Int. Journal of Math. Analysis, Vol. 7, 2013, no. 63, 3125 - 3142
HIKARI Ltd, www.m-hikari.com
http://dx.doi.org/10.12988/ijma.2013.311286
Evaluation of College Choice Set Construction
Questionnaire Using Factor Analysis
P. Mahendran
Department of Mathematics
Bharathidasan Institute of Technology
Anna University, Tiruchirappalli
S. Saravanan
Department of Management Studies
Bharathidasan Institute of Technology
Anna University, Tiruchirappalli
Copyright ©2013 P. Mahendran and S. Saravanan. This is an open access article distributed under
the Creative Commons Attribution License, which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Abstract
The main objective of this paper is to test the validity and reliability of a
questionnaire designed to measure the opinion about the variables which helped in
the formulation of the college choice construct of students who aspired for
engineering education after their higher secondary examination. Thirty nine
variables were identified as variables helping in constructing the choice set for the
selection of institutions by the students. The find out the construct validity, factor
analysis was used and to check the reliability, the Cronbach’s alpha was used. In
this study it was concluded that the questionnaire considered was found to be
construct valid and reliable, from factor and reliability analysis.
Keywords: Choice Set Construct, Questionnaire Design, Factor Analysis,
Reliability and Cronbach’s Alpha
3126
P. Mahendran and S. Saravanan
1. Introduction
In developing countries such as India, after liberalization, mushroom
growth of engineering colleges has lead to the confusion of students in making
their choice of college after their higher secondary examination. In India, a large
number of Engineering Colleges with different categories (such as University
Campus colleges, Constitutional Colleges, Government aided colleges, Selffinancing with Autonomy, and Self-Financing – Affiliating type), large number of
branches of studies, reservation systems etc., has put the students and their parents
into complex situation in selecting a suitable college and branch of study based on
their performance in the Higher Secondary level. Formulation of choice set of the
college is essential for the students after finishing their higher secondary
examination.
The student’s characteristics such as socio economic status, their higher
secondary school performance, parents, friends, role model, school senior and the
influence of school teachers influence, aptitude, academic ability, educational
aspiration, educational achievement and other factors such as campus visits of
students, previous year admissions, ambience, control, advertisement or
publications, and recruiting activities (Chapman, 1981 and Litten 1982), decided
the choice of the college for the students. Location of the institution and its
advantage, Programme outcome / job opportunity/ student expectation and Rank
order (Ritesh patel and Mitesh patel, 2012), place such as urban area, rural area or
sub-urban area in which the institution was located, Institution's fame / Brand
name, cost, financial aid and Institution accreditation (Joseoh Kee Ming Sia,
2013), proximity (Ley Maguire,1980), number of educational institutions in the
home town (Abrahamse, 1996), academic programs / Curriculum (Christopher
confer and Ketevan Mamiseishvili, 2012), size of the institution (Keiling S.B.A,
2006), Parent's expectation and Institution Reputation / Retention and Safety (Poo
Bee Tin et al, 2012) and Student -Teacher interaction (Douglas and Powers,
1985) are the variables that could influence the students motivation in finalizing
their college choice set to continue their engineering education after finishing their
higher secondary examination.
Although the students, motivation level in finalizing their college choice
set is to be taken into account in order to draw valid conclusions about the factors
influencing the formulation of college choice set, it is rather difficult to measure
such attitude (O’Keefe, 2002). One cannot look into students’ minds. They will be
Evaluation of college choice set construction questionnaire
3127
asked to externalize the attitude the researcher is interested in, but then we
probably do not get a truthful answer (Thurstone, 1977). To avoid socially
preferred answers and be able to receive information about an attitude and aspects
related to an attitude, researchers prefer the use of questionnaires asking for a
person’s degree of agreement with evaluative statements about the object of
attitude and related aspects (O’Keefe, 2002).
However, the use of such method does not necessarily mean that reliable
and valid indications of someone’s attitude can be obtained. In the end, some
items can measure a completely different construct than the attitude of interest
(Ratray and Jones, 2007).
In this paper, two statistical methods are discussed extensively with which the
validity and reliability of a questionnaire measuring an attitude and attitude related
aspects can be tested: exploratory factor analysis and Cronbach’s alpha
(Bornstedt, 1977; Ratray and Jones, 2007). To show how these tests should be
conducted and the results interpreted, a questionnaire used to determine the higher
secondary passed out students’ motivation level in finalizing the college choice
will be evaluated.
2. Data
The Population of the given study is the students of engineering colleges
in Tamil Nadu. In Tamil Nadu there are 570 Engineering Colleges which are
controlled by five regional centers of Anna University during the academic year
2013-14. Hence, out of these five regions, one region was selected randomly.
The random selection resulted Trichy region for conducting the study. In Trichy
region 72 Engineering Colleges are available. Out of 72 Engineering colleges,
five engineering colleges have been selected randomly and in each college, 27
students were selected as sample units. The respondents were the first year
students who joined the institution freshly. The respondents were asked to fill a
questionnaire to indicate their opinion level.
The level of opinion of the students focused on 39 research variables
which influence the students in the formulation engineering college choice set.
The respondents had to indicate their opinion level on 39 evaluative statements
about selection of college on a five point Likert Scale (ranging from very high to
very low). In this paper, just the reliability and validity check of the questionnaire
– College Choice Set formulation – is discussed.
