution of faculty over
ranks was significantly, but weakly, related to only one instructional
service measure--the adjusted graduate university-based measure.

The last set of relationships between the twelve instructional
service measures and the descriptor variables focused on the number
(headcount and FTE) of graduate assistants employed in academic depart—
ments. Both measures of graduate assistant employment were significantly
related to all six university-based instructional service measures and
to the adjusted graduate department-based measure. In addition, the FTE
measure had a weak, but significant relationship with the adjusted total
department-based measure.

Summary--From the results of the chi-square tests for independence,
three points can be made. First, departments that served predominately
lower division students tended to have high adjusted and unadjusted
undergraduate university-based instructional service measures. Second,
departments with rated graduate programs/faculty tended to be classified
as medium unadjusted and adjusted graduate department-based instructional
service measures. Third, for the university—based graduate instructional
service measures, the rated departments were primarily distributed in
the medium and high categories for the unadjusted and adjusted measures.

Of the one hundred and eighty correlations under consideration in

this part of the analysis, sixty-four (35.6%) were statistically

88

significant. These significant relationships were identified in the
preceding discussion. However, of these sixty-four significant rela-
tionships, only twenty-two (12.2%) were moderate or strong (greater than
.50). Thus, approximately thirty-six percent of the relationships
studied were significant and only twelve percent were moderate or strong.
These twenty-two moderate to strong relationships are summarized in
Table 16. Interestingly, no department-based instructional service
measures were strongly related to any of the descriptor variables, and
no variables representing research grant and contract expenditures were
strongly related to any of the instructional service measures. In addi-
tion, the strong correlations between the unadjusted undergraduate and
unadjusted total and between the adjusted undergraduate and adjusted
total university-based instructional service measures were reflected

in Table 16 since these pairs of measures had similar relationships with
the descriptor variables. Finally, the adjusted graduate university-
based instructional service measure appeared only twice (graduate
assistant-numbers and FTE) in Table 16, while the unadjusted graduate

measure was not represented.

DiscriminatorygVariables

The final purpose of this study was to classify departments on the
basis of the instructional service measures and to determine which
descriptor variables discriminated among the categories of instructional
service. A multiple discriminant analysis was conducted on the four

undergraduate measures and the four graduate instructional service

89

 

 

Table 16. Descriptor Variables with Moderate and Strong Relationships
to Instructional Service Measures

Variable Instructional Service Measure §h2_
1 General Fund Total UBIS unadjusted undergraduate .66
2 " UBIS unadjusted total .70
3 " UBIS adjusted undergraduate .64
4 " UBIS adjusted total .65
5 General Fund Salary UBIS unadjusted undergraduate .66
6 " UBIS unadjusted total .71
7 " UBIS adjusted undergraduate .64
8 " UBIS adjusted total .66
9 Faculty Index - Number ‘UBIS unadjusted undergraduate .59
10 " UBIS unadjusted total .60
ll " UBIS adjusted undergraduate .52
12 " UBIS adjusted total .54
13 Faculty Index - FTE UBIS unadjusted undergraduate .72
14 " UBIS unadjusted total .75
15 " UBIS adjusted undergraduate .71
16 " UBIS adjusted total .73
17 Graduate Asst. - Number UBIS adjusted graduate .60
18 Graduate Asst. - FTE UBIS unadjusted undergraduate .56
19 " UBIS unadjusted total .55
20 " UBIS adjusted undergraduate .57
21 " UBIS adjusted graduate .66
22 " UBIS adjusted total .59

 

 

90

measures defined in this study. The input variables for these analyses
were factor scores derived by using a principal-axes factor analysis
with a varimax rotation. The results of the classification, factor
analytic, and discriminatory techniques are discussed in this part of
Chapter V.

Classification Schema--Using the rankings of departments on all
undergraduate and graduate instructional service measures which are
displayed in Appendix C, Tables 26-27, 29-30, 32-33, and 35-36, depart-
ments with ranks of 1-27 were classified as low, 28—55 as medium, and
56-82 as high. Thus, each category represented approximately one-third
of the departments in the study. The stratification was based on ranking
because the numerous tied ranks and the skewness of the distributions
rendered the standard deviation approach inutile. In addition, approxi-
mately equal cell sizes were advantageous in the multiple discriminant
analyses conducted on each undergraduate and graduate instructional
service measure. The largest deviations from the one-third approxima-
tions occurred for the adjusted graduate university-based measure which
had cell frequencies of twenty—five for the low category and thirty for
the medium category. While each instructional service measure was
analyzed separately, the departments in each category are presented as
two-dimensional (undergraduate-graduate) arrays. The two arrays repre-
senting the unadjusted and adjusted departmentebased instructional
measures are displayed in Table 17, and the two arrays representing the
unadjusted and adjusted university-based instructional service measures

are displayed in Table 18. Each dimension of these four arrays was used

S11

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93

in the multiple disciminant analyses.

Factor Scores—-As previously explained, the factor scores which
were generated by a principal axes factor analysis with.a varimax
rotation were the input variables for the multiple discriminant analyses.
This factor analytic technique was performed on thirtyvfive descriptor
variables which represented various characteristics of the instructional
load and output of academic departments (i.e., teaching credits, student
credit hours (SCH), enrollment, degrees, and majors). Six orthogonal
factors (statistically independent, linear combinations of the original
variables) were created through the factor analytic techniques used in
this study. The variables which comprised these six factors and their
loadings are reported in Table 19. The loadings in Table 19 are the
correlation coefficients which indicate the extent to which each vari—
able is related to the hypothetical factor. The square of the loading
multiplied by one hundred equals the percent of a variable's variance
accounted for by the factor. Thus, strong correlations (high loadings)
were used to identify dominant variables in each factor. The percentages
of the total variance (the average squared loadings for each factor)
accounted for by each factor are reported in Table 20. These values
ranged from 24% for the first factor to 4% for Factor 6. The sum of
these average squared loadings (.82) multiplied by one hundred is the
percentage of variance of the original data explained by the factors.
Thus, these six factors accounted for 82% of the variance in the orige
inal data. Therefore, these six factors are a good representation of

the original data. The standard score alpha coefficients for each

94

Table 19. Factors and Their Loadings

 

 

Factor 1

Teaching Credits — Undergraduate Total
Teaching Credits - Undergraduate Recitation
SCH - Undergraduate

Enrollment - Undergraduate Lower Division
Teaching Credits — Total

SCH — Undergraduate Recitation

SCH - Total

Enrollment - Undergraduate Total

Enrollment - Total

QQNOM§WNH
O 0

011
m
0
('1’
O
H
N

SCH - Graduate Classes

SCH - Graduate Total
Enrollment - Graduate Total
Teaching Credits - Graduate
Enrollment - Master's Level
Majors - Master's Level
Degrees - Master's Level
Majors - Graduate Total

GNOM&U¢NH

Factor 3

l. Majors - Undergraduate Total

2. Majors - Undergraduate Upper Division

3. Degrees - Bachelor's

4. Majors - Undergraduate Lower Division

5. Majors - Total

6. Degrees - Total

7. Enrollment - Undergraduate Upper Division
8. SCH - Undergraduate Independent Study

9. Enrollment - Graduate-Professional

Factor 4

l. Enrollment - Doctoral Level

2. Majors - Doctoral Level

3. Degrees - Doctoral_Leve1

4. SCH - Graduate Independent Study

Factor 5
l. SCH - Undergraduate Laboratory
2. Teaching Credits - Undergraduate Laboratory

3. Teaching Credits - Undergraduate Lecture
4. SCH - Undergraduate Lecture

Factor 6
l;_ Enrollment - Sub College

v—v—

Lass-lies. ’

.91
.91
.91
.90
.90
.90
.89
.88
.88

Loading

.96
.91
.88
.83
.81
.68
.65
.64

Loading

.93
.92
.87
.86

.72
.56
.55
-.30

Loading

.81
.73
.70
.66

Loading

.92
.91
.78
.68

Loading

.54

Table 20.

95

Descriptive Data--Factors and Their Loadings

 

 

 

 

 

 

 

 

 

Number of Proportion of Coefficient
Factor Variables Variance
1 9 .24
2 8 .18
3 9 .17
4 4 .10
5 4 .09
6 1 .423
.82
INTER—FACTOR-CORRELATIONS
FACTOR 1 1.00
2 .37 1.00
_3__ .46 .52 1.00
4 .52 .66 .54 1.00
5 .38 .07 .23 .33 1.00
6 .40 .20 .21 .29 .06 1.00
1 2 3 4 5 6

 

 

 

 

 

 

96

factor are also displayed on Table 20. These alphas are the measure

of internal consistency of each factor.“

These extremely high alpha
values indicated that the factors are highly internally consistent and,
thus, are very reliable factors. Finally, the correlations among these
six factors are also reported in Table 20. These correlations ranged
from .66 for Factors 2 and 4 to .06 for Factors 5 and 6.

The interpretation of these factors was based on the dominant
variables in each factor. Variables with loading of at least .80 were
considered dominant variables for the purposes of this analysis.5 In
Factor 1, all the variables in this factor were dominant. This factor
basically represented instructional load characteristics associated with
undergraduate education in academic departments. Similarly, the domi-
nant variables in Factor 2 represented the instructional load character-
istics of graduate education in academic departments. However, the
other variables in Factor 2 had strong correlations (greater than .60)
and emphasized the master's level of graduate education. Undergraduate
instructional output characteristics (majors and degrees) were the domi-
nant variables in Factor 3. In addition, the variable representing
total degrees had a strong (.72) factor loading while undergraduate upper

division enrollment (.56) and undergraduate independent study student

credit hours (.55) had moderate loadings. Factor 3 was the only factor

 

I'J. C. Nunnally, Psychometric Theory (New York: McGraw-Hill Book
Company, 1967), pp. 196-98.

5This was an arbitrary decision based on the distributions of
factor loadings, and the definition by Marascuilo of a very strong cor-
relation referred to in footnote 3.

97

which had a variable with a negative loading (graduate—professional
enrollment, -.30). While the loading represented a weak correlation
between this variable and factor, this relationship indicated a tendency
for departments with high graduate-professional enrollments to have a
relatively small number of undergraduate majors and low undergraduate
degree output. This type of relationship is exemplified by depart—
ments associated with the health programs such as Human Development and
Psychiatry. Factor 4 has only one dominant variable, doctoral enroll-
ment, but the other three variables in the factor had strong factor
loadings. This factor was interpreted as representing graduate educa—
tion at the doctoral level. On the basis of its two dominant variables,
Factor 5 represented undergraduate laboratory instructional load. Yet,
variables representing undergraduate lecture instructional load were
also strongly related to this factor. Finally, Factor 6 represented
undergraduate instruction in sub-college courses. Though only one
variable was included in this factor, its loading is not unity because
of the orthogonality criteria of the varimax rotation.

The factor scores which were used as the variables in the multiple
discriminant analyses were calculated using the loadings as weighting
coefficients. The six scores for each department were computed using
the following equationss:

Fl - .91X1 + .91X + .9lX + .90X + .9OX + .90X + 89X

3 11 5 17 15 2 9

+ .88X19 + .88X24

 

6The subscripts for each variable in these equations are the number
assigned the variable prior to analysis.

98

'11
I

2 ‘ .96X6 + .91X8 + .88X23 + .83X14 + .81X21 + .68X28 + .65X33

F = .93X + .92X + .87X + .86X + .80X + .72X + .56Xl

3 27 26 32 25 31 35 8
+ .55S4 - .30X20
F4 3 .81X22 + .73X29 + .70X34 + .66X7
F5 = .92X3 + .9lX12 + .78X10 + .68Xl
F6 - .54X16

The scores for each department which were used in the multiple dis-
criminant analyses are present in Appendix C, Table 45.

Multiple Discriminant Analyses--As explained in Chapter IV, multi-
ple discriminant analysis is a regression-like technique for reducing
the six factor scores for each department to two orthogonal linear com-
binations of these variables which have the maximum potential for dis-
tinguishing among members of the three categories of instructional
service. Rao's chi-square test was used to test the hypothesis of no
significant difference between the groups on the discriminant functions.7

Standardized function weights were used to compare the discriminant func-

tions after the effects units of measurement had been largely removed.

 

7"Rather than testing the significance of each root separately,
the strategy is to test the total discrimination as a chi-square with
p(k—l) degrees of freedom. If significant, it is accepted that at least
one discriminant function is significant, and if any is significant, it
should be the one with the largest associate variance A1. Next the
first root A1 is subtracted from the total of all roots..., and the
residual is tested as a chi-square with p(k-l)-(p+k-2) degrees of free-
dom. If this test is significant, it is concluded that at least one
discriminant function in addition to the first is significant."
(J. E. Overall and C. J. Klett, Applied Multivariate Analysis (New York:
McGrawbHill Book Company, 1972), p. 289.)

99

As in the factor analytic results reported above, the weighting coef-
ficients of each variable in the discriminant functions represented
the extent to which each variable is related (contributed) to the dis-
criminant functions. The two standardized discriminant functions for
each undergraduate and graduate instructional service measure are

a on each of these discrimi-

displayed in Table 21, and the group means
nant functions are reported in Table 22.
For seven of the eight multiple discriminant analyses, only one
of the two discriminant functions was significant, and for the adjusted
graduate department-based instructional service measure, no discriminant
function was significant.9 In the analyses of the instructional service
categories for the unadjusted and adjusted undergraduate department-
based measures, the highest weighting coefficients in the significant
functions occurred for Factor 3 (undergraduate instructional output).
These factors had weighting coefficients of .84 and .77 respectively.
The configurations of the group means presented in Figures 1 and 210

indicated that for these two measures, group 3 (high) differed substan-

tially from the other two and occupied an extreme position in the

 

8Group means for each discriminant function are computed by apply-
ing the discriminant function weights to the group means on the original
data.

9The significance of the total function, not the significance of
individual weighting coefficients, was tested by chi-square. Thus,
significant and non-significant functions could both have significant
(dominant) weighting coefficients.

10The figures were constructed using the group means for the two
discriminant functions (yl and y2) which are reported in Table 22.

100

 

 

H~.I HN.I mN.I . m«.| mH. mm. mw.w .uHm Hoz
om.l no. «m.| wo.l nw.l MH. mH.Hm .on u<lmHmD
Nm.| «N.I oo.: mm.| HH. om. mm. .0Hm Hoz
om.l «H. Ho. mH. mH. «m. m«.mm .UHm D<ImHmD
oo. HN. 05.: «H. mH. «o. om.~ .uHm Hoz
N~.| Ho.l . NH.I mm. mm.l Hm. OH.nm .me UDImHmD
mo.| om.| . cm.| mm.| mH. mm. N«.m .on aoz
mH.I no. No.1 mo. mH. mm. mn.om .me DalmHmD
mo. Hm. em. a«. m~.I o~.| mm.om .uHm Hoz
mm.| «H. «m.| mo. Hn.| om. mn.mo .uHm Hoz o<lmHma
om.| mm. 05.: om.l mm. Ho. mH.«H .on .902
no. mH.I mH.I mm. mm.| mm.| «w.mw .uHm D<ImHmn
om.l wH. mw.| mc.l «m. mm. m~.HN .on 902
«0.: mm. NH.| m«. Nn.| N«. mm.mn .uHm UDImHmQ
wH.I mo. cm.l NH.I No.| mm.| No.~H .uHm Hoz
m~.| wH.I n~.| «m. mo.| Hm.l mm.mm .UHm DDImHmQ
o acuomm m “cuowm « Houowm m nouomm N nouumm H Houomm manna pl, x aw ounmmoz
ucwwmz coHuocsm uwNHvumccmum mo ucmuumm N oua>umm
Hmaofiu
lusuquH

 

 

macauocsm uamsHaHHumHn umuwvummamum

.HN wanna

101

Table 22. Group Means on Standardized Functions

 

 

 

Instructional Service Measure Group 1 Group 2 Group 3
DBIS-UU 173 80 -l47
-84 -245 —124
DBIS-UG 644 316 -382
10 -89 -10
DBIS-AU 521 236 -779
—37 -112 -61
DBIS-AG 10 ~113 -161
340 579 257
UBIS-UU 114 231 889
-22 -61 -38
UBIS-UG 17 -57 -423
148 54 116
UBIS-AU 89 198 710
-101 -137 -114
UBIS-AG -64 —148 -398
26 -92 ~12

 

3U

so,

102

16

EU

 

Figure 1. Group Means-~DBIS-UU and DBIS-UG.

ZG
0

3G

16

 

‘lU

 

y2

Figure 2. Group Means--DBIS-AU and DBIS-AG.

103

measurement domain. Three of the four discriminant analyses on gradu-
ate instructional service measures yielded one significant discriminant
function. For each of these discriminant functions representing the
unadjusted graduate department-based measures and the unadjusted and
adjusted graduate university-based measures, the most dominant variable
in the function was Factor 2 (graduate instructional load). The coef-
ficients for this factor were -.72 for unadjusted department-based,
—.92 for unadjusted university-based, and -.87 for adjusted university-
based. The information in Table 22 and in Figures 1, 3 and 4 suggested
that for these three measures, group 3 (high) differed substantially
from the other two and occupied an extreme position in the measurement
domain. Similarly, for the significant discriminant functions for the
unadjusted and adjusted undergraduate university-based instructional
service measures, one factor--Factor 1, undergraduate instructional load--
was the dominant factor with weighting coefficients of .97 and .94
respectively. Finally, the configurations of the group means presented
in Figures 3 and 4 depicted group 3 (high) as substantially different
from other two groups on both of these instructional service measures.
Summary-—These multiple discriminant analyses were conducted to
identify the descriptor variables which discriminated among the categor-
ies of each instructional service measures. Factor scores instead of
the original descriptor variables were used in the discriminant analyses
because of the interdependence among these original variables. The re-
sults of these discriminant analyses are summarized by three statements.

First, no factor used in these analyses discriminated significantly

104

10
3c; ,

113 0 3t?

 

Figure 3. Group Means--UBIS-UU and UBIS-UG.

30

O
|-'
CT

‘2U

 

Figure 4. Group Means--UBIS-AU and UBIS-AG.

105

among the three categories of the adjusted graduate department-based
instructional service measures. Second, three factors emerged which
discriminated among the categories of the instructional service
measures. Factor 1 (undergraduate instructional load) was the dominant
variable in the analyses of the unadjusted and adjusted undergraduate
university—based measures. Factor 2 (graduate instructional load) was
the dominant variable for the unadjusted graduate department-based
measure and the unadjusted and adjusted graduate university-based
measures. Factor 3 (undergraduate instructional output) was the domi-
nant variable for the unadjusted and adjusted undergraduate deparmment-
based instructional service measures. Finally, in all the analyses,
group 3 (high) substantially differed from the other two groups and

occupied an extreme position in the measurement domain.

Summary

The results of the numerous analyses conducted in this study were
presented and summarized in this chapter. Two hundred fifty-two
Spearman rank correlations were studied along with the results of eight
chi-square tests of independence. In addition, the results of the
preparatory analyses (classification and factor analysis) and the eight
multiple discriminant analyses were also reported. The implications of
these results and the conclusions drawn from them are discussed in

Chapter VI.

