A measurement model of multiple intelligence profiles of management graduates

Abstract

In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner’s nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the managementgraduates for employability. In order to develop a fit measurement model, Structural EquationModeling(SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) managementgraduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM managementgraduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM managementgraduates are just at the borderline.

Full text

A measurement model of multiple intelligence profiles of management graduates
Heamalatha Krishnan and Siti Rahmah Awang
Citation: AIP Conference Proceedings 1842, 030031 (2017); doi: 10.1063/1.4982869
View online: http://dx.doi.org/10.1063/1.4982869
View Table of Contents: http://aip.scitation.org/toc/apc/1842/1
Published by the American Institute of Physics
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A Measurement Model of Multiple Intelligence Profiles of
Management Graduates
Heamalatha Krishnan1, a) and Siti Rahmah Awang1, b)
1Department of Human Resource Development, Faculty of Management,
Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.
a) Corresponding author: heama7@yahoo.com
b) sitirahmah@utm.my
Abstract. In this study, developing a fit measurement model and identifying the best fitting items to represent Howard
Gardner’s nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical
intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal
intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of
the management graduates for employability. In order to develop a fit measurement model, Structural Equation
Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the
instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM)
management graduates for job placement purposes. The initial measurement model contains nine unobserved variables
and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed
to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of
Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates
possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist
intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences
such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal
intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.
INTRODUCTION
Unemployment is a serious issue in developing economies. High unemployment means that labour resources are
not being used efficiently [1]. Unemployed rate in Malaysia was 3.30% in December 2015, up from 3.20% in
November 2015 and slightly above market expectations [2]. Employers are searching for graduates who not only
have good academic results but also possess soft skills such as communication skills, problem solving skills,
interpersonal skills and ability to be flexible. The major issue to be discussed in this study pertains to the role of
multiple intelligences in employment among management graduates and the awareness about one’s multiple
intelligences to get a job.
Howard Gardner introduced Theory of Multiple Intelligences (MI) in his 1983 book Frames of Mind [3].
Initially Gardner identified seven intelligences; however, it later became nine with the addition of two intelligences
[4]. These intelligences include musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical
intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal
intelligence, naturalist intelligence and spiritual intelligence. According to Gardner [3], all humans possess these
intelligences in varying degree where each individual has a personal intelligence profile that consists of
combinations of nine different intelligences types.
The 3rd ISM International Statistical Conference 2016 (ISM-III)
AIP Conf. Proc. 1842, 030031-1–030031-13; doi: 10.1063/1.4982869
Published by AIP Publishing. 978-0-7354-1512-6/$30.00
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Graduates who have clearer understanding of their skills and abilities can identify potential career that fit their
intelligences, and can also expand their career possibilities [5]. Furthermore, individuals who discovered their
multiple intelligence profiles do not need to focus on only one job, as they can explore multiple aspects to have
better career choice. In addition, recognizing one’s MI profiles can enhance self-esteem, self-confidence, and can
improve performance at workplace. Multiple intelligences assist organizations to use human capital more
effectively as understanding MI theory may help the Human Resource personnel to recruit the right candidates for
each position which is critical to the success and failure of their organization [6]. In this study, the application of MI
concentrates on intelligence profile of management graduates for job placement purposes based on Gardner’s nine
MI theory. In order to measure the MI of graduates, Structural Equation Modeling (SEM) was applied where it was
used to develop a measurement model for MI profiles of UTeM management graduates.
RELATED WORK
Mohamed and Awang [5] aimed to find the multiple intelligence profile of graduates in order to enhance the
opportunities of management graduates to secure employment. Two-step cluster analysis is applied in order to
measure and classify the MI of graduates. The cluster is based on the graduates’ demographic background and
Gardner’s nine intelligences. The nine intelligence types of the graduates had been successfully clustered into four
more meaningful clusters based on their intelligence scores and characteristics that agree with Gardner’s MI theory.