3128
P. Mahendran and S. Saravanan
3. Factor analysis
With factor analysis, the construct validity of a questionnaire can be tested
(Bornstedt, 1977; Ratray & Jones, 2007). If a questionnaire is construct valid, all
items together represent the underlying construct well. Hence, one’s total score on
the thirty nine items of the questionnaire of interest should represent the students’
expectation about the college which they join to study engineering course
correctly. Exploratory factor analysis detects the constructs - i.e. factors – that
underlie a dataset based on the correlations between variables (in this case,
questionnaire items) (Field, 2009; Tabachnik & Fidell, 2001; Rietveld & Van
Hout, 1993). The factors that explain the highest proportion of variance the
variables share are expected to represent the underlying constructs. In contrast to
the commonly used principal component analysis, factor analysis does not have
the presumption that all variance within a dataset is shared (Costello & Osborne,
2005; Field, 2009; Tabachnik & Fidell, 2001; Rietveld & Van Hout, 1993). Since
that generally is not the case either, factor analysis is assumed to be a more
reliable questionnaire evaluation method than principal component analysis
(Costello & Osborne, 2005).
3.1. Prerequisites
In order to conduct a reliable factor analysis the sample size needs to be
big enough (Costello & Osborne, 2005; Field, 2009; Tabachnik & Fidell, 2001).
The smaller the sample, the bigger the chance that the correlation coefficients
between items differ from the correlation coefficients between items in other
samples (Field, 2009). The Kaiser-Meyer-Okin measure of sampling adequacy
(KMO) can signal in advance whether the sample size is large enough to reliably
extract factors (Field, 2009). The KMO “represents the ratio of the squared
correlation between variables to the squared partial correlation between
variables.” (Field, 2009, p. 647). When the KMO is near 0, it is difficult to extract
a factor, since the amount of variance just two variables share (partial correlation)
is relatively large in comparison with the amount of variance two variables share
with other variables (correlation minus partial correlation). When the KMO is
near 1, a factor or factors can probably be extracted, since the opposite pattern is
visible. Therefore, KMO “values between 0.5 and 0.7 are mediocre, values
between 0.7 and 0.8 are good, values between 0.8 and 0.9 are great and values
above 0.9 are superb.” (Field, 2009. p. 647). The KMO value of this dataset falls
within the good category (KMO=0. 751).
Another prerequisite for factor analysis is that the variables are measured
at an interval level (Field, 2009). A Likert scale is assumed to be an interval scale
Evaluation of college choice set construction questionnaire
3129
(Ratray & Jones, 2007), although the item scores are discrete values. That hinders
the check of the next condition: the data should be approximately normally
distributed to be able to generalize the results beyond the sample (Field, 2009)
and to conduct a maximum likelihood factor analysis to determine validly how
many factors underlie the dataset (Costello & Osborne, 2005). The result of
normality test is given in table 2.
From table.2 it is inferred that normality test signals non normality of
distribution in this dataset by rendering p-values far lower than 0.05. But based on
the Q-Q plots, It is concluded that the dataset is approximately normally
distributed, and therefore usable in a maximum likelihood factor analysis.
The final step before a factor analysis can be conducted is generating the
correlation matrix and checking whether the variables do not correlate too highly
or too lowly with other variables (Field, 2009). If variables correlate too highly (r
> 0.8 or r < -.8), “it becomes impossible to determine the unique contribution to a
factor of the variables that are highly correlated.” (Field, 2009, p. 648). If a
variable correlates lowly with many other variables, the variable probably does
not measure the same underlying construct as the other variables. Both the highly
and lowly correlating items should be eliminated. The correlation results are
presented in table -3
It is evidenced from the Table 3 that, none of the questionnaire items
correlates too highly with other items, but some correlate too lowly with several
other items. That did not necessarily mean that the items should be eliminated: the
variables with which they do not correlate enough could constitute another factor.
There is one objective test to determine whether the items do not correlate too
lowly: Barlett’s test. However, that test tests a very extreme case of noncorrelation: all items of the questionnaire do not correlate with any other item. If
the Barlett’s test gives a significant result, it can be assumed that the items
correlate anyhow. For the data set of this research the calculated Barlett’s
ψ2 = 1339.465 at 741df p=0.000. Since the Barlett’s test gives a significant result
the items correlate at most were not excluded for factor analysis.
3.2 Factor Analysis
The factor analysis was conducted using SPSS package and the results of
eigen values, factor loadings after varimax rotation and communality values are
given table-4 and table -5
Table 5 portrayed the details of the factors extracted and they were
Institution related factor formed by the variables such as Rank order, Size of the
3130
P. Mahendran and S. Saravanan
institution , Institution accreditation, Institution's fame / Brand name, Programme
outcome / Job opportunity / Student expectation, Previous year admissions,
Safety, Tradition & Activities in the institution, Students control, Student Teacher interaction and Ambience, The Student’s aspiration related factor
formed by Campus visits of the students and Specific academic program /
Curricula and educational aspiration, Locational aspect related factor includes
the number of Educational institutions in the home town, Location of the
institution and Proximity, Students’ related factor includes Class rank, self
image, Aptitude and Achievement, Internal influence factor includes Friends
influence, Relatives/ peers Influence, School teacher influence and School seniors
influence, Students reach related factor includes written information /
advertisement / publications and transport facility, General amenities provision
related factor includes hostel facility and canteen facility, Factor related to
External influence of students formed by influence of role model and Counsellor’s
influence, Infrastructure related factors workshop and laboratory facilities, library
resources, number of faculty members and wifi facilities, Factor related to
Institutional Quality is comprised by the combination of academic qualification
of faculty members and website features and Economy related factor comprises
of financial aid and cost related factors.