Chapter VI

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
FOR FURTHER STUDY

Overview of the Study

One of the more pressing problems facing institutions of
higher education today is the development of effective and effici-
ent methods of resource allocation within each institution. While
many states have developed techniques of formula or program
budgeting for appropriating funds to institutions, once insti-
tutions have these funds in their possession, they tend to divide
these funds among operating units in traditional ways. This allo-
cation procedure often takes the form of uniform percentages changes
across these units which reinforce the relative position of units
and indirectly establishes institutional priorities. _Thus, a more
dynamic resource allocation system is needed which can respond to
changes in societal goals and public needs and to alterations in
assigned or implied institutional responsibilities while satisfying
the demands for accountability. This study of the instructional
service component of academic departments is only part of a
broader study funded by a grant from the Exxon Education Foundation
and centered at the Office of Institutional Research at Michigan
State University under the direction of Dr. Paul L. Dressel. One

of the foci of this third phase of the Exxon Departmental Study

106

107

Project is the develOpment of a model of the dynamic budgeting
schema alluded to in Chapter I which accounts for the inherent
differences in disciplines, the concomitant instructional method-
ologies which affect input and output properties of departments,
and the operational differences imposed by the role of each
department in the university community.

Since the present study is a portion of this larger project,
a brief discussion of the current Departmental Study Project is
necessary to bring this study into proper perspective. The dynamic
budgeting schema which is the goal of the current Departmental
Study Project will be based on a series of departmental clusters.
These clusters represent groups of departments with similar
intrinsic characteristics and similar institutional roles. This
clustering strategy was predicated on the assumption that budgetary
procedures for departments with similar characteristics and
missions should utilize the same funding principles and variables.
When this strategy is applied, each department is compared only
with other departments in its cluster and not with every depart-
ment in the university. This approach permits variability among
departmental clusters while stressing the development of uniform
funding criteria within clusters.

"Process" variables are associated with the disciplines that
make up a department and describe the intrinsic characteristic of

a discipline and its instructional modes. These variables reflect

108

questions such as:
1. What is unique about the discipline?

2. Are certain modes of instruction required by the
discipline?

3. Is there a minimum number of specializations that
must be represented to have a “legitimate" univer—
sity department?

4. Are the skills that are acquired by students of a
discipline predictive of success and in that disci-
pline reflective of the internal processes of a
department?

The identification of "process" variables is an effort to par-
tition out the institutional effects on departments. For example,
when studying departmental data, one cannot account for a chair-
man's political activities in acquiring funds or for the histor-
ically determined status of a department. Add-on budgeting methods
only further complicate an analysis. Institutional politics

and idiosyncracies cannot be ignored, but a department-oriented
budgeting schema should also include elements that transcend
institutional bounds. "Process" variables have been used in this
model to represent these supra-institutional dimensions.

The identification of fundamental "process" variables is
hindered by the inadequacy of curricular theory and pedagogy in
higher education. The common elements of curricular and peda-
gogical theory across institutions or disciplines are not adequately
addressed in the literature. However, two dimensions have been

identified in this project through theoretical analysis which do

reflect intrinsic characteristics of a discipline. These are

109

laboratory modes and gpecializations. In addition to reflecting

 

the intrinsic characteristics of a discipline, these variables
also have budgetary and planning implications. Laboratory modes
refers to those disciplines whose operations involve non-classroom
experience as well as those whose operations require specially
equipped work spaces. It should be noted that curricular innova-
tions may alter the assignment of departments along this dimension,
but such reassignment of a discipline would not invalidate the
model. The second dimension, specializations, refers to the
number of faculty members necessary to staff a department. A
university department cannot usually include a member to represent
each possible specialization within a discipline. For example,
the National Register of Scientific and Technical Personnel lists
over 150 specialities for physics alone and nearly 1000 distinct
specializations in natural sciences. The issue can be stated:
regardless of student enrollment, how’many specializations must
be represented in order to have a"legitimate" university depart-
ment. When a department includes all possible specializations,
enrollments would determine the number of faculty needed in each
specialization. In the absence of criteria for selecting the
number of specializations to be included, the size of the depart-
mental faculty would be determined by enrollment, by the desired
educational thrust of the department, and by a department's role
within the university.

"Role" variables reflect those characteristics that can be

110

ascribed to a department by the institution or by a state-wide
system. These variables might fluctuate with changing student
body interests or with the whims of the department chairmen.
However, they can also be key decision points for administrators
with the consequences of these decisions having many budgetary
and educational ramifications. The inclusion of these variables
in a model does not presuppose a given decision-making process.
Decisions about these variables may be made by an individual or
by a committee at several levels of review. The model does,
however, make these variables overt and points out the consequences
of changes in these variables. Dimensions considered for the
model include the following:

1. service (major y§_nonmajor)

2. undergraduate yg_graduate enrollment

3. size

4. quality (prestige)

5. public service

6. research

7. societal needs
Each dimension will be explored in depth and correlated with
other available information about departments. Then the dimensions
will be multivariately combined and their effects on cost and
faculty time and rank distribution will be determined.

Finally, "cost” variables need to be identified which include

both direct and indirect costs that stem from "process" or "role"

lll

designations. For example, a laboratory department would have
equipment costs, repair costs, and replacement costs, as well
as salary dollars for technical personnel (glassblowers, elec-
tronic personnel and store room managers). These expenses must
be accounted for in departmental budgets. The cost variables
translate the department typology into a budgeting schema.

In this study, the instructional service component of
academic departments was examined in light of the other available
data about the characteristics of academic departments. The
selection of this aspect of departmental Operations as a focus
of study was predicated on the possibility of its inclusion as
a dimension of the clustering framework. The concept of instruc-
tional service has received attention at Michigan State University;
in the organization of this university, the three medical colleges
(veterinarian, osteopathic, and allopathic) subsidize certain
departments for the service instruction that these shared depart-
ments give to the medical students enrolled in departmental courses.
With the need for more accountability, the university has begun to
study more closely the parameters of these exchanges of financial
support and instructional service. No solution to this problem of
rates of exchange has yet been found. At-present, department chair-
men bargain directly with each dean for the funds each department
receives.

This type of exchange could extend to all service instruction

within the institution. Each department could receive part of its

112

funding from the service instruction it provides to various
colleges, at different rates of exchange. In lieu of a formalized
pricing system for service instruction, this study identified the
amount of service instruction in each academic department and
sought to determine how the extent of instructional service was
reflected in other data about the department (i.e., level of
funding and staffing patterns).

Purposes--This study was exploratory in nature and was designed
to identify the relationships between measures of instructional ser-
vice and the other available data about academic departments. Specifi-
cally, the purposes of this study were to 1) develop appropriate
measures of the instructional service component of academic.depart-
ments; 2) identify relationships among these measures and between
these instructional service measures and other departmental charac-
teristics, and 3) classify departments according to each under-
graduate and graduate instructional service measure and determine
which variables discriminate among the categories of the instruc-
tional service measures.

Instructional Service Measures--Two sets of instructional service
measures were constructed to represent the instructional service
component of academic departments. The department-based instructional
service measures represented the relative amount of the total instruc-
tional load of each department directed to service students (non-majors)
while the university-based instructional service measures reflected

the relative amount of the total instructional service load of the

113

institution (instruction to non-majors) which was assumed by each
department. Within each of these two sets of measures, six measures
representing various aggregates of courses within the departments
were also constructed. The unadjusted measures (undergraduate,
graduate, and total) represented instructional service in all courses
in each of these categories. On the other hand, the three adjusted
measures (undergraduate, graduate and total) did not include sub-
program and short courses (undergraduate and total) and graduate-
professional courses (graduate and total). The difference between
the corresponding unadjusted and adjusted instructional service
measures reflected the effects of these predominantly non-major
types of instruction on the level of instructional service in
academic departments.

Research Designf-The research design developed for this study

 

centered around ten questions about the relationships among the twelve
instructional service measures and between each of these measures

and departmental descriptor variables. A variety of statistical tech-
niques was used to assess these relationships. Among these were
Spearman rank correlations, chi-square tests for independence, prin-
cipal axes factor analysis, and multiple discriminant analyses. In
this study, two hundred fifty-two Spearman rank correlations and.
eight chi-square tests for independence were used to analyze the
relationships among the twelve instructional service measures and
between each of these measures and variables representing funding,

faculty rank distributions, average salary, number of graduate

114

assistants, prestige of graduate programs/faculty, and level of
students served in undergraduate courses. In addition, the multiple
discriminant analyses identified factors (generated from the prin-
cipal axes factor analysis) which discriminated among the levels

of eight of the instructional service measures. The findings of

this study based on the results of the analyses of the twelve instruc-
tional service measures and the eighty-six descriptor variables

which were reported in Chapter V and the implications of these

results are.discussed in the following passages.

 

Summary of Findingg

The following statements summarize the major findings of this
study of the instructional service component of academic departments
at Michigan State University. A discussion of the implications of
these findings is presented in the next section of this chapter.

1. When all course offerings of departments were considered,
every department provided instruction to service students
(non-majors) during Fall 1971.

2. Generally, for departments that offered both undergraduate
and graduate courses, the level of the instructional ser-
vice in undergraduate courses as measured by the department-
based measures was greater than the level of instructional

service in graduate courses.

3. The undergraduate and graduate instructional service measures
were mutually independent.

4. The department—based and university-based instructional ser-
vice measures are not mutually independent.

5. The unadjusted and adjusted instructional service measures
are not mutually independent.

10.

ll.

12.

l3.

14.

115

Departments that serve predominantly lower division under-
graduate students tended to have relatively high under-
graduate university-based instructional service measures.

Departments with prestigious graduate programs/faculty

as indicated in the ACE reports tended to have medium
graduate department-based instructional service measures
and medium to high graduate university-based instructional
service measures.

0f the one hundred eighty Spearman rank correlations be-
tween the instructional service measures and the descrip-
tor variables representing funding, faculty rank distribu-
tions, number of graduate assistants, and average salary,
sixty-four (35.6%) were statistically significant, but
only twenty-two of these correlations (12.2%) were strong
(greater than .50) and, therefore, meaningful.

No department—based instructional service measure was
strongly related to any of the descriptor variables
representing funding, faculty rank distributions, average
salary, and number of graduate assistants.

No variable representing research grant and contract expen-
ditures was strongly related to any of the instructional
service measures.

The undergraduate and total university-based instructional
service measures were strongly related to the following
variables: 1) general fund total, 2) general fund salary,
3) faculty index based on headcount, 4) faculty index
based on FTE's, and 5) number of graduate assistants

based on headcount.

The adjusted graduate university-based instructional ser-
vice measure was strongly related to the descriptor vari-
ables representing the number of graduate assistants based
on FTE's.

Six factors were defined within the descriptor variables
through the principal axes factor analysis with a varimax
rotation. These factors were good representations of the
original data (explained 82% of the variance) and were
highly internally consistent (alphas greater than .90).

For each of the eight multiple discriminant analyses, two
discriminant functions (groups-l) were computed. These
linear combinations of variables were orthogonal and have

116

potential for discriminating among the groups of each in-
structional service measure. For the adjusted graduate
department-based instructional service measure, neither
one of the discriminant functions were significant. In
addition, the interpretation of the results of these
analyses was greatly enhanced because in the remaining
seven analyses, only the first discriminant function

was significant. Thus, the categories of each of these
instructional service measures differed significantly in
multivariate mean profiles, and the contribution of each
factor to this overall difference is expressed by the
weighting coefficients of the first discriminant function.

15. Three factors emerged which were dominant in these sig-
nificant discriminant functions. In addition, the emergence
of a single dominant factor in each discriminant function
greatly aided the interpretation of the results of the
multiple discriminant analyses. Factor 1 (undergraduate
instructional load) was the dominant variable in the sig-
nificant discriminant functions for the unadjusted and
adjusted university-based instructional service measures.
Factor 2 (graduate instructional load) was the dominant
variable for the unadjusted graduate department-based
instructional service measure and the unadjusted and
adjusted graduate university-based instructional service
measure. Similarly, Factor 3 (undergraduate instructional
output) was the dominant variable for the unadjusted and
adjusted undergraduate department-based instructional
service measures.

l6.- In all the significant multiple discriminant analyses,
group 3 (high) substantially differed from the other
two groups and occupied an extreme position in the
measurement domain.

Conclusions

 

Since this study is part of the more extensive Departmental
Study Project, the conclusions and implications of these findings
extend beyond the scope and purposes of this study. In the following
paragraphs the more statistically-based conclusions which flow

directly from the findings of this study are first discussed, and

117

then the more general implications of these findings for the clus-
tering and budgeting schema being developed in the Departmental
Study Project and for similar studies of academic departments are
discussed.

One of the purposes of this study was the development of
appropriate measures of the instructional service component of
academic departments. The summary measures used in this study
represented possible course aggregates upon which instructional
service could be described. Since no g_priori criteria existed
for choosing among these measures, all twelve measures were included
in the study and the relationships among these twelve measures were
examined. However, the inclusion of all twelve instructional ser-
vice measures as part of one dimension of the departmental clustering
schema may be a meaningful representation of this dimension, but a
linear combination of these variables would be very difficult to
interpret (low utility) and may not be the most parsimonious way of
expressing this dimension. Parsimony and utility along with meaning-
fulness and efficiency are important criteria for any model and for
the selection of variables which are included in the model. Through
the study of the relationships among the instructional service measures,
overlap and redundancy within the measures can be identified and a
subset of these measures chosen to represent the dimension of instruc-
tional service in the cluster-oriented budgeting model.

The findings of this study reported in the preceding section

indicated that overlap among the measures did exist. However, the

118

mutual independence between the undergraduate and graduate instruc-
tional service measures indicated that measures representing aggre-
gates of both these course bases should be included in any further
analysis of instructional service in academic departments. On the
other hand, since both of these measures were strongly related to
the total measure for the department, the use of the total measure
in conjunction with both the undergraduate and graduate measure

is unnecessary for an adequate representation of the instructional
service component of academic departments.

However, decisions about the selection between unadjusted and
adjusted measures and the selection between department-based and
university-based measures involved certain pragmatic considerations
and a pgg£_hgg analysis and were not directly discernible from the
data. With the exception of the relationship between the unad-
justed total measures for the department-based and the universitye
based measures (significant but weak), the relationships between
the corresponding department-based and university-based measures were
strong and significant. Thus, the use of both measures of each of
these pairs would result in redundancy within the instructional ser-
vice dimension of the clustering schema. However, the analyses
provided no indication of which measure of each set should be chosen.
Since the unadjusted measures represented instructional service in
all courses in each department and, thus, are a better representation
of the workload within each department, the unadjusted measures

rather than the adjusted measures will be used in any further analysis

119

of instructional service. The effect of sub-program and graduate-
professional courses on the instructional service load of each
department can be expressed through an internal pricing system in
which different types of instruction have different rates of exchange.
The selection of the department-based measures over the
university-based measures was.aided by a pg§£_hgg examination of the
relationships between these measures and the enrollments in each
department. This analysis indicated that the relationships between
the unadjusted department-based measures and the corresponding
enrollments were .43, .31, and .13 for the undergraduate, graduate
and total measures respectively. For the university-based measures
these relationships were .94, .83, and .93 for the undergraduate,
graduate, and total respectively. Thus, the university-based
instructional service measures were much more a function of the
size of the department than were the department-based measures.
For example, Agricultural Economics and American Thought and Lan-
guage have the same.unadjusted undergraduate department-based instruc-
tional service measure--100.0-dwhile the enrollment for each is 179
and 6971 respectively. Therefore, the department-based measures
were chosen because they_best reflect the role of instructional ser-
vice in departmental operations and these measures are less sensi-
tive to departmental size. In summary, the set of twelve instruc—
tional service measures was reduced to two mmasures--unadjusted
undergraduate and graduate department-based--which will represent

instructional service in further analyses.

120

A second facet of the results of this study is that no
department-based instructional service measure was strongly related
to any of the descriptor variables representing funding, faculty,
rank distributions, number of graduate assistants, or average salary.
Thus, the staffing and funding of the departments do not appear to
be meaningfully related to the "role" of instructional service in
these departments. These findings also indicate that the size-related
university-based measures (undergraduate and total) were strongly
related to these descriptor variables. Thus, instructional volume
rather than the parameters of the instructional processes appears
to be the primary determinant of departmental funding and staffing.
This point is further evidenced by the finding that_the faculty
index based on the percentage distribution over ranks (which
standardizes the size of the faculty in each department) was not
related to any of the university-based instructional service measures.

Finally, the results of the multiple discriminant analyses of
the undergraduate and graduate instructional service measures suggest
that relationships existed between these measures of instructional
service and the six factors derived from the descriptor variables.
These multiple discriminant analyses were important because they
clarify the role of instructional service in academic departments by
identifying linear combinations of variables which reflect differences‘
along the instructional service dimension. However, even though the
results of these analyses were unusually decisive (only one signifi-

cant discriminant function which was dominated by one of the factors),

121

the use of factors instead of variables greatly complicated the
interpretation of these results. In this study the most appro-
priate statistical techniques did not yield the most interpretable
and meaningful results. Further research which clarifies the inter-
actions of variables within these dominant factors is needed before

a clear understanding of the relationships between the level of
instructional service and variables representing instructional load
(enrollment, student credit hours, and teaching credits) and instruc-
tional output (degrees and majors) emerges. However, such further
research must also be related to the realities of departmental organi-
zation and the budgetary process. Procedures which deviate too far
from practical and traditional patterns of organization and budgeting
are unlikely to seriously affect existing patterns of university
operations.

At this point, the discussion focuses on the more general impli-
cations of these results for the Departmental Study Project and for
other research on academic departments. These implications center on
two basic issues--a "costing" or "pricing" schema and staffing stan-
dards. In Chapter II there was presented an economic framework for
instructional service in which the instructional service provided by
academic departments was "traded" to other academic units at a yet to
be determined rate of exchange. Two basic questions associated with
this “pricing" schema are: (1) At what level of course offering should
these prices be set? and (2) Should these prices reflect marginal or

average costs?

122

In relation to the first question, the analyses in this study
compared measures based on different quantities across the same aggre-
gate level of instruction. These analyses produced two measures
(unadjusted undergraduate and graduate department-based) which could
be used in future analyses to represent the "role" of instructional
service in academic departments. While these two measures seem to
represent the best measurement base, they do not necessarily repree
sent the best costing base. Indeed, a further differentiation of
undergraduate and graduate unadjusted department-based measures into
their components (subprogram, lower level, upper level, graduate-
professional, master‘s, and doctoral) may offer a more viable frame-
work for a "pricing" schema. A "pricing" schema based on course
aggregates within these six broader levels of instruction rather than
on individual courses may result in a more easily managed system of
exchange. Further research using the unadjusted department-oriented
measurement base identified through this study with different levels
of aggregation must be conducted to identify the most appropriate
level of specification for a pricing system.

For the second coat question-whether to use marginal or average
costs in the "pricing" schema-—consideration of the level of instruc-
tional service provides some insight. Assuming similar instructional
modes in several departments, a department with a low instructional
service “role" will have its instructional load primarily generated
by majors. In such a case, the relatively low preportion of service

students taught by the department might best be reflected by a mar-

123

ginal cost (increment of one student to a base coat). On the other
hand, if a department's instructional service "role" is relatively
high, an average cost (total cost/number of students) might.be the
most appropriate foundation for a “pricing" schema. Again, this
concept needs to be explored through a study which compares the two
costing principle in selected departments which have relatively low
or relatively high instructional service "roles." In addition, the
impact of the instructional mode on the cost of adding a student to
a particular course needs to be examined. It may be that equipment
and space restrictions of laboratory versus non-laboratory courses
are greater determinants in the choice of an apprOpriate cost base
than the level of instructional service.

