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CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE
ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING
ENVIRONMENT
Thesigan Nadarajan
Assumption University, Bangkok
Creativity Selected Elements Questionnaire herewith shall be called (CSEQ) as a creative
psychological assessment instrument was developed on the theoretical foundations of “Creative
Product Semantic Scale” by Besemer & Quin (1987) and the “Propulsion Model” by Sternberg,
Kaufman & Pretz (2002). It covered the four innate creativity elements of: Originality, Ingenuity,
Resolution, Synthesis and four external creativity elements of Replication, Redefinition,
Reconstruction, and Reinitiation. CSEQ was applied to study 900 students from three colleges
(Engineering, Architecture and Information Technology) of Nueva Ecija University of Science
and Technology herewith shall be called (NEUST) for: H1o: The significant relationships
between the selected student demographic variables, namely: age, gender, study preference, year
of study, GPA, student reasons for studying their program, and student’s linguistic ability with the
eight creativity elements; H2o: The significant relationships between the selected family
demographic variables, namely: parental family status, family income, and family educational
background with the eight creativity elements. Highlights from the findings of the demographic,
correlational, MANOVA and reliability statistical analyses were: 1) Age, gender, year of study,
student reasons for studying their program, student’s linguistic ability had both positive and
inverse significant relationships to/for creativity; 2) Mother’s educational background and family
income had significant positive and inverse relationships to/for creativity. CSEQ could be: 1) Used
for new student orientation for assessment of student creativity that would enable the development
of creative leadership activities, projects and programs; 2) In the design, implementation and
assessment of creative educational content, methods, strategies and presentations within NEUST
environment; 3) In developing creative-centered experimental hubs for creative designs and
trainings within NEUST environment for those identified with creative forte.
The topic of this current research,
“Creativity Selected Elements Questionnaire
(CSEQ): A Creative Assessment Instrument
for Interactive And Creative Learning
Environment,” was the result of the
researcher’s interest in the study of creativity
in the context of interactive and creative
learning environment. Vernon (1978) notes
that creativity was a buzzword in Educational
Psychology as far back as 1978. It is not
something new in the field of education.
Besides the educational environment, it was
only recently that creativity was explained in
terms of innovation in the work place which
is now becoming crucial for organizational
adaptation and survival. Recognition of
creativity in educational environment and
work place has combined to highlight the
significance of creativity in economic value
and social influence in varied areas of
humanity’s endeavors and achievements that
has evolved to become a need rather than a
want justifying this current study involving
CSEQ, an assessment instrument for
interactive and creative learning environment
(Palmon, 2011).
CSEQ as a creative psychological
assessment instrument was developed on the
theoretical foundations of “Creative Product
Semantic Scale” by Besemer & O’ Quin
(1987) and the “Propulsion Model” by
Sternberg, Kaufman & Pretz (2002). It
covered the four innate creativity elements of:
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Originality, Ingenuity, Resolution, Synthesis
and four external creativity elements of
Replication, Redefinition, Reconstruction,
and Reinitiation.
CSEQ was applied to study 900 students
from three colleges (Engineering,
Architecture and Information Technology) of
NEUST for testing: H1o: There are
significant relationships between the selected
student demographic variables, namely: age,
gender, study preference, year of study, GPA,
student reasons for studying their program,
and student’s linguistic ability with the eight
creativity elements; H2o: There are
significant relationships between the selected
family demographic variables, namely:
parental family status, family income, and
family educational background with the eight
creativity elements.
Definition of Terms
The definition of terms was provided for the
purpose facilitating a clearer understanding.
NEUST refers to Nueva Ecija University of
Science and Technology which is publicly
funded and is located in Cabanatuan city,
Philippines. CSEQ refers to the Creativity
Selected Elements Questionnaire. Positive
Psychology was envisioned by Seligman and
Csikszentmihalyi (2000) as a means to
motivate a change in the fixation with
repairing the “worst things in life to building
positive qualities.” Strengths and Virtues refer
to the six domains of core virtues, namely:
Wisdom & Knowledge; Courage; Humanity
and Love; Justice; Temperance and
Transcendence. Selected Creativity Elements
refers to the eight innate and external
elements of creativity namely: Originality,
Ingenuity, Resolution, Synthesis, Replication,
Redefinition, Reconstruction, and
Reinitiation. Propulsion model refers to the
external criterion as proposed by Sternberg,
Kaufman & Pretz (2002). Innate creativity
refers to creativity elements of Originality,
Ingenuity, Resolution and Synthesis. External
creativity refers to creativity elements of
Replication, Redefinition, Reconstruction,
and Reinitiation. Originality was defined by
Stokes (1999) as a kind of novelty that was
useful, valuable and generative. Ingenuity,
refers to smartness, originality and innovative
in generating one-of-kind solutions for
problems and needs (Peterson and Seligman,
2004). Resolution allows for the creation of
something which is valuable, logical, useful,
and understandable (Besemer & O’Quin,
1987). Synthesis refers to links that are
constructed between two or more apparently
separate ideas (Sternberg, Kaufman & Pretz,
2002). Replication refers to the known which
is transferred to a new setting” (Sternberg,
Kaufman & Pretz, 2002). Redefinition refers
to the known which is extended in a new
direction (Sternberg, Kaufman & Pretz,
2002). Reconstruction refers to the new life
that is breathed into an approach previously
abandoned (Sternberg, Kaufman & Pretz,
2002). Reinitiation refers to the thinking that
begins at a radically different point from the
current one and takes off in a new direction
(Sternberg, Kaufman & Pretz, 2002).
Literature Review
In the literature review, the researcher
examined the theoretical justifications for: 1)
Contribution of positive psychology through
the six strengths and virtues domains to the
study of creativity (Peterson & Seligman,
2004); 2) The selection of eight creativity
elements used for the development of CSEQ
derived from the “Creative Product Semantic
Scale” by Besemer & Quin (1987) and the
“Propulsion Model” by Sternberg, Kaufman,
& Pretz (2002); 3) The use of each of the
eight elements of creativity (Originality,
Ingenuity, Resolution, Synthesis, Replication,
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Redefinition, Reconstruction, and
Reinitiation) derived from (Sternberg,
Kaufman & Pretz, 2002); 4) The study of the
demographic variables of the two hypotheses
(Piers, 1968; Kuhn & Holling, 2009).
Method
Research Design
The current study is a causal comparative
research that incorporates descriptive and
inferential analyses methodology to achieve
its objectives.
Participants
A total of 900 participants from three
colleges (Engineering, Architecture and
Information Technology) of NEUST
comprised the study sample. The breakdown
of student demographics consisted of 65.3%
(n=588) male students and 34.7% (N=312)
females. Their ages ranged from 15 to 32
years, with a mean age of 19 years. The
samples for study preferences included
abstract, social sciences, religion, science,
arts, technical and math. In terms of ethnicity,
they were all Pilipino and this was why
ethnicity was not included as a variable in the
demographics as statically it would be
meaningless. A purposive sampling technique
was utilized for data collection as the research
was targeted for the three colleges with seven
study preferences. Participants gave informed
consent prior to answering the questionnaires
which were voluntary and involved no
compensation. Strict confidentiality was
observed to protect privacy
Instrumentation
CSEQ was divided into two sections:
demographics and question items. The
demographic sections were further divided
into: 1) Student; 2) Family; 3) Family
Education Background; 4) Reasons for
Choosing the Program and 5) Student’s
Linguistic Ability categories.
The questions items section consisted of a
Likert scale of 40 items with a five point
responses (1 – Not At All, 2- Seldom, 3 –
Uncertain, 4 – Often, 5 – All the Time).
The item coding consisted of five items for
each of the eight scales of: Originality (items
2, 4, 18, 14, 23); Ingenuity (items 5, 17, 32,
28, 36); Resolution (7, 21, 25, 19, 34);
Synthesis (8, 24, 12, 37, 27); Replication
(items 9, 31, 38, 16, 33); Redefinition (items
10, 29, 35, 22,39); Reconstruction (items 6,
40, 13, 26, 30); and Reinitiation (items 11, 15,
20, 3, 1).
Data Collection Procedures
The data collection process was carried out
in two stages: the pilot study and the actual
data collection. The pilot study of 100 %
(n=300) cases was conducted on forty items.
A Cronbach alpha of .886 (.89) was obtained
which confirmed the participant’s
comprehension of the scale items.
Actual Data Collection
For the actual data collection, a total of
1,050 CSEQ questionnaires were distributed
to the three colleges, each receiving 350
copies. Out of the 1,050 CSEQ questionnaires
were distributed, only 920 were returned to
the researcher. The rest (130 questionnaires)
were either lost or unaccounted for at the time
of the collection. When the 920
questionnaires were individually inspected for
errors, 20 questionnaires were found to be
non-usable due to respondents’ error in
answering. Only 900 valid questionnaires
were utilized for data analysis.
Data Analysis
4
The valid 900 questionnaires (n= 900) were
statistically analyzed for Frequency,
Percentile, Reliability, Pearson Correlation,
MANOVA gender differences output.
Results
Demographic Analysis
The demographics profile of respondents
consisted of two categories namely, student
demographics backgrounds and family
demographics backgrounds. In terms of
student demographics backgrounds, the
sample consisted of 900 students; 65.3%
(n=588) male students and 34.7% (N=312)
females. Their ages ranged from 15 to 32
years, with a mean age of 19 years. In terms
of ethnicity, they were all Pilipino and this
was why ethnicity was not included as a
variable in the demographics as statically it
would be meaningless. Their study
preferences in an ascending order were as
follows: 3.4% (N=31) abstract, 14.4%
(N=130) social sciences, 6.7% (N=60)
religion, 14.4% (N=130) science, 16.6%
(N=149) arts, 25.7% (N=231) technical and
28.8% (N=259) math. In terms of year of
study in ascending order, there were: 18.2%
(N=164) 1st
year, 22.4% (N=202) 2nd
year,
27.8% (N=250) 3rd
year, 21.4% (N=193) 4th
year, 9.7% (N=87) 5th
year and .4% (N=4) 6th
year students. For GPA in ascending order:
6.3% (N=57) were 1.0, 8.0% (N=72) were
1.25, 8.2% (N=74) were 1.50, 8.8% (N=79)
were 1.75, 16.1% (N=145) were 2.0, 16.4%
(N=148) were 2.25, 19.0% (N=171) were
2.50, 16.4% (N=148) were 2.25, 19.0%
(N=171) were 2.50, 12.7% (N=114) were
2.75, 4.1 (N=37) were 3.0 and .3% (N=3)
were 5.0. Their reasons for their choice of
programs were: 26.1% (N=235) considered
them to be their field of interest, 15.8%
(N=142) had related basic knowledge /
experience, 19.1% (N=172) were graduates in
those programs, 26.0% (N=234) saw them as
an opportunity to study and work abroad,
10.8% (N=97) saw them as opportunity to
begin and manage their own businesses and
2.2% (N=20) chose because they felt they
couldn’t find jobs for lesser qualifications. In
terms of linguistics, for spoken languages:
2.3% (N=21) spoke 1, 65.0% (N=585) spoke
2, 9.1% (N=262) spoke 3, 1.3% (N=12) spoke
4 and 2.2% (N=20) spoke 5. In terms of
linguistics, for written languages: 3.8%
(N=34) wrote 1), 68.0% (N=612) wrote 2,
24.4% (N=220) wrote 3, 1.9% (N=17) wrote
4, 1.8% (N=16) wrote 5 and .1% (N=1) wrote
6. For family demographics backgrounds, the
areas covered were parental family status in
ascending order: 91.0% (N=819) were
married, 6.9% (N=62) were separated, .2%
(N=2) were divorced, 1.6% (N=14) were
remarried and .3% (N=3) were orphaned. For
family income in pesos in descending order:
11.4% (N=103) earned >25,000.00, 14.0%
(N=126) earned 20,000 to 25,000.00, 17.0
(N=153) earned 15,000.00 to 20,000.00,
19.7% (N=177) earned 10,000.00 to
15,000.00, 22.1% (N=199) earned 5,000.00 to
10,000.00, 15.8% (N=142) earned < 5000.00
and .1% (N=1) earned 64.00. In terms of
family educational backgrounds for fathers:
5.1% (N=46) were elementary levels, 3.9%
(N=35) were elementary graduates, 8.0%
(N=72) were high school levels, 20.9%
(N=188) were high school graduates, 27.4%
(N=247) were college levels and 34.7%
(N=312) were college graduates. For family
educational backgrounds for mothers: 4.3%
(N=39) were elementary levels, 4.4% (N=40)
were elementary graduates, 7.7% (N=69)
were high school levels, 24.9% (N=224) were
high school graduates, 20.2% (N=182) were
college levels and 38.4% (N=346) were
college graduates.