4. Cronbach’s Alpha
Field (2009) explained that the questionnaire at issue is reliable when
people completely identical - at least with regard to the students engineering
college choice decision making – should get the same score and people
completely different should get different score. But it was hard to find two
students who were completely equal or unequal. Hence, a questionnaire could be
considered reliable in statistics when an individual item or a set of items rendered
the same result as the entire questionnaire. Field (2009) found the internal
consistency of a questionnaire by dividing the scores from the respondents on a
questionnaire into two equal sets and calculating the correlation between the sets.
A high correlation will signal high consistency.
The internal consistency
represents the reliability of the questionnaire. The reliability of the questionnaire
is measured by Cronbach alpha.
Cronbach α = / (∑ ∑, where N = number of items,
M = Mean, COV = covariance of between scales.
Evaluation of college choice set construction questionnaire
3131
Using SPSS package the Reliability analysis was conducted and the results
were presented in table.6 & 7
The Reliability statistics measure Cronbach’s alpha 0.797 indicated that
questionnaire formulated can be considered as reliable.
5. Conclusions
The questionnaire formulated with 39 variables using Likert Scaling
Technique was evaluated using factor analysis and reliability analysis. The
evaluated questionnaire is considered to be reliable and construct valid. The items
measured the same in the underlying construct. The extraction of eleven factors in
the factor analysis seemed to be consequence of mind set construct of higher
secondary passed out students. The reliability measure is also relatively high.
Hence all the items contributed to the reliability and construct validity of the
questionnaire to a high extent since the item correlate more than 0.4 with the
factors that underlie them the Cronbach’s alpha did not increase when one of the
questionnaire items is deleted.
APPENDIX
Table .1 Statements for the Questionnaire
Variable
Code
V01
V02
V03
V04
Statements
The atmosphere prevailing in the institution is an important factor to be considered
for the selection of an institution for higher educations.
The academic achievements gave me a confidence to build an image of the
institution in which I wish to pursue my Engineering degree
My Natural ability will help me to get seat in a Engineering college of my choice
The institution should have a good Hostel.
3132
P. Mahendran and S. Saravanan
Table1 (Cont’d)
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
The Institutions governed by strict rules and regulations were the institutions of my
choice
The tradition of an Engineering Institution will portray students about their goals
I will follow my school teacher’s advice in the formulation of institution choice
I consider the interaction between a student and the faculty member as one of the
important characteristics in formulation of my Institutional choice set
I have a strong desire to an institution , I wish
I want to get seat in Engineering colleges located in urban area
I visited the campuses of Engineering colleges of my choice set
I wish to select an engineering college in which I can select the branch of my
choice
I want to study in an engineering college situated at my hometown
I wish to choose an engineering college which had a better placement record
The safety and security provided by institution is considered by in the selection of
an Engineering college
I wish to select a reputed institution
Anna University ranking helped me to formulate my choice set among the
institutions
I wish to select an engineering college where previous years admissions were very
high.
I wish to select one the colleges among NBA accredited colleges
I wish to select an engineering college which offers more number of engineering
branches of study
My performance in the school level helped me to estimate the higher secondary