Finally, the implications of the role of instructional service
for the staffing pattern of academic departments should be explored.
The department-based measures reflected the relative amount of a
department's total instructional load related to service (non-major)
students. Thus, these measures of instructional service indicate
the thrust of the educational process in each department. One of
the basic questions in an accountability model is whether or not a
department staffing pattern is congruent with its objectives and
"roles." This question is especially important since a large propor-
tion of the budget of each department is salary money. In a rigorous
accountability model the requirement that the number of faculty mem-
here be commensurate with the enrollment of the department could be

coupled with the requirement that these faculty members be assigned

124

to tasks which are congruent with the instructional load and missions
of the department. For example, if a department is a low service,
graduate-oriented department, this department could possible justify

a faculty rank distribution which was skewed toward the ranks of
associate and full professors and a workload model which included

low teaching load and a high research commitment. However, this same
staffing and workload pattern might be very hard to justify for a

high service, undergraduate—oriented department. Since the results

of this study indicated that the funding and staffing of academic
departments were not related to the instructional service "role,"
present departmental data can not be used to identify staffing
patterns which are congruent with the "role" of the department. In
the continuing work of the Departmental Study Project, this problem

of staffing and workload will be approached through a more theoretical
orientation. Appropriate staffing and workload patterns must be
hypothesized for each configuration of departmental "roles," and

the effects of these patterns of departmental funding closely analyzed.
If these postulated patterns prove workable, these patterns can be
used as targets for future departmental staffing.

One final point should be made about the available institutional
data on academic departments. The results of the study suggested that
most of the data collected about academic departments is size-related.
While the concept of volume of instruction has some merit when the mag-
nitude of the departmental efforts is discussed, size should not be

the sole criterion for funding or staffing departments. The core-

125

service dichotomy (reflecting the distinction between instruction of
majors and nondmajors) utilized in this study may provide a vehicle

for partially overcoming this problem. If the core department is
considered first as the basic unit necessary to maintain the integrity
of the departments in the eyes of the discipline and the academic com-
munity, then the resource requirements necessary for the first n majors
could be identified. The addition of more majors to this basic depart-
ment would result in further resource requirements. The service dimen-
sion could then be treated as instructional overhead which requires
certain resource requirements which are reflected through the "pricing"
schema. The main point in this discussion is that in any funding and
staffing model the basic integrity of the department must be maintained,
thus fostering departmental contributions to the discilpine and society.
The core-service framework helps protect this departmental integrity by
highlighting the needs of the core department, especially in high in-

structional service departments.

Recommendations for Further Study)

 

The results of this study indicated that instructional service is
a viable dimension for a departmental clustering and budgeting schema.
In addition, this dimension can be represented by two measures of
instructional service: the unadjusted undergraduate and graduate
department-based instructional service measures. Four areas of study
need to be further explored in order to make the concept of instruction-

al service usable in a department-oriented management schema.

126

First, the concept of instructional service needs to be expanded
to include the other aspects of service which are provided by depart-
ments (i.e., academic advising to nondmajors, graduate committee work,
and committee assignment in other units). The basic science departments
"shared" by the medical colleges provide an excellent arena for this
study for two reasons. Presently, these units are involved in a facule
ty activity analysis which can provide information about the time expen-
ditures of faculty in various research and instructional activities.
This form could be modified to include a division between time spent
with majors and time spent with non-majors. Further, members of these
"shared“ departments have formalized responsibilities for committee
and instructional.responsibility within the medical schools. Thus,
the "shared" department~medica1 program interactions provide a good
microcosm for the study of non-instructional service aspects.

The second area of needed research is the assignment of "prices"
to the services provided by academic departments. Here again, the
present fiduciary arrangements between the "shared" departments and the
medical colleges provide an appropriate subject for study. Techniques
of cost accounting coupled with the information from the faculty activity
analysis can be used to define the parameters of these exchanges.

"prices" derived from these tech-

Hypothetical exchanges based on the
niques can then be compared to the amount of existing financial subsidy
to gain further insight into the pricing problem.

A third area of needed research implied in this study is the

identification of other possible dimensions of departmental activity

127

which can be used in the departmental clustering and budgeting schema
which is the primary thrust of the current Exxon Departmental Study
Project. However, this study has identified a methodology by which

each of these proposed dimensions can be studied and has pointed to

the need for better understanding of the relationships among the
variables within each factor prior to such an analysis. Techniques such
as multi-dimensional scaling or hierarchical clustering need to be
explored as alternatives to the principal axes factor analysis used

in this study.

Finally, the effect of size on the costs and instructional processes
within the departments must be understood before a sound budgetary scheme
can be developed which considers the intrinsic characteristics of the
departments as well as its volume. This understanding of size is also
important in developing sound staffing standards for academic depart-

ment 8 e

APPENDICES

APPENDIX A

DEPARTMENTS IN STUDY

128

129

APPENDIX A

DEPARTMENTS IN STUDY

 

 

Department College Affiliation
Agricultural Economics Agriculture 8 Nat. Res.
Agricultural Engineering "

Animal Husbandry "

Crop 8 Soil Science "

Dairy "

Fisheries & Wildlife "
Food Science 8 Human Nutrition
Forestry

Horticulture

Packaging . "
Park 8 Recreation Resources
Poultry Science

Resource Development "

Art Arts and Letters
English "
German and Russian "
History "
Linguistics-Orienta1 8 African Langauges "
Music "
Philosophy "
Religion ' "
Romance Languages "
Accounting 8 Financial Administration Business
Business Law and Office Administration "
Economics "
Hotel, Restaurant, 8 Inst. Management "
Management "
Marketing 8 Transportation Administration "
Advertising Communication Arts
Audiology 8 Speech Science "
Communication "
Journalism, School of "

TV 8 Radio ".
Theatre "
Chemical Engineering Engineering

Civil 8 Sanitary Engineering

Computer Science

Electrical Engineering 8 Systems Science
Mechanical Engineering "
Metallurgy, Mechanics, 8'Materials Sci. "
Family Ecology Human Ecology
Family and Child Science "

Human Nutrition 8 Foods "

Human Environment 8 Design "

Human Deve10pment Human Medicine
Medicine "
Psychiatry

continued

130

APPENDIX A-—Continued

 

Department

Astronomy
Biochemistry

BiOphysics

Botany 8 Plant Pathology
Chemistry

Entomology

Geology

Mathematics

Nursing

Physics

Statistics

Zoology

Anthronology

Criminal Justice

Geography

Labor 8 Industrial Relations
Political Science
Psychology

Social Work
Sociology

Urban Planning 8 Landscape Architecture
American Thought 8 Language

Humanities

Natural Science

Social‘Science

Anatomy

Large Animal Surgery 8 Medicine
Medical Technology

Microbiology 8 Public Health

Pathology

Pharmacology

Physiology

Small Animal Surgery 8 Medicine

Family 8 Community Medicine
Medicine

CollegEAffiliation

Natural Science
Natural'Scieuce
Human‘Medicine
Natural Science
Human Medicine

Natural Science
ll

Natural Science
Human Medicine

Social Science
H

Social Science
Human Medicine
Social Science
Social Science
Human Medicine
Social Science
University College
1!

Veterinary Medicine
Human Medicine
Veterinary Medicine
Veterinary Medicine
lumen Medicine
Veterinary Medicine
Human Medicine
Natural Science
Veterinary Medicine
Human Medicine
Veterinary Medicine
Human Medicine
Veterinary Medicine
Human Medicine
Veterinary‘Medicine

OsteOpathic Medicine
OsteOpathic Medicine

APPENDIX B

LIST OF MSU DEPARTMENT DESCRIPTOR VARIABLES

131

132

APPENDIX B

LIST OF MSU DEPARTMENT DESCRIPTOR.VARIABLES
GeneralfiFund Expenditures

1. Total, 1971—72

2. Salary, 1971-72

3. Labor, 1971-72

4. Supplies 8 Services, 1971-72
5. Equipment, 1971-72

Research Grant 8 Contract Expenditures

 

6. Salary, 1971-72

7. Equipment, 1971-72
8. Other, 1971-72

9. Total

Student Credit Hours

 

10. Undergraduate Lecture, Fall 1971

11. Undergraduate Recitation, Fall 1971

12. Undergraduate Laboratory, Fall 1971

13. Undergraduate Independent Study-Variable Credit, Fall 1971
14. Undergraduate Total, Fall 1971

15. Percent, Undergraduate Laboratory SCH

16. Graduate Classes, Fall 1971

17. Graduate Independent Study-Variable Credit, Fall 1971

18. Total Graduate SCH, Fall 1971

19. Total SCH, Fall 1971

Teaching Credits

 

20. Undergraduate Lecture, Fall 1971

21. Undergraduate Recitation, Fall 1971

22. Undergraduate Laboratory, Fall 1971

23. Undergraduate Total, Fall 1971

24. Percent, undergraduate Lab/Undergraduate Total, Fall 1971
25. Graduate, Fall 1971

26. Total, Fall 1971

Total Head Count

 

27. Full-time Faculty, Fall 1971

28. Part-time Faculty, Fall 1971

29. Graduate Assistants, Fall 1971

30. Total, Fall 1971

31. Total, Full and Part-time Faculty, Fall 1971

FTE
32. Full-time Faculty, Fall 1971

33. Part-time Faculty, Fall 1971 continued

133

APPENDIX B--Continued

FTE Cont'd.

 

34. Graduate Assistants, Fall 1971
35. Total, Fall 1971
36. Total Full and Part-time Faculty, Fall 1971

FTE - General Fund

 

37. A-Faculty, 1971-72
38. B-Faculty, 1971-72

Faculty Headcount - Bngagg

 

39. Professors, 1971-72

40. Associate Professors, 1971-72
41. Assistant Professors, 1971-72
42. Instructors, 1971-72

43. Other, 1971-72

44. Total, 1971-72

1m: - By Rank

 

45. Professor, 1971-72

46. Associate Professor, 1971-72
47. Assistant Professor, 1971-72
48. Instructor, 1971-72

49. Total, 1971-72

Faculty Rank Percentages

 

50. Percent Professors, 1971-72

51. Percent Associate Professors, 1971-72
52. Percent Assistant Professors, 1971—72
53. Percent Instructors, 1971-72

54. Percent Other, 1971-72

Course Enrollments

 

SS. Sub-College, Fall 1971

56. Lower Division, Fall 1971

57. Upper Division, Fall 1971

58. Undergraduate (Lower 8 Upper), Fall 1971
59. Graduate-Professional, Fall 1971

60. Masters, Fall 1971

61. Doctors, Fall 1971

62. Graduate Total, Fall 1971

63. Total, Fall 1971 continued

134

APPENDIX B--Continued

Majors

64. Lower Division, Fall 1971
65. Upper Division, Fall 1971
66. Undergraduate Total

67. Masters, Fall 1971

68. Doctoral, Fall 1971

69. Graduate Total

70. Departmental Total

Degrees

71. No. of Bachelor Degrees, 1971
72. No. of Masters Degrees, 1971
73. No. of Doctor Degrees, 1971
74. Total, 1971

Average Salary

75.
76.
77.
78.
79.
80.

Professor, 1971-72

Associate Professor, 1971-72
Assistant Professor, 1971-72
Instructor, 1971-72

Ten Month Salary — All Ranks
Twelve Month Salary - All Ranks

Quality Measures

81.
82.
83.
84.
85.
86.

Cartter Report, Quality of Faculty
Cartter Report, Quality of Program
Roose-Andersen Report, Quality of Faculty
Roose-Andersen Report, Quality of Program
Composite of Cartter Report

Composite of Roose-Andersen Report

APPENDIX C

TABLES OF DATA USED IN THIS STUDY .

135

Table 23.

List of Departments with Disparate Unadjusted and

Adjusted Department-Based Instructional Service

Measures

Departments with

Sub

l.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
l6.
17.
18.
19.
20.
21.
22.
23.

Program and Short Courses

Agricultural Economics
Agricultural Engineering
Animal Husbandry

Crop and Soil Science
Dairy

Food Sci. and Human Nutr.
Forestry

Horticulture

Poultry Science

Resource Development
English

Accounting and Finance
Business Law and Office Ad.
'Marketing and Transportation
Advertising

Audiology and Speech Sci.
Biochemistry

Botany and Plant Path.
Entomology

‘Mathematics

Urban Planning and Land. Arch.

ATL
Microbiology*

Departments with Graduate-
Professional Courses

\DmVO‘UlJ-‘UJNH
O

h‘h‘
1a<3
O O

12.

Human Development
Psychiatry

Medicine (HM)
Anatomy

Large Animal Surgery
Microbiology*
Pathology
Pharmacology
Physiology

Small Animal Surgery
Pam. and Comm. Med.
Medicine (OM)

 

1L37

Table 24. Departmental Rankings on Department-based Instructional Service Measures

hin¥

4-

 

 

 

__ U N A D J U S T E D A D J U S T E D
Department Undegggaduate Graduate Total Undergraduate Graduate Total
Ag. Economics T79.0 15 32 T 5.5 22 8
Ag. Engineering T69.5 64 62 45 74 40
Animal Husbandry T50.5 19 50 48 _ 26 54
Crap 8 Soil Sci. 68 50 65 61 6O 58
Dairy 64 12 58 67 ‘ 19 67
Fisheries 8 Wildlife 33 16 24 34 23 32
Food Sci. 8 Hum. Nutr. 34 T37.5 26 35 T45.5 34
Forestry 27 57 22 ' 25 67 T27.5
Horticulture 48 30 T43.5 37 37 37
Packaging l6 T27.5 7 l7 T34.5 15
Park 8 Rec. Resources 28 61 23 30 71 31
Poultry Science 29 T 4.5 14 19 T 8.0 11
Resource Development 49 55 33 51 65 41
Art ‘ 25 14 20 28 21 29
English 42 43 37 T39.5 52 44
German 8 Russian 53 13 49 T55.5 20 59
History 54 33 T51.5 57 40 62
Linguistics 58 39 T43r5 62 48 53
Music 22 9 T16.5 24 16 T24.5
PhilosOphy 65 54 67 69 64 74
Religion 73 T79.0 70 74 T81.5 77
Romance Languages 44 17 46 49 24 56
Acct. 8 Finance Adm. 35 65 29 36 75 39
Bus. Law 8 Office Adm. 4O T79.0 39 T39.5 T81.5 49
Economics 55 69 55 58 77 65
Hotel, Rest. 8 Inst.Mgt. l4 T23.5 S 15 T30.5 13
Management 57 70 53 60 78 63
Marketing 8 Transp. Adm. T50.5 6O 38 - 53 70 50
Advertising 32 68 27 '33 76 36
Audiology 8 Speech Sci. 30 10 21 31 17 30
Communications 38 62 34 42 72 46
Journalism 23 42 18 26 51 26
TV 8 Radio . 20 20 12 22 27 21
Theatre 26 ll 19 29 _18 T27.5
Chemical Engineering 11 34 2 12 41 9
Civil 8 Sanitary Eng. 21 22 13 23 29 22
Computer Science 41 36 - 36 44 44 48
Electrical Engineering 12 51 4 13 61, 12
Mechanical Engineering 13 29 3 14 36 10
Metal, Mach, 8 Mat.Sci. 60 52 54 64 62 64
Family Ecology 31 58 25 32 68 33
Family 8 Child Sci. 36 46 31 38 56 45
Human Nutr. 8 Foods 39' 35 35 43 43 47
Human Envir. 8 Design 17 18 8 18 25 16
Human Development T 5.0 T79.0 T78.0 T 5.5 T 8.0 T 3.5
Medicine (HM) T 5.0 T79.0 T78.0 T 5.5 T 8.0 T 3.5
Psychiatry T 5.0 T79.0 T78.0 T 5.5 T 8.0 T 3.5

138

Table 24--Continued

 

U N A D J U S T E D A D J U S T E D

 

 

 

Department Undergraduate Graduate Total Undergraduate Graduate Total
Astronomy 67 T 4.5 68 70 T 8.0 75
Biochemistry 47 47 28 46 57 35
BiOphysics T 5.0 45 9 T 5.5 54 17
Botany 8 Plant Path. 63 48 4O 59 58 T42.5
Chemistry 71 32 63 72 39 73
Entomology 66 56 59 68 66 69
Geology 46 41 42 52 50 52
Mathematics 56 T25.5 T51.5 T55.5 T32.5 60
Nursing 10 T 4.5 l 11 T 8.0 7
Physics T69.5 T25.5 61 71 T32.5 72
Statistics T74.5 63 69 T75.5 73 76
Zoology 37 T37.5 3O 41 T45.5 T42.5
AnthrOpology 61 40 60 T65.5 49 71
Criminal Justice 19 31 11 21 38 20
Geography 52 21 45 54 28 55
Labor 8 Indust. Rel. T 5.0 53 Tl6.5 T 5.5 63 T24.5
Political Science 45 49 48 50 59 57
Psychology 43 44 41 47 53 51
Social Work 24 T27.5 15 27 T34.5 23
Sociology 62 59 57 T65.5 69 68
Urban Plan. 8 Land.Arch. 18 T23.5 10 20 T30.5 18
Amer. Thought 8 Lang. T79.0 T 4.5 T78.0 T79.5 T 8.0 T80.5
Humanities T79.0 T 4.5 T78.0 T79.5 T 8.0 T80.5
Natural Science T79.0 T 4.5 T78.0 T79.5 T 8.0 T80.5
Social Science T79.0 T 4.5 T78.0 T79.5 T 8.0 T80.5
Anatomy T74.5 73 72 T75.5 79 78
Lg. Anim. Surg. 8 Med. T 5.0 75 73 T 5.5 T 8.0 T 3.5
Medical Technology 15 T 4.5 6 16 T 8.0 14
Microbiology 59 66 56 63 42 61
Pathology T79.0 72 66 T79.5 80 66
Pharmacology T79.0 67 47 T79.5 T 8.0 38
Physiology 72 71 64 73 47 70
Sm. Anim. Surg. 8 Med. T 5.0 74 71 T 5.5 55 19
Family 8 Comm. Med. T 5.0 T79.0 T78.0 T 5.5 T 8.0 T 3.5
Medicine (OM) T 5.0 T79.0 T78.0 T 5.5 T 8.0 T 3.5

 

139

Table 25. Departmental Rankings on University-based Instructional Service Measures

 

 

 

 

 