Reliability Analyses
Prior to computing the eight scales of
CSEQ, Reliability analysis was conducted on
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the items that represented these scales. The
Cronbach alpha coefficients were: Originality
(.48), Ingenuity (.50), Resolution (.50),
Synthesis (.37) and four external creativity
elements of Replication (.44), Redefinition
(.49), Reconstruction (.35), and Reinitiation
(.32). The computed Cronbach’s alpha
coefficients for all eight scales were a low to
high and ranged from .32 to .50. This was
expected given the small number of items
representing each scale. The computed
Cronbach’s alpha coefficient for the eight
scales of CSEQ was .84. Items are considered
internally consistent if their corrected item-
total correlations (I-T) are ≥ .33 which
represent approximately 10% of the variance
of the total scale accounted for in the analysis.
The corrected item - total correlations (I-T)
were from a low (.47) to high (.64) which
clearly proved internal consistency of the
eight scales of CSEQ that justified its use.
Hypothesis Testing
The results of the two hypotheses testing
were as follows:
H1o: There are significant relationships
between the selected student demographic
variables, namely: age, gender, study
preference, year of study, GPA, student
reasons for studying their program, and
student’s linguistic ability with the eight
creativity elements.
A Correlational analysis of the selected
student demographic of: age, study
preference, year of study, GPA, student
reasons for studying their program, and
student’s linguistic ability with the eight
creativity elements found that: 1) Age had
positive significant relationship with
Replication (r=.088, p<.05); 2) Year of Study
had an inverse significance relationship with
originality (r=-.077, p<.05) and redefinition
(r=-.076, p<.05); 3) Student reasons for
studying their program had positive
significant relationship with Synthesis
(r=.067, p<.05); 4) Student’s linguistic ability
(spoken and written language) had positive
significant relationship with Synthesis
(r=.067, p<.05), (r=.075, p<.05) and
Reinitiation (r=.087, p<.05);
A multivariate analysis of variance
(MANOVA) was employed to test for gender
difference among the eight creativity
elements. The analysis yielded significant
overall gender effect among the eight
creativity elements, multivariate Pillai F Pillai
F (8,890)=2.71, p<.05. However, follow-up
tests of between-subject effects yielded
significant male gender effects for the
creative element of originality F(1,897)=4.91,
p<.05; ingenuity (1,897)=4.70, p<.05;
Replication F(1,897)=7.50, p<.05 and
Reconstruction F(1,897)=11.11, p<.05.
H2o: There are significant relationships
between the selected family demographic
variables, namely: parental family status,
family income, and family educational
background with the eight creativity elements.
A Correlational analysis of the selected
family demographic variables, namely:
parental family status, family income, and
family educational background with the eight
creativity elements found that: 1) Family
educational background (mother’s
background) had a significant positive
relationship with resolution (r=.084, p<.05)
and Redefinition (r=.074, p<.05). 2) Family
income had a significant inverse relationship
with ingenuity (r=-.071, p<.05); resolution
(r=-.077, p<.05); redefinition (r=-.073,
p<.05).
Discussion
The researcher will divide the discussion of
the findings into: 1) Findings from the
6
Demographic analysis; 2) Findings on gender
difference; 3) Findings from Hypothesis one
and 4) Findings from Hypothesis two of this
research.
Demographic Findings
The notable highlight from the demographic
findings is the students’ mean age. The
students’ ages ranged from 15 to 32 years,
with a mean age of 19 years. What does the
mean age indicate? According Stang & Story
(2005), the students are in the adolescent
period that emphasizes on biological,
psychosocial and cognitive changes. And how
does the transitional stage affect adolescence
creativity? Wai, Lubinski, & Benbow (2005)
reports in their longitudinal study that spans
from age 13 to 33, that adolescence are prone
to qualitative accomplishments when
creativity is paired with their preferences.
Thus, the opportunity to inculcate the students
Engineering, Architecture and Information
Technology within NEUST for qualitative
accomplishments by pairing creativity with
their preferences is open by the status of the
students’ mean age.
Discussion of Findings Of Hypothesis 1
Age had positive significant relationship
with Replication (r=.088, p<.05).
What has age to do with creativity element
of replication? Researches related to age and
creativity has pointed out that creativity can
decline or increase with age. (McCrae,
Arenberg, & Costa, 1987). And the creativity
element of replication in which the known is
extended in a new direction, can also decline
or increase with age. In the field of music, it
was found that classical composers were able
to extend their known knowledge in new
directions in terms of “melodic originality,
melodic variation, repertoire popularity,
aesthetic significance, listener accessibility,
performance duration, and thematic size” as
they aged (Simonton, 1991b). Thus, the
students from the colleges of Engineering,
Architecture and Information Technology
within NEUST have the potential to extend
their creativity abilities and skills in new
directions as they mature with age.
Year of Study had an inverse significance
relationship with originality (r=-.077, p<.05)
and redefinition (r=-.076, p<.05).
This specific finding indicates that an
increase in students’ year of study have a
decrease (inverse) in their creativity element
of originality (novelty / generative) and
redefinition (the known is extended in a new
direction) creativity elements. Why? A
possible explanation can be found in an article
by Maisuria (2005) who noted the demise of
creativity (originality / replication) in the
national curriculum of England and Wales
due to the demands of “standardization,
centralization, and vocationalization of
education” that focused on business-education
orientation rather than a student-centered
learning experience. Depending on the year of
study, the students from the colleges of
Engineering, Architecture and Information
Technology within NEUST whose exposure
(lesser / greater) to the demands of
standardization, centralization, and
vocationalization of education may similarly
focus on business-education-orientation and
passing of examinations resulting in the
decline of creativity (originality /
redefinition). Thus, as an institution it is
necessary to strategize towards a balance
between creativity and bureaucratic demands.
Student reasons for studying their program
had positive significant relationship with
Synthesis (r=.067, p<.05).
Student reasons for the choice of their
programs were positively associated with the
7
creativity element of synthesis. Why?
Synthesis involves linking between two or
more apparently separate ideas (Sternberg,
Kaufman & Pretz, 2002). When a student
chose a program, he/she had to determine
between multiple reasons in which each
reason might have multiple advantages and
disadvantages. In making a final decision, the
student had to link (synthesize) the various
reasons, advantages and disadvantages to
derive to a specific reason to support their
final choice. Thus, it is natural for the student
to endorse the creativity element of synthesis.
Student’s linguistic ability (spoken and
written language) had positive significant
relationship with Synthesis (r=.067, p<.05),
(r=.075, p<.05) and Reinitiation (r=.087,
p<.05).
Why was there a positive relationship
between student’s linguistic ability (spoken /
written language) and creativity element of
synthesis? The explanation may be found in
the research done on spoken and written
language. Olofin & Olusoji (2013) concluded
that written and spoken languages are two
different things and requires two different
skills. The students endorsement of synthesis
highlights the fact that different and separate
ideas and skills had to be linked together to
bring about comprehension in communication
(written & spoken). Thus, it was natural for
the students to find a relationship and thereby
endorse their linguistic abilities (written &
spoken) with creativity element of synthesis.
Another important point is that spoken
language in linguistics is always a blending
within a social-cultural background that gives
meanings to words that are used in shared
communications (Samovar & Porter, 1987).
When the students found a positive
relationship between their spoken language
and the creativity element of Reinitiation –
they were endorsing their willingness to
explore shared ideas and meanings in a
different social-cultural linguistic platform
than the one they were in currently. In short,
they are willing to explore new starting points
and directions in their lives (Sternberg, 2006).
Findings On Gender Difference
There was overall gender effect among the
eight creativity elements, multivariate Pillai F
(8,890)=2.71, p<.05. The follow-up tests of
between-subject effects also yielded
significant male gender effects for the
creative element of originality F(1,897)=4.91,
p<.05; ingenuity (1,897)=4.70, p<.05;
Replication F(1,897)=7.50, p<.05 and
Reconstruction F(1,897)=11.11, p<.05. This
finding raises the issue for the need to
develop the female students of the three
colleges who lag behind in the creativity
elements. It is not unusual as females still live
in a ‘Patriarchy world’ (male ruled) in which
the female gender suffers from
discriminations, exploitations and inequalities
which is not helpful for creative
psychological developments (Walby, 1990).
Findings on Hypothesis 2
Family educational background (mother’s
background) had a significant positive
relationship with resolution (r=.084, p<.05)
and Redefinition (r=.074, p<.05).
It is interesting to note that the family
educational background of the fathers had no
significance relationship with the eight
creativity elements. While the family
educational background of the mothers had
significant positive relationships with the
eight creativity elements namely, resolution
and Redefinition. Fasko (2000-2001) in his
article entitled “Education and Creativity” had
pointed out that creativity can be developed
through education as creative activities are
8
instances of learning. This findings together
with the proposal of Fasko establishes that
females living in a Patriarchy world (male-
ruled) can develop creativity through
education. In short, learnings and education
empowers females to be creative (Robinson,
2001).
Family income had a significant inverse
relationship with ingenuity (r=-.071, p<.05);
resolution (r=-.077, p<.05); redefinition (r=-
.073, p<.05.
Kiernan & Mensah (2011) have clearly
shown in their research that parenting styles
and persistent poverty is detrimental to
children’s’ development including creativity.
It is interesting to note in the current research
that an increase in family income (economics)
has an inverse impact on the creativity of
children. How can this be explained? Despite
the abundance of economic resources,
children may decline in ingenuity (smartness,
originality and innovative in generating one-
of-kind solutions for problems and needs) if
they are exposed to poor parenting styles
(Ermisch , Iacovou & Skew, 2011). In short,
though persistent poverty affects creativity -
economic abundance with poor parenting
styles also may lead to a decline in creativity.
Conclusions
The findings of this current research have at
least three immediate uses: 1) It can be used
for new student orientation for assessment of
student strengths that would enable the
development of student leadership activities,
projects and programs; 2) It can be used in the
design, implementation and assessment of
creative educational content, methods,
strategies and presentations within university
environments; 3) It can be used in developing
a creative-centered experimental hubs for
creative designs within a university
environment for those identified with creative
strengths.
Limitations of the Study
The researcher would like to list five
limitations of this study: 1) The single
ethnicity of the sample (Pilipino) only could
limit the objectivity of a wider possible
responses; 2) The CSEQ questionnaire is a
type of self-report measurement which is
dependent on the participants’ truthfulness in
responding to the question items that cannot
be realistically validated. The honesty of the
respondents is accepted in good faith; 3) The
question items can be rephrased and
redesigned according different social-cultural
perspectives that may affect the responses of
the participants. 4) There is the possibility of
additions of more than eight creativity
elements which may prove the present
research to be limited in its coverage of the
scope of creativity elements; 5) There could
be a limitation factor in the findings through
the lack of execution of the CSEQ in other
languages.
