Institutional Research in Iowa:
Challenges and Opportunities
Kristin Moser, kristin.moser@uni.edu
Thulasi Kumar, thuslasi.kumar@uni.edu
Office of Information Management & Analysis
University of Northern Iowa
Cedar Falls, IA 50614-0005
November 11, 2004
Purpose of the Survey
„
To better understand the status, nature, strengths and
weaknesses in institutional research functions in Iowa;
„
To stimulate dialogue among IR professionals; and
„
To develop a statewide IR association, either physical
or virtual.
Background
„
Survey instrument modeled from two studies on
the role of IR in Higher Education
„
Anne Marie Delaney from Babson College
„
„
Delaney, A.M. (1997). The role of institutional research in higher
education: Enabling researchers to meet new challenges. Research in
Higher Education, 38(1), 1-16.
William Knight from Bowling Green State University
„
Knight, W.E., Moore, M.E., & Coperthwaite, C.A. (1997).
Institutional research: Knowledge, skills, and perceptions of
effectiveness. Research in Higher Education, 38(4), 419-433.
Population Characteristics
„
„
„
Population
„ 33 Four-year
colleges/universities
„ 16 Two-year colleges
(community, trade etc.)
Sample
„ 22 Four-year
colleges/universities
„ 12 Two-year colleges
(community, trade etc.)
Response Rate
„
„
4-Year response rate = 66.7%
2-Year response rate = 75.0%
Number
Sample Characteristics
20
18
16
14
12
10
8
6
4
2
0
18
11
3
2
Public
Private
Community
College
Institution Type
Other
IR Office Characteristics
„
„
„
„
Mean IR office staff = 2.17 (minimum 1, maximum 5)
Years of experience in IR Mean = 8.62 years (minimum 6
months, maximum 35 years)
Mean FY04 Budget $129,167, median $90,000.
Report to which office…
N
%
Provost/VP for Academic Affairs
14
53.8
Other
5
19.2
Office of the President
4
15.4
VP for Enrollment Management
2
7.7
Office of the Registrar/Student
Services
1
3.8
IR Office Characteristics (cont.)
„
„
Majority of IR staff
members have at least a
Masters degree
Top 5 Degree Fields
„
„
„
„
„
Education
Psychology
Sociology
Business
Higher Ed Administration
N
%
PhD
14
29.2
Masters Degree
19
39.6
Bachelors Degree
10
20.8
Associates Degree
3
6.3
HS Diploma
2
4.2
Total
48
100
Education Level
IR Presence at Institutions
No
12%
No, but
people
engaged
in IR
32%
Yes,
have an
IR office
56%
Percent*
Software in Use
100
90
80
70
60
50
40
30
20
10
0
89.3
71.4
46.4
42.9
21.4
7.1
MS
SPSS/SAS Online/ Mainframe
Office/
scannable
Word
surveys
Perfect
Other
WebFocus
*Numbers do not add up to 100% as individuals were able to choose more than one option
Hardware in Use
100
96.2
94.1
90
80
Percent*
70
60
50
40
30
20
7.7
10
0
IBM
Compatible/PC
Other
Macintosh
*Numbers do not add up to 100% as individuals were able to choose more than one option
IR Membership
Organization
%*
AIR
AIRUM
MidAIR
Other
Associated Colleges of the Midwest
Higher Education Data Sharing Consortium
57.7
42.3
23.1
19.2
11.5
7.7
Society for College University and Planning
7.7
*Numbers do not add up to 100% as individuals were able to choose more than one organization
ra
d
&
Re
t
Ac
en
a d Co
ti
em mm I o n
ic
o PE
Pr n D D
A s og
at S
r
s e am a S
Pr ssm R et
o d en ev
uc t S iew
in
ur
g
Ca F v ey
m ac t s
In
p
b
st
itu Ex us S ook
tio tern ur
v
En na l al R eys
r o Co ep
ll m st
or
A
en n ts
Fa t
a
P r ly s
c
Fi ul
i
na ty ojec s
nc W tio
ia ork n
lA
id Loa
An d
al
ys
is
G
Percent
Key IR Responsibilities
Percent Responding Important or Very Important
100
90
80
70
60
50
40
30
20
10
0
4-Year
2-Year
What Do IR People Know?
Strongest Skills
Weakest Skills
Standard variable categories
Instructional evaluation
Basic counting rules
Faculty workload analysis
Work successfully with others
Student flow modeling
General knowledge of structures
Enrollment forecasting
Written communication
Values and attitudes
Oral communication skills
0
10 20 30 40 50 60
Possess to Large Extent
Expert
0
10 20 30 40 50 60
Possess to Large Extent
Expert
m
an
d
Ca
em
fo
rr
ou
tin
e
pu
re
sp
po
ol
r ti
i
ng
t
i
Re
cs
su
in
te
lt s
re
t
oo
fe
D
re
iff
c
om
.a
nt
pl
ic
ic
N
i
at
pa
ot
ed
ti n
pa
g
rt
re
of
qu
M
le
es
ak
ad
ts
er
in
sh
g
re
ip
po
te
r
am
t
Le
su
ad
nd
er
er
sd
st
D
oo
on
isa
d
'
tw
gr
ee
an
ti
o
La
ve
nf
ri
ck
o.
m
ac
pt
ce
.i
Re
ss
ss
co
ue
t
o
m
s
d
m
ec
en
.m
da
ak
ti o
er
ns
s
in
re
po
r ts
D
Mean
Obstacles to IR
4.0
3.5
3.0
2.5
2.0
1.5
1.0
4-Year Institutions
2-Year Institutions
Information Technology
Applications in IR
„
„
5 institutions (14.7%) reported that they used data mining
techniques and 6 (18.2%) said they planned on investing in data
mining software in the near future
45.5% of respondents have a data warehouse
60
Percent
45.5
40
20
18.2
9.1
9.1
9.1
9.1
Association
Rules
Neural
Networks
Rule
Induction
Sequence
Detection
0
Linear &
Logistic
Regression
Clustering
Pe
rs
o
na
l C ata
M
om
pu ana
g
te
r A em
en
pp
t
lic
R
es
at
io
ea
ns
r
c
St
h
at
D
is
es
tic
ig
al
n
D
A
at
n
aW
al
ys
ar
is
eh
Su ous
i
rv
ey ng
D
es
D
ig
at
n
a
M
M
in
ai
in
nf
g
ra
m
O
eA
pp ther
lic
at
io
ns
O
LA
P
D
Percent
New Training Needed
70
60
50
40
30
20
10
0
4-Year
2-Year
Interest in an All-Iowa IR org?
Type of Organization
%
State level membership
60.9
Web-based
26.1
Combination of types
8.7
Internet newsgroup
4.3
Conclusions
„
„
„
Traditional IR practices still strong
Lack of leadership/advocacy skills
Lack of skills in emerging areas of Information
Technology
Challenges Ahead
„
„
Resource constraint
Emerging Information Technology