U N A D J U S T E D A D J U S T E D
_Qgpartment Undergraduate Graduate Total Undergraduate Graduate Total
Ag. Economics 22 T20.5 17 T 5.5 T27.5 T 8.0
Ag. Engineering 44 T57.5 45 18 T64.5 19
Animal Husbandry 3O T11.5 T27.5 27 ' T18.0 24
Crop 8 Soil Sci. 51 44 49 36 52 36
Dairy 37 T11.5 '34 37 T18.0 37
Fisheries 8 Wildlife 20 T17.5 16 22 T23.5 21
Food Sci. 8 Hum. Nutr. 26 37 21 24 43 25-
Forestry 32 T41.5 31 32 T50.0 33
Horticulture 41 T26.0 40 31 T32.5 30
Packaging 14 ' 15 11 15 21 15
Park 8 Rec. Resources 25 53 24 28 ' 60 29
Poultry Science 12 T 4.5 5 11 T 8.0 T 8.0
Resource Deve10pmcnt 36 63 39 38 7O 40
Art 55 T26.0 55 56 T32.5 56
English 74 64 74 74 71 73
German 8 Russian 56 T17.5 56 57 T23.5 57
History 75 T55.5 75 75 63 75
Linguistics 24 T32.5 19 26 T38.5 26
Music _ 66 T11.5 64 66 T18.0 64
Philosophy 67 50 66 67 - 57 67
Religion 53 22 51 53 . T27.5 53
Romance Languages 69 T26.0 69 69 T32.5 69
Acct. 8 Finance Adm. 65 78 67 65 80 66
Bus. Law 8 Office Adm. 57 39 57 55 47 55
Economics 73 80 73 73 81 74
Hotel, Rest. 8 Inst. Mgt. l8 T17.5 14 20 T23.5 18
Management ' 59 82 65 59 82 65
Marketing 8 Transp. Adm. 58 75 61 58 79 60
Advertising 45 T34.5 44 46 T40.5 45
Audiology 8 Speech Sci. 29 T11.5 26 33 T18.0 T31.5
Communications 64 71 63 64 76 63
Journalism 31 T32.5 3O 35 T38.5 35
TV 8 Radio 27 T26.0 23 30 T32.5 27
Theatre 23 T11.5 18 25 T18.0 23
Chemical Engineering 11 31 T 6.5 13 37 12
Civil 8 Sanitary Eng. 19 T29.5 15 21 T35.5 20
Computer Science 61 T34.5 - 58 61 T40.5 58
Electrical Engineering 21 68 25 23 74 . T31.5
Mechanical Engineering 15 23 T12.5 16 30 16
Metal, Mach, 8 Mat.Sci. 48 54 47 49 62 49
Family Ecology 33 52 32 39 59 38
Family 8 Child Sci. 54 T47.5 53 ~ 54 T54.5 54
Human Nutr. 8 Foods 38 T17.5 36 42 T23.5 41
Human Envir. 8 Design 39 T20.5 37 43 T27.5 42
Human Deve10pment T 5.0 T11.5 1 T 5.5 T 8.0 T 3.5
Medicine (HM) T 5.0 T26.0 T 2.5 T 5.5 T 8.0 T 3.5
Psychiatry T 5.0 T41.5 T 6.5 T 5.5 T 8.0 T 3.5

14()

Table 25-«Continued

 

 

 

 

U N A D J U S T‘E D A D J U S T E D
9gpar£ment Undergraduate Graduate Total Undergraduate Graduate Total
Astronomy T34.5 T 4.5 33 41 T 8.0 39
Biochemistry 42 67 43 40 73 43
BiOphysics T 5.0 T29.5 4 T 5.5 T35.5 11
Botany 8 Plant Path. T34.5 T57.5 35 34 T64.5 34
Chemistry 77 62 77 77 69 77
Entomology 40 T45.5 41 44 48 44
Geology 50 T41.5 48 52 T50.0 52
Mathematics 80 59 80 79 66 79
.Nursing 10 ’ T 4.5 T 2.5 12 T 8.0 10
Physics 72 T47.5 72 72 T54.5 72
Statistics 63 66 62 63 72 62
Zoology 60 49 59 60 56 59
Anthropology ' 68 T45.5 68 68 53 68
Criminal Justice 46 T41.5 46 47 T50.0 47
Geography 62 - 36 60 62 42 61
Labor 8 Indust. Rel. T 5.0 61 10 T 5.5 68 14
Political Science 70 51 70 70 58 70
Psychology 81 73 81 A 81 78 81
Social Work 43 60 42 45 67 46
Sociology 71 72 71 71 77 71
Urban Plan. 8 Land.Arch. 28 38 T27.5 29 T45.0 28
Amer. Thought 8 Lang. 82 T 4.5 82 82 T 8.0 82
Humanities 78 T 4.5 79 80 T 8.0 80
Natural Science 79 T 4.5 78 78 T 8.0 78
Social Science 76 T 4.5 76 76 T 8.0 76
Anatomy 47 79 54 48 61 48
Lg. Anim. Surg. 8 Med. T 5.0 77 22 T 5.5 T 8.0 T 3.5
Medical Technology 13 T 4.5 9 14 T 8.0 13
Microbiology 52 70 50 T50.5 T45.0 T50.5
Pathology 16 74 29 17 75 22
Pharmacology 17 69 20 19 T 8.0 17
Physiology 49 76 52 T50.5 T45.0 T50.5
Sm. Anim. Surg. 8 Med. T 5.0 81 38 T 5.5 T27.5 T 8.0
Family 8 Comm. Med. T 5.0 T55 5 8 T 5.5 T 8.0 T 3.5
Medicine (OM) T 5.0 65 T12.5 T 5.5 T 8.0 T 3.5

 

Table 26.

llll

Rank Ordering of Departments According to Unadjusted Undergraduate Depart-
ment-based Instructional Service

 

 

T 5.0 Human Development

Medicine (HM)

Psychiatry

BiOphysics

Labor 8 Industrial Rel.
Large Animal Surg. 8 Med.
Small Animal Surg. 8 Med.
Family 8 Community Med.
Medicine (OM)

Nursing

Chemical Engineering
Electrical Engineering
Mechanical Engineering
Hotel, Rest. 8 Inst. Mgt.
Medical Technology
Packaging

Human Environment 8 Design

Urban Plan. 8 Land. Arch.
Criminal Justice

TV 8 Radio

Civil 8 Sanitary Eng.
Music

Journalism

Social Work

Art

Theatre

Forestry

Park 8 Recreation Res.
Poultry Science
Audiology 8 Speech Sci.
Family Ecology
Advertising

Fisheries 8 Wildlife
Food Sci. 8 Human Nutr.
Acct. 8 Finance Adm.
Family 8 Child Science
Zoology

Communications

Human Nutrition 8 Foods

Business Law 8 Office Adm.

Computer Science

(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(2.5)
(5.5)

4(12.4)

(14.8)
(18.5)
(19.4)
(22.1)
(22.9)
(28.6)
(30.9)
(32.8)
(35.4)
(35.8)
(41.0)
(43.0)
(44.0)
(44.4)
(46.2)
(49.5)
(50.0)
(53.4)
(56.4)
(62.9)
(64.8)
(68.0)
(70.3)
(72.0)
(73.0)
(73.6)
(73.8)
(73.9)
(74.7)

English

Psychology

Romance Languages
Political Science
Geology

Biochemistry
Horticulture

Resource Deve10pment
Animal Husbandry
Marketing 8 Transp. Adm.
Geography -
German 8 Russian
History

Economics

Mathematics

Management

Linguistics
Microbiology

Meta1., Mech. 8 Mat. Sci.
Anthropology

Sociology

Botany 8 Plant Pathology
Dairy

Philosophy

Entomology

Astronomy

Crop 8 Soil Science
Agricultural Engineering
Physics

Chemistry

Physiology

Religion

Statistics

Anatomy

Agricultural Economics
American Thought 8 Lang.
Humanities

Natural Science

Social Science
Pathology

Pharmacology

(76.2)
(80.6)
(80.9)
(81.4)
(82.4)
(83.3)
(83.6)
(83.8)
(83.9)
(83.9)‘
(84.8)
-(85.5)
(86.1)
(86.5)
(86.8)
(88.4)
(89.6)
(90.3)
(90.5)
(91.0)
(91.0)
(91.6)
(92.5) .
(93.2)
(93.3)
(94.3)
(94.6)
(94.8)
(94.8)
(95.3)
(96.1)
(96.6)
(99.8)
(99.8)
(100.0)
(100.0)
(100.0)
(100.0)
(100.0)
(100.0)
(100.0)

1J42

 

 

Table 27. Rank Ordering of Departments According to Unadjusted Graduate Department-
based Instructional Service

I 4.5 Poultry Science (0.0) 42 Journalism (22.2)
Astronomy (0.0) 43 English (22.9)
Nursing (0.0) 44 Psychology (23.1)
American Thought 8 Lang. (0.0) 45 BiOphysics (24.2)
Humanities (0.0) 46 Family 8 Child Science (28.4)
Natural Science (0.0) 47 Biochemistry ' (29.1)
Social Science (0.0) 48 Botany 8 Plant Pathology (29.9)
Medical Technology (0.0) 49 Political Science (30.6)
9 Music (0.5) 50 Crap 8 Soil Science (32.2)
10 Audiology 8 Speech Sci. (1.0) 51 Electrical Engineering (33.9)
11 Theatre (2.2) 52 Metal., Mech., 8 Mat. Sci. (34.0)
12 Dairy (4.0) 53 Labor 8 Industrial Rel. ' (34.2)
13 German 8 Russian (4.3) 54 Philosophy (36.2)
14 Art (4.7) 55 Resource Development (36.3)
15 Agricultural Economics (4.8) 56 Entomology (37.7)
16 Fisheries 8 Wildlife (4.9) 57 Forestry (39.1)
17 Romance Languages (6.6) 58 Family Ecology (42.1)
18 Human Environment 8 Design (7.4) 59 Sociology (42.9)
19 Animal Husbandry (7.7) 60 Marketing 8 Transp. Adm. (45.7)
20 TV 8 Radio (8.6) 61 Park 8 Recreation Res. (47.9)
21 Geography - (8.8) 62 Communications (50.4)
22 Civil 8 Sanitary Eng. (10.1) 63 Statistics (52.3)
T23.5 Hotel, Rest. 8 Inst. Mgt. (10.3) 64 Agricultural Engineering (52.4)
Urban Plan. 8 Land. Arch. (10.3) 65 Acct. 8 Finance Adm. (58.6)
T25.5 Mathematics (10.4) 66 Microbiology (60.7)
Physics (10.4) 67 Pharmacology (66.5)
T27.5 Packaging (10.5) 68 Advertising (68.8)
Social Work (10.5) 69 Economics (69.6)
29 Mechanical Engineering (11.6) 70 Management (72.7)
30 Horticulture (11.9) 71 Physiology (74.4)
31 Criminal Justice (13.3) 72 Pathology (86.0)
32 Chemistry (15.0) 73 Anatomy (95.5)
33 History (15.3) 74 Small Animal Surg. 8 Med. (97.5)
34 Chemical Engineering (15.5) 75 Large Animal Surg. 8 Med. (99.1)
35 Human Nutrition 8 Foods (15.8) T79.0 Religion (100.0)
36 Computer Science (16.9) Business Law 8 Office Adm.(lO0.0)
T37.5 Food Sci. 8 Human Nutr. (17.1) Human Deve10pment (100.0)
Zoology (17.1) Medicine (HM) (100.0)
39 Linguistics (20.0) Psychiatry (100.0)
40 AnthrOpology (21.3) Family 8 Community Med. (100.0)
41 Geology (21.7) Medicine (OM) (100.0)

 

1413

 

 

Table 28. Rank Ordering of Departments According to Unadjusted Total Department-
based Instructional Service
1 Nursing (2.5) 42 Geology (76.5)
2 Chemical Engineering (8.1) T43.5 Horticulture (76.8)
3 Mechanical Engineering (14.5) Linguistics (76.8)
4 Electrical Engineering (15.9) 45 Geography (77.8)
5 Hotel, Rest. 8 Inst. Mgt. (18.1) 46 Romance Languages ,(77.9)
6 Medical Technology (19.4) 47 Pharmacology (78.7)
7 Packaging (21.4) 48 Political Science (79.8)
8 Human Environment 8 Design (22.4) 49 German 8 Russian (80.6)
9 BiOphysics (24.2) 50 Animal Husbandry (80.8)
10 Urban Plan. 8 Land. Arch. (26.0) T51.5 History (82.3)
11 Criminal Justice (29.8) Mathematics (82.3)
12 TV 8 Radio (30.2) 53 Management (82.7)
13 Civil 8 Sanitary Eng. (30.8) 54 Metal., Mech., 8 Mat. Sci. (82.8)
14 Poultry Science (32.4) 55 Economics (83.9)
15 Social Work (33.8) 56 Microbiology. (84.1)
Tl6.5 Music (34.2) 57 Sociology (86.3)
Labor 8 Industrial Rel. (34.2) 58 Dairy (87.2)'

18 Journalism (39.9) 59 Entomology (87.9)
19 Theatre (40.5) 60 AnthrOpology (88.1)
20 Art (41.4) 61 Physics (89.2)
21 Audiology 8 Speech Sci. (44.2) 62 Agricultural Engineering (89.4)
22 Forestry (45.7) _63 Chemistry (89.5)
23 Park 8 Recreation Res. (49.3) 64 Physiology (89.6)
24 Fisheries 8 Wildlife (52.1) 65 Crop 8 Soil Science (89.7)
25 Family Ecology (54.8) 66 Pathology (89.9)
26 Food Sci. 8 Human Nutr. (57.9) 67 Philosophy (91.0)
27 Advertising (63.0) 68 Astronomy (94.3)
28 . Biochemistry (65.2) 69 Statistics (94.9)
29 Acct. 8 Finance Adm. (68.2) 70 Réligion (96.6)
30 Zoology (68.5) 71 Small Animal Surg. 8 Med. (97.5)
31 Family 8 Child Science (69.4) 72 Anatomy (98.3)
32 Agricultural Economics (69.6) 73 Large Animal Surg. 8 Med. (99:1)
33 Resource DevelOpment (69.8) T78.0 Human Development (100.0)
34 Communications (70.8) Medicine (HM) (100.0)
35 Human Nutrition 8 Foods (71.9) Psychiatry (100.0)
36 Computer Science (72.2) American Thought 8 Lang. (100.0)
37 English (72. 8) Humanities (100.0)
38 Marketing 8 Transp. Adm. (73.9) Natural Science (100.0)
39 Business Law 8 Office Adm. (74.2) Social Science (100.0)
40 Botany 8 Plant Pathology (75.1) Family 8 Community Med. (100.0)
41 Psychology (75.7) Medicine (OM) (100.0)

Table 29.

based Instructional Service

141)

Rank Ordering of Departments According to Adjusted Undergraduate Department-

 

 

T 5.5

Agricultural Economics
Human Development
Medicine (HM)
Psychiatry

BiOphysics

Labor 8 Industrial Rel.

Large Animal Surg. 8 Med.
Small Animal Surg. 8 Med.

Family 8 Community Med.
Medicine (OM)

Nursing

Chemical Engineering
Electrical Engineering
Mechanical Engineering

Hotel, Rest. 8 Inst. Mgt.

Medical Technology
Packaging

Human Environment 8 Design

Poultry Science
Urban Plan.
Criminal Justice

TV 8 Radio

Civil 8 Sanitary Eng.
Music

Forestry

Journalism

Social Work

Art

Theatre

Park 8 Recreation Res.
Audiology 8 Speech Sci.
Family Ecology
Advertising

Fisheries 8 Wildlife
Food Sci. 8 Human Nutr.
Acct. 8 Finance Adm.
Horticulture

Family 8 Child Science
English

Business Law 8 Office Adm.

Zoology

8 Land. Arch.

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(0.0)

(2.5)

(5.5)
(12.4)
(14.8)
(18.5)
(19.4)
(22.1)
(22.9)
(26.7)
(26.9)
(30.9)
(32.8)
(35.4)
(35.8)
(40.6)
(41.0)
(43.0)
(44.0)
(44.4)
(49.5)
(53.0)
(56.4)
(62.5)
(64.8)
(66.0)
(68.0)
(71.8)
(72.0)
(72.4)
(72.4)
(73.0)

Communications

Human Nutrition 8 Foods
Computer Science
Agricultural Engineering
Biochemistry

Psychology

Animal Husbandry
Romance Languages
Political Science
Resource DeveIOpment
Geology

Marketing 8 Transp. Adm.
Geography

German 8 Russian
Mathematics

History

Economics

Botany 8 Plant Pathology
Management

Crop 8 Soil Science
Linguistics
Microbiology

Metal., Mech., 8 Mat. Sci.

AnthrOpology
Sociology

Dairy
Entomology
PhilosOphy
Astronomy
Physics
Chemistry
Physiology
Religion
Statistics
Anatomy
American Thought 8 Lang.
Humanities
Natural Science
Social Science
Pathology
Pharmacology

(73.6)
(73.8)
(74.7)
(75.8)
(79.1)
(80.6)
(80.7)
(80.9)
(81.4)
(82.2)
(82.4)
(83.4)
(84.8)
(85.5)
(85.5)
(86.1)
(86.5)
(88.3)
(88.4)
(89.0)
(89.6)
(89.7)
(90.5) '
(91.0)
(91.0)
(91.5)
(93.1)
(93.2)
(94.3)
(94.8)
(95.3)
(96.1)
(96.6)
(99.8)
(99.8)
(100.0)
(100.0)
(100.0)
(100.0)
(100.0)
(100.0)

 

Table 30.

based Instructional Service

]J45

Rank Ordering of Departments According to Adjusted Graduate Department-

 

 

T 8.0 Poultry Science

Human DevelOpment
Medicine (HM)

Psychiatry

Astronomy

Nursing

American Thought 8 Lang.
Humanities

Natural Science

Social Science

Large Animal Surg. 8 Med.
Medical Technology
Pharmacology

Family 8 Community Med.
Medicine (OM)

Music

Audiology 8 Speech Sci.
Theatre

Dairy

German 8 Russian

Art

Agricultural Economics
Fisheries 8 Wildlife
Romance Languages

Human Environment 8 Design
Animal Husbandry

TV 8 Radio

Geography

Civil 8 Sanitary Eng.
Hotel, Rest. 8 Inst. Mgt.
Urban Plan. 8 Land. Arch.
Mathematics

Physics

Packaging

Social Work

Mechanical Engineering
Horticulture

Criminal Justice
Chemistry

History

Chemical Engineering

(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.0)
(0.5)
(1.0)
(2.2)
(4.0)
(4.3)
(4.7)
(4.8)
(4.9)
(6.6)
(7.4)
(7.7)
(8.6)
(8.8)
(10.1)
(10.3)
(10.3)
(10.4)
(10.4)
(10.5)
(10.5)
(11.6)
(11.9)
(13.3)
(15.0)
(15.3)
(15.5)

42

43

44
T45.5

Microbiology

Human Nutrition 8 Foods
Computer Science

Food Sci. 8 Human Nutr.
Zoology ‘
Physiology

Linguistics

AnthrOpology

Geology

Journalism

English

Psychology

Biophysics

Small Animal Surg. 8 Med.
Family 8 Child Science
Biochemistry

Botany 8 Plant Pathology
Political Science

Crop 8 Soil Science
Electrical Engineering
Metal., Mech., 8 Mat. Sci.
Labor 8 Industrial Rel.
Philosophy

Resource Deve10pment
Entomology

Forestry

Family Ecology

Spciology

Marketing 8 Transp. Adm.
Park 8 Recreation Res.
Communications
Statistics

Agricultural Engineering
Acct. 8 Finance Adm.
Advertising

Economics

Management

Anatomy

Pathology

Religion

(15.6)
(15.8)
(16.9)
(17.1)
(17.1)
(18.4)
(20.0)
(21.3)
(21.7)
(22.2)
(22.9)
(23.1)
(24.2)
(26.7)
(28.4)
(29.1)
(29.9)
(30.6)
(32.2)
(33.9)
(34.0)
(34.2)
(36.2)
(36.3)
(37.7)
(39.1)
(42.1)
(42.9)
(45.7)
(47.9)
(50.4)
(52.3)
(52.4)
(58.6)
(68.8)
(69.6)
(72.7)
(72.9)
(75.4)

(100.0)

Business Law 8 Office Adm.(100.0)