examination marks I can score and hence it is easier for me to formulate the college
choice set
My role model is acting as an influencing factor for selection of the college
The institution should have a well equipped library
The institution should have a good Wi-Fi Facility
The institutions charging nominal fee will be considered by me
The institution should have enough faculty members in all the branches of
engineering they offer
I follow my school senior advise in the selection of the institution
The institution should have more number of Ph.D qualified teachers
The institutions should have good canteen
I wish to study in an institution which is situated near my home town
I follow my friends suggestion to formulate a list of engineering colleges in which
I can select one
Evaluation of college choice set construction questionnaire
3133
Table1 (Cont’d)
V32
V33
V34
V35
V36
V37
V38
V39
I formulate my choice set from the advertisements given by the institutions in
various media
The opinion on myself will be the major influencing factor for the institutional
choice
I follow my relative’s advice in the selection of an institution
I follow the college counselors’ advice for selection of the institution
I expect a good workshop and laboratory facilities in the institution of my choice
I will select an institution where I can get the educational loan and scholarship
easily
I wish to select an institution which offers a good transport facility
The website features of the institutions impressed me by giving details about the
institution so that I am more informative
Table -2 Test of Normality
Variable
Shapiro-Wilks Lambda
Code
Statistic Df Significance
probability
.867 135
.000
V01
.880 135
.000
V02
.796 135
.000
V03
.912 135
.000
V04
.891 135
.000
V05
.901 135
.000
V06
.880 135
.000
V07
.878 135
.000
V08
.879 135
.000
V09
.908 135
.000
V10
.000
.868 135
V11
.882 135
.000
V12
.883 135
.000
V13
.000
.900 135
V14
.880 135
.000
V15
.893 135
.000
V16
.904 135
.000
V17
.890 135
.000
V18
.911 135
.000
V19
.891 135
.000
V20
Variable
Shapiro-Wilks Lambda
Code
Statistic Df Significance
probability
.869 135
.000
V21
.876 135
.000
V22
.869 135
.000
V23
.875 135
.000
V24
.884 135
.000
V25
.888 135
.000
V26
.869 135
.000
V27
.893 135
.000
V28
.905 135
.000
V29
.886 135
.000
V30
.000
.889 135
V31
.878 135
.000
V32
.904 135
.000
V33
.000
.895 135
V34
V35
.880 135
.000
V36
.883 135
.000
V37
.894 135
.000
V38
.892 135
.000
V39
.893 135
.000
P. Mahendran and S. Saravanan
3134
Table 3 Correlation Analysis
V01
V01
V02
V03
V04
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
V32
V33
V34
V35
V36
V37
V38
V39
0.2359
0.4951
0.0283
0.0019
0
0.0068
0
0.0016
0.0945
0.0002
0.0388
0.0799
0.0005
0
0.0002
0
0
0.0038
0.0026
0.2713
0.3911
0.0836
0.4173
0.3765
0.1197
0.1156
0.2083
0.3474
0.1071
0.3809
0.2791
0.4158
0.1425
0.0806
0.4167
0.109
0.0888
0.0284
V02
0.2359
0.3847
0.2907
0.0433
0.4626
0.0823
0.12
0.0744
0.3572
0.2603
0.4502
0.2838
0.3187
0.3174
0.3387
0.0226
0.1437
0.0209
0.3032
0.0089
0.1345
0.0552
0.2709
0.2452
0.0851
0.2531
0.0633
0.2355
0.4194
0.0653
0.3402
0.0795
0.3555
0.2059
0.1822
0.164
0.0688
0.4873
V03
0.4951
0.3847
0.4711
0.0657
0.0852
0.2631
0.1198
0.3317
0.0996
0.0131
0.2798
0.0564
0.3482
0.3631
0.4033
0.1638
0.196
0.3643
0.0972
0.0048
0.259
0.4051
0.1187
0.2618
0.2312
0.0842
0.1657
0.4221
0.4571
0.4085
0.078
0.1081
0.4679
0.0551
0.2918
0.4161
0.1206
0.3021
V04
0.0283
0.2907
0.4711
0.0007
0.0004
0.0001
0
0.0143
0.1535
0.4965
0.4249
0.4255
0
0.0048
0.0034
0.0188
0.0689
0.0819
0.0396
0.2056
0.3015
0.3335
0.5
0.4446
0.3279
0.1357
0.0819
0.2258
0.0978
0.3884
0.2917
0.1908
0.0155
0.1574
0.4002
0.104
0.0663
0.096
V05
0.0019
0.0433
0.0657
0.0007
0.0018
0.0015
0.0043
0.008
0.1525
0.0044
0.2518
0.386
0
0.0003
0
0
0.0005
0.0029
0
0.0784
0.4101
0.1837
0.3504
0.428
0.2326
0.4219
0.1755
0.1916
0.2676
0.2272
0.2123
0.4105
0.1543
0.0033
0.0966
0.074
0.2729
0.4452
V06
0
0.4626
0.0852
0.0004
0.0018
0
0.0001
0.0028
0.4046
0.0088
0.0001
0.3226
0
0.0001
0
0
0
0.0008
0
0.2452
0.1721
0.4307
0.0924
0.0765
0.1274
0.17