Gardner’s Multiple Intelligence (MI) theory was also used by [7]. The purpose of this study is to identify the
intelligence profile of epilepsy patients for job placement purposes using Hierarchical Cluster Analysis. This
research aims to introduce intelligence profiles of people with epilepsy in order to improve the probability of
employment. From this study, three clusters were formed based on their type of intelligence and type of illness. The
results of this study indicated that to be employable and have a successful career, one needs to be skilful in math -
logic, visual/spatial, personal and musical skills.
Gardner’s MI Theory was also used among teachers. In this study, the researchers investigated the MI profile of
science and mathematics teachers. The aim of this study is to ensure science and mathematics teachers realized the
strengths of MI they have and how they can apply them in their teaching. Thus, Sulaiman, Abdurahman, and Rahim
[8] examine the relationship between MI profile of science and mathematics teachers in Malaysia with the teaching
strategies based on MI applied in the classroom. Results from this study showed that teachers’ profile of MI support
them to gain a greater understanding of their prospective intelligence and interests in strengthening their teaching
strategies.
METHOD
Sample
The data of this study are secondary data retrieved from [9] on Multiple Intelligences in Employability among
Universiti Teknikal Malaysia Melaka (UTeM) management graduates. The population was 173 students that
involved graduates from Faculty of Technology Management and Technopreneurship (FPTT), Universiti Teknikal
Malaysia Melaka (UTeM). Out of 173 students, 167 students graduated in the first cohort as remaining 6 students
have extended their academic programme due to their inability to complete the academic programme requirements.
137 out of the 167 questionnaires were completed and returned, which represented a rate of 82.04%. Thus, the
sample size consisting of 137 management graduates was selected.
Research Instrument
The main instrument used in this study is a psychometric test known as the Ability Test in Employment or
ATIEm [9] ATIEm is the improvement of Ability Test in Epilepsy or ATIE© [10]. The first section is about the
demographic profiles of the respondents and consists of 14 items. The other nine sections contain 10 items for each
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section to explore the perceptions of the graduates on their intelligence strengths and weaknesses based on Howard
Gardner’s MI theory. In this section, the respondents will be asked to rate themselves based on a five-point scale,
ranging from 1 (not at all like me) to 5 (definitely me). The format of ATIEm is summarized in Table 1.
Statistical Analysis
The statistical technique used in this study is Structural Equation Modelling (SEM). The technique was used as
it can assess theoretical constructs that cannot be measured directly, referred to as unobserved variables [11]. Hence,
in this study the unobserved variables are Gardner’s nine types of intelligences. These nine unobserved variables
were measured using ATIEm which consists of 90 items. Each unobserved variables was measured by 10 items.
SEM was used to run the Confirmatory Factor Analysis (CFA) to determine the best fitting items to represent each
unobserved variable (Gardner’s nine MI) and to develop a fit measurement model for MI profiles of UTeM
management graduates.
TABLE 1. Distribution of Questions in ATIEm
RESULTS
Participants
Out of 137 respondents, a little less than three-fourths of the respondents (71.5%) were female and a little over
one-fourth (28.5%) were male. It is also clear that more than three-fourths of the respondents (77.4%) were Malay.
15.3% of the respondents were Chinese, and a mere 2.2% of the respondents were Indian while 5.1% were others.
The largest proportion of the respondents (97.1%) were single while 2.9% were married. The results revealed that
the majority (98.5%) of the respondents were aged between 20 to 25 years old and 0.7% of the respondents were in
age group 26-30 and 31 years and above respectively. More than three-fourths of the respondents (78.8%) were
Muslims. A fewer number of respondents (13.1%) were Buddhist and a mere 2.2% were Hindu while 5.8% were
others. 34.3% of the respondents were from Bachelor of Technology Management (BTMM) with Honours
(Innovation Technology) programme, followed by 32.8% from Bachelor of Technology Management (BTMI) with
Honours (High Technology Marketing) and Bachelor of Technopreneurship (BTEC) with Honours respectively.