 

14f)

 

 

Table 31. Rank Ordering of Departments According to Adjusted Total Department-based
Instructional Service

T 3.5 Human DeveIOpment (0.0) T42.5 Botany 8 Plant Pathology (68.5)
Medicine (0.0) Zoology (68.5)
Psychiatry (0.0) 44 English (68.8)
Large Animal Surg. 8 Med. (0.0) 45 Family 8 Child Science (69.4)
Family 8 Community Med. (0.0) 46 Communications (70.8)
Medicine (OM) (0.0) 47 Human Nutrition 8 Foods (71.9)
7 Nursing (2.5) 48 Computer Science (72.2)
8 Agricultural Economics (4.8) 49 Business Law 8 Office Adm. (72.7)
9 Chemical Engineering (8.1) 50 Marketing 8 Transp. Adm. (73.4)
10 Mechanical Engineering (14.5) 51 Psychology (75.7)
11 Poultry Science (14.8) 52 Geology (76.5)
12 Electrical Engineering (15.9) 53 Linguistics (76.8)
13 Hotel, Rest. 8 Inst. Mgt. (18.1) 54 Animal Husbandry (77.1)
14 Medical Technology (19.4) 55 Geography (77.8)
15 Packaging (21.4) 56 Romance Languages (77.9)
16 Human Environment 8 Design (22.4) 57 Political Science (79.8)
17 Biophysics (24.2) 58 CrOp 8 Soil Science (80.5)
18 Urban Plan. 8 Land. Arch. (24.6) 59 German 8 Russian (80.6)
19 Small Animal Surg. 8 Med. (26.7) 60 Mathematics (80.7)
20 Criminal Justice (29.8) '61 Microbiology (81.1)
21 TV 8 Radio (30.2) 62 History (82.3)
22 Civil 8 Sanitary Eng. (30.8) 63 Management (82.7)
23 Social Work (33.8) 64 Metal., Mech., 8 Mat. Sci. (82.8)
T24.5 Music (34.2) 65 Economics (83.9)
Labor 8 Industrial Rel. (34.2) 66 Pathology (85.5)
26 Journalism ' (39.9) 67 Dairy (85.6)
T27.5 Forestry (40.5) 68 Sociology (86.3)
Theatre (40.5) 69 Entomology (87.6)
29 Art (41.4) 70 Physiology (87.9)
30 Audiology 8 Speech Sci. (43.8) 71 AnthrOpology (88.1)
31 Park 8 Recreation Res. (49.3) 72 Physics (89.2)
32 Fisheries 8 Wildlife (52.1) 73 Chemistry (89.5)
33 Family Ecology (54.8) 74 Philosophy (91.0)
34 Food Sci. 8 Human Nutr. (55.9) 75 Astronomy (94.3)
35 Biochemistry (59-8) 76 Statistics (94.9)
36 Advertising (62.5) 77 Religion (96.6)
37 Horticulture (62.6) 78 Anatomy (97.8)
38 Pharmacology (64.2) T80.5 American Thought 8 Lang. (100.0)
39 Acct. 8 Finance Adm. (66.1) Humanities (100.0)
40 Agricultural Engineering (66.3) Natural Science (100.0)
41 (67.8) Social Science (100.0)

Resource Development

Table 32.

1137

University-based Instructional Service

Rank Ordering of Departments According to Unadjusted Undergraduate

 

 

T 5.0 Human Development

Medicine (HM)

Psychiatry

BiOphysics

Labor 8 Industrial Rel.
Large Animal Surg. 8 Med.
Small Animal Surg. 8 Med.
Family 8 Community Med.
Medicine (OM)

Nursing

Chemical Engineering
Poultry Science

Medical Technology
Packaging

Mechanical Engineering
Pathology

Pharmacology

Hotel, Rest. 8 Inst. Mgt.
Civil 8 Sanitary Eng.
Fisheries 8 Wildlife
Electrical Engineering
Agricultural Economics
Theatre

Linguistics

Park 8 Recreation Res.
Food Sci. 8 Human Nutr.
TV 8 Radio

Urban Plan. 8 Land. Arch.
Audiology 8 Speech Sci.
Animal Husbandry
Journalism

Forestry

Family Ecology

Astronomy

Botany 8 Plant Pathology
Resource Development
Dairy

Human Nutrition 8 Foods

Human Environment 8 Design

Entomology
Horticulture

(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.008)
(0.010)
(0.012)
(0.042)
(0.069)
(0.076)
(0.090)
(0.106)
(0.118)
(0.139)
(0.161)
(0.172)
(0.196)
(0.213)
(0.217)
(0.221)
(0.230)
(0.245)
(0.260)
(0.268)
(0.275)
(0.314)
(0.328)
(0.360)
(0.396)
(0.396)
(0.400)
(0.403)
(0.446)
(0.465)
(0.504)
(0.513)

Biochemistry

Social Werk
Agricultural Engineering
Advertising

Criminal Justice
Anatomy

Metal., Mech. 8 Mat. Sci.
Physiology

Geology

Crop 8 Soil Science
Microbiology

Religion '

Family 8 Child Science
Art

German 8 Russian

Bus. Law 8 Office Adm. ‘
Marketing 8 Transp. Adm.
Management

Zoology

Computer Science
Geography

Statistics
Communications

Acct. 8 Finance Adm.
Music

PhilOSOphy

AnthrOpology

Romance Languages
Political Science
Sociology

Physics

Economics

English

History

Social Science
Chemistry

Natural Science
Humanities

Mathematics

Psychology

American Thought 8 Lang.

(0.514)
(0.547)
(0.582)
(0.597)
(0.638)
(0.644)
(0.648)
(0.675)
(0.701)
(0.709)
(0.723)
(0.878)
(0.905)
(0.991)

' (1.012)

(1.055)
(1.098)
(1.135)
(1.184)
(1.185)
(1.262)
(1.395)
(1.403)
(1.602)
(1.671)
(1.804)
(2.207)
(2.246)
(2.337)
(2.843)
(2.972)
(3.039)
(3.840)
(3.998)
(5.026)
(5.143)
(5.692)
(6.228)
(6.584)
(7.005)
(7.628)

 

1413

 

 

Table 33. Rank Ordering of Departments According to Unadjusted Graduate University-
based Instructional Service

T 4.5 Poultry Science (0.000) T41.5 Geology (0.380)
Astronomy (0.000) Criminal Justice _ (0.380)
Nursing (0.000) 44 CrOp and 8011 Science (0-401)
American Thought 8 Lang. (0.000) T45.5 Entomology (0.422)
Humanities (0.000) AnthrOpology (0.422)
Natural Science (0.000) T47.5 Family 8 Child Science (0.444)
Social Science (0.000) Physics (0.444)
Medical Technology (0.000) 49 Zoology (0.465)
T11.5 Animal Husbandry (0.021) 50 Philosophy (0.528)
Dairy (0.021) 51 Political Science (0.549)
Music (0.021) 52 Family Ecology (0.676)
Audiology 8 Speech Sci. (0.021) 53 Park 8 Recreation Res. (0.718)
Theatre (0.021) 54 Metal., Mech. 8 Mat. Sci. (0.739)
Human DeveIOpment (0.021) T55.5 History (0.760)
15 Packaging (0.042) Family 8 Community Med. (0.760)
T17.5 Fisheries 8 Wildlife (0.063) T57.5 Agricultural Engineering (0.908)
German 8 Russian (0.063) Botany 8 Plant Pathology (0.908)
Hotel, Rest. 8 Inst. Mgt. (0.063) 59 Mathematics (0.951)
Human Nutrition 8 Foods (0.063) 60 Social Work (1.104)
T20.5 Agricultural Economics (0.084) 61 Labor 8 Industrial Rel. (1.141)
Human Environment 8 Design (0.084) 62 Chemistry (1.225)
22 Religion (0.085) 63 Resource Development (1.394)
23 Mechanical Engineering (0.106) 64 English (1.500)
T26.0 Horticulture (0.148) 65 Medicine (OM) (1.563)
Art (0.148) 66 Statistics (1.648)
Romance Languages (0.148) 67 Biochemistry (1.732)
TV 8 Radio (0.148) 68 Electrical Engineering (1.796)
Medicine (HM) (0.148) 69 Pharmacology (2.387)
T29.5 Civil 8 Sanitary Eng. (0.169) 70 Microbiology (2.514)
Biophysics (0.169) 71 Communications (2.535)
31 Chemical Engineering (0.190) 72 Sociology (2.831)
T32.5 Linguistics (0.211) 73 Psychology (3.612)
Journalism (0.211) 74 Pathology (3.887)
T34.5 Advertising (0.232) 75 Marketing 8 Transp. Adm. (4.056)
Computer Science (0.232) 76 Physiology (4.288)
36 Geography (0.253) 77 Large Animal Surg. 8 Med. (4.774)
37 Food Sci. 8 Human Nutr. (0.275) 78 Acct. 8 Finance Adm. (5.767)
38 Urban Plan. 8 Land. Arch. (0.296) 79 Anatomy (6.760)
39 Bus. Law 8 Office Adm. (0.317) 80 Economics (8.365)
T41.5 Forestry (0.380) 81 Small Animal Surg. 8 Med. .(9.lO4)
Psychiatry (0.380) 82 ‘Management (10.414)

 

IL49

 

 

Table 34. Rank Ordering of Departments According to Unadjusted Total University-based
Instructional Service
1 Human Deve10pment (0.001) 42 Social Work (0.570)
T 2.5 Medicine (HM) (0.007) 43 Biochemistry (0.574)
Nursing (0.007) 44 Advertising (0.579)
4 BiOphysics (0.008) 45 Agricultural Engineering (0.598)
5 Poultry Science (0.011) 46 Criminal Justice (0.625)
T 6.5 Chemical Engineering (0.019) 47 Metal., Mech. 8 Mat. Sci. (0.652)
Psychiatry (0.019) 48 Geology (0.686)
8 Family 8 Community Med. (0.037) 49 Crap 8 Soil Science (0.694)
9 Medical Technology (0.040) 50 Microbiology (0.811)
10 Labor 8 Industrial Rel. (0.056)' 51 Religion (0.839)
11 Packaging (0.068) 52 Physiology (0.853)
T12.5 Mechanical Engineering (0.077) 53 Family 8 Child Science (0.882)
Medicine (OM) (0.077) 54 Anatomy (0.946)
14 Hotel, Rest. 8 Inst. Mgt. (0.115) 55 Art (0.950)
15 Civil 8 Sanitary Eng. (0.140) 56 German 8 Russian (0.965)
16 Fisheries 8 Wildlife (0.156) 57 Bus. Law 8 Office Adm. (1.018)
17 Agricultural Economics (0.190) 58 Computer Science (1.138)
18 Theatre (0.204) 59 Zoology (1.149)
19 Linguistics (0.216) 60 Geography (1.212)
20 Pharmacology (0.218) 61 Marketing 8 Transp. Adm. (1.243)
21 Food Sci. 8 Human Nutr. (0.232)" 62 Statistics (1.408)
22 Large Animal Surg. 8 Med. (0.235) 63 Communications (1.459)
23 TV 8 Radio (0.240) 64 Music (1.590)
24 Park 8 Recreation Res. (0.246) 65 Management (1.592)
25 Electrical Engineering (0.252) 66 Philosophy (1.742)
26 Audiology 8 Speech Sci. (0.256) 67 Acct. 8 Finance Adm. (1.807)
T27.5 Animal Husbandry (0.262) 68 Anthropology (2.119)
Urban Plan. 8 Land. Arch. (0.262) 69 Romance Languages (2.143)
29 Pathology (0.277) 70 Political Science (2.249)
30 Journalism (0.309) 71 Sociology (2.842)
31 Forestry (0.331) 72 Physics (2.847)
32 Family Ecology (0.376) 73 Economics (3.301)
33 Astronomy (0.377) 74 English (3.724)
34 Dairy (0.384) 75 History (3.839)
35 Botany 8 Plant Pathology (0.421) 76 Social Science (4.778)
36 Human Nutrition 8 Foods (0.428) 77 Chemistry (4.950)
37 Human Environment 8 Design (0.446) 78 Natural Science (5.412)
38 Small Animal Surg. 8 Med. (0.448) 79 Humanities (5.922)
39 Resource DevelOpment (0.449) 80 .Mathematics (6.307)
40 Horticulture (0.495) 81 Psychology (6.838)
41 Entomology (0.500) 82 American Thought 8 Lang. (7.252)

 

Table 35.

based Instructional Service

ILSO

Rank Ordering of Departments According to Adjusted Undergraduate University-

 

 

T 5.5 Agricultural Economics

Human Development
Medicine (HM)

Psychiatry

Biophysics

Labor 8 Industrial Rel.
Large Animal Surg. 8 Med.
Small Animal Surg. 8 Med.
Family 8 Community Med.
Medicine (OM)

Poultry Science

Nursing

Chemical Engineering
Medical Technology
Packaging

Mechanical Engineering
Pathology

Agricultural Engineering
Pharmacology

Hotel, Rest. 8 Inst. Mgt.
Civil 8 Sanitary Eng.
Fisheries 8 Wildlife
Electrical Engineering
Food Sci. 8 Human Nutr.
Theatre

Linguistics

Animal Husbandry

Park 8 Recreation Res.
Urban Plan. 8 Land. Arch.
TV 8 Radio

Horticulture

Forestry

Audiology 8 Speech Sci.
Botany 8 Plant Pathology
Journalism

Crap 8 Soil Science
Dairy

Resource Development
Family Ecology
Biochemistry

Astronomy

(0.000)
(0.000)
(0.000)

’(0.000)

(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.005)
(0.008)
(0.010)
(0.043)
(0.072)
(0.078)
(0.093)
(0.103)
(0.110)
(0.123)
(0.144)
(0.167)
(0.179)
(0.218)
(0.222)
(0.225)
(0.229)
(0.230)
(0.249)
(0.255)
(0.266)
(0.272)
(0.274)
(0.283)
(0.326)
(0.340)
(0.365)
(0.373)
(0.374)
(0.405)
(0.412)

Human Nutrition 8 Foods

Human Environment 8 Design

Entomology

Social Work
Advertising

Criminal Justice
Anatomy '

Metal., Mech. 8 Mat. Sci.
Microbiology
Physiology

Geology

Religion

Family 8 Child Science
Bus. Law 8 Office Adm.
Art .

German 8 Russian
Marketing 8 Transp. Adm.
Management

Zoology

Computer Science
Geography

Statistics
Communications

Acct. 8 Finance Adm.
Music

PhilosOphy
Anthropology

Romance Languages
Political Science
Sociology

Physics

Economics

English

History

Social Science
Chemistry

Natural Science
Mathematics

Humanities

Psychology

American Thought 8 Lang.

(0.464)
(0.483)
(0.507)
(0.569)
(0.610)
(0.663)
(0.670)
(0.673)
(0.702)
(0.702)
(0.729)
(0.912)
(0.940)
(1.015)
(1.030)
(1.052)
(1.103)
(1.179)
(1.230)
(1.232)
(1.311)
(1.450)
(1.458)
(1.491)
(1.736)
(1.875)
(2.294)
(2.335)
(2.429)
(2.954)
(3.089)
(3.158)
(3.274)
(4.155)
(5.223)
(5.345)
(5.916)
(6.167)
(6.473)
(7.280)
(7.669)

_.-

2151

 

 

Table 36. Rank Ordering of Departments According to Adjusted Graduate University-based
Instructional Service

T 8.0 Poultry Science (0.000) '42 Geography (0.380)
Human DeveIOpmcnt (0.000) 43 Food Sci. 8 Human Nutr. (0.412)
Medicine (HM) (0.000) T45.0 Urban Plan. 8 Land. Arch. (0.443)
Psychiatry (0.000) Microbiology (0.443)
Astronomy (0.000) Physiology (0.443)
Nursing (0.000) 47 Bus. Law 8 Office Adm. (0.475)
American Thought 8 Lang. (0.000) T49.0 Forestry (0.570)
Humanities (0.000) Geology (0.570)
Natural Science (0.000) Criminal Justice (0.570)

Social Science (0.000) 51 Crop 8 Soil Science (0.602)

Large Animal Surg. 8 Med. (0.000) T52.5 Entomology (0.633)
Medical Technology (0.000) AnthrOpology (0.633)
Pharmacology (0.000) T54.5 Family 8 Child Science (0.665)

Family 8 Community Med. (0.000) Physics (0.665)
Medicine (OM) (0.000) 56 Zoology (0.697)

T18.0 Animal Husbandry (0.032) 57 Philosophy (0.792)
Dairy (0.032) 58 Political Science (0.823)

Music (0.032) 59 Family Ecology (1.013)
Audiology 8 Speech Sci. (0.032) 60 Park 8 Recreation Res. (1.077)
Theatre (0.032) T6l.5 Metal., Mech. 8 Mat. Sci. (1.108)

21 Packaging (0.063) Anatomy (1.108)
T23.5 Fisheries 8 Wildlife (0.095) 63 History (1.140)
German 8 Russian (0.095) T64.5 Agricultural Engineering (1.362)

Hotel, Rest. 8 Inst. Mgt. (0.095) Botany 8 Plant Pathology (1.362)

Human Nutrition 8 Foods (0.095) 66 Mathematics (1.425)

T27.5 Agricultural Economics (0.127) 67 Social Work (1.520)
Religion (0.127) 68 Labor 8 Industrial Rel. (1.710)

Human Environment 8 Design (0.127) 69 Chemistry (1.834)

Small Animal Surg. 8 Med. (0.127) 70 Resource Deve10pment (2.090)

30 Mechanical Engineering (0.158) 71 English - (2.248)
T32.5 Horticulture (0.222) 72 Statistics (2.470)
Art (0.222) 73 Biochemistry (2.597)
Romance Languages (0-222) 74 Electrical Engineering (2.692)

TV 8 Radio (0.222) 75 Pathology (2.818)

T35.5 Civil 8 Sanitary Eng. (0.253) 76 Communications (3.800)
Biophysics (0.253) 77 Sociology (4.243)

37 Chemical Engineering (0.285) 78 Psychology (5.415)
T38.5 Linguistics (0.317) 79 Marketing 8 Transp. Adm. (6.080)
Journalism (0.317) 80 Acct. 8 Finance Adm. (8.645)

T40.5 Advertising (0.348) 81 Economics (12.540)
Computer Science (0.348) 82 Management (15.611)

 

1152

 

 

Table 37. Rank Ordering of Departments According to Adjusted Total University-based
Instructional Service