Delimitations
The researcher would like to list two
delimitations of this study. 1) CSEQ was
designed for measuring the eight creativity
elements and therefore it cannot be
generalized for other forms of study (i.e.,
personality); 2) The current study was
designed for student population (university
level) and therefore caution must be exercise
in generalizing to other age groups (i.e., high
school).
Due to the above limitations and
delimitations, the findings of this research
should be interpreted with caution. However,
regardless of the above limitations and
delimitations, the study of CSEQ is a new
psychological instrument for measuring the
eight creativity elements but is based on the
9
strong theoretical foundations of established
researches.
Recommendations
The recommendations based on this study
are:
1) Validation of CSEQ instrument within a
multi-cultural population
In order to counter the points of one, three
and five in Limitations, it is recommended
that future research of CSEQ be conducted
within multi-cultural populations.
2) Future studies with different
demographic parameters for generalization
purposes.
In order to counter the point 2 in
Delimitations, it is recommended that future
researches would be designed to include
different demographic parameters (age
groups) for wider generalizations.
Since this research utilizing CSEQ as a
psychological assessment instrument is new,
this research is only meant to be a pilot or
exploratory study for more substantial
research in the area of the eight creativity
10
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12
APPENDICES
13
APPENDIX A: CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ)
14
CREATIVITY: SELECTED ELEMENTS QUESTIONNAIRE (CSEQ)
Dear Participants,
The researcher is currently conducting a research on “Sustainable Educational Development:
Identifying, Describing and Comparing Selected Elements of Creativity that may Promote
Educational Excellence,” and gratefully thank you for your voluntary participation in answering
this questionnaire. All information collected will be kept confidential and secured.
DEMOGRAPHICS
Student’s Demographics
Age Gender Study Preference Year of
Study in
College
GPA
Fill in,
________yrs
Check relevant,
Male__ / Female__
Check relevant,
Arts:___/ Science:
____ / Math: ___ /
Technical: ___ /
Abstract: ___ / Social
Sciences: ___ /
Religion: ___
Check
relevant,
1st
:___
2nd
: ___
3rd
: ___
4th
: ___
5th
: ___
Fill in the correct
answer on the
line below,
1.0 / 1.25 / 1.50 /
1.75 / 2.0 / 2.25 /
2.50 / 2.75 / 3.0 /
5.0 / Inc / D
15
Family Demographics
Parental Family Status
Married (M) / Separated (S) /
Divorced (D) / Remarried (R) /
Orphaned (O)
Family Income
1: 25,000 > / 2: 20,000 – 25,000 / 3: 15,000 – 20,000
4: 10,000 – 15,000 / 5: 5,000 – 10,000 / 6: 5,000 <
Strike off the irrelevant,
M / S / D / R / O
Circle your selection,
1: / 2: / 3: / 4: / 5: / 6:
Family Educational Background
Mother
Check,
Father
Check
Elementary Level Elementary Level
Elementary Graduate Elementary Graduate
High School Level High School Level
High School
Graduate
High School
Graduate
College Level College Level
College Graduate College Graduate
16
Reasons for Choosing the Program
Check relevant,
My field of interest
I have basic knowledge / experience related to this program
Graduates in this program are in demand
Opportunity to study / work abroad
Opportunity to begin and manage my own business
I can’t find jobs for lesser qualifications
Student’s Linguist Ability
Number of Spoken Language
Circle number,
Number of Written Languages
Circle number,
1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9
/ 10
1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9
/ 10
17
Answering Questions
Please answer all questions by checking your relevant choice in the blank space below the
choices,
1. Have you tried travelling on a different route to reach a same destination?
1 - Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 - All the Time
2. Have you ever chosen an entirely new solution to solve an old repetitive problem?
1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time
3. Have you ever tried changing your hair style to have new look?
1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 - All the Time
4. Have you chosen an old solution to solve an entirely new problem?
1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time
5. Have you ever thought that in the absence of any other resources, trying to cross a
torrential river on a fallen tree log was a feasible idea?
1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time
6. Have you ever considered analyzing a problem by viewing it under different scenarios?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
7. Have you preferred value in quality over cheapness in cost when making decisions for
personal purchases?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
18
8. Have you tried generating a new idea using two existing ideas?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
9. Have you ever wondered whether the performance of the pop group “KARA” can be
replicated in your own country?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
10. Have you tried using “H2o” rather than “water” in your daily conversation?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
11. Have you ever considered moving to a different town or city to restart a same business that
has failed in the current venue?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
12. Have you ever wondered, what is the common link between Hitler, Jack the Ripper and
Nero?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
13. Have you ever tried using bamboo to make arrows, planks for flooring and a spear?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
14. Have you risked venturing into a new and unknown project or business?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
15. Have you considered studying an entirely new course in the event you fail your present
course?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
19
16. Have you considered that a replicated version of a hit song can be equally valuable in price
and quality?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
17. Have you ever thought that you could find a way to cross a field filled with landmines,
poisonous snakes and pitfalls?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
18. Have you supported any law or a group that protects an original work of art, authorship or
music?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
19. Have you tried to understand comprehensively the functions of the products that you
bought?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
20. Have you ever considered learning a foreign language for a new vocational move in your
life?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
21. Have you used logical reasoning during emotional conflicts?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
22. Have you ever been convinced that a same element can be transformed into water, gas, and
ice?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
20
23. Have you bought and used an entirely revolutionary new electronic product that had no
performance track record?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
24. Have you thought that a new religion can be created by combining two or more existing
religions?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
25. Have you considered the usefulness of the things or products you have bought?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
26. Have you tried taking a short story and rewriting it to have a different conclusion but with
the same characters?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
27. Have you ever thought why children became more active after eating more sweets or
chocolates?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
28. Have you ever thought how you can remember a thousand contact names and phone
numbers without any form of gadget aid?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
29. Have you ever tried painting a same picture in water color, charcoal, and oil color?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
30. Have you ever thought that wine can be made out of mango rather than grapes?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
21
31. Have you seen, purchased or owned a replicated art piece?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
32. Have you ever tried to get an income without working, without breaking any laws and
without asking anyone for help?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
33. Have you ever tried replicating a successful activity, project, or business?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
34. Have you ever asked yourself that according to your income status, whether buying a
hummer is logical?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
35. Have you ever thought that Michael Jackson’s portrait in color is the same when it is in
black and white?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
36. Have you ever thought how you can remember a thousand faces without any form of
gadget aid?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
37. Have you ever linked your feeling of freshness with the amount of sleep you have had
daily?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
22
38. Have you ever tried replicating you friends’ successful study methods and strategies?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
39. Have you ever tried singing a same song in country, rock and hip-hop?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
40. Have you ever tried to remake a broken toy into a different one?
1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
23
APPENDIX B: ITEM CODING FOR CREATIVITY: SELECTED ELEMENTS
QUESTIONNAIRE (CSEQ)
24
ITEM CODING FOR CREATIVITY: SELECTED ELEMENTS QUESTIONNAIRE
No Items Creative Elements
2
4
18
14
23
Have you ever chosen an entirely new solution to solve an
old repetitive problem?
Have you chosen an old solution to solve an entirely new
problem?
Have you supported any law or a group that protects an
original work of art, authorship or music?
Have you risked venturing into a new and unknown project
or business?
Have you bought and used an entirely revolutionary new
electronic product that had no performance track record?
Originality
25
5
17
32
28
36
Have you ever thought that in the absence of any other
resources, trying to cross a torrential river on a fallen tree
log was a feasible idea?
Have you ever thought that you could find a way to cross a
field filled with landmines, poisonous snakes and pitfalls?
Have you ever tried to get an income without working,
without breaking any laws and without asking anyone for
help?
Have you ever thought that it was possible to eat using your
feet while your hands are tied behind your back?
Have you ever thought how you can remember a thousand
contact names and phone numbers without any form of
gadget aid?
Ingenuity
26
7
21
25
19
34
Have you preferred value in quality over cheapness in cost
when making decisions for personal purchases?
Have you used logical reasoning during emotional conflicts?
Have you considered the usefulness of the things or products
you have bought?
Have you tried to understand comprehensively the functions
of the products that you bought?
Have you ever asked yourself that according to your income
status, whether buying a hummer is logical?
Resolution
27
8
24
12
37
27
Have you tried generating a new idea using two existing
ideas?
Have you thought that a new religion can be created by
combining two or more existing religions?
Have you ever wondered, what is the common link between
Hitler, Jack the Ripper and Nero?
Have you ever linked your feeling of freshness with the
amount of sleep you have had daily?
Have you ever thought why children became more active
after eating more sweets or chocolates?
Synthesis
28
9
31
38
16
33
Have you ever wondered whether the performance of the
pop group “KARA” can be replicated in your own country?
Have you seen, purchased or owned a replicated art piece?
Have you ever tried replicating you friends’ successful study
methods and strategies?
Have you considered that a replicated version of a hit song
can be equally valuable in price and quality?
Have you ever tried replicating a successful activity, project,
or business?
Replication
29
10
29
35
22
39
Have you tried using “H2o” rather than “water” in your
daily conversation?
Have you ever tried painting a same picture in water color,
charcoal, and oil color?
Have you ever thought that Michael Jackson’s portrait in
color is the same when it is in black and white?
Have you ever been convinced that a same element can be
transformed into water, gas, and ice?
Have you ever tried singing a same song in country, rock
and hip-hop?
Redefinition
30
6
40
13
26
30
Have you ever considered analyzing a problem by viewing it
under different scenarios?
Have you ever tried to remake a broken toy into a different
one?
Have you ever tried using bamboo to make arrows, planks
for flooring and a spear?
Have you tried taking a short story and rewriting it to have a
different conclusion but with the same characters?
Have you ever thought that wine can be made out of mango
rather than grapes?
Reconstruction
31
11
15
20
3
1
Have you ever considered moving to a different town or city
to restart a same business that has failed in the current
venue?
Have considered studying an entirely new course in the
event you fail your present course?
Have you ever considered learning a foreign language for a
new vocational move in your life?
Have you ever tried changing your hair style to have new
look?
Have you tried travelling on a different route to reach a
same destination?
Reinitiation
32
APPENDIX C: FREQUENCIES FOR DEMOGRAPHICS
33
FREQUENCIES FOR DEMOGRAPHICS
Statistics
Age Gen
der
Study
Prefere
nce
Year
of
Stud
y in
Colle
ge
GPA Paren
tal
Fami
ly
Statu
s
Fami
ly
Inco
me
Father
Famil
Educati
onal
Backgro
und
Mother
Famil
Educati
onal
Backgro
und
Reaso
ns for
Choos
ing
Progra
m
Numbe
r of
Spoken
Langua
ges
Numbe
r of
Written
Langua
ges
N
Valid 900 900 900 900 900 900 900 900 900 900 900 900
Missi
ng
0 0 0 0 0 0 0 0 0 0 0 0
Mean
19.23
56
1.34
67
3.2500 2.832
2
5.360
0
1.133
3
3.743
3
4.6567 4.6756 2.862
2
2.3611 2.3022
Median
19.00
00
1.00
00
3.0000 3.000
0
6.000
0
1.000
0
4.000
0
5.0000 5.0000 3.000
0
2.0000 2.0000
Mode 20.00 1.00 3.00 3.00 7.00 1.00 5.00 6.00 6.00 1.00 2.00 2.00
Std.