0.4747
0.3945
0.2697
0.0259
0.1921
0.1789
0.0473
0.1146
0.4479
0.0393
0.2281
0.3551
V07
0.0068
0.0823
0.2631
0.0001
0.0015
0
0
0.0044
0.2389
0.0022
0.0068
0.044
0.0003
0.0021
0.0215
0.0011
0.0007
0.0369
0.0001
0.2455
0.3585
0.1727
0.4138
0.2919
0.3662
0.0332
0.3735
0.302
0.3711
0.0433
0.0849
0.4474
0.0072
0.335
0.3398
0.405
0.2472
0.464
V08
0
0.12
0.1198
0
0.0043
0.0001
0
0.0013
0.3273
0.0333
0.0025
0.2033
0
0.0001
0
0.0001
0
0.0011
0.0012
0.0339
0.3074
0.4191
0.1769
0.1385
0.1466
0.3884
0.3408
0.3609
0.241
0.2268
0.4747
0.2787
0.2129
0.3109
0.2579
0.0738
0.2926
0.3591
V09
0.0016
0.0744
0.3317
0.0143
0.008
0.0028
0.0044
0.0013
0.0047
0
0
0.1101
0.008
0.0025
0.0125
0.0016
0.0211
0.1246
0.0095
0.2758
0.447
0.1782
0.2172
0.194
0.2662
0.4816
0.0732
0.4551
0.2443
0.184
0.2278
0.2912
0.3628
0.3816
0.4347
0.3302
0.1395
0.413
Evaluation of college choice set construction questionnaire
3135
Table 3 (Cont’d)
V01
V02
V03
V04
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
V32
V33
V34
V35
V36
V37
V38
V39
V20
0.0026
0.3032
0.0972
0.0396
0
0
0.0001
0.0012
0.0095
0.2426
0.0139
0.0018
0.4477
0
0
0
0
0
0
0.4499
0.0695
0.4084
0.0344
0.4039
0.2931
0.3204
0.252
0.268
0.3443
0.4631
0.369
0.2631
0.1443
0.0099
0.3629
0.0241
0.153
0.1415
V21
0.2713
0.0089
0.0048
0.2056
0.0784
0.2452
0.2455
0.0339
0.2758
0.2214
0.4547
0.3805
0.3979
0.0039
0.2369
0.0599
0.3853
0.469
0.3935
0.4499
0.3747
0.2052
0.1063
0.254
0.4674
0.1027
0.3902
0.042
0.5
0.2315
0.0147
0.0002
0.2587
0.4234
0.4082
0.1948
0.3348
0.1068
V22
0.3911
0.1345
0.259
0.3015
0.4101
0.1721
0.3585
0.3074
0.447
0.0932
0.4773
0.2075
0.3215
0.4473
0.2035
0.1294
0.4298
0.0363
0.3791
0.0695
0.3747
0.2833
0.4015
0.3176
0.4004
0.03
0.1755
0.0853
0.4638
0.4942
0.1849
0.1227
0.075
0.0121
0.1475
0.4383
0.0827
0.2801
V23
0.0836
0.0552
0.4051
0.3335
0.1837
0.4307
0.1727
0.4191
0.1782
0.0237
0.3167
0.0736
0.0025
0.3478
0.3159
0.1616
0.4413
0.3803
0.4298
0.4084
0.2052
0.2833
0.2272
0.2697
0.2
0.366
0.2067
0.3624
0.2857
0.4872
0.2817
0.1931
0.3448
0.1304
0.0162
0.4562
0.0022
0.0377
V24
0.4173
0.2709
0.1187
0.5
0.3504
0.0924
0.4138
0.1769
0.2172
0.0203
0.232
0.2001
0.2792
0.2903
0.4597
0.1216
0.1636
0.183
0.1176
0.0344
0.1063
0.4015
0.2272
0.4172
0.203
0.499
0.112
0.0809
0.4147
0.4587
0.2372
0.1265
0.0621
0.0996
0.0102
0.1112
0.4931
0.0259
V25
0.3765
0.2452
0.2618
0.4446
0.428
0.0765
0.2919
0.1385
0.194
0.4711
0.1473
0.4209
0.2959
0.0735
0.1244
0.3434
0.4111
0.4333
0.3811
0.4039
0.254
0.3176
0.2697
0.4172
0.2009
0.4248
0.4048
0.3174
0.1019
0.1422
0.1257
0.3497
0.4868
0.2191
0.2384
0.0693
0.1556
0.2142
V26
0.1197
0.0851
0.2312
0.3279
0.2326
0.1274
0.3662
0.1466
0.2662
0.4024
0.2918
0.2313
0.1496
0.2765
0.1088
0.152
0.3499
0.2081
0.3725
0.2931
0.4674
0.4004
0.2
0.203
0.2009
0.2192
0.1434
0.332
0.3328
0.3333
0.1062
0.4815
0.141
0.242
0.0074
0.0213
0.4954
0.3971
V27
0.1156
0.2531
0.0842
0.1357
0.4219
0.17
0.0332
0.3884
0.4816
0.272
0.3456
0.1263
0.1047
0.3311
0.35
0.3934
0.1376
0.1966
0.2527
0.3204
0.1027
0.03
0.366
0.499
0.4248
0.2192
0.1084
0.3688
0.196
0.0268
0.4177
0.4567
0.1261
0.1214
0.3512
0.1883
0.23
0.3253
V28
0.2083
0.0633
0.1657
0.0819
0.1755
0.4747
0.3735
0.3408
0.0732
0.3963
0.101
0.266
0.3889
0.1892
0.481
0.4021
0.402
0.0763
0.0548
0.252
0.3902
0.1755
0.2067
0.112
0.4048
0.1434
0.1084
0.1535
0.2175
0.2574
0.2669
0.0238
0.1149
0.2011
0.1993
0.0369
0.295
0.0023
V29
0.3474
0.2355
0.4221
0.2258
0.1916
0.3945
0.302
0.3609
0.4551
0.0322
0.3558
0.4941
0.3318
0.2256
0.4247
0.2273
0.1038
0.3397
0.2421
0.268
0.042
0.0853
0.3624
0.0809
0.3174
0.332
0.3688
0.1535
0.4485
0.4332
0.3309
0.3527
0.4026
0.126
0.194
0.3732
0.2587
0.4598
P. Mahendran and S. Saravanan
3136
Table 3 (Cont’d)
V01
V02
V03
V04
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
V32
V33
V34
V35
V36
V37
V38
V39
V30
0.1071
0.4194
0.4571
0.0978
0.2676
0.2697
0.3711
0.241
0.2443
0.0489
0.3507
0.4137
0.0762
0.0142
0.0096
0.1369
0.1767
0.2316
0.303
0.3443
0.5
0.4638
0.2857
0.4147
0.1019
0.3328
0.196
0.2175
0.4485
0.43
0.4368
0.2196
0.1744
0.1827
0.4009
0.2526
0.2936
0.1946
V31
0.3809
0.0653
0.4085