Section
Item
Number of questions
1
Demographic Information
14
2
Musical
10
3
Bodily/Kinaesthetic
10
4
Mathematical/logical
10
5
Spatial
10
6
Linguistic
10
7
Interpersonal
10
8
Intrapersonal
10
9
Naturalist
10
10
Spiritual
10
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The Factor Loadings for the Initial and Modified Measurement Model
In this study, nine unobserved variables as indicated by the nine ellipses were measured using ATIEm, which
consists of 90 items as represented by the 90 rectangles where each unobserved variable was measured by 10 items
as diagrammatically presented in Fig. 1. Each observed variable loads on one and only one unobserved variable. In
addition, errors of measurement associated with each observed variable (e1 – e90) are uncorrelated as there are no
double-headed arrows connecting any two-error terms. In terms of model estimation, the measurement model in Fig.
1 is computed by means of a default technique in AMOS, namely, the Maximum Likelihood (ML) estimation.
The Maximum Likelihood estimation for the initial and modified measurement model is shown in Appendix A.
It is suggested that each observed variable should, for acceptable construct validity, have a minimum factor loadings
of 0.60 for its hypothesized constructs [11]. 59 items in initial measurement model displayed poor factor loadings
and did not meet the minimum recommended value of factor loadings of 0.60 [11]. Thus, those items were removed
and excluded from further analysis and only 31 items were included. Fig. 2 shows the modified measurement model
while Appendix B shows the constructs used in the modified measurement model. Fig. 2 contains 31 observed
variables which have factor loadings greater 0.60. The 31 items can be categorized into 4 items in musical
intelligence; 3 items in bodily-kinaesthetic intelligence, 4 items in logical and mathematical intelligence, 3 items in
visual-spatial intelligence, 3 items in verbal/linguistic intelligence, 3 items in interpersonal intelligence, 3 items in
intrapersonal intelligence, 4 items in naturalist intelligence and 4 items in spiritual intelligence.
The Goodness-of-fit (GOF) Indices
The analysis of model fit is achieved by a variety of fit indices that subjectively indicate whether the theoretical
model fits the data. In this study, a set of statistical tests were examined to determine model fit such as Normed chi-
square (NC), Incremental Fit Index (IFI) and Root Mean Square Error of Approximation (RMSEA). Normed chi-
square (NC) is a ratio of chi-square (χ2) to the degree of freedom for the model. The number of degree of freedom
for a SEM model is determined by the following equation, where p is the total number of observed variables and k is
the number of estimated (free) parameters. Generally, a NC ratio of two or less indicates a reasonable model fit. The
df is shown in equation below.
df = ଵ
ଶ[(p)(p + 1)] - k (1)
Incremental Fit Index (IFI) assesses how well a specified model fits relative to some alternative baseline model.
To compute the IFI, first the difference between chi-square of the independence model and the chi-square of the
hypothesized model is calculated. Next, the difference between the chi-square of independence model and the
degree of freedom for the hypothesized model is calculated. The IFI is shown in equation as below.
IFI = ௑బ
మି௑ೖ
మ
௑బ
మିௗ௙ೖ (2)
Root Mean Square Error of Approximation (RMSEA) is a measure of discrepancy per degree of freedom.
RMSEA is a badness-of-fit index, in which a zero value indicates the best fits and higher values correspond to worse
fit. The formula for RMSEA is defined in equation below.