Deviation
2.137
66
.476
17
1.6149
8
1.252
21
2.198
03
.5036
0
1.596
61
1.38838 1.38932 1.441
06
.66171 .66687
Variance 4.570 .227 2.608 1.5684.831 .254 2.549 1.928 1.930 2.077 .438 .445
Skewness 1.779 .645 .610 .112 -.384 4.841 -.227 -1.050 -.950 .113 1.571 1.619
Std. Error of
Skewness
.082 .082 .082 .082 .082 .082 .082 .082 .082 .082 .082 .082
Kurtosis
7.048 -
1.58
7
.061 -.902 -.754 26.16
1
-
1.076
.475 .243 -1.125 3.894 4.525
Std. Error of
Kurtosis
.163 .163 .163 .163 .163 .163 .163 .163 .163 .163 .163 .163
Range 17.00 1.00 6.00 5.00 9.00 4.00 5.00 5.00 5.00 5.00 4.00 5.00
Minimum 15.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Maximum 32.00 2.00 7.00 6.00 10.00 5.00 6.00 6.00 6.00 6.00 5.00 6.00
Percent
iles
25
18.00
00
1.00
00
2.0000 2.000
0
4.000
0
1.000
0
2.000
0
4.0000 4.0000 1.000
0
2.0000 2.0000
34
50
19.00
00
1.00
00
3.0000 3.000
0
6.000
0
1.000
0
4.000
0
5.0000 5.0000 3.000
0
2.0000 2.0000
75
20.00
00
2.00
00
4.0000 4.000
0
7.000
0
1.000
0
5.000
0
6.0000 6.0000 4.000
0
3.0000 3.0000
Age
Frequency Percent Valid Percent Cumulative
Percent
Valid
15.00 2 .2 .2 .2
16.00 45 5.0 5.0 5.2
17.00 121 13.4 13.4 18.7
18.00 181 20.1 20.1 38.8
19.00 181 20.1 20.1 58.9
20.00 199 22.1 22.1 81.0
21.00 89 9.9 9.9 90.9
22.00 30 3.3 3.3 94.2
23.00 23 2.6 2.6 96.8
24.00 7 .8 .8 97.6
25.00 7 .8 .8 98.3
26.00 6 .7 .7 99.0
27.00 1 .1 .1 99.1
28.00 1 .1 .1 99.2
29.00 2 .2 .2 99.4
30.00 1 .1 .1 99.6
32.00 4 .4 .4 100.0
Total 900 100.0 100.0
35
Gender
Frequency Percent Valid Percent Cumulative
Percent
Valid
Male 588 65.3 65.3 65.3
Female 312 34.7 34.7 100.0
Total 900 100.0 100.0
Study Preference
Frequency Percent Valid Percent Cumulative
Percent
Valid
Arts 149 16.6 16.6 16.6
Science 130 14.4 14.4 31.0
Math 259 28.8 28.8 59.8
Technical 231 25.7 25.7 85.4
Abstract 31 3.4 3.4 88.9
Social Science 40 4.4 4.4 93.3
Religion 60 6.7 6.7 100.0
Total 900 100.0 100.0
Year of Study in College
Frequency Percent Valid Percent Cumulative
Percent
Valid
1st Year 164 18.2 18.2 18.2
2nd Year 202 22.4 22.4 40.7
3rd Year 250 27.8 27.8 68.4
36
4th Year 193 21.4 21.4 89.9
5th Year 87 9.7 9.7 99.6
6.00 4 .4 .4 100.0
Total 900 100.0 100.0
GPA
Frequency Percent Valid Percent Cumulative
Percent
Valid
1.0 57 6.3 6.3 6.3
1.25 72 8.0 8.0 14.3
1.50 74 8.2 8.2 22.6
1.75 79 8.8 8.8 31.3
2.0 145 16.1 16.1 47.4
2.25 148 16.4 16.4 63.9
2.50 171 19.0 19.0 82.9
2.75 114 12.7 12.7 95.6
3.0 37 4.1 4.1 99.7
5.0 3 .3 .3 100.0
Total 900 100.0 100.0
Parental Family Status
Frequency Percent Valid Percent Cumulative
Percent
Valid
Married 819 91.0 91.0 91.0
Separated 62 6.9 6.9 97.9
Divorced 2 .2 .2 98.1
37
Remarried 14 1.6 1.6 99.7
Orphaned 3 .3 .3 100.0
Total 900 100.0 100.0
Family Income
Frequency Percent Valid Percent Cumulative
Percent
Valid
25000> 103 11.4 11.4 11.4
20000 - 25000 126 14.0 14.0 25.4
15000 - 20000 153 17.0 17.0 42.4
10000 - 15000 177 19.7 19.7 62.1
5000 - 10000 199 22.1 22.1 84.2
5000< 142 15.8 15.8 100.0
Total 900 100.0 100.0
Father Family Educational Background
Frequency Percent Valid Percent Cumulative
Percent
Valid
Elementary Level 46 5.1 5.1 5.1
Elementary Graduate 35 3.9 3.9 9.0
High School Level 72 8.0 8.0 17.0
High School Graduate 188 20.9 20.9 37.9
College Level 247 27.4 27.4 65.3
College Graduate 312 34.7 34.7 100.0
Total 900 100.0 100.0
38
Mother Family Educational Background
Frequency Percent Valid Percent Cumulative
Percent
Valid
Elementary Level 39 4.3 4.3 4.3
Elementary Graduate 40 4.4 4.4 8.8
High School Level 69 7.7 7.7 16.4
High School Graduate 224 24.9 24.9 41.3
College Level 182 20.2 20.2 61.6
College Graduate 346 38.4 38.4 100.0
Total 900 100.0 100.0
Reasons for Choosing Program
Frequency Percent Valid Percent Cumulative
Percent
Valid
My field of interest 235 26.1 26.1 26.1
I have basic knowledge /
experience related to this
program
142 15.8 15.8 41.9
Graduates in this program
are in demand
172 19.1 19.1 61.0
Opportunity to study / work
abroad
234 26.0 26.0 87.0
Opportunity to begin and
manage my own business
97 10.8 10.8 97.8
I can't find jobs for lesser
qualifications
20 2.2 2.2 100.0
Total 900 100.0 100.0
39
Number of Spoken Languages
Frequency Percent Valid Percent Cumulative
Percent
Valid
1 21 2.3 2.3 2.3
2 585 65.0 65.0 67.3
3 262 29.1 29.1 96.4
4 12 1.3 1.3 97.8
5 20 2.2 2.2 100.0
Total 900 100.0 100.0
Number of Written Languages
Frequency Percent Valid Percent Cumulative
Percent
Valid
1 34 3.8 3.8 3.8
2 612 68.0 68.0 71.8
3 220 24.4 24.4 96.2
4 17 1.9 1.9 98.1
5 16 1.8 1.8 99.9
6 1 .1 .1 100.0
Total 900 100.0 100.0
40
HISTOGRAM
41
42
43
44
45
46
47
48
49
50
51
52
APPENDIX D: RELIABILITY ANALYSES
53
SCALE: RELIABILITY ANALYSIS - PILOT STUDY
Case Processing Summary
N %
Cases
Valid 300 100.0
Excludeda
0 .0
Total 300 100.0
a. Listwise deletion based on all variables
in the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.886 .907 40
54
SCALE: ORIGINALITY
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables
in the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.484 .485 5
Item Statistics
Mean Std. Deviation N
Have you ever chosen an entirely new solution to
solve an old repetitive problem?
3.0800 1.09516 900
Have you chosen an old solution to solve an
entirely new problem?
2.9489 1.07848 900
Have you supported any law or group that
protects an original work of art, authorship or
music?
2.6867 1.26194 900
55
Have you risked venturing into a new and
unknown project or business?
2.4122 1.16305 900
Have you bought and used an entirely
revolutionary new product that had no
performance track record?
2.3667 1.30414 900
Inter-Item Correlation Matrix
Have you
ever
chosen an
entirely
new
solution to
solve an
old
repetitive
problem?
Have you
chosen an
old
solution to
solve an
entirely
new
problem?
Have you
supported
any law or
group that
protects
an original
work of
art,
authorship
or music?
Have you
risked
venturing
into a new
and
unknown
project or
business?
Have you
bought and
used an
entirely
revolutionary
new product
that had no
performance
track
record?
Have you ever chosen an entirely
new solution to solve an old
repetitive problem?
1.000 .345 .173 .082 .111
Have you chosen an old solution
to solve an entirely new
problem?
.345 1.000 .148 .047 -.006
Have you supported any law or
group that protects an original
work of art, authorship or
music?
.173 .148 1.000 .203 .171
Have you risked venturing into a
new and unknown project or
business?
.082 .047 .203 1.000 .309
Have you bought and used an
entirely revolutionary new
product that had no
performance track record?
.111 -.006 .171 .309 1.000
56
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of
Items
Item Means 2.699 2.367 3.080 .713 1.301 .100 5
Item Variances 1.402 1.163 1.701 .538 1.462 .057 5
Inter-Item
Correlations
.159 -.006 .345 .352 -53.686 .011 5
Item-Total Statistics
Scale
Mean if
Item
Deleted
Scale
Variance
if Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you ever chosen an entirely
new solution to solve an old
repetitive problem?
10.4144 8.412 .287 .143 .413
Have you chosen an old solution
to solve an entirely new
problem?
10.5456 8.951 .204 .131 .463
Have you supported any law or
group that protects an original
work of art, authorship or
music?
10.8078 7.797 .290 .085 .407
Have you risked venturing into a
new and unknown project or
business?
11.0822 8.218 .279 .120 .416
Have you bought and used an
entirely revolutionary new
product that had no
performance track record?
11.1278 7.931 .245 .117 .441
57
SCALE: INGENUITY
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables
in the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.499 .558 5
Item Statistics
Mean Std. Deviation N
Have you ever thought that in the absence of any
other resources, trying to cross a torrential river
on a fallen tree log was a feasible idea?
2.6967 1.06736 900
Have you ever thought that you could find a way
to cross a field filled with landmines, poisonous
snakes and pitfalls?
2.5022 2.17146 900
58
Have you tried to get an income without working,
without breaking any laws and without asking
anyone for help?
2.4689 1.29778 900
Have you ever thought how you can remember a
thousand contact names and phone numbers
without any form of gadget aid?
2.4456 1.17080 900
Have you ever thought how you can remember a
thousand faces without any form of gadget aid?
2.4744 1.18030 900
Inter-Item Correlation Matrix
Have you
ever
thought
that in the
absence of
any other
resources,
trying to
cross a
torrential
river on a
fallen tree
log was a
feasible
idea?
Have you
ever
thought
that you
could find
a way to
cross a
field filled
with
landmines,
poisonous
snakes and
pitfalls?
Have you
tried to get
an income
without
working,
without
breaking
any laws
and
without
asking
anyone for
help?
Have you
ever
thought
how you
can
remember
a thousand
contact
names and
phone
numbers
without
any form
of gadget
aid?
Have you
ever
thought
how you
can
remember
a thousand
faces
without
any form
of gadget
aid?
Have you ever thought that in
the absence of any other
resources, trying to cross a
torrential river on a fallen tree
log was a feasible idea?
1.000 .063 .093 .196 .173
Have you ever thought that you
could find a way to cross a field
filled with landmines, poisonous
snakes and pitfalls?
.063 1.000 .131 .174 .134
59
Have you tried to get an income
without working, without
breaking any laws and without
asking anyone for help?
.093 .131 1.000 .225 .252
Have you ever thought how you
can remember a thousand
contact names and phone
numbers without any form of
gadget aid?
.196 .174 .225 1.000 .578
Have you ever thought how you
can remember a thousand faces
without any form of gadget aid?