0.3884
0.2272
0.0259
0.0433
0.2268
0.184
0.4742
0.3106
0.3693
0.4131
0.0472
0.0286
0.395
0.2856
0.328
0.4388
0.4631
0.2315
0.4942
0.4872
0.4587
0.1422
0.3333
0.0268
0.2574
0.4332
0.43
0.1268
0.1892
0.0005
0.3849
0.2509
0.2136
0.4815
0.4345
V32
0.2791
0.3402
0.078
0.2917
0.2123
0.1921
0.0849
0.4747
0.2278
0.4845
0.2552
0.379
0.1928
0.0424
0.1782
0.4628
0.4247
0.0311
0.1881
0.369
0.0147
0.1849
0.2817
0.2372
0.1257
0.1062
0.4177
0.2669
0.3309
0.4368
0.1268
0.4019
0.4031
0.2817
0.0838
0.2085
0.175
0.0503
V33
0.4158
0.0795
0.1081
0.1908
0.4105
0.1789
0.4474
0.2787
0.2912
0.1138
0.4251
0.3576
0.4401
0.3985
0.3025
0.3886
0.3751
0.4244
0.3484
0.2631
0.0002
0.1227
0.1931
0.1265
0.3497
0.4815
0.4567
0.0238
0.3527
0.2196
0.1892
0.4019
0.0013
0.2705
0.4356
0.2336
0.0664
0.1031
V34
0.1425
0.3555
0.4679
0.0155
0.1543
0.0473
0.0072
0.2129
0.3628
0.0889
0.4103
0.4712
0.1183
0.4247
0.1248
0.2173
0.1211
0.1846
0.3137
0.1443
0.2587
0.075
0.3448
0.0621
0.4868
0.141
0.1261
0.1149
0.4026
0.1744
0.0005
0.4031
0.0013
0.3536
0.3124
0.2135
0.1346
0.2943
V35
0.0806
0.2059
0.0551
0.1574
0.0033
0.1146
0.335
0.3109
0.3816
0.034
0.1997
0.2483
0.2718
0.0328
0.0237
0.3041
0.2261
0.0298
0.0494
0.0099
0.4234
0.0121
0.1304
0.0996
0.2191
0.242
0.1214
0.2011
0.126
0.1827
0.3849
0.2817
0.2705
0.3536
V36
0.4167
0.1822
0.2918
0.4002
0.0966
0.4479
0.3398
0.2579
0.4347
0.1765
0.4398
0.1706
0.3009
0.3044
0.0919
0.1876
0.1528
0.3743
0.2161
0.3629
0.4082
0.1475
0.0162
0.0102
0.2384
0.0074
0.3512
0.1993
0.194
0.4009
0.2509
0.0838
0.4356
0.3124
0.3404
V37
0.109
0.164
0.4161
0.104
0.074
0.0393
0.405
0.0738
0.3302
0.4164
0.2738
0.4578
0.4559
0.0047
0.3297
0.0218
0.2779
0.1111
0.1878
0.0241
0.1948
0.4383
0.4562
0.1112
0.0693
0.0213
0.1883
0.0369
0.3732
0.2526
0.2136
0.2085
0.2336
0.2135
0.1933
0.4519
V38
0.0888
0.0688
0.1206
0.0663
0.2729
0.2281
0.2472
0.2926
0.1395
0.4008
0.2698
0.033
0.4494
0.0121
0.2612
0.4587
0.315
0.2152
0.4754
0.153
0.3348
0.0827
0.0022
0.4931
0.1556
0.4954
0.23
0.295
0.2587
0.2936
0.4815
0.175
0.0664
0.1346
0.1708
0.401
0.383
0.3404
0.1933 0.4519
0.1708 0.401 0.383
0.0835 0.255 0.4579 0.0284
V39
0.0284
0.4873
0.3021
0.096
0.4452
0.3551
0.464
0.3591
0.413
0.4262
0.2189
0.23
0.2231
0.0468
0.2197
0.1265
0.4372
0.4995
0.2558
0.1415
0.1068
0.2801
0.0377
0.0259
0.2142
0.3971
0.3253
0.0023
0.4598
0.1946
0.4345
0.0503
0.1031
0.2943
0.0835
0.255
0.4579
0.0284
Evaluation of college choice set construction questionnaire
Table-4 Total Variance Explained
Extraction Sums of Squared
Initial Eigen values
Loadings
Component Total % of Var. Cum. % Total % of Var. Cum.%
1
6.108 13.255 13.255 6.108 13.255 13.255
2
3.163
6.863 20.119 3.163
6.863 20.119
3
2.833
6.149 26.268 2.833
6.149 26.268
4
2.663
5.779 32.046 2.663
5.779 32.046
5
2.376
5.156 37.202 2.376
5.156 37.202
6
2.180
4.731 41.933 2.180
4.731 41.933
7
2.114
4.587 46.521 2.114
4.587 46.521
8
1.990
4.318 50.838 1.990
4.318 50.838
9
1.855
4.025 54.863 1.855
4.025 54.863
10
1.803
3.913 58.776 1.803
3.913 58.776
11
1.750
3.797 62.573 1.750
3.797 62.573
12
1.197
13
1.078
14
1.058
15
.992
16
.949
17
.928
18
.886
19
.837
20
.792
21
.771
22
.745
23
.729
24
.638
25
.620
26
.572
27
.547
28
.543
29
.448
30
.431
31
.370
32
.363
33
.325
34
.301
35
.279
36
.241
37
.219
38
.206
39
.181
3137
Rotation Sums of Squared
Loadings
Total % of Var. Cum. %
5.689 12.346
12.346
2.809
6.096
18.441
2.538
5.508
23.949
2.459
5.337
29.286
2.319
5.032
34.318
2.298
4.986
39.304
2.265
4.915
44.218
2.196
4.766
48.985
2.143
4.651
53.636
2.087
4.530
58.166
2.031
4.407
62.573
P. Mahendran and S. Saravanan
3138
Table 5 Rotated Factor Loadings and Communality
V01
V02
V03
V04
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
V32
V33
V34
V35
V36
V37
V38
V39
F1
0.833
0.773
0.756
0.728
0.722
0.716
0.637
0.565
0.549
0.508
0.451
0.242
0.237
0.325
0.024
0.086
-0.061
-0.096
-0.039
-0.103
0.265
0.147
0.115
0.386
-0.064
-0.003
0.076
0.296
-0.089
0.000
0.197
0.044
0.113
0.038
-0.194
0.086
-0.143
0.199
-0.010
F2
0.163
0.120
-0.166
0.231
0.121
0.113
0.274
0.236
0.058
0.189
0.300
0.822
0.773
0.725
-0.066
0.153