RMSEA = ට௑మିௗ௙
ௗ௙ሺேିଵሻ (3)
The comparison of the fit statistics for the initial and modified measurement model is presented in Table 2. The
Normed chi-square (NC) value for the initial measurement as in Fig. 1 is 1.950. The Incremental Fit Index (IFI) for
the initial model is 0.564, which is below the acceptable level of model fit (criterion IFI ≥ 0.90). The Root-Mean-
Square Error of Approximation (RMSEA) is 0.084 which is around the acceptable range of model fit (criterion
RMSEA ≤ 0.08). From this particular set of model fit indices, it can be concluded that the model fit for initial
measurement model is not acceptable, but that some modification might allow in achieving a more acceptable model
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to data fit. After modification of the measurement model, the fit indices yield the following values: [NC = 1.331, IFI
= 0.940, RMSEA = 0.049]. Modification procedures significantly improved the model fit.
Reliability and Average Variance Extracted (AVE) Analysis
Cronbach’s alpha was used in order to assess the internal consistency reliability for each construct. The values
for the nine unobserved variables ranged from 0.719 to 0.930, which were above the suggested benchmark value of
0.70 and indicated that the 31 items were reliable for measuring the respective constructs [12]. AVE reflects the
overall amount of variance in the observed variables accounted for by the unobserved variables. The suggested
accepted level of AVE is 0.50 or above for an unobserved variable. AVE is computed as the total of all squared
standardized factor loadings (squared multiple correlations) divided by the number of items [11]. The formula for
calculating AVE is shown below. The AVE of each factor exceeded 0.50, indicating that the measurement model is
acceptable. Table 3 shows the Cronbach’s alpha and AVE values obtained.
 ൌ σ௅಺
మ
೙
೔సభ
௡ (4)
TABLE 2. Measurement Model Fit Indices
Fit indices Recommended level
Value of Initial
Measurement Model
Value of Modified
Measurement Model
Chi
-square/df or CMIN ≤ 2.0 1.950 1.331
Incremental Fit Index (IFI)
≥ 0.90 0.564 0.940
Root Mean Square of
Approximation (RMSEA)
≤ 0.08
0.084 0.049
TABLE 3. Results of Cronbach’s Alpha and AVE of Modified Model
Section
Factor
α
AVE
1
Musical
0.870
0.635
2
Bodily-kinaesthetic
0.766
0.522
3
Mathematical/Logical
0.930
0.768
4
Spatial/Visual
0.786
0.564
5
Linguistic
0.775
0.537
6
Interpersonal
0.719
0.500
7
Intrapersonal
0.770
0.536
8
Naturalist
0.831
0.561
9
Spiritual
0.871
0.635
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FIGURE 1. Initial Measurement Model
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FIGURE 2. Modified Measurement Model
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DISCUSSION AND CONCLUSION
The study has developed a measurement model that specifies the indicators for each intelligence. The
measurement model is developed through CFA. Based on MI theory, a series of relationships among observed and
unobserved variables were hypothesized. The plausibility of the model is tested with the data. This was done by
assessing the goodness-of-fit between the hypothesized model and the observed data. However, the initial model did
not fit the data and the model was modified and retested until meaningful interpretation was found. Finally, the
modified measurement model which consists of nine unobserved variables and 31 observed variables was found to
be the most fit model for the data. This study describes Gardner’s nine MI among UTeM management graduates and
indicates that the management graduates possess all the nine intelligences in varying amounts and the intelligences
possess is very much related to their field of study. Nurturing and exposure to MI is very important for the graduates
to develop the necessary skills required for them to have successful career.
Four items loaded highly on musical intelligence. Those items are Muz4 (I like to sing as a soloist or part of
group), Muz5 (I remember a lot of song melodies), Muz8 (I find it easy to engage in musical activities) and Muz9
(Family and friend compliment my singing). The result showed that students enjoy themselves singing rather than
neither playing musical instrument nor creating a song. Three items loaded highly on bodily kinaesthetic intelligence.
Those items are Kin6 (I am known for being active all the time), Kin7 (I use a lot of body movements and gestures
when talking) and Kin10 (I like to solve problems through “doing” or “taking” action).