.173 .134 .252 .578 1.000
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of
Items
Item Means 2.518 2.446 2.697 .251 1.103 .010 5
Item Variances 2.061 1.139 4.715 3.576 4.139 2.240 5
Inter-Item
Correlations
.202 .063 .578 .515 9.182 .020 5
Item-Total Statistics
Scale
Mean if
Item
Deleted
Scale
Variance
if Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you ever thought that in
the absence of any other
resources, trying to cross a
torrential river on a fallen tree
log was a feasible idea?
9.8911 14.531 .181 .046 .493
60
Have you ever thought that you
could find a way to cross a field
filled with landmines, poisonous
snakes and pitfalls?
10.0856 9.820 .192 .041 .575
Have you tried to get an income
without working, without
breaking any laws and without
asking anyone for help?
10.1189 13.006 .262 .082 .450
Have you ever thought how you
can remember a thousand
contact names and phone
numbers without any form of
gadget aid?
10.1422 12.118 .448 .357 .351
Have you ever thought how you
can remember a thousand faces
without any form of gadget aid?
10.1133 12.259 .422 .353 .364
61
SCALE: RESOLUTION
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.497 .510 5
Item Statistics
Mean Std. Deviation N
Have you preferred value in quality over cheapness in
cost when making decisions for personal purchases?
3.2848 1.45274 900
Have you used logical reasoning during emotional
conflicts?
3.1156 1.07349 900
Have you considered the usefulness of the things or
products you have bought?
3.4067 1.54616 900
62
Have you tried to understand comprehensively the
functions of the products that you bought?
3.2300 1.16177 900
Have you ever asked yourself that according to your
income status, whether buying a hummer is logical?
2.4478 1.21565 900
Inter-Item Correlation Matrix
Have you
preferred
value in
quality
over
cheapness
in cost
when
making
decisions
for
personal
purchases?
Have you
used
logical
reasoning
during
emotional
conflicts?
Have you
considered
the
usefulness
of the
things or
products
you have
bought?
Have you tried
to understand
comprehensively
the functions of
the products that
you bought?
Have you
ever asked
yourself
that
according
to your
income
status,
whether
buying a
hummer is
logical?
Have you preferred value in
quality over cheapness in cost
when making decisions for
personal purchases?
1.000 .149 .149 .173 .086
Have you used logical reasoning
during emotional conflicts?
.149 1.000 .255 .309 .144
Have you considered the
usefulness of the things or
products you have bought?
.149 .255 1.000 .340 .032
Have you tried to understand
comprehensively the functions of
the products that you bought?
.173 .309 .340 1.000 .085
Have you ever asked yourself that
according to your income status,
whether buying a hummer is
logical?
.086 .144 .032 .085 1.000
63
Inter-Item Covariance Matrix
Have you
preferred
value in
quality
over
cheapness
in cost
when
making
decisions
for
personal
purchases?
Have you
used
logical
reasoning
during
emotional
conflicts?
Have you
considered
the
usefulness
of the
things or
products
you have
bought?
Have you tried
to understand
comprehensively
the functions of
the products that
you bought?
Have you
ever asked
yourself
that
according
to your
income
status,
whether
buying a
hummer is
logical?
Have you preferred value in
quality over cheapness in cost
when making decisions for
personal purchases?
2.110 .233 .336 .292 .153
Have you used logical reasoning
during emotional conflicts?
.233 1.152 .423 .385 .187
Have you considered the
usefulness of the things or
products you have bought?
.336 .423 2.391 .612 .060
Have you tried to understand
comprehensively the functions of
the products that you bought?
.292 .385 .612 1.350 .119
Have you ever asked yourself that
according to your income status,
whether buying a hummer is
logical?
.153 .187 .060 .119 1.478
64
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of Items
Item Means 3.097 2.448 3.407 .959 1.392 .143 5
Item Variances 1.696 1.152 2.391 1.238 2.075 .279 5
Inter-Item
Correlations
.172 .032 .340 .308 10.632 .010 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you preferred value in quality
over cheapness in cost when
making decisions for personal
purchases?
12.2000 9.944 .221 .050 .479
Have you used logical reasoning
during emotional conflicts?
12.3692 10.472 .354 .140 .400
Have you considered the usefulness
of the things or products you have
bought?
12.0781 8.829 .311 .147 .414
Have you tried to understand
comprehensively the functions of
the products that you bought?
12.2548 9.916 .385 .179 .374
Have you ever asked yourself that
according to your income status,
whether buying a hummer is
logical?
13.0370 11.565 .126 .027 .526
65
SCALE: SYNTHESIS
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.374 .386 5
Item Statistics
Mean Std. Deviation N
Have you tried generating a new idea using two
existing ideas?
3.2011 1.66044 900
Have you thought that a new religion can be created
by combining two or more existing religions?
2.2878 1.19810 900
Have you ever wondered, what is the common link
between Hitler, Jack the Ripper and Nero?
2.2622 1.17450 900
Have you ever linked your feeling of freshness with
the amount of sleep you have had daily?
3.1144 1.55765 900
66
Have you ever thought why children became more
active after eating more sweets or chocolates?
3.1000 1.25369 900
Inter-Item Correlation Matrix
Have you
tried
generating
a new idea
using two
existing
ideas?
Have you
thought that
a new
religion can
be created
by
combining
two or
more
existing
religions?
Have you
ever
wondered,
what is the
common
link
between
Hitler, Jack
the Ripper
and Nero?
Have you
ever linked
yor feeling
of freshness
with the
amount of
sleep you
have had
daily?
Have you
ever
thought
why
children
became
more active
after eating
more
sweets or
chocolates?
Have you tried generating a new
idea using two existing ideas?
1.000 .030 .072 .109 .130
Have you thought that a new
religion can be created by
combining two or more existing
religions?
.030 1.000 .250 .077 .118
Have you ever wondered, what is
the common link between Hitler,
Jack the Ripper and Nero?
.072 .250 1.000 .039 .058
Have you ever linked your feeling
of freshness with the amount of
sleep you have had daily?
.109 .077 .039 1.000 .236
Have you ever thought why
children became more active after
eating more sweets or chocolates?
.130 .118 .058 .236 1.000
67
Inter-Item Covariance Matrix
Have you
tried
generating
a new idea
using two
existing
ideas?
Have you
thought that
a new
religion can
be created
by
combining
two or
more
existing
religions?
Have you
ever
wondered,
what is the
common
link
between
Hitler, Jack
the Ripper
and Nero?
Have you
ever linked
yor feeling
of freshness
with the
amount of
sleep you
have had
daily?
Have you
ever
thought
why
children
became
more active
after eating
more
sweets or
chocolates?
Have you tried generating a new
idea using two existing ideas?
2.757 .060 .141 .282 .270
Have you thought that a new
religion can be created by
combining two or more existing
religions?
.060 1.435 .352 .143 .177
Have you ever wondered, what is
the common link between Hitler,
Jack the Ripper and Nero?
.141 .352 1.379 .071 .086
Have you ever linked your feeling
of freshness with the amount of
sleep you have had daily?
.282 .143 .071 2.426 .461
Have you ever thought why
children became more active after
eating more sweets or chocolates?
.270 .177 .086 .461 1.572
68
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of Items
Item Means 2.793 2.262 3.201 .939 1.415 .225 5
Item Variances 1.914 1.379 2.757 1.378 1.999 .401 5
Inter-Item
Correlations
.112 .030 .250 .220 8.289 .006 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you tried generating a new
idea using two existing ideas?
10.7644 9.393 .148 .027 .366
Have you thought that a new
religion can be created by
combining two or more existing
religions?
11.6778 10.757 .186 .075 .325
Have you ever wondered, what is
the common link between Hitler,
Jack the Ripper and Nero?
11.7033 10.976 .167 .067 .338
Have you ever linked your feeling
of freshness with the amount of
sleep you have had daily?
10.8511 9.315 .201 .064 .311
Have you ever thought why
children became more active after
eating more sweets or chocolates?
10.8656 10.094 .250 .077 .277
69
SCALE: REPLICATION
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.440 .459 5
Item Statistics
Mean Std. Deviation N
Have you ever wondered whether the
performance of the pop group "KARA" can be
replicated in your own country?
2.2844 1.53389 900
Have you seen, purchased owned a replicated art
piece?
2.4256 1.36621 900
Have you ever tried replicating your friends'
successful study methods and strategies?
2.7222 1.18413 900
70
Have you considered that a replicated version of
a hit song can be equally valuable in price and
quality?
2.4989 1.60471 900
Have you ever tried replicating a successful
activity, project, or business?
2.5667 1.21586 900
Inter-Item Correlation Matrix
Have you
ever
wondered
whether the
performance
of the pop
group
"KARA"
can be
replicated in
your own
country?
Have you
seen,
purchased
owned a
replicated
art piece?
Have you
ever tried
replicating
your
friends'
successful
study
methods
and
strategies?
Have you
considered
that a
replicated
version of a
hit song
can be
equally
valuable in
price and
quality?
Have you
ever tried
replicating
a
successful
activity,
project, or
business?
Have you ever wondered whether
the performance of the pop group
"KARA" can be replicated in your
own country?
1.000 .114 .020 .093 .113
Have you seen, purchased owned a
replicated art piece?
.114 1.000 .169 .123 .301
Have you ever tried replicating
your friends' successful study
methods and strategies?
.020 .169 1.000 .116 .261
Have you considered that a
replicated version of a hit song can
be equally valuable in price and
quality?
.093 .123 .116 1.000 .138
Have you ever tried replicating a
successful activity, project, or
business?
.113 .301 .261 .138 1.000
71
Inter-Item Covariance Matrix
Have you
ever
wondered
whether the
performance
of the pop
group
"KARA"
can be
replicated in
your own
country?
Have you
seen,
purchased
owned a
replicated
art piece?
Have you
ever tried
replicating
your
friends'
successful
study
methods
and
strategies?
Have you
considered
that a
replicated
version of a
hit song
can be
equally
valuable in
price and
quality?
Have you
ever tried
replicating
a
successful
activity,
project, or
business?
Have you ever wondered whether
the performance of the pop group
"KARA" can be replicated in your
own country?
2.353 .239 .037 .229 .210
Have you seen, purchased owned a
replicated art piece?
.239 1.867 .274 .269 .501
Have you ever tried replicating
your friends' successful study
methods and strategies?
.037 .274 1.402 .221 .376
Have you considered that a
replicated version of a hit song can
be equally valuable in price and
quality?
.229 .269 .221 2.575 .270
Have you ever tried replicating a
successful activity, project, or
business?
.210 .501 .376 .270 1.478
72
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of Items
Item Means 2.500 2.284 2.722 .438 1.192 .026 5
Item Variances 1.935 1.402 2.575 1.173 1.836 .270 5
Inter-Item
Correlations
.145 .020 .301 .281 14.859 .006 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you ever wondered whether
the performance of the pop group
"KARA" can be replicated in your
own country?
10.2133 11.142 .140 .025 .457
Have you seen, purchased owned a
replicated art piece?
10.0722 10.494 .290 .111 .341
Have you ever tried replicating
your friends' successful study
methods and strategies?
9.7756 11.709 .224 .083 .391
Have you considered that a
replicated version of a hit song can
be equally valuable in price and
quality?
9.9989 10.373 .191 .037 .421
Have you ever tried replicating a
successful activity, project, or
business?
9.9311 10.736 .340 .148 .315
73
SCALE: REDEFINITION
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.492 .497 5
Item Statistics
Mean Std. Deviation N
Have you tried using "H2o" rather than "water"
in your daily conversation?
2.3022 1.42978 900
Have you ever tried painting a same picture in
water color, charcoal, and oil color?
2.6767 1.22493 900
Have you ever thought that Michael Jackson's
portrait in color is the same when it is in black
and white?
2.5156 1.40268 900
74
Have you ever been convinced that a same
element can be transformed into water, gas, and
ice?