T 3.5 Human Development (0.000) 42 Human Environment 8 Design (0.471)
Medicine (HM) (0.000) 43 Biochemistry (0.481)
Psychiatry (0.000) 44 Entomology (0.512)
Large Animal Surg. 8 Med. (0.000) 45 Advertising (0.600)
Family 8 Community Med. (0.000) 46 Social Work (0.602)
Medicine (OM) (0.000) 47 Criminal Justice (0.660)
T 8.0 Agricultural Economics (0.004) 48 Anatomy (0.685)
Poultry Science (0.004) 49 Metal., Mech. 8 Mat. Sci. (0.688)
Small Animal Surg. 8 Med. (0.004) T50.5 Microbiology (0.693)
10 Nursing (0.008) Physiology (0.693)
11 Biophysics (0.009) 52 Geology (0.723)
12 Chemical Engineering (0.020) 53 Religion (0.885)
13 Medical Technology (0.042) 54 Family 8 Child Science (0.931)
14 Labor 8 Industrial Rel. (0.059) 55 Bus. Law 8 Office Adm. (0.997)
15 Packaging (0.071) 56 Art (1.002)
16 Mechanical Engineering (0.081) 57 German 8 Russian (1.019)
17 Pharmacology (0.106) 58 Statistics (1.201)
18 Hotel, Rest. 8 Inst. Mgt. (0.122) 59 Zoology (1.212)
19 Agricultural Engineering (0.147) 60 Marketing 8 Transp. Adm. (1.276)
20 Civil 8 Sanitary Eng. (0.148) 61 Geography . (1.279)
21 Fisheries 8 Wildlife (0.165) 62 Statistics (1.485)
22 Pathology (0.188) 63 Communications (1.539)
23 Theatre (0.215) 64 Music (1.677)
24 Animal Husbandry (0.222) 65 Management (1.680)
25 Food Sci. 8 Human Nutr. (0.225) 66 Acct. 8 Finance Adm. (1.739)
26 Linguistics (0.228) 67 Philosophy (1.838)
27 TV 8 Radio (0.254) 68 Anthropology (2.236)
28 Urban Plan. 8 Land. Arch. (0.256) 69 Romance Languages (2.261)
29 Park 8 Recreation Res. (0.259) 70 5 Political Science (2.373)
30 Horticulture (0.265) 71 Sociology (2.999)
T31.5 Audiology 8 Speech Sci. (0.266) 72 Physics (3.005)
Electrical Engineering (0.266) 73 English (3.238)
33 Forestry (0.282) 74 Economics (3.483)
34 Botany 8 Plant Pathology (0.321) 75 History (4.051)
35 Journalism (0.326) 76 Social Science (5.042)
36 CrOp 8 Soil Science (0.349) 77 Chemistry (5.223)
37 Dairy (0.353) 78 Natural Science (5.711)
38 Family Ecology (0.396) 79 Mathematics (6.003)
39 Astronomy (0.397) 80 Humanities (6.248)
40 Resource DevelOpment (0.433) 81 Psychology (7.216)
41 Human Nutrition 8 Foods (0.451) 82 American Thought 8 Lang. (7.403)

153

Table 38. Departmental Rankings on General Fund Expenditures, 1971-72

 

 

 

Supplies 8
Department Total Salagy Labor Services Equip;
Ag. Economics 23 25 28 49 T11.5
Ag. Engineering 32 32 62 48 36
Animal Husbandry 33 22 74 72 56
Crop 8 Soil Sci. 50 47 67 61 42
Dairy 19 6 80 35 46
Fisheries 8 Wildlife 17 20 37 19 38
Food Sci. 8 Human Nutr. 28 24 70 54 2
Forestry 20 19 ' 27 3O 6O
Horticulture 45 36 78 50 40
Packaging 7 9 22 16 58
Park 8 Rec. Resources 2 2 1 6 1
Poultry Science 12 3 77 58 59
Resource Development 5 7 30 17 3
Art 73 73 51 ' 71 72
English 78 79 17 37 20
German 8 Russian 54 57 ll 15 T11.5
History 68 69 6 22 27
Linguistics 11 15 9 3 21
Music 75 75 54 6O 73
PhiIOSOphy 53 58 14 2 22
Religion 3 5 4 l 24
Romance Languages 72 74 19 32 23
Acct. 8 Finance Adm. 67 67 56 40 T11.5
Bus. Law and Office Adm. 27 34 24 12 T11.5
Economics 71 72 31 52 T11.5
Hotel, Rest. 8 Inst. Mgt. 13 17 T 2.5 13 T11.5
Management 52 52 12 27 T11.5
Marketing 8 Transp. Adm. 60 62 21 10 ° T11.5
Advertising 8 13 15 8 28
Audiology 8 Speech Sci. 25 29 16 38 39
Communications 56 55 53 53 54
Journalism 22 23 20 18 35
TV 8 Radio 9 12 34 7 48
Theatre 24 31 23 24 25
Chemcial Engineering 10 10 10 23 67
Civil 8 Sanitary Eng. 31 35 42 9 47
Computer Science 34 28 72 56 50
Electrical Engineering 59 59 71 63 53
Mechanical Engineerigg 41 43 35 34 33
Metal, Mech., 8 Mat. Sci. 47 49 25 51 45
Family Ecology 15 18 29 5 51
Family 8 Child Science 21 21 48 11 31
Human Nutr. 8 Foods l6 14 64 33 44
Human Envir. 8 Design 36 39 36 28 49
Human Development 37 37 59 68 63
Medicine (HM) 39 38 45 62 74

Psychiatry 18 16 32 59 55

154

Table 38—-Continued

 

 

 

, Supplies 8
Department Total Salary, Labor Services Eauip.
Astronomy - 4 4 47 55 64
Biochemistry 51 42 58 66 79
Biophysics 6 8 T 2.5 14 34
Botany 8 Plant Path. 58 56 61 7O 68
Chemistry 82 A 81 82 ‘ 82 82
Entomology 14 ll 65 43 65
Geology 44 44 52 ‘ 46 57
Mathematics 81 82 55 79 T11.5
Nursing 48 50 5 20 29
Physics 79 78 81 78 78
Statistics 49 51 8 21 26
Zoology 57 54 57 69 71
Anthropology 38 41 41 44 52
Criminal Justice 43 46 13 ' 41 30
Geography 55 53 43 45 37
Labor 8 Indust. Rel. 64 64 6O 65 T11.5
Political Science 66 66 33 74 43
Psychology 80 80 76 80 80
Social Work 40 4O 7 57 66
Sociology 69 68 50 77 61
Urban Plan. 8 Land. Arch. 42 45 38 36 32
Amer. Thought 8 Lang. 77 77 39 39 T11.5
Humanities 70 71 46 29 T11.5
Natural Science 76 76 68 64 T11.5
Social Science 636 65 44 25 T11.5
Anatomy 62 60 66 75 81
Lg. Anim. Surg. 8 Med. 26 27 63 26 T11.5
Medical Technology 1 1 26 4 41
Microbiology 74 70 79 81- 77
Pathology 65 63 75 73 76
Pharmacology 35 26 69 67 75
Physiology 61 61 73 76 62
Sm. Anim. Surg. 8 Med. 46 48 49 31 T11.5
Family 8 Comm. Med. 30 30 40 47 70

Medicine (0M) 29 33 18 42 69

‘

Table 39. Departmental Rankings on Research Grant and Contract Expenditures, 1971—72

155

 

f

 

Dgpartment Total Salary Eguip. Other
Ag. Economics 80 81 58 81
Ag. Engineering 55 58 62 54
Animal Husbandry 64 63 64 66
Crap 8 Soil Sci. 72 73 65 68
Dairy 60 57 49 65
Fisheries 8 Wildlife 57 55 75 59
Food Sci. 8 Human Nutr. 65 60 74 71
Forestry 4O 44 46 40
Horticulture 63 64 70 60
Packaging 48 50 61 43
Park 8 Rec. Resources 31 35 T22.5 31
Poultry Science 44 46 T22.5 46
Resource Development 49 48 T22.5 49
Art 33 T12.5 68 T 9.0
English 26 27 T22.5 30
German 8 Russian T 8.5 T12.5 T22.5 T 9.0
History T 8.5 T12.5 T22.5 T 9.0
Linguistics 25 T12.5 T22.5 28
Music 21 T12.5 T22.5 23
Philosophy 29 25 T22.5 34
Religion T 8.5 T12.5 T22.3 T 9.0
Romance Languages 23 T12.5 T22.5 25
Acct. 8 Finance Adm. 27 31 T22.5 29
Bus. Law 8 Office Adm. T 8.5 T12.5 T22.5 T 9.0
Economics 52 54 T22.5 20
Hotel, Rest. 8 Inst. Mgt. 22 30 T22.5 20
Management T 8.5 T12.5 T22.5 T 9.0
Marketing 8 Transp. Adm. 35 38 T22.5 36
Advertising 20 28 T22.5 21
Audiology 8 Speech Sci. 53 45 44 55
Communications 61 61 48 63
Journalism T 8.5 T12.5 T22.5 T 9.0
TV 8 Radio 39 T12.5 T22.5 50
Theatre T 8.5 T12.5 T22.5 T 9.0
Chemical Engineering T 8.5 T12.5 T22.5 T 9.0
Civil 8 Sanitary Eng. 'T 8.5 T12.5 T22.5 T 9.0
Computer Science T 8.5 T12.5 T22.5 T 9.0
Electrical Engineering 43 47 57 39
Mechanical Engineering T 8.5 T12.5 T22.5 T 9.0
Metal, Mech., 8 Mat. Sci. 19 T12:5 T22.5 22
Family Ecology 24 26 T22.5 24
Family 8 Child Science 70 69 50 72
Human Nutr. 8 Foods 34 40 56 26
Human Envir. 8 Design T 8.5 T12.5 T22.5 T 9.0
Human DeveIOpment 59 62 71 57
Medicine (HM) 47 43 60 51
Psychiatry 66 71 53 64

Table 39--Continued

IL56

 

 

 

Department Total Salary Eguip. Other
Astronomy 28 29 T22.5 32
Biochemistry 79 79 79 80
Biophysics 75 75 76 75
Botany 8 Plant Path. 68 68 63 70
Chemistry 81 80 82 78
Entomology 74 76 72 73
Geology 46 41 1 52
Mathematics 69 74 T22.5 58
Nursing 62 65 53 56
Physics 82 82 80 82
Statistics 45 51 T22.5 41
Zoology 67 66 54 67
AnthrOpology ' 38 37 45 38
Criminal Justice 50 49 T22.5 48
Geography 17 T12.5 T22.5 18
Labor 8 Indust. Rel. 58 59 47 62
Political Science 41 42 T22.5 45
Psychology 78 78 59 79
Social Work 71 72 T22.5 69
Sociology 56 52 52 61
Urban Plan. 8 Land.Arch 30 34 T22.5 27
Amer. Thought 8 Lang. T 8.5 T12.5 T22.5 T 9.0
Humanities T 8.5 T12.5 T22.5 T 9.0
Natural Science 37 36 T22.5 37
Social Science 18 T12.5 T22.5 19
Anatomy 54 56 69 53
Lg. Anim. Surg. 8 Med. 32 33 51 33
Medical Technology T 8.5 T12.5 T22.5 T 9.0
Microbiology 76 7O 81 76
Apthology 42 39 73 42
Pharmacology 73 67 77 74
Physiology 77 77 787 .77
Sm. Anim. Surg. 8 Med. 36 32 67 35
Family 8 Comm. Med. 51 53 66 44
T 8.5 T12.5 T22.5 T 9.0

Medicine (0M)

 

2157

Tabla 40. Faculty Rank Distribution Indices

 

 

 

 

 

FACULTY RANK INDICES RANKINGS J
'Qgpartment _Hgadcount FT§‘> Z Dist. Num. FTE X Dist.
Ag. Economics 145 22.60 333 76.0 20.0 T59.5
Ag. Engineering 68 25.65 337 T57.5 30.0 T63.5
Animal Husbandry 54 20.00 360 48.0 17.0 T74.5
Crop 8 Soil Sci. 148 43.08 343 78.0 50.0 67.0
Dairy 57 12.40 317 T49.5 4.0 '4720
Fisheries 8 Wildlife 36 25.20 324 T28.5 27.0 T52.5
Food Sci. 8 Hum. Nutr. 71 24.55 360 60.0 26.0 T74.5
Forestry 62 25.35 326 53.0 28.0 57.0
Horticulture 104 30.60 320 71.0 38.0 149.5
Packaging '-19 15.30 220 T 8.0 11.0 4.0
Park 8 Rae. Resources 12 3.50 240 T 3.5 2.0 8.0
Poultry Science 34 9.35 340 T24.5 3.0 ’ 66.0
Resource Development 33 17.20 346 T21.5 13.0 70.0
Art 117 105.00 308 72.0 74.0 T41.0
Englisb- 146 132.77 359 77.0 78.0 73.0
German 8 Russian 47 »53.00 250 T38.5 62.0 10.0
History 96 85.00 304 68.0 71.0 36.0
Linguistics 21 21.16 245 10.0 18.0 9.0
Music 137 139.50 299 74.0 79.0 .T31.0
PhiloBOphy 67 59.67 302 56.0 65.0 35.0
Religion 14 15.20 350 5.0 10.0 71.0
Romance Languages 88 86.34 276 66.0 72.0 21.0
Acct. 8 Finance Adm. 68 73.00 283 T57.5 68.0 25.0
Bus. Law 8 Office Adm. 30 32.00 299 17.0 39.0 T31.0
Economics 91 84.91 323 ‘ 67.0 70.0 51.0
Hotel, Rest. 8 last. Mgt. 23 25.75 380 T12.5 32.0 T79.5
Management 48 39.00 333 T41.0 46.0 T59.5
Marketing 8 Transp. Adm. .27 58.85 389 T14.5 64.0 81.0
Advertising 19 19.00 266 T 8.0 16.0 T17.5
Audiology 8 Speech Sci. 33 29.50 275 T21.5 36.0 20.0
Communications 53 36.50 314 T46.5 43.0 44.0
Journalism 31 26.00 230 T18.5 33.0 5.0
TV 8 Radio 17 13.25 325 6.0 5.0 T55.0
Theatre 11 23.00 233 2.0 T22.5 6.0
Chemcial Engineering 23 21.50 329 T12.5 19.0 58.0
Civil 8 Sanitary Eng. 34 36.70» 324 T24.5 45.0 T52.5
Computer Science .33 27.20 260 T21.5 35.0 14.0
Electrical Engineering 59 47.40 305 51.0 56.0 T37.5
Mechanical Engineering 60 45.50 339 52.0 53.0 65.0
Met., Mech. 8 Mat. Sci. 63 45.75 337 54.0 54.0 T63.5
Family Ecology 36 24.05 274 T28.5 25.0 19.0
Family 8 Child Sci. 33 22.90 266 T21.5 21.0 T17.5
Human Nutr. 8 Foods 38 18.50 306 T30.5 15.0 39.0
Human Envir. 8 Design 29 25.70 203 16.0 31.0 3.0
Human DeveIOpment 31 - 13.51 257 T18.5 7.0 13.0
Medicine (HM) 57 23.00 320 T49.5 T22.5 T49.5
Psychiatry 35 13.50 264 T26.5 6.0 16.0

IL58

Table 40—-Continued

 

 

 

 

 

. FACULTY RANK INDICES RANKINGS
Dgpartment Headcount FTE Z Dist. Num. FTE Z Dist.
Astronomy 12 14.00 280 T 3.5 8.0 24.0
Biochemistry 75 30.55 371 T61.5 37.0 78.0
BiOphysics 19 15.00 380 T 8.0 9.0 T79.5
Botany 8 Plant Pathology 101 48.50 335 69.0 58.0 62.0
Chemistry 102 91.40 316 70.0 73.0 T45.5
Entomology 50 17.45 300 T44.5 14.0 T33.5
Geology 43 46.00 367 35.0 55.0 77.0
Mathematics 221 182.04 345 82.0 82.0 T68.5
Nursing . 47 40.25 174 T38.5 49.0 2.0
Physics 156 118.18 345 80.0 75.0 T68.5
Statistics 48 49.22 _ 316 T41.0 59.0 T45.5
Zoology . 64 49.25 351 55.0 60.0 72.0
Anthropology 44 36.55 297 . T36.5 44.0 T28.5
Criminal Justice 44 34.00 310 T36.5 41.0 43.0
Geography 39 44.40 308 T32.5 ' 51.0 T41.0
Labor 8 Indust. Rel. 50 48.00 325 T44.5 57.0 T55.0
Political Science 70 65.11 305 59.0 66.0 T37.5
Psychology 168 130.33 334 81.0 77.0 61.0
Social Work 53 39.50 308 T46.5 47.0 T41.0
Sociology 75 53.78 297 » T61.5 63.0 T28.5
Urban Plan. 8 Land. Arch. 48 39.55 319 T4l.0 48:0 48.0
Amer. Thought 8 Language 140 175.35 '252 75.0 81.0 11.0
Humanities ' 133 121.17 .286 73.0 76.0 26.0
Natural Science 153 163.55 279 ‘ 79.0 80.0 23.0
Social Science 84 75.00 299 65.0 69.0 T31.0
Anatomy 42 35.60 262 34.0 42.0 15.0
Lg. Anim. Surg. 8 Med. 35 23.65 254 T26.5 24.0 12.0
Medical Technology 1 3.00 150 1.0 1.0 1.0
Microbiology 80 68.03 292 63.0 67.0 27.0
Pathology 49 44.50 325 43.0 52.0 T55.0
Pharmacology 38 25.50 278 T30.5 29.0 22.0
Physiology 81 51.15 361 64.0 61.0 76.0
Sm. Anim. Surg. 8 Med. 39 32.85 234 , T32.5 40.0 7.0
Family 8 Comm. Med. 22 16.47 300 11.0 12.0 T33.5
Medicine (OM) 27 26.69 400 T14.5 34.0 82.0

 

Table 41. Graduate Assistants, 1971-72

159

 

 

R A N K I N G S

 

Department Headcount FTE Headcount FTE
Ag. Economics 50 0 76 T 7.0
Ag. Engineering 16 1.00 43 T23.5
Animal Husbandry 13 1.00 39 T23.5
Crop 8 Soil Sci. 39 2.45 T72.0 39
Dairy 25 0.50 T55.5 T17.0
Fisheries 8 Wildlife 38 0.50 T70.0 Tl7.0
Food Sci. 8 Hum. Nutr. 37 0 T67.5 T 7.0
Forestry 22 0 52 T 7.0
Horticulture 37 3.00 T67.5 42
Packaging 4 1.50 T19.0 T30.5
Park 8 Rec. Resources 4 0.50 T19.0 Tl7.0
Poultry Science 11 1.50 T33.5 T30.5
Resource Development 14 1.00 T40.5 T23.5
Art 28 10.25 60 T65.5
English 51 25.50 77 79
German 8 Russian 21 10.25 T50.0 T65.5
History 43 16.00 T73.0 76
Linguistics 14 4.81 T40.5 51
Music 36 11.50 T65.5 T69.5
PhiIOSOphy 15 6.70 42 56
Religion 1 0.50 T12.0 T17.0
Romance Languages 44 22.75 74 78
Acct. 8 Finance Adm. 38 13.25 T70.0 74
Bus. Law 8 Office Adm 3 1.25 Tl6.5 T27.5
Economics 25 11.50 T55.5 T69.5
Hotel, Rest. 8 Inst. Mgt. 11 3.50 T33.5 T43.5
Management 26 11.15 T58.0 67
Marketing 8 Transp. Adm. 20 8.75 48 T62.5
Advertising 5 1.75 T22.0 33
Audiology 8 Speech Sci. 1 0.50 T12.0 T17.0
Communications 35 9.25 64 64
Journalism 8 2.25 T27.0 T36.5
TV 8 Radio 6 2.50 T24.5 T40.5
Theatre 23 11.25 T53.5 68
Chemical Engineering 3 1.00 T16.5 T23.5
Civil 8 Sanitary Eng. 9 3.50 29 T43.5
Computer Science 5 2.25 T22.0 T36.5
Electrical Engineering 19 8.50 47 61
Mechanical Engineering 4 1.25 T19.0 T27.5
Metl, Mech., 8 Mat.Sci. 10 4.25 30 T48.0
Family Ecology 12 3.75 T37.5 45
Family 8 Child Sci. 29 4.25 61 T48.0
Human Nutr. 8 Foods 11 2.25 T33.5 T36.5
Human Envir. 8 Design 11 4.00' T33.5 46
Human Development 8 1.00 T27.0 T23.5
Medicine 2 0.50 T14.5 Tl7.0
Psychiatry 6 1.00 T24.5 T23.5

160

Table 41e-Continued

 

 

R A N K I N G S

 

 

Department Headcount FTE Headcount FTE
Astronomy 0 0 T 5.5 T 7.0
Biochemistry 46 8.75 75 T62.5
Biophysics 12 2.25 T37.5 T36.5
Botany 8 Plant Path. 38 6.00 T70.0 T54.0
Chemistry 163 58.28 82 81
Entomology 23 1.50 T53.5 T30.5
Geology 17 7.25 T44.5 58
Mathematics 133 63.75 81 82
Nursing 0 0 T 5.5 T 7.0
Physics 78 15.75 79 75
Statistics 17 6.75 T44.5 57
Zoology 36 11.55 T65.5 71
Anthropology 18 7.50 46 59
Criminal Justice 11 5.50 T33.5 52
Geography 30 12.75 62.5 72
Labor 8 Indust. Rel. 21 8.25 T50.0 60
Political Science 26 13.00 T58.0 73
Psychology 85 34.75 80 80
Social WOrk 21 4.25 T50.0 T48.0
Sociology 60 21.25 78 77
Urban Plan. 8 Land. Arch. 8 2.50 T27.0 T40.5
Amer. Thought 8 Lang. 0 0 T 5.5 T 7.0
Humanities 0 0 T 5.5 T 7.0
Natural Science 1 0.50 T12.0 Tl7.0
Social Science 0 0 T 5.5 T 7.0
Anatomy 11 4.50 T33.5 50
Lg. Anim. Surg. 8 Med. 0 0 T 5.5 T 7.0
Medical Technology 0 0 T 5.5 T 7.0
Microbioloby 30 6.00 T62.5 T54.0
Pathology 2 1.50 T14.5 T30.5
Pharmacology 5 2.00 T22.0 34
Physiology 26 6.00 T58.0 T54.0
Sm. Animal Surg. 8 Med. 0 0 T 5.5 T 7.0
Family 8 Comm. Med. 0 0 T 5.5 T 7.0
Medicine (OM) O 0 T 5.5 T 7.0

 

Table 42.