Four items loaded highly on mathematical/logical intelligence. Those items include Math4 (I like answering
mathematical/logical problems), Math5 (I can learn concepts faster when they are supported by numbers and
statistics), Math6 (In school, I used to get high marks/score in mathematics) and Math7 (I like to play with numbers
like counting). It is believed that UTeM management graduates possess the simplest application of
mathematical/logical skill such as basic counting. Among the 10 items in visual/spatial intelligence, three items have
higher factor loadings. Those items include Vis2 (I love to do crafts or arts projects), Vis3 (I have sharp eye for
colour and detail) and Vis9 (If I have to memorize something, I draw a diagram or a picture to help me remember).
Three items loaded highly on verbal/linguistic intelligence such as Ling5 (I learn faster through reading or
discussion), Ling7 (I like talking or writing about my ideas) and Ling8 (I am able to negotiate and convince
someone using words).
Three items loaded highly on interpersonal intelligence. Those items are Inter7 (Before making decisions, I
usually discuss it with my family), Inter8 (I always put myself in other people’s situation) and Inter9 (I am sensitive
to the feelings of others). UTeM management graduates have high sensitivity to other people’s feelings. It is
important for a student to have good interpersonal skills in order to perform well especially in group assignments.
Three items loaded highly on intrapersonal intelligence. Those items are Intra4 (Most of the time, I like myself),
Intra6 (I know my strength and weakness) and Intra7 (I am confident of my own abilities). UTeM management
graduates possess the ability to understand oneself, recognizing emotions and also personal strengths and
weaknesses.
Among the 10 items in naturalist intelligence, four items have high factor loadings. Those items include Nar6 (I
enjoy learning names of living things in the environment like flora and fauna), Nar7 (I like fishing and jungle
trekking), Nar9 (I am actively involved in activities protecting the environment) and Nar10 (I solve problems by
exploring and observing nature, visiting museums and zoos, or doing outdoor activities). Four items in spiritual
intelligence yielded higher factor loadings. Those items are Spr7 (I need to develop meaningful life), Spr8
(Forgiveness is an important part of my spirituality), Spr9 (I frequently feel very close to God in prayer) and Spr10
(My spiritual views have had an influence upon my life). As a graduate who will pursue a job in future, spiritual
intelligence is the key to personal achievement and sustainable lifelong performance at extraordinary levels.
The findings showed that in general, the UTeM management graduates possessed all nine intelligences, either
high or low. According to Gardner’s MI theory, everyone possesses all types of multiple intelligences. However, the
extent to which each is developed in an individual varies from person to person [3]. It is important to nurture all the
intelligences of graduates in order to be successful especially at the workplace [13].
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ACKNOWLEDGMENTS
The authors would like to thank Faculty of Management, Universiti Teknologi Malaysia (UTM). Authors also
appreciate the financial support received from UTM research grant Vote 12H17.
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Management Graduates,” Master's Thesis, University Teknologi Malaysia, 2014.
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Prentice Hall, 2010).
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with Epilepsy,” International Conference on Management, Economics and Social Science (Bangkok, 2011).