2.7167 1.22939 900
Have you ever tried singing a same song in
country, rock, and hip-hop?
2.9478 1.23201 900
Inter-Item Correlation Matrix
Have you
tried using
"H2o" rather
than "water"
in your daily
conversation?
Have you
ever tried
painting a
same
picture in
water
color,
charcoal,
and oil
color?
Have you
ever
thought
that
Michael
Jackson's
portrait in
color is the
same when
it is in
black and
white?
Have you
ever been
convinced
that a same
element can
be
transformed
into water,
gas, and
ice?
Have you
ever tried
singing a
same song
in country,
rock, and
hip-hop?
Have you tried using "H2o" rather
than "water" in your daily
conversation?
1.000 .087 .156 .145 .080
Have you ever tried painting a
same picture in water color,
charcoal, and oil color?
.087 1.000 .201 .159 .270
Have you ever thought that
Michael Jackson's portrait in color
is the same when it is in black and
white?
.156 .201 1.000 .169 .194
Have you ever been convinced that
a same element can be transformed
into water, gas, and ice?
.145 .159 .169 1.000 .190
Have you ever tried singing a same
song in country, rock, and hip-
hop?
.080 .270 .194 .190 1.000
75
Inter-Item Covariance Matrix
Have you
tried using
"H2o" rather
than "water"
in your daily
conversation?
Have you
ever tried
painting a
same
picture in
water
color,
charcoal,
and oil
color?
Have you
ever
thought
that
Michael
Jackson's
portrait in
color is the
same when
it is in
black and
white?
Have you
ever been
convinced
that a same
element can
be
transformed
into water,
gas, and
ice?
Have you
ever tried
singing a
same song
in country,
rock, and
hip-hop?
Have you tried using "H2o" rather
than "water" in your daily
conversation?
2.044 .152 .313 .255 .141
Have you ever tried painting a
same picture in water color,
charcoal, and oil color?
.152 1.500 .346 .240 .408
Have you ever thought that
Michael Jackson's portrait in color
is the same when it is in black and
white?
.313 .346 1.967 .291 .335
Have you ever been convinced that
a same element can be transformed
into water, gas, and ice?
.255 .240 .291 1.511 .288
Have you ever tried singing a same
song in country, rock, and hip-
hop?
.141 .408 .335 .288 1.518
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of Items
Item Means 2.632 2.302 2.948 .646 1.280 .058 5
Item Variances 1.708 1.500 2.044 .544 1.362 .075 5
76
Inter-Item
Correlations
.165 .080 .270 .190 3.366 .003 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you tried using "H2o" rather
than "water" in your daily
conversation?
10.8567 10.312 .188 .041 .493
Have you ever tried painting a
same picture in water color,
charcoal, and oil color?
10.4822 10.288 .292 .105 .421
Have you ever thought that
Michael Jackson's portrait in color
is the same when it is in black and
white?
10.6433 9.542 .297 .089 .415
Have you ever been convinced that
a same element can be transformed
into water, gas, and ice?
10.4422 10.423 .270 .074 .434
Have you ever tried singing a same
song in country, rock, and hip-hop?
10.2111 10.218 .298 .111 .417
77
SCALE: RECONSTRUCTION
Case Processing Summary
N %
Cases
Valid 899 99.9
Excludeda
1 .1
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.346 .392 5
Item Statistics
Mean Std. Deviation N
Have you ever considered analyzing a problem
by viewing it under different scenarios?
3.2970 1.31536 899
Have you tried to remake a broken toy into a
different one?
3.0189 1.21364 899
Have you ever tried using bamboo to make
arrows, planks for flooring and a spear?
2.3526 1.15657 899
78
Have you tried taking a short story and rewriting
it to have a different conclusion but with the
same characters?
2.8621 2.46871 899
Have you ever thought that wine can be made out
of mango rather than grapes?
2.6352 1.70494 899
Inter-Item Correlation Matrix
Have you
ever
considered
analyzing a
problem by
viewing it
under
different
scenarios?
Have you
tried to
remake a
broken toy
into a
different
one?
Have you
ever tried
using
bamboo to
make
arrows,
planks for
flooring
and a
spear?
Have you
tried taking
a short
story and
rewriting it
to have a
different
conclusion
but with the
same
characters?
Have you
ever
thought
that wine
can be
made out of
mango
rather than
grapes?
Have you ever considered
analyzing a problem by viewing it
under different scenarios?
1.000 .112 .058 .008 .039
Have you tried to remake a broken
toy into a different one?
.112 1.000 .201 .135 .183
Have you ever tried using bamboo
to make arrows, planks for flooring
and a spear?
.058 .201 1.000 .104 .191
Have you tried taking a short story
and rewriting it to have a different
conclusion but with the same
characters?
.008 .135 .104 1.000 .112
Have you ever thought that wine
can be made out of mango rather
than grapes?
.039 .183 .191 .112 1.000
79
Inter-Item Covariance Matrix
Have you
ever
considered
analyzing a
problem by
viewing it
under
different
scenarios?
Have you
tried to
remake a
broken toy
into a
different
one?
Have you
ever tried
using
bamboo to
make
arrows,
planks for
flooring
and a
spear?
Have you
tried taking
a short
story and
rewriting it
to have a
different
conclusion
but with the
same
characters?
Have you
ever
thought
that wine
can be
made out of
mango
rather than
grapes?
Have you ever considered
analyzing a problem by viewing it
under different scenarios?
1.730 .179 .088 .027 .087
Have you tried to remake a broken
toy into a different one?
.179 1.473 .282 .406 .378
Have you ever tried using bamboo
to make arrows, planks for flooring
and a spear?
.088 .282 1.338 .297 .376
Have you tried taking a short story
and rewriting it to have a different
conclusion but with the same
characters?
.027 .406 .297 6.095 .472
Have you ever thought that wine
can be made out of mango rather
than grapes?
.087 .378 .376 .472 2.907
Summary Item Statistics
Mean MinimumMaximum Range Maximum /
Minimum
Variance N of Items
Item Means 2.833 2.353 3.297 .944 1.401 .130 5
Item Variances 2.708 1.338 6.095 4.757 4.556 3.967 5
80
Inter-Item
Correlations
.114 .008 .201 .193 24.564 .004 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you ever considered
analyzing a problem by viewing it
under different scenarios?
10.8687 16.232 .072 .014 .363
Have you tried to remake a broken
toy into a different one?
11.1468 14.762 .267 .082 .243
Have you ever tried using bamboo
to make arrows, planks for flooring
and a spear?
11.8131 15.301 .230 .070 .270
Have you tried taking a short story
and rewriting it to have a different
conclusion but with the same
characters?
11.3037 10.227 .152 .031 .362
Have you ever thought that wine
can be made out of mango rather
than grapes?
11.5306 13.191 .212 .064 .258
81
SCALE: REINITIATION
Case Processing Summary
N %
Cases
Valid 900 100.0
Excludeda
0 .0
Total 900 100.0
a. Listwise deletion based on all variables in
the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based on
Standardized
Items
N of Items
.320 .389 5
Item Statistics
Mean Std. Deviation N
Have you ever considered moving to a different
town or city to restart a same business that has
failed in the current venue?
2.0811 1.17779 900
Have you considered studying an entirely new
course in the event you fail your present course?
2.2556 1.29825 900
Have you considered learning a foreign language
for a new vocational move in your life?
3.1400 1.33005 900
82
Have you ever tried changing your hair style to
have a new look?
3.1900 2.61137 900
Have you tried travelling on a different route to
reach a same destination?
2.9033 1.38102 900
Inter-Item Correlation Matrix
Have you
ever
considered
moving to
a different
town or
city to
restart a
same
business
that has
failed in
the current
venue?
Have you
considered
studying an
entirely
new course
in the event
you fail
your
present
course?
Have you
considered
learning a
foreign
language
for a new
vocational
move in
your life?
Have you
ever tried
changing
your hair
style to
have a new
look?
Have you
tried
travelling
on a
different
route to
reach a
same
destination?
Have you ever considered moving
to a different town or city to restart
a same business that has failed in
the current venue?
1.000 .269 .137 .027 .125
Have you considered studying an
entirely new course in the event
you fail your present course?
.269 1.000 .163 .014 .030
Have you considered learning a
foreign language for a new
vocational move in your life?
.137 .163 1.000 .072 .149
Have you ever tried changing your
hair style to have a new look?
.027 .014 .072 1.000 .144
Have you tried travelling on a
different route to reach a same
destination?
.125 .030 .149 .144 1.000
83
Inter-Item Covariance Matrix
Have you
ever
considered
moving to a
different
town or
city to
restart a
same
business
that has
failed in the
current
venue?
Have you
considered
studying an
entirely
new course
in the event
you fail
your
present
course?
Have you
considered
learning a
foreign
language
for a new
vocational
move in
your life?
Have you
ever tried
changing
your hair
style to
have a new
look?
Have you
tried
travelling
on a
different
route to
reach a
same
destination?
Have you ever considered moving
to a different town or city to restart
a same business that has failed in
the current venue?
1.387 .411 .214 .084 .203
Have you considered studying an
entirely new course in the event
you fail your present course?
.411 1.685 .282 .046 .054
Have you considered learning a
foreign language for a new
vocational move in your life?
.214 .282 1.769 .250 .274
Have you ever tried changing your
hair style to have a new look?
.084 .046 .250 6.819 .519
Have you tried travelling on a
different route to reach a same
destination?
.203 .054 .274 .519 1.907
Summary Item Statistics
Mean Minimum Maximum Range Maximum /
Minimum
Variance N of Items
Item Means 2.714 2.081 3.190 1.109 1.533 .264 5
84
Item Variances 2.714 1.387 6.819 5.432 4.916 5.304 5
Inter-Item
Correlations
.113 .014 .269 .255 19.828 .006 5
Item-Total Statistics
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
Have you ever considered moving
to a different town or city to restart
a same business that has failed in
the current venue?
11.4889 15.031 .200 .092 .253
Have you considered studying an
entirely new course in the event
you fail your present course?
11.3144 14.970 .158 .089 .275
Have you considered learning a
foreign language for a new
vocational move in your life?
10.4300 14.430 .202 .056 .243
Have you ever tried changing your
hair style to have a new look?
10.3800 9.624 .111 .023 .398
Have you tried travelling on a
different route to reach a same
destination?
10.6667 14.236 .201 .051 .241
85
APPENDIX E: RELIABILTY ANALYSIS OF THE EIGHT SCALES OF CSEQ
86
SCALE: RELIABILTY ANALYSIS OF THE EIGHT SCALES OF CSEQ
Case Processing Summary
N %
Cases
Valid 899 99.9
Excludeda
1 .1
Total 900 100.0
a. Listwise deletion based on all variables
in the procedure.