0.044
0.055
0.057
0.155
-0.159
-0.205
-0.140
0.198
-0.083
0.198
-0.302
-0.049
0.117
-0.049
-0.042
-0.031
-0.258
-0.381
0.039
-0.145
0.131
-0.068
0.000
F3
0.051
-0.108
0.062
-0.058
0.136
-0.162
0.317
-0.061
-0.006
0.069
0.184
0.042
0.168
-0.109
0.847
0.837
-0.426
0.079
-0.156
0.374
0.045
0.119
0.192
0.073
0.132
0.035
0.009
0.078
0.283
0.000
-0.255
0.057
-0.421
0.178
0.194
-0.095
-0.104
-0.029
0.043
F4
-0.048
-0.164
0.051
-0.037
0.152
-0.010
0.013
0.040
0.061
0.325
0.001
0.036
0.039
0.020
0.080
-0.142
0.059
-0.815
0.665
0.555
0.434
0.110
-0.335
0.200
0.321
0.238
-0.324
0.010
-0.339
-0.066
-0.034
0.010
0.046
0.100
0.300
0.047
-0.028
0.025
-0.027
F5
-0.032
0.042
0.001
0.004
-0.056
0.120
-0.160
0.372
-0.035
0.256
0.025
0.009
0.133
0.133
0.140
-0.063
0.015
-0.021
-0.252
0.075
-0.015
-0.785
0.679
0.599
0.570
0.023
0.066
0.257
0.053
0.009
-0.075
0.023
0.123
0.131
-0.184
-0.131
-0.086
0.016
-0.081
F6
0.149
-0.206
0.004
-0.171
-0.276
0.456
-0.106
0.337
-0.047
0.181
0.426
-0.075
0.005
0.111
-0.023
0.039
0.165
0.282
0.224
-0.155
0.155
0.003
-0.043
-0.019
-0.047
-0.762
-0.546
-0.108
0.024
-0.124
-0.129
-0.109
-0.305
0.239
0.051
0.118
0.421
-0.026
0.264
Evaluation of college choice set construction questionnaire
3139
Table 5 (Cont’d)
V01
V02
V03
V04
V05
V06
V07
V08
V09
V10
V11
V12
V13
V14
V15
V16
V17
V18
V19
V20
V21
V22
V23
V24
V25
V26
V27
V28
V29
V30
V31
V32
V33
V34
V35
V36
V37
V38
V39
F7
0.001
0.006
-0.259
0.123
0.370
-0.015
0.164
0.282
0.358
0.256
0.378
0.014
0.112
-0.209
-0.062
0.069
-0.253
-0.112
0.028
-0.145
-0.359
-0.014
0.144
0.246
-0.386
0.094
0.170
0.770
-0.366
0.189
0.223
-0.079
-0.095
0.252
0.317
0.182
0.049
-0.055
0.109
F8
-0.107
-0.100
0.081
-0.118
0.134
0.139
0.244
0.178
0.013
0.070
0.120
0.049
-0.075
0.116
0.014
-0.250
-0.198
0.112
0.208
0.049
-0.386
0.009
-0.176
0.002
0.365
-0.047
0.311
-0.034
0.260
-0.865
0.691
-0.131
0.093
0.229
-0.125
0.108
0.109
-0.039
0.005
F9
-0.025
-0.082
-0.149
0.052
0.078
0.010
0.159
-0.088
0.179
-0.055
-0.086
0.057
0.062
-0.211
-0.157
0.087
0.060
-0.011
0.022
0.047
0.398
0.103
0.008
0.156
-0.014
-0.174
0.223
0.107
0.272
-0.203
-0.108
-0.905
0.519
-0.449
0.440
-0.011
-0.190
-0.023
0.083
F10
0.012
0.041
-0.109
0.002
-0.120
-0.147
-0.007
-0.031
0.431
-0.114
0.109
0.248
0.167
-0.267
-0.007
0.027
0.008
-0.020
-0.096
-0.019
0.329
0.083
0.151
0.036
0.176
0.017
-0.131
-0.121
0.015
0.189
0.308
0.005
-0.042
0.224
-0.309
-0.837
0.679
-0.085
0.062
F11 COMM
-0.102
0.771
0.105
0.725
-0.005
0.713
0.208
0.692
0.268
0.905
-0.152
0.838
0.116
0.743
0.161
0.778
0.042
0.660
0.077
0.595
-0.011
0.685
-0.154
0.834
0.004
0.751
0.065
0.851
0.010
0.777
-0.067
0.836
-0.374
0.465
-0.080
0.794
-0.023
0.639
-0.169
0.567
0.064
0.859
0.086
0.731
-0.080
0.726
-0.088
0.686
0.308
0.868
-0.111
0.733
-0.148
0.719
0.119
0.808
0.078
0.502
0.136
0.902
0.163
0.789
-0.101
0.871
-0.128
0.672
-0.442
0.826
-0.182
0.642
0.163
0.843
0.118
0.760
0.770
0.652
0.712
0.609
Table 6 Reliability Statistics
Cronbach's
.797
Cronbach's Alpha Based on Standardized
Items
.871
No of Items
39
P. Mahendran and S. Saravanan
3140
Table 7 Reliability Analysis (after subsequent elimination of single variable)
Variable Name
Rank Order
Size Of The Institution
Institution Accreditation
Institution's Fame / Brand
Name
Programme Outcome / Job
Opportunity/ Student
Expectation
Previous Year Admissions
Safety
Tradition And Activities In The
Institution
Control
Student -teacher interaction
Ambience
Campus visits of students
Academic programs /
curriculum
Educational aspiration
Number of educational
institutions in the home town
Location of the institution
Proximity
Class rank
Self image
Aptitude
Achievement
Friends influence
Relatives/ peers influence
School teacher influence
School seniors influence
Written infmn / advt /
publications
Transport facility
Hostel facility
Canteen facility
Influence Of Role Model
Counsellors Influence
Workshop And Laboratory
Corrected
Squared
Cronbach's
Item-Total
Multiple
Alpha if
Item
Correlation Correlation
Deleted
.548
.546
.797
.204
.402
.797
.081
.367
.797
.427
.500
.797
Mean
Std.