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APPENDIX A. Factor Loadings for the Initial and Modified Measurement Model
Variables
Items Initial Model Modified Model
Musical
Muz1
0.549
-
Muz2
0.378
-
Muz3
0.526
-
Muz4
0.713
0.694
Muz5
0.715
0.658
Muz6
0.604
-
Muz7
0.703
-
Muz8
0.877
0.872
Muz9
0.878
0.931
Muz10
0.544
-
Bodily-Kinaesthetic
Kin1
0.499
-
Kin2
0.441
-
Kin3
0.479
-
Kin4
0.651
-
Kin5
0.607
-
Kin6
0.711
0.727
Kin7
0.761
0.705
Kin8
0.626
-
Kin9
0.458
-
Kin10
0.692
0.735
Mathematical/Logical
Math1
0.484
-
Math2
0.644
-
Math3
0.675
-
Math4
0.881
0.873
Math5
0.846
0.873
Math6
0.818
0.865
Math7
0.887
0.895
Math8
0.750
-
Math9
0.514
-
Math10
0.594
-
Visual/Spatial
Vis1
0.662
-
Vis2
0.728
0.803
Vis3
0.744
0.820
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Vis4
0.621
-
Vis5
0.622
-
Vis6
0.572
-
Vis7
0.589
-
Vis8
0.620
-
Vis9
0.714
0.612
Vis10
0.617
-
Verbal/Linguistic
Ling1
0.322
-
Ling2
0.583
-
Ling3
0.584
-
Ling4
0.671
-
Ling5
0.730
0.699
Ling6
0.552
-
Ling7
0.732
0.775
Ling8
0.709
0.723
Ling9
0.619
-
Ling10
0.575
-
Interpersonal
Inter1
0.663
-
Inter2
0.620
-
Inter3
0.662
-
Inter4
0.555
-
Inter5
0.487
-
Inter6
0.640
-
Inter7
0.600
0.524
Inter8
0.664
0.837
Inter9
0.617
0.724
Inter10
0.564
-
Intrapersonal
Intra1
0.477
-
Intra2
0.635
-
Intra3
0.437
-
Intra4
0.643
0.663
Intra5
0.432
-
Intra6
0.565
0.759
Intra7
0.570
0.770
Intra8
0.309
-
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Intra9
0.508
-
Intra10
0.600
-
Naturalist
Nar1
0.672
-
Nar2
0.427
-
Nar3
0.584
-
Nar4
0.509
-
Nar5
0.605
-
Nar6
0.753
0.738
Nar7
0.694
0.674
Nar8
0.680
-
Nar9
0.727
0.791
Nar10
0.767
0.788
Spiritual
Spr1
0.668
-
Spr2
0.659
-
Spr3
0.602
-
Spr4
0.716
-
Spr5
0.661
-
Spr6
0.728
-
Spr7
0.753
0.768
Spr8
0.762
0.776
Spr9
0.765
0.795
Spr10
0.798
0.845
030031-12

APPENDIX B. Constructs and Items in the Modified Measurement Model
Constructs
Items
Items Wording
Musical
Muz4
I like to sing as a soloist or part of group
Muz5
I remember a lot of song melodies
Muz8
I find it easy to engage in musical activities
Muz9
Family and friends love and compliment my singing
Kinesthetic
Kin6
I am known for being active all the time
Kin7
I use a lot of body movements and gestures when talking
Kin10
I like to solve problems through “doing” or “taking” action
Mathematical
Math4
I like answering mathematical/logic problems
Math5
I can learn concepts faster when they are supported by numbers and statistics
Math6
In school, I use to get high marks/score in mathematics
Math7
I like to play with numbers like counting
Visual/Spatial
Vis2
I love to do crafts or arts projects
Vis3
I have a sharp eye for colour and detail
Vis9
If I have to memorize something, I draw a diagram or a picture to help me
remember
Linguistic
Ling5
I learn faster through reading or discussion
Ling7
I like talking or writing about my ideas
Ling8
I am able to negotiate and convince someone using words
Interpersonal
Inter7
Before making decisions, I usually discuss it with my family
Inter8
I always put myself in other people’s situation
Inter9
I am sensitive to the feelings of others
Intrapersonal
Intra4
Most of the time, I like myself
Intra6
I know my strength and weakness
Intra7
I am confident of my own abilities
Naturalist
Nar6
I enjoy learning names of living things in the environment like flora and fauna
Nar7
I like fishing or jungle tracking
Nar9
I am actively involved in activities protecting the environment
Nar10
I solve problems by exploring and observing nature, visiting museums and
zoos,
or doing outdoor activities
Spiritual
Spr7
I need to develop meaningful life
Spr8
Forgiveness is an important part of my spirituality
Spr9
I frequently feel very close to God in prayer
Spr10
My spiritual views have had an influence upon my life
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