Reliability Statistics
Cronbach's
Alpha
Cronbach's
Alpha Based
on
Standardized
Items
N of Items
.840 .842 8
Inter-Item Correlation Matrix
Originalit
y
Ingenuit
y
Resolutio
n
Synthes
is
Replicati
on
Redefiniti
on
Reconstructi
on
Reinitiati
on
Originality 1.000 .452 .410 .431 .439 .470 .450 .429
Ingenuity .452 1.000 .378 .437 .440 .500 .440 .308
Resolution .410 .378 1.000 .436 .250 .355 .407 .292
Synthesis .431 .437 .436 1.000 .391 .425 .432 .321
Replication .439 .440 .250 .391 1.000 .462 .381 .299
Redefinition .470 .500 .355 .425 .462 1.000 .466 .369
87
Reconstructi
on
.450 .440 .407 .432 .381 .466 1.000 .349
Reinitiation .429 .308 .292 .321 .299 .369 .349 1.000
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
Originality 95.4386 367.017 .639 .412 .814
Ingenuity 96.3463 350.070 .607 .386 .816
Resolution 93.4449 373.145 .511 .297 .828
Synthesis 94.9670 364.517 .589 .357 .819
Replication 96.4397 366.340 .541 .329 .825
Redefinition 95.7723 357.622 .631 .410 .813
Reconstruction 94.7690 345.831 .601 .366 .817
Reinitiation 95.3652 365.711 .473 .244 .835
Scale Statistics
Mean Variance Std. Deviation N of Items
108.9347 461.316 21.47828 8
Inter-Item Correlation Matrix
88
Originalit
y
Ingenuit
y
Resolutio
n
Synthes
is
Replicati
on
Redefiniti
on
Reconstructi
on
Reinitiati
on
Originality 1.000 .452 .410 .431 .439 .470 .450 .429
Ingenuity .452 1.000 .378 .437 .440 .500 .440 .308
Resolution .410 .378 1.000 .436 .250 .355 .407 .292
Synthesis .431 .437 .436 1.000 .391 .425 .432 .321
Replication .439 .440 .250 .391 1.000 .462 .381 .299
Redefinition .470 .500 .355 .425 .462 1.000 .466 .369
Reconstructi
on
.450 .440 .407 .432 .381 .466 1.000 .349
Reinitiation .429 .308 .292 .321 .299 .369 .349 1.000
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
Originality 95.4386 367.017 .639 .412 .814
Ingenuity 96.3463 350.070 .607 .386 .816
Resolution 93.4449 373.145 .511 .297 .828
Synthesis 94.9670 364.517 .589 .357 .819
Replication 96.4397 366.340 .541 .329 .825
Redefinition 95.7723 357.622 .631 .410 .813
Reconstruction 94.7690 345.831 .601 .366 .817
Reinitiation 95.3652 365.711 .473 .244 .835
Scale Statistics
Mean Variance Std. Deviation N of Items
89
108.9347 461.316 21.47828 8
APPENDIX F: CORRELATIONAL ANALYSES
90
CORRELATION BETWEEN AGE AND EIGHT CREATIVITY ELEMENTS
Age Ori
gin
alit
y
Ingenu
ity
Resolut
ion
Synthe
sis
Replicat
ion
Redefinit
ion
Reconstruc
tion
Reinitiat
ion
Age
Pearson
Correlat
ion
1 .05
3
.031 .003 -.018 .088**
.005 .045 .033
Sig. (1-
tailed)
.05
6
.177 .465 .296 .004 .440 .089 .160
N 900 900 900 900 900 900 900 899 900
Originality
Pearson
Correlat
ion
.053 1 .452**
.411**
.431**
.439**
.470**
.450**
.428**
Sig. (1-
tailed)
.056 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Ingenuity
Pearson
Correlat
ion
.031 .45
2**
1 .378**
.437**
.440**
.500**
.440**
.307**
Sig. (1-
tailed)
.177 .00
0
.000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Resolution
Pearson
Correlat
ion
.003 .41
1**
.378**
1 .436**
.249**
.356**
.407**
.291**
Sig. (1-
tailed)
.465 .00
0
.000 .000 .000 .000 .000 .000
91
N 900 900 900 900 900 900 900 899 900
Synthesis
Pearson
Correlat
ion
-.018 .43
1**
.437**
.436**
1 .390**
.425**
.432**
.320**
Sig. (1-
tailed)
.296 .00
0
.000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Replication
Pearson
Correlat
ion
.088**
.43
9**
.440**
.249**
.390**
1 .462**
.381**
.299**
Sig. (1-
tailed)
.004 .00
0
.000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Redefinitio
n
Pearson
Correlat
ion
.005 .47
0**
.500**
.356**
.425**
.462**
1 .466**
.368**
Sig. (1-
tailed)
.440 .00
0
.000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Reconstruc
tion
Pearson
Correlat
ion
.045 .45
0**
.440**
.407**
.432**
.381**
.466**
1 .349**
Sig. (1-
tailed)
.089 .00
0
.000 .000 .000 .000 .000 .000
N 899 899 899 899 899 899 899 899 899
Reinitiatio
n
Pearson
Correlat
ion
.033 .42
8**
.307**
.291**
.320**
.299**
.368**
.349**
1
Sig. (1-
tailed)
.160 .00
0
.000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
**. Correlation is significant at the 0.01 level (1-tailed).
92
CORRELATIONS BETWEEN YEAR OF STUDY AND EIGHT CREATIVITY
ELEMENTS
Year
of
Study
in
Colle
ge
Origina
lity
Resolut
ion
Synthe
sis
Replicat
ion
Ingenu
ity
Redefinit
ion
Reconstruc
tion
Reinitiat
ion
Year of
Study in
College
Pearson
Correlat
ion
1 -.077*
.000 -.049 -.017 -.038 -.076*
.032 -.055
Sig. (2-
tailed)
.021 .998 .141 .606 .254 .022 .331 .100
N 900 900 900 900 900 900 900 899 900
Originality
Pearson
Correlat
ion
-
.077*
1 .411**
.431**
.439**
.452**
.470**
.450**
.428**
Sig. (2-
tailed)
.021 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Resolution
Pearson
Correlat
ion
.000 .411**
1 .436**
.249**
.378**
.356**
.407**
.291**
Sig. (2-
tailed)
.998 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Synthesis
Pearson
Correlat
ion
-.049 .431**
.436**
1 .390**
.437**
.425**
.432**
.320**
Sig. (2-
tailed)
.141 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
93
Replicatio
n
Pearson
Correlat
ion
-.017 .439**
.249**
.390**
1 .440**
.462**
.381**
.299**
Sig. (2-
tailed)
.606 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Ingenuity
Pearson
Correlat
ion
-.038 .452**
.378**
.437**
.440**
1 .500**
.440**
.307**
Sig. (2-
tailed)
.254 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Redefinitio
n
Pearson
Correlat
ion
-
.076*
.470**
.356**
.425**
.462**
.500**
1 .466**
.368**
Sig. (2-
tailed)
.022 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Reconstruc
tion
Pearson
Correlat
ion
.032 .450**
.407**
.432**
.381**
.440**
.466**
1 .349**
Sig. (2-
tailed)
.331 .000 .000 .000 .000 .000 .000 .000
N 899 899 899 899 899 899 899 899 899
Reinitiatio
n
Pearson
Correlat
ion
-.055 .428**
.291**
.320**
.299**
.307**
.368**
.349**
1
Sig. (2-
tailed)
.100 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
94
CORRELATIONS BETWEEN STUDENT REASONS FOR STUDYING THEIR
PROGRAMS AND THE EIGHT CREATIVITY ELEMENTS
Reaso
ns for
Choosi
ng
Progra
m
Origina
lity
Resolut
ion
Synthe
sis
Replicat
ion
Ingenu
ity
Redefini
tion
Reconstru
ction
Reinitiat
ion
Reasons
for
Choosing
Program
Pearson
Correlat
ion
1 .000 -.036 .067*
.050 .039 .030 .015 .007
Sig. (2-
tailed)
.988 .274 .044 .134 .238 .373 .661 .829
N 900 900 900 900 900 900 900 899 900
Originality
Pearson
Correlat
ion
.000 1 .411**
.431**
.439**
.452**
.470**
.450**
.428**
Sig. (2-
tailed)
.988 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Resolution
Pearson
Correlat
ion
-.036 .411**
1 .436**
.249**
.378**
.356**
.407**
.291**
Sig. (2-
tailed)
.274 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Synthesis
Pearson
Correlat
ion
.067*
.431**
.436**
1 .390**
.437**
.425**
.432**
.320**
Sig. (2-
tailed)
.044 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
95
Replicatio
n
Pearson
Correlat
ion
.050 .439**
.249**
.390**
1 .440**
.462**
.381**
.299**
Sig. (2-
tailed)
.134 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Ingenuity
Pearson
Correlat
ion
.039 .452**
.378**
.437**
.440**
1 .500**
.440**
.307**
Sig. (2-
tailed)
.238 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Redefinitio
n
Pearson
Correlat
ion
.030 .470**
.356**
.425**
.462**
.500**
1 .466**
.368**
Sig. (2-
tailed)
.373 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Reconstruc
tion
Pearson
Correlat
ion
.015 .450**
.407**
.432**
.381**
.440**
.466**
1 .349**
Sig. (2-
tailed)
.661 .000 .000 .000 .000 .000 .000 .000
N 899 899 899 899 899 899 899 899 899
Reinitiatio
n
Pearson
Correlat
ion
.007 .428**
.291**
.320**
.299**
.307**
.368**
.349**
1
Sig. (2-
tailed)
.829 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
96
CORRELATIONS BETWEEN STUDENTS LINGUISTIC ABILITY (SPOKEN /
WRITTEN AND THE EIGHT CREATIVITY ELEMENTS
Numb
er of
Spoke
n
Langu
ages
Numb
er of
Writte
n
Langu
ages
Origin
ality
Resolu
tion
Synth
esis
Replica
tion
Ingen
uity
Redefin
ition
Reconstru
ction
Reinitia
tion
Number
of Spoken
Language
s
Pearso
n
Correla
tion
1 .655**
.064 .041 .067*
.018 .017 .055 .034 .087**
Sig. (2-
tailed)
.000 .054 .223 .046 .591 .618 .100 .309 .009
N 900 900 900 900 900 900 900 900 899 900
Number
of
Written
Language
s
Pearso
n
Correla
tion
.655**
1 .027 .001 .075*
.024 .008 .047 .045 .048
Sig. (2-
tailed)
.000 .420 .967 .024 .472 .817 .155 .180 .150
N 900 900 900 900 900 900 900 900 899 900
Originalit
y
Pearso
n
Correla
tion
.064 .027 1 .411**
.431**
.439**
.452**
.470**
.450**
.428**
Sig. (2-
tailed)
.054 .420 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Resolutio
n
Pearso
n
Correla
tion
.041 .001 .411**
1 .436**
.249**
.378**
.356**
.407**
.291**
97
Sig. (2-
tailed)
.223 .967 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Synthesis
Pearso
n
Correla
tion
.067*
.075*
.431**
.436**
1 .390**
.437**
.425**
.432**
.320**
Sig. (2-
tailed)
.046 .024 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Replicatio
n
Pearso
n
Correla
tion
.018 .024 .439**
.249**
.390**
1 .440**
.462**
.381**
.299**
Sig. (2-
tailed)
.591 .472 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Ingenuity
Pearso
n
Correla
tion
.017 .008 .452**
.378**
.437**
.440**
1 .500**
.440**
.307**
Sig. (2-
tailed)
.618 .817 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Redefiniti
on
Pearso
n
Correla
tion
.055 .047 .470**
.356**
.425**
.462**
.500**
1 .466**
.368**
Sig. (2-
tailed)
.100 .155 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
Reconstru
ction
Pearso
n
Correla
tion
.034 .045 .450**
.407**
.432**
.381**
.440**
.466**
1 .349**
98
Sig. (2-
tailed)
.309 .180 .000 .000 .000 .000 .000 .000 .000
N 899 899 899 899 899 899 899 899 899 899
Reinitiati
on
Pearso
n
Correla
tion
.087**
.048 .428**
.291**
.320**
.299**
.307**
.368**
.349**
1
Sig. (2-
tailed)
.009 .150 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 900 899 900
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
99
GENERAL LINEAR MODEL (MANOVA) GENDER DIFFERENCE BETWEEN THE
EIGHT CREATIVITY ELEMENTS
Between-Subjects Factors
Value Label N
Gender
1.00 Male 587
2.00 Female 312
Box's Test of Equality of
Covariance Matricesa
Box's M 114.463
F 3.146
df1 36
df2 1419800.525
Sig. .000
100
Multivariate Testsa
Effect Value F Hypothesis df Error df Sig.