1971-72

161.

Rank Ordering of Departments According to Average 10—month Equated Salary,

 

‘DQNO‘UIO‘UNH

Medical Technology
Nursing

Theatre

Family 8 Child Science
Human Envir. 8 Design
Packaging

Park and Rec.Resources
Linguistics

Amer. Thought 8 Lang.
Sm. Anim. Surg. 8 Med.
Hum. Nutr. 8 Foods
Humanities '

German 8 Russian
Natural Science
Family Ecology
Anatomy

Romance Languages
Entomology

Audiology

Music

Ag. Engineering

Art

Journalism
Philosophy

Astronomy

Lg. Anim. Surg. 8 Med.
TV and Radio
Horticulture
Microbiology

Botany

Advertising

Religion
Anthropology

History

Fisheries 8 Wildlife
Ag. Economics
Political Science
Social Science

Social Work

Forestry

Crap and Soil Science

(10,868)
(11,538)
(11,737)
(12,001)
(12,546)
(13,200)
(13,224)
(13,361)
(13,484)
(13,518)
(13,283)
(13,851)
(13,932)
(14,117)
(14,183)
(14,209)
(14,384)
(14,555)
(14,589)
(14,661)
(14,664)
(14,792)
(14,987)
(15,062)
(15,138)
(15,317)
(15,329)
(15,352)
(15,466)
(15,476)
(15,498)
(15,697)
(15,700)
(15,711)
(15,776)
(15,850)
(15,988)
(15,993)
(16,060)
(16,079)
(16,091)

Mathematics

Dairy

Poultry Science
Geography

Bus. Law 8 Office Adm.
Animal Husbandry
English

Electrical Engineering

Urban Plan. 8 Land. Arch.

Pharmacology

Geology

Computer Science
Sociology

Chemistry

Labor 8 Indust. Rel.
Biochemistry
Physiology
Communications
Psychology

Food Sci. 8 Human Nutr.
Resource Development
Criminal Justice
Mechanical Engineering
Zoology

Phyéics

Statistics

Pathology

Civil 8 Sanitary Eng.

Metal, Mech. 8 Mat. Sci.

Acct. 8 Finance Adm.
Chemical Engineering
Human DeveIOpment
Family 8 Comm. Med.
Biophysics
Management

Hotel, Rest., 8 Inst. Mgt.

Economics
Psychiatry

Marketing 8 Transp. Adm.

Medicine (HM)
Medicine (OM)

(16,103)

,(l6,108)

(16,110)
(16,131)
(16,144)
(16,216)

.(l6,222)

(16,355)
(16,400)
(16,484)
(16,496)
(16,503)
(16,665)
(16,775)
(16,807)
(16,815)
(16,826)
(16,915)
(16,966)
(17,024)
(17,036)
(17,135)
(17,384)
(17,404)
(17,514)
(17,565)
(17,689)
(17,920)
(18,110)
(18,263)
(18,612)
(18,623)
(18,896)
(19,037)
(19,320)
(19,800)
(19,806)
(21,119)
(21,337)
(22,271)
(25,105)

 

1152

 

 

 

 

 

NNH No NN NN NH oH Ho ooH oo oo NNH No NN NN oN oH cannons
HNN oH NN oN NN NH No ooH oo oo «NN No NN HN NN NH oHona on. >9
NNN No NN NN NH NH oH oN oN oo NNN No NN NN «H NH aNHHaauaoo
No«H No NH HN NH N« oNH No No No NNNH oo «H NN NH N« .noHuuuHaaaaoo
N«N No NN o« NN oH Ho oo ooH oo N«N No «N o« NN oH .HuN auooom N NNoHoHo=<
NNN «o NH NN oN NH .HH ooH oo oo N«N No NH NN oN NH NaHNHuuo>u<
NNHH NH NN N« No No NNH «o No Ho NooH Ho NN o« oH No NoHuuxuuz
oNNH NN «N NN No «o NN« No «o oo NNoH Ho o« NN No No uaoaowanm:
HHH No NN NN NN HN No . ooH oo oo NoH Ho NN NN NN HN .NN: .uNaH N .Nom .Houom
NNHN NH HN NN «N No NNN No No oo NNNN No NN NN NN No NUHBoaoum
oNo No NN NN No oH NH NN NH oo «No Ho NN NN No oH 38H omoaHuso
NNNH NH HN NN oN HH NNN «N «o oo «N«H. Ho NN NN «N NH .o< .on N NaHuasouu<
oooN No NH NN NN HN No ooH oo oo NNoN Ho NH NN NN HN nowaawcoa ouomaom
NoN Ho «N «N NN NH «o ooH oo oo NoN Ho «N «N NN NH cOHNHH6N
«NNH No NN NN NN NH NN oN No NH N«NH No NN NN NN NH NnaouoHHNN
NNNH Ho «H NN NN «N Ho ooH oo oo NNNH Ho «H NN NN «N uHmoz
NoN NN NN NN NH HH oH oN oN oH NNH HN NN NN NH NH ouHuNstaHH
ooNN No NN o« NH «H NN NN No HH «NNN Ho NN o« NH «H NuouNHm
NNN Ho NH NN NN HN No NN NN NN NNN No «H NN NN HN aaHNusx N ametwo
oNNN No NN «N «H oH HN No NN oo ooNN No NN «N «H oH NNHHNNN
NHN No HN NN NH NH No N« N« «H NoN No oN «N NH NH uu<
NN« NN «N NN No HH No oN No No NNN «H NN NN No NH uaoaooHo>oo cousomom
HH NH oo oo NN N« oo oo oo oo HH NH oo oo on N« oucoHoN NuuHsoN
NNN NN N« NH HH No «N «N No oo NoN oH NN HN NH No nouuaouom .uoN N Nana
NNo oo «N NN NN No No ooH oo oo Noo No NN oN NN No NoHwauma
NN« No NH HN NH N« No ooH oo oo oo« oo «H HN NH N« ouauHsuHotoN
NHN NH «N NH HH «N NH ooH oo oo ooN No NN NH NH «N Nuuaouom
NNN No «N NN NH No NH ooH oo oo oHN No NN NN NH , No .uuaz ones: N .HuN Noon
oNH HN N« NH No Ho No ooH oo oo N«H oN N« NH No Ho «NHHNHHa N ooHuoaoHN
NNN HH NH HH No NN Ho ooH oo oo NNN HH NH HH No NN NuHNo
NNN No NH NH NH «N oH ooH oo oo N«N No NH NH NH NN ououHum HHoN N oouo
NNN No No No oo NN Ho ooH oo oo HNN Ho No No No NN r Nuoouomam HmaH:<
NNN oo No No No oN N« No No oo NNN No No No oH NN oHuoooHNam HausuH36HNN<
NNH No oo Ho NH NN «o ooH oo oo NNH oo oo Ho NH «N aoHaoooom HousuHsthN<
Hooch mono um um snow um Hmuoa mono um um Hmuoa vouu um um snow um ucoauummon
NNNNooo HH< Nmmmooo .o4mo

 

 

 

 

mummsou mh<an<mumm925.

 

 

 

 

mums vaunafivmaallao>uu uaovsum an muaovaum oow>uom Hmaowuoauumam mo aoHuanHuumHn eunuaoouom

.nQ «Hana

163

 

 

 

 

 

 

 

 

 

nnno oo no nH on nH ; oo oo oo OO nnno oo no nH on nH ooaUHon HoHoon
uoun oo NO No No nN oo. oo OO oo uOun oo No No No nN ooaUHon Huuauaz
unnn oo no nH nn nH oo oo OO OO unnn OO no nH nn nH uuHanmasn
HNnn oo no uo no no oo oo oo oo HNnn oo no uO oo nn .naiH n unnaonh .uoad
unu nH nu ou nH nH oH nn oH oo nnu HH on nu .nH NH ncHaamHn dunno
unNu no nu on nH nH onH nn oO OO nnnu no nu nn ou oH nnoHoHoon.
non OH ou nu nH nH no nN Hu oo OOn no nu Hn ou Hu duo: HnHoon
nNnn oo. nH nu NH on . HNH on no uo uoon uo ou Nu NH on nnOHononun
unHu uo nu oo NH nH nu nn uH no nnHu Ho nu oo nH nH ovaUHon HuoHuHHon
on Hn no oo oo oo 2 on Hn no oo OO oo oo oo oo OO .Huu Hunuumancn n honed
nnHH no nn nn nH nH uH nN nu oo nnHH uo nn on nH nH nnnounooo
Hon nO Hu Ou nu On nH no HH 8 nnn HO uu ON nu Hn Conan-NH Hanna—HHO
NnOu uo ou on uu nu Ou nn oo no NHou HO Ou on uu Nu nnOHooouaua<
oOHH No nn uo no no uu nn oH OO unOH no nn no no no .nnOHoou
nnnH uu uu nn nH no nN nN NH OH nNuH nH nu nn nH no moHuoHuuun
NnNu Ho uH on no no Hu un no OO nHNu HO uH on No no QOHonnn
NO oH oH no nu co co no no oo No oH oH no nu oo naHauaz
unon oo no nH nH nn no nN nH .HH NHon no no nH nH nn moouuamnuu:
nnn no on Nn nH HH nH nn nn oo Hon HO on nn nH HH NnOHooo
Hno .no Hn no OH no ou OOH OO oo Hno no Hn no OH no nnoHoaouan
.nnNo uO no nH nH nn nn oN Hu no ooNo Ho no nH nH nn nuunHauno
, noo ou nH ou no nu no OOH Oo OO unn OH ou Nu OH un ..nuom uaiHn n ncmuon
no on nn uH OO on no on nn uH oo _ oo oo oo OO oo manNAAOHn
unn nn uH nu no Hu un. Hn oO oo oNo on oH nu no ou NuuuHaonoOHn
unn HO un Nn Hu OH OO OO OO OO unn Ho un Nn Hu OH Nioaouund
nH OOH OO OO OO OO nH OOH OO oo. OO oo OO OO OO OO nuuuHAonum
No OOH OO co co OO NO OOH OO OO OO OO OO OO co co . GOG oaHUHvuI
HO OOH OO OO oo OO HO OOH OO OO OO OO OO oo OO OO ucoanoHo>ao canon
nuo uO Ou Nu ou nu oo OOH OO OO nuo Ho Hu Nu nu nu anHooo n .qunn canon
HHo no nH nn Hu NH no Nn OO nn noo oo nH nn uu NH coach n .uuaz awash
non no Nu nn Ou NO Hu OOH OO OO Nun oo nu Oo Hu No .Hon nHHzo n nHHaun
Hnn no on nn no nH un nn uH OO nun HO nn nn no nH nnOHoom nHHauu
Nun no nH on Hu HO nn no NH OO unn OO Ou Nn Nu HO .HUan: nfioux ...Hduwx
oN uu Ho ou no oo no OOH OO OO nn nH oo nu OH oO naHuoooHnan HeoHamnomx
uou un nu nn oo OO nn un, oH oO NnH oo Nn nn no OO naHuoocann HaoHuuooHn
onOH no nH nn Hu ou HH Nu Nu no nnOH no oH nn Hu ou ooauHon wouanaoo
nnH , HH on nn nH no no nn uH OO NuH no nn nn NH no .nan nuwuHaun n HH>Ho
nH nn nn OO HH Oo no OOH OO OO no HH Nn OO uu Oo naHuooaHnau HuuHaunu
HouOH nuuo um unWhmAOn. um .HWuoa nauo um, an Hauoa nouo an un anon um ucuauunumm
mango Add mango“. .93 «£38 Has—gag

 

 

gain 0%

1154

 

 

 

 

 

 

 

 

 

«N ooH oo oo oo oo «N ooH oo oo o oo oo oo oo oo 98 2:33:
NN ooH oo oo oo oo NN ooH oo oo o oo oo oo oo oo Nu: NuHauaaoo N NHHaua
HN« No oo oo oo oo HN« oo oo oo o oo oo oo oo oo a: N NuaN HuaHa< HHuaN
oNN HN NN NN NH 8 NoN No No oo NHN No NN «N NH No NNoHoHNNfi
oHN NN «N NH oo oo NHH No No oo NN NH NN NN Ho oo NNoHoumauNoN
NNN HN NN No oo oo «NH No No oo NN oH NN HH oo oo NNoHoNuua
oNN NH NN HN NH No NHH NN No No HNN «o N« «N NH No NNoHoHNouon
NN No HH NN oN No o oo oo oo NN No HH NN oN No NNoHoaauoH HuoHoo:
NNN ooH oo oo oo oo NNN ooH oo oo o oo oo oo oo oo on: N Noam Hanna 2:3
NoN NN HH oN NN No oNN No No Ho NNN Ho NH N« «N «o Nsouuao
Hmuoa nmuo um .HH. noon um H33. n30 .3 .HH. Hmuoa omuo pm .3. anon .Hm . ucmauuog
mmnnooo 4.2 nmmnooo 92o nmnxnoo ma<oo<nonnoz=

 

oosaHuooou.N« oHN-H

165

 

 

 

 

NNH No NN NN NH oH H ooH oo oo NNH No NN NN oN oH ouuuuoa
HNN oH NN oN NN NH N ooH oo oo «NN No NN HN NN NH oHoNN New >H
NNN No NN NN NH NH oH oN oN oo NNN No NN NN «H NH aNHHaauaoN
No«H No NH HN NH N« oNH NN No No NNNH oo. «H NN NH N« maoHuNoHcaaaoo
N«N . No NN o« NN oH H oo ooH oo H«N No NN H« NN oH .Hum Noomom N NNoHoHooN
N«N «o NH NN oN HH HH ooH oo oo NNN No oN NN HN HH NNHNHNN6>N<
NNHH NH NN N« No Ho NNH «N No Ho oNN Ho NN HN No Ho NcHuuxuN:
oNNH NN «N NN No «o NN« NN «o oo NNoH Ho N« NN No No NcaamNNamz
HHH No NN NN NN HN N ooH oo oo NoH Ho NN NN NN HN .NN: .NNoH N .NNN .Huuom
NNHN NH HN NN «N No NNN NN No oo NNNN No . NN . NN NN No muHeooooN
NoN No NN oN No No NH NN NH oo NNN Ho NN oN No No ..NN NOHNNo N 38H .NNN
«NNH NH «N NN HN No NNN NN «o oo HHNH Ho NN N« NN No .NN .aHN N NcHuoaouo<
oNoN No NH NN NN HN N ooH oo oo NNoN Ho NH NN NN HN mmNmachH monocom
NoN Ho «N «N NN NH « ooH oo oo NoN Ho «N «N NN NH ooHNHHoN
«NNH No NN NN NN NH NN oN No NH N«NH No NN NN NN NH NNNoNoHHNN
NNNH Ho «H NN NN «N H ooH _ oo oo NNNH Ho «H NN NN «N 6Hmaz
NoN NN NN NN NH HH oH oN oN oH NNH HN NN NN NH NH NUHNNHNNNHH
oNNN No NN o« NH «H NN NN No HH «NNN Ho NN o« NH «H NHONNHN
NNN Ho NH NN NN HN N NN NN NN NNN No «H NN NN HN NNHNNNN N omenmo
oNNN No NN H« (NH NH HN NN NN oo NNNN Ho NN N« NH NH NNHHNNN
NHN No HN NN NH NH N N« N« «H NoN No oN «N NH NH HnN
«NN NN NN «N No No NN NN No No NNN NH N« NN oH No NooaooHo>mo ouuaNmom
« oN oo oo oN oo o oo oo .oo « oN oo oo oN oo ouaoHuN NuuHsom
NNN NN N« NH HH No «N «N No oo NoN oH NN HN NH No mouuoomma .uoN N NNNNN
NN No «N NN NN No N ooH oo oo NN No NN NN NN No NNHNNHNNN
H«N «o NN NN NN No N ooH oo oo «NN Ho NN H« «N No NNNNH=UHNN6N
NNN NH oN NN NH NH NH ooH oo oo NNN oH NN «N NH HN Nuummuom
NoN oH NN NN NH No NH ooH oo oo NNH «o o« NN NH No .uusz cmsom N .HUN Noon
oNH. HN N« NH No Ho N ooH oo oo N«H oN N« NH No Ho 6NHHNHH: N NNHNNNNHN
NNN NH oN NH No N« H ooH oo oo HNN NH HN NH No oN NNHNo
NHN HH NN «N NH oH NH ooH oo oo NNN No NN NN HN HH moaoHum HHoN New N8o
NoN No HH No No NN H ooH oo oo HoN Ho HH No No NN Nuocmamom HNaH=<
«NH NN HN HN «o No N« NN No oo HN No «« HN No HH NaHuoooHNcN HausuHsuHuNN
« ooH oo oo oo oo « ooH oo oo o oo oo oo oo oo NUHaoaoom HausuHaoHuNN
Hmuoa NNHN .NN no HmoN Hm HNNoN oono uN Ho Hosea oauo NN no NNNN Na Ncmsunmomm
NNNNooo .o<No NNNNooo NHNNNNNNNNozo

mmmmaoo HH<

 

 

 