Deviation
2.6222
2.5630
2.1407
3.2222
.95313
.96666
1.30534
1.11078
3.4519
1.07702
.506
.494
2.9630
2.8074
2.4889
1.12241
1.00370
1.04999
.596
.557
.565
.660
.503
.558
.797
.797
.797
2.5556
3.1407
2.7630
2.5185
3.1556
.97481
1.04498
.97128
.99889
.96093
.410
.272
.404
.379
.185
.454
.531
.479
.472
.486
.797
.797
.797
.797
.797
3.4148
3.1926
1.03221
1.00370
.729
.622
.734
.587
.797
.797
3.1778
2.8889
2.6222
3.1333
3.0444
2.3333
2.9704
3.1259
2.9333
2.8815
1.17731
1.13734
1.06411
1.22657
1.31505
1.03664
1.47081
1.47835
1.46705
1.41975
.597
.642
.547
.549
.611
-.081
.046
.046
-.052
.148
.680
.623
.614
.503
.622
.406
.317
.379
.390
.240
3.2074
1.34994
.090
.334
.797
.797
.797
.797
.797
.797
.797
.797
.797
.797
.797
3.1037
2.9704
2.8889
3.2222
3.1630
3.0889
1.48763
1.38726
1.30250
1.35859
1.39406
1.45821
.078
.092
.014
-.069
.054
.107
.361
.409
.224
.191
.374
.307
.797
.797
.797
.797
.797
.797
.797
Evaluation of college choice set construction questionnaire
3141
Table 7 (Cont’d)
Library Resources
2.9630
1.31811
.091
.359
.797
Number Of Faculty Members
Wifi Facilities
Academic Qualification Of
Faculty Members
Web Site Features
Financial Aid
Cost
3.1407
3.0815
1.36679
1.43023
.164
.248
.406
.381
2.8889
1.42822
.061
.347
.797
.797
.797
2.9185
2.9556
2.9407
1.38247
1.35969
1.38091
.249
.068
.014
.306
.354
.371
.797
.797
.797
References
[1] Abrahamse, A. and Vernez, G . (1996). How immigrants fare in U.S.
Education. Santa Monica, C A : R A N D Corp.
[2] Bornstedt, G. W. 1977. “Reliability and validity assessment in attitude
measurement”, Attitude measurement. In G. F. Summers (Ed.),.pp 80-99. London,
England.
[3] Chapman, D.,(1981) “A model of student college choice,” Journal of
HigherEducation, 52(5), pp. 490-505.
[4] Christopher Confer and Ketevan Mamiseishvili(2012), College choice of
minority students and admitted to institutions in the council for Christian colleges
and universities’ Journal of College Admission Fall 2012.
[5] Cortina, J.M. (1993). What is coefficient alpha? An examination of theory and
applications. Journal of Applied Psychology, 78, 98-104.
[6] Costello, A.B. & Osborne, J.W. (2005). Best Practices in Exploratory Factor
Analysis: Four Recommendations for Getting the Most From Your Analysis.
Practical Assessment, Research and Evaluation, 10, 1-9
[7] Douglas, P. and S. Powers. 1985. Factors in the choices of higher educational
institutions by students with high ability. Journal of College Student Personnel.
26: 552-53.
3142
P. Mahendran and S. Saravanan
[8] Field, A. (2009). Discovering Statistics using SPSS. Sage: London
Joseph Kee Ming Sia (2013) ,’ University Choice: Implications for Marketing and
Positioning Education 2013, 3(1): 7-14 DOI: 10.5923/j.edu.20130301.02.
[9] Lay L & Maguire, J. (1981), “Coordinating market and evaluation research on
the admission rating process,” Research in Higher Education, 14(1), pp. 71-85.
[10] Litten, L. (1982) “Different strokes in the applicant pool: some refinements
in model of student choice,” Journal of Higher Education, 4, pp. 378.
[11] O'Keefe, D.J. (2002). Persuasion. Theory & Research. Sage: Thousand Oaks.
[12] Poo Bee Tin, Rahmah Ismail, Norasmah Othman and Noorasiah
Sulaiman(2012), ‘Globalization and the Factors Influencing Households Demand
for Higher Education in Malaysia’, International Journal of Education And
Information Technologies,Issue 3, Volume 6, 2012
[13] Rattray, J.C. and Jones, M.C. (2007), “Essential elements of questionnaire
design and development”, Journal of Clinical Nursing, 16, pp 234-243.
[14] Ritesh Patel and Mitesh Patel (2012),’ A Study On Perception And Attitude
Of Students Regarding Factors Which They Consider While Making Selection of
Institute In Mba Programme In Gujarat State, Journal of Arts, Science &
Commerce, Vol.– III, Issue –1,Jan. 2012
[15] Thurstone, L.T. (1977). “Attitudes can be measured”, Attitude Measurement
In: G.F. Summers (Ed). ), pp127-141 Kershaw Publishing Company: London.
Received: November 19, 2013