 

 

 

 

 

mama noumonn<ulHo>oH uconsun an muaonsun ooH>uon HchHuoauumcH no nOHuanHuan ammunoouom .oo OHan

1156

 

 

 

 

NNN«, oo No NH «N NH o oo oo oo NNN« oo No NH «N NH ououHom HNHuoN
NoNN oo No No No NN o oo oo oo NoNN oo No No No NN ouaoHON Honoumz
NNNN oo No NH NN NH o oo oo oo NNNN oo No NH NN NH . NNHNHNNaNN
««NN oo No No «o NN o oo oo oo ««NN oo No No «o. NN NuaNauH N uaNaoNH .uoaN
NNN NH NN NN NH oH «H NN «H oo NHN NH NN NN NH HH .N6u<.N:uH N .NNHN NNNH:
NNNN No NN «N NH NH «NH NN «o oo NNNN No NN NN oN «H NNoHoHuom
N«N oH «N NN NH NH 1 N« NN , HN oo ooN No NN HN oN HN sues HNHuoN
NNNN «o NH NN NH «N HNH oN No No No«N No oN NN NH «N NNoHoauNNN
NNHN No NN o« NH NH NN NN NH No NNHN Ho NN o« NH NH moauHoN HNuHNHHoN
«N HN No oo oo oo «N .HN No oo o oo oo oo oo oo .HoN HNHuuosoaH N uoNNH
NNHH No NN NN NH NH NH NN NN oo NNHH No NN «N NH NH NNNNNNooo
HoN No HN oN NN oN NH NN HH oo NNN Ho NN oN NN HN ouHuoao HucHaHuo
NNoN No oN oN NN NN oN NN oo No NHoN Ho oN oN NN NN NNoHoooNNNNN
«oHH No NN N« No No NN NN «H oo NNoH No NN N« No No NNoHoON
NNNH NN NN NN NH No NN NN NH oH NNNH NH NN NN NH No ouHNNHNNNN
NNNN Ho NH «N N« No HN NN N« oo NHNN Ho NH «N N« No uuHmNNN
N «H «H N« NN oo o oo oo oo N «H «H N« NN oo Nchuaz
NN«N «o No NH NH «N N« NN NH HH NN«N No No NH NH «N NoHNNaoouoz
NNN No oN NN NH HH NH NN NN oo H«N Ho oN NN NH HH NNoHooo
NN« No NN N« oH No oN ooH oo oo N«« No NN N« HH No NNoHoaoucN
NNN« No No NH NH NN. NN «N HN No ooN« Ho No NH NH NN NNNNHENNN
NNN NN NN NN NH Ho N« ooH oo oo N«N NH NN NN NH Ho .NNNN NoNHN N NcNNoN
N oN NN NH oo oo N oN NN NH o oo oo oo oo oo moHNNNNoHN
NN« oN NH HN No oo NN HN «o «o NNN o« NH NN «o Ho . NuumHamauoHN
NNN Ho NN NN HN oH o oo oo oo NNN Ho NN NN HN oH Naoaouumo
o oo oo oo oo oo o oo oo oo o oo oo oo oo oo NuuuHNUNNN
o oo . oo oo oo oo o oo oo oo o oo oo oo oo oo HzNo ocHuHomz
o oo oo oo oo oo o oo oo oo o oo oo oo oo oo NouaooHo>6o seas:
NN« No oN NN «N. NN « ooH oo oo NN« Ho HN NN NN NN oNHNuo N .uH>aN guano
HH« No NH NN HN NH N NN oo NN No« «o NH NN NN NH Nooom N coHaHuuaz noes:
N«N No NN NN oN No HN ooH oo oo NNN «o NN o« HN No oucoHUN NHHNN N NHHaNN
HNN No «N NN No NH NN NN NH oo NNN Ho NN NN No NH NNoHoUN NHHaNN
NNN No NH «N, HN Ho NN NN NH oo NNN oo oN NN NN Ho .HUN.NNz N.N66: ..Hmuuz
«N NN H« «N No «o N ooH oo oo NN NH «« NN oH «o NcHuooaHNso HNUHNNNUNN
N«N NN NN NN «o oo NN NN «H «o NNH «o NN NN No oo NaHnoonHNcN HouHuuuoHN
«NoH No NH NN HN «N HH NN NN N« NNoH No «H NN HN «N oucoHUN nouaaaoo
NNH HH «N NN NH No N NN NH oo NNH No NN NN NH No .NaN NNNNHNNN N HH>Ho
NH NN NN oo HH oo N ooH oo oo N HH NN oo NN No NaHuuoaHNoN HNuHaNNo
H33. noun .5 ..NH. flow uh H3 OH. 230 um. .HN. Houon. vauo um . .HN. snow .Hm ucoauuwg
NNNNooo HH« NNNNNoo .o<No NNNNooo NHNNNNNNNNozo

 

 

 

 

 

 

 

NNNNHNaoouu«« NHNNH

167

 

 

 

 

 

 

 

 

 

 

 

 

O oo oo oo oo OO o OO OO OO O OO oo OO oo oo 93 .oaHoH—No:
o OO oo oo OO OO O oo oo OO O oo oo OO . oo co co: nuHHHaa-uoo n nHHamh
o OOH oo OO OO oo o OOH OO oo O oo oo oo OO oo out n nuan Had—Had HHS—Hm
Hnn HH on nn NH oo oH n n No oo NHn no nn on NH no . nnOHOHmNHrH
Nn nH nn nn Ho oo o OO OO OO Nn nH nn nn Ho OO nnOHoooaumsn
HNH nn nn no OO OO nn nn uo oo un OH nN HH oo oo nNOHosuun
Hnn no no nu nH uO oH nn NO No . Sn .5 no nu nH uo nnOHoHnouon
nn no HH un .On no O OO OO oo .nn no HH un on no nnOHonHHooh HmoHoox
o O oo OO oo OO oo O OO OO. OO o oo OO oo OO oo out n nuon HHH—H5 onus
oun no nH on un no nn Hn no oo nnn Ho nH no on no nHH—cum:
Hnuou. nauo .Hn .HN. noon uh Hanan. omuo an .H H. HauOH no.5 an .HN. can um ucofiuummoo

mmgoo .H.H<

nun—958 O55

wand—HOO flak—Hague:—

 

 

 

ooanHuaouauS «HHNH

Table 45.

Factor Scores

168

 

 

 

Department 1 2 3 4 5 _Qfi
Ag. Economics 341 238 1,338 76 18 98
Ag. Engineering 3,926 579 952 105 1,241 245
Animal Husbandry 2,067 88 1,567 45 789 28
Crop 8 Soil Sci. 5,152 476 1,066 108 769 191
Dairy 3,113 140 868 83 926 26
Fisheries 8 Wildlife 1,311 476 4,900 216 435 0
Food Sci. 8 Human Nutr. 2,306 484 974 152 720 10
Forestry 5,156 344 2,698 81 979 33
Horticulture 4,164 431 1,565 105 1,301 127
Packaging 3,590 190 3,620 20 619 0
Park 8 Rec. Resources 3,345 560 1,980 13 83 0
Poultry Science 204 113 333 75 O 4
Resource Development 4,403 1,562 1,871 94 0 21
Art 18,629 947 8,643 391 4,717 0
English 38,626 2,001 11,025 393 657 327
' German 8 Russian 11,454 507 1,467 87 291 0
History 35,908 2,266 7,672 309 2,265 0
Linguistics 2,927 380 367 32 269 0
Music 23,773 1,089 7,196 263 4,341 0
Philosophy 14,994 565 1,586 127 216 0
Religion 6,741 18 305 8 0 0
Romance Languages 26,178 797 4,071 83 449 0
Acct. 8 Finance Adm. 24,229 4,288 8,832 200 632 82
Bus. Law 8 Office Adm. 10,564 103 3,001 21 371 38
Economics 34,223 4,949 4,430 263 0 0
Hotel, Rest., 8 Inst. Mgt. 5,097 344 5,456 0 754 0
Management 12 ,523 6,035 3.960 293 732 0
Marketing 8 Transp. Adm. 10,838 4,314 4,764 204 1,794 17'
Advertising 6,855 176 3,810 14 693 5
Audiology 8 Speech Sci. 3,731 742 2,497 209 279 3
Communications 15,288 1,983 4,089 160 0 0
Journalism 6,233 417 4,909 46 1,006 0
TV 8 Radio 6,458 723 4,406 59 510 0
Theatre 4,036 370 2,126 63 863 0
Chemical Engineering 1,433 365 1,595 64_ 0 0
Civil 8 Sanitary Eng. 2,926 618 3,093 75 866 0
Computer Science 12,934 -1,476 3,490 68 506 0
Electrical Engineering 8,893 933 5,459 116 402 0
Mechanical Engineering 3,515 347 3,573 61 655 0
Metal, Mech. 8 Mat. Sci. 6,046 649 780 94 5 515 0
Family Ecology 4,243 438 604 106 365 0
Family 8 Child Sci. 7,997 564 2,917 110 248 0
Human Nutr. 8 Foods 4,713 111 1,522 39 931 0
Human Envir. 8 Design 13,603 408 8,632 34 2,526 0
Human Development 3 3 0 1 O 0
Medicine (HM) 1,085 1,274 1,522 281 119 0
Psychiatry 55 56 -5 29 0 0

 

Table 45--Continued

169

 

 

 

Qgp:rtmcnt_wfl 1 2 3 4 5 6

Astronomy 3,745 1 507 0 36 ,0
Biochemistry 5,611 1,342 2,613 263 350 63
BiOphysics 169 311 227 57 0 0
Botany 8 Plant Path. 3,286 983 1,048 263 1,096 62
Chemistry 34,940 2,142 3,990 684 11,159 0
Entomology 3,478 376 813 139 624 8
Geology 5,727 470 1,463 135 1,310 0
Mathematics 71,718 3,897 2,822 370 7,173 329
Nursing 3,694 0 6,012 0 1,396 0
Physics 19,392 1,392 2,385 312 3,125 0
Statistics 11,138 1,284 898 85 1,541 0
Zoology 12,334 803 5,411 273 2,252 0
AnthrOpology 18,997 567 2,264 302 3,234 0
Criminal Justice 19,734 895 9,854 375 604 0
Geography 9,828 873 1,909 297 2,506 0
Labor 8 Indust. Rel. 741 1,556 560 30 0 0
Political Science 25,768 778 5,360 125 0 0
Psychology 68,087 4,997 7,533 1,231 1,447 0
Social Work 9,554 4,003 6,420 26 756 0
Sociology 26,344 1,958 4,199 753 172 0
Urban Plan. 8 Land. Arch. 7,272 1,144 3,668 22 1,251 11
Amer. Thought 8 Lang. 57,048 0 66 0 0 .124
Humanities 56,461 0 23 0 992 0
Natural Science 43,059 0 53 0 12,006 0
Social Science 44,943 0 130 O 918 0
Anatomy 7,944 3,132 361 322 446 0
Lg. Anim. Surg. 8 Med. 1,440 2,764 -34 7 0 0
Medical Technology 810 0 3,310 0 0 0
Microbiology 6,110 1,812 1,604 113 2,362 24
Pathology 1,728 1,971 ,179 73 332 0
Pharmacology 1,371 1,247 217 89 0 0
Physiology 5,926 2,660 802' 141 1,645 0
Sm. Anim. Surg. 8 Med. 1,388 2,412 -72 43 0 0
Family 8 Comm. Med. 98 168 -11 0 0 0
Medicine (OM) 234 415 -22 0 0

 

BIBLIOGRAPHY

BIBLIOGRAPHY

Breneman, D. W. (Ed.). Internal Pricing Within the University--A Con-
ference Report. Berkeley, Calif.: University of California, 1971.

Brubacher, J. S., and Rudy, W. Higher Education in Transition.
New York: Harper and Brothers Publishers, 1958.

Buchanan, J. M. , and Develetoglou, N. E. Academia in Anarchy.
New York: Basic Books, Inc., Publisher, 1970.

Cartter, AN M. An Assessment of Quality in Graduate Education.
Washington, D. C.: American Council on Education, 1966.

Cattell, R. B. Handbook of Multivariate Experimental Psychology.
Chicago: Rand McNally and Company, 1966.

Charters, W. W., Jr., and Gage, N. L. Readipgp in the Social Psychology_
of Education. Boston: Allyn and Bacon, 1963.

Cheit, E. F. The New Depression in Higher Education. New York:
McGraw—Hill Book Company, 1971.

Comrey, A. L. A First Course in Factor Analysis. New York: Academic
Press, 1973.

Conover, W. J. Practical Nonparametric Statistics. New York: John
Wiley and Sons Inc., 1971.

Corson, J. J. Governance in Collgges and Universities. New York:
McGraw-Hill Book Company, 1960.

Currie, I. D. ggugl. "Images of the Professors and Interest in the
Academic Profession." Sociolpgy of Education, 39 (Fall, 1966),

 

Doyle, E. A. The Status and Function of the Department Chairman.
Washington, D. C.: Catholic University of America Press, 1953.

Dressel, P. and Reichard, D. "The University Department: Retrospect
and Prospect." Journal of Higher Education, 41 (May, 1970),
387-402.

Dressel, P. L., and Faricy, W. H. Return to Responsibilipy.
San Francisco: Jossey-Bass, Inc. Publishers, 1972.

170

171

Dressel, P. L.; Johnson, F. C.: and Marcus, P. M. The Confidence Crisis.
San Francisco: Jossey-Bass, Inc. Publishers, 1970.

Euwema, B. "The Organization of the Department." Educational Record,
34 (January, 1953), 38-43.

 

Featherstone, R. L. The Development of Management Systems for the
Academic Department. Boulder, Colo.: Western Interstate Commission
for Higher Education, 1972.

Fox, K. A. (Ed.). Economic Analysis for Educational Planning. Baltimore:
The Johns Hopkins University Press, 1972.

Freeman, L. D. "The Management of Knowledge."
tion, 45 (February, 1974), 81-97.

Journal of Higher Educa-

Fruchter, B. Introduction to Factor Analysis. New York: Van Nostrand,
1954.

Gaff, J. C., and Wilson, R. C. "Faculty Cultures and Interdisciplinary
Studies." Journal of Higher Education, 43 (March, 1971), 186-201.

Gouldner, A. W. "Cosmopolitans and Locals: Toward an Analysis of
Latent Social Roles." Administrative Science_9uarter1y, 2 (June,
1958), 444-480.

Grassell, E. M. "The President Needs Management Training." College
Management, 6 (August, 1971), 28-29.

Gunter, C. W. "The Role of Department Chairmen in the Governance of
State Universities." Unpublished Ed.D. Dissertation, Washington
State University, 1964.

Halsey, A. H. "The Changing Functions of Universities." In A. H.
Halsey, J. Floud, and C. A. Anderson (Eds.) Education, Economy,
and Society. Glencoe, Ill.: The Free Press, 1961.

Halsey, A. H.; Floud, J.; and Anderson, C. A. Education, Economics,
and Society. Glencoe, Ill.: The Free Press, 1961.

Hamblin, R. L., and Smith, C. R. "Values, Status, and Professors."
Sociometry, 29 (September, 1966), 183-196.

Hemphill, J. K. "Leadership Behavior Associated With the Administra-
tive Reputation of College Departments." In W. W. Charters, Jr.
and N. L. Gage (Eds.). Readiggs in the Social Psychology of Edu-
cation. Boston: Allyn and Bacon, 1963.

Hill, W. W., and French, W. L. "Perceptions of Power of the Department
Chairman by Professors." Administrative Science Quarterly, 11
(March, 1967), 548-574.

172

Hirschleifer, J. "Economics of the Divisionalized Firm." Journal of
Business, 30 (April, 1957), 96-108.

 

Hobbs, W. C., and Anderson, L. G. "The Operation of Academic Depart-
ments." Management Science, 15 (December, 1971), B-134-143.

Hoenack, S. A., and Norman, A. L. "Incentives and Resource Allocation
in Universities." Journal of Higher Education, 45 (January, 1974),
21-37 0

Hunter, J. E. "FACTRB-~Preliminary User's Manual." Computer Institute
for Social Science Research, Michigan State University, n.d.
(Mimeographed.)

Hunter, J. E. and Cohen, S. H. "PACKAGE." Version 1.0. Computer
Institute for Social Science Research, Michigan State University,
June 1, 1971. (Mimeographed.)

Hutchins, R. "The University and the Multiversity." The New Republic,

Kerlinger, F. N., and Pedhazur, E. J. Multiple Regression in Behavioral
Research. New York: Holt, Rinehart and Winston, Inc., 1973.

Key, W. The Department Chairman: One Man's Viewpoint. Boulder, Colo.:
Western Interstate Commission for Higher Education, 1970.

Marascuilo, L. A. Statistical Methods for Behavioral Science Research.
New York: McGraw-Hill Book Company, 1971.

McConnell, T. R. Notes for a Talk on Departmental Orggnization.
Monograph 5. Boulder, Colo.: Western Interstate Commission for
Higher Education, 1969.

McKeachie, W. J. "Memo to a New Department Chairman." Educational
Record, 42 (Spring, 1968), 221-227.

Michigan State University. Bylaws for Faculty Governance. East Lansing,
Mich.: Michigan State University, 1971.

Millett, J. D. The Academic Community. New York: McGraw-Hill Book
Company, 1962.

Minahan, J. P. "Administrative Cost Accounting: Whose Cost and Whose
Accounting?" Journal of Higher Education, 45 (January, 1974),
38-4 7 o

 

National Center for Higher Education Management Systems. A Blueprint
for RRPM 1.6 Application. Boulder, Colo.: western Interstate
Commission for Higher Education, 1973.

173

Nunnally, J. C. Payphometric Theory. New York: McGraw—Hill Book
Company, 1967.

Overall, J. E., and Klett, C. J. Applied Multivariate Analysis.
New York: McGraw—Hill Book Company, 1972. '

Patterson, L. M. "Preferences in Administrative Style Based on an
Inquiry Into the Perceptions of the Ideal Role of the Department
Chairman." Unpublished Ph.D. Dissertation, University of Texas,
1966.

Perkins, J. A. (Ed.). The University as an Organization. New York:
McGraw—Hill Book Company, 1973.

Plessnar, Y.; Fox, K. A.; and Sanyal, B. C. "0n the Allocation of
Resources in a University Department." Mbtroeconomica, 20
(September, 1968), 256—271.

Porter, K. "Department Head or Chairman?" AAUP Bulletin, 47
(December, 1961), 339-342.

Rummel, R. J. Applied Factor Analysis. Evanston, Ill.: Northwestern
University Press, 1970.

Roose, K., and Andersen, C. J. A Ratigg of Graduate Programs.
Washington, D. C.: American Council on Education, 1970.

 

Shubik, M. On Different Methods of Allocating;Resources. RAND Report
No. P-4161. New York: RAND Corporation, 1969.

Thomas, S. "DISCRIM2." Technical Report No. 33. Computer Institute
for Social Science Research, Michigan State University, July 5,
1968. (Mimeographed.)

Veysey, L. R. The Emepgence of the American University. Chicago:
The University of Chicago Press, 1965.

Vreeland, R. S., and Bidwell, C. E. "Classifying University Departments:
An Approach to the Analysis of Their Effects." Sociology of Edu-
cation, 39 (Spring, 1966), 237-254.

Williams, R. L. "The Cost of Educating One College Student."
Educational Record, 2 (October, 1961), 322-329.

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