Intercept
Pillai's Trace .962 2833.707b
8.000 890.000 .000
Wilks' Lambda .038 2833.707b
8.000 890.000 .000
Hotelling's Trace 25.472 2833.707b
8.000 890.000 .000
Roy's Largest Root 25.472 2833.707b
8.000 890.000 .000
Gender
Pillai's Trace .024 2.710b
8.000 890.000 .006
Wilks' Lambda .976 2.710b
8.000 890.000 .006
Hotelling's Trace .024 2.710b
8.000 890.000 .006
Roy's Largest Root .024 2.710b
8.000 890.000 .006
a. Design: Intercept + Gender
b. Exact statistic
Levene's Test of Equality of Error Variancesa
F df1 df2 Sig.
Originality .333 1 897 .564
Ingenuity 1.716 1 897 .190
Resolution 1.112 1 897 .292
Synthesis 1.251 1 897 .264
Replication 3.244 1 897 .072
Redefinition .463 1 897 .496
Reconstruction 1.863 1 897 .173
Reinitiation .060 1 897 .806
Tests the null hypothesis that the error variance of the dependent
variable is equal across groups.
a. Design: Intercept + Gender
101
Tests of Between-Subjects Effects
Source Dependent
Variable
Type III Sum
of Squares
df Mean Square F Sig.
Corrected
Model
Originality 55.974a
1 55.974 4.912 .027
Ingenuity 79.911b
1 79.911 4.675 .031
Resolution 1.387c
1 1.387 .098 .754
Synthesis .081d
1 .081 .006 .939
Replication 111.092e
1 111.092 7.492 .006
Redefinition 25.922f
1 25.922 1.842 .175
Reconstruction 205.707g
1 205.707 11.110 .001
Reinitiation 5.907h
1 5.907 .323 .570
Intercept
Originality 146667.837 1 146667.837 12871.942 .000
Ingenuity 127174.905 1 127174.905 7440.472 .000
Resolution 195197.777 1 195197.777 13854.375 .000
Synthesis 159050.537 1 159050.537 11625.532 .000
Replication 124933.250 1 124933.250 8424.913 .000
Redefinition 140008.863 1 140008.863 9949.636 .000
Reconstruction 159991.246 1 159991.246 8640.835 .000
Reinitiation 149469.756 1 149469.756 8179.008 .000
Gender
Originality 55.974 1 55.974 4.912 .027
Ingenuity 79.911 1 79.911 4.675 .031
Resolution 1.387 1 1.387 .098 .754
Synthesis .081 1 .081 .006 .939
Replication 111.092 1 111.092 7.492 .006
Redefinition 25.922 1 25.922 1.842 .175
Reconstruction 205.707 1 205.707 11.110 .001
Reinitiation 5.907 1 5.907 .323 .570
102
Error
Originality 10220.762 897 11.394
Ingenuity 15331.809 897 17.092
Resolution 12638.059 897 14.089
Synthesis 12271.983 897 13.681
Replication 13301.635 897 14.829
Redefinition 12622.367 897 14.072
Reconstruction 16608.598 897 18.516
Reinitiation 16392.498 897 18.275
Total
Originality 174025.000 899
Ingenuity 157875.000 899
Resolution 228339.090 899
Synthesis 187665.000 899
Replication 153769.000 899
Redefinition 168399.000 899
Reconstruction 197215.000 899
Reinitiation 181933.000 899
Corrected Total
Originality 10276.736 898
Ingenuity 15411.720 898
Resolution 12639.446 898
Synthesis 12272.065 898
Replication 13412.727 898
Redefinition 12648.289 898
Reconstruction 16814.305 898
Reinitiation 16398.405 898
a. R Squared = .005 (Adjusted R Squared = .004)
b. R Squared = .005 (Adjusted R Squared = .004)
c. R Squared = .000 (Adjusted R Squared = -.001)
103
d. R Squared = .000 (Adjusted R Squared = -.001)
e. R Squared = .008 (Adjusted R Squared = .007)
f. R Squared = .002 (Adjusted R Squared = .001)
g. R Squared = .012 (Adjusted R Squared = .011)
h. R Squared = .000 (Adjusted R Squared = -.001)
Estimated Marginal Means
Gender
Dependent Variable Gender Mean Std. Error 95% Confidence Interval
Lower Bound Upper Bound
Originality
Male 13.678 .139 13.405 13.951
Female 13.154 .191 12.779 13.529
Ingenuity
Male 12.806 .171 12.471 13.141
Female 12.179 .234 11.720 12.639
Resolution
Male 15.518 .155 15.214 15.822
Female 15.436 .213 15.019 15.853
Synthesis
Male 13.961 .153 13.661 14.260
Female 13.981 .209 13.570 14.392
Replication
Male 12.751 .159 12.439 13.063
Female 12.013 .218 11.585 12.441
Redefinition
Male 13.286 .155 12.982 13.590
Female 12.929 .212 12.513 13.346
Reconstruction
Male 14.514 .178 14.166 14.863
Female 13.510 .244 13.032 13.988
Reinitiation
Male 13.629 .176 13.282 13.975
Female 13.458 .242 12.983 13.933
104
CORRELATIONS BETWEEN FAMILY EDUCATIONAL BACKGROUND: FATHER
AND THE EIGHT CREATIVITY ELEMENTS
Father
Family
Educati
onal
Backgro
und
Origina
lity
Ingenu
ity
Resolut
ion
Synthe
sis
Replicat
ion
Redefini
tion
Reconstru
ction
Reinitia
tion
Father
Famil
Education
al
Backgroun
d
Pearson
Correlat
ion
1 -.019 .037 .050 .032 -.026 .025 .000 -.033
Sig. (2-
tailed)
.559 .269 .133 .342 .444 .446 .994 .326
N 900 900 900 900 900 900 900 899 900
Originality
Pearson
Correlat
ion
-.019 1 .452**
.411**
.431**
.439**
.470**
.450**
.428**
Sig. (2-
tailed)
.559 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Ingenuity
Pearson
Correlat
ion
.037 .452**
1 .378**
.437**
.440**
.500**
.440**
.307**
Sig. (2-
tailed)
.269 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Resolution
Pearson
Correlat
ion
.050 .411**
.378**
1 .436**
.249**
.356**
.407**
.291**
Sig. (2-
tailed)
.133 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
105
Synthesis
Pearson
Correlat
ion
.032 .431**
.437**
.436**
1 .390**
.425**
.432**
.320**
Sig. (2-
tailed)
.342 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Replicatio
n
Pearson
Correlat
ion
-.026 .439**
.440**
.249**
.390**
1 .462**
.381**
.299**
Sig. (2-
tailed)
.444 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Redefiniti
on
Pearson
Correlat
ion
.025 .470**
.500**
.356**
.425**
.462**
1 .466**
.368**
Sig. (2-
tailed)
.446 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Reconstru
ction
Pearson
Correlat
ion
.000 .450**
.440**
.407**
.432**
.381**
.466**
1 .349**
Sig. (2-
tailed)
.994 .000 .000 .000 .000 .000 .000 .000
N 899 899 899 899 899 899 899 899 899
Reinitiatio
n
Pearson
Correlat
ion
-.033 .428**
.307**
.291**
.320**
.299**
.368**
.349**
1
Sig. (2-
tailed)
.326 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
**. Correlation is significant at the 0.01 level (2-tailed).
106
CORRELATIONS BETWEEN FAMILY EDUCATIONAL BACKGROUND: MOTHER
AND THE EIGHT CREATIVITY ELEMENTS
Mother
Family
Educati
onal
Backgro
und
Origina
lity
Ingenu
ity
Resolut
ion
Synthe
sis
Replicat
ion
Redefini
tion
Reconstru
ction
Reinitia
tion
Mother
Family
Education
al
Backgroun
d
Pearson
Correlat
ion
1 -.030 .036 .084*
.058 .008 .074*
.034 .038
Sig. (2-
tailed)
.365 .287 .011 .082 .812 .026 .304 .260
N 900 900 900 900 900 900 900 899 900
Originality
Pearson
Correlat
ion
-.030 1 .452**
.411**
.431**
.439**
.470**
.450**
.428**
Sig. (2-
tailed)
.365 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Ingenuity
Pearson
Correlat
ion
.036 .452**
1 .378**
.437**
.440**
.500**
.440**
.307**
Sig. (2-
tailed)
.287 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
Resolution
Pearson
Correlat
ion
.084*
.411**
.378**
1 .436**
.249**
.356**
.407**
.291**
Sig. (2-
tailed)
.011 .000 .000 .000 .000 .000 .000 .000
N 900 900 900 900 900 900 900 899 900
CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT
CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT
CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT
CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT
CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT

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CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT

  • 1. 1 CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ): A CREATIVE ASSESSMENT INSTRUMENT FOR INTERACTIVE AND CREATIVE LEARNING ENVIRONMENT Thesigan Nadarajan Assumption University, Bangkok Creativity Selected Elements Questionnaire herewith shall be called (CSEQ) as a creative psychological assessment instrument was developed on the theoretical foundations of “Creative Product Semantic Scale” by Besemer & Quin (1987) and the “Propulsion Model” by Sternberg, Kaufman & Pretz (2002). It covered the four innate creativity elements of: Originality, Ingenuity, Resolution, Synthesis and four external creativity elements of Replication, Redefinition, Reconstruction, and Reinitiation. CSEQ was applied to study 900 students from three colleges (Engineering, Architecture and Information Technology) of Nueva Ecija University of Science and Technology herewith shall be called (NEUST) for: H1o: The significant relationships between the selected student demographic variables, namely: age, gender, study preference, year of study, GPA, student reasons for studying their program, and student’s linguistic ability with the eight creativity elements; H2o: The significant relationships between the selected family demographic variables, namely: parental family status, family income, and family educational background with the eight creativity elements. Highlights from the findings of the demographic, correlational, MANOVA and reliability statistical analyses were: 1) Age, gender, year of study, student reasons for studying their program, student’s linguistic ability had both positive and inverse significant relationships to/for creativity; 2) Mother’s educational background and family income had significant positive and inverse relationships to/for creativity. CSEQ could be: 1) Used for new student orientation for assessment of student creativity that would enable the development of creative leadership activities, projects and programs; 2) In the design, implementation and assessment of creative educational content, methods, strategies and presentations within NEUST environment; 3) In developing creative-centered experimental hubs for creative designs and trainings within NEUST environment for those identified with creative forte. The topic of this current research, “Creativity Selected Elements Questionnaire (CSEQ): A Creative Assessment Instrument for Interactive And Creative Learning Environment,” was the result of the researcher’s interest in the study of creativity in the context of interactive and creative learning environment. Vernon (1978) notes that creativity was a buzzword in Educational Psychology as far back as 1978. It is not something new in the field of education. Besides the educational environment, it was only recently that creativity was explained in terms of innovation in the work place which is now becoming crucial for organizational adaptation and survival. Recognition of creativity in educational environment and work place has combined to highlight the significance of creativity in economic value and social influence in varied areas of humanity’s endeavors and achievements that has evolved to become a need rather than a want justifying this current study involving CSEQ, an assessment instrument for interactive and creative learning environment (Palmon, 2011). CSEQ as a creative psychological assessment instrument was developed on the theoretical foundations of “Creative Product Semantic Scale” by Besemer & O’ Quin (1987) and the “Propulsion Model” by Sternberg, Kaufman & Pretz (2002). It covered the four innate creativity elements of:
  • 2. 2 Originality, Ingenuity, Resolution, Synthesis and four external creativity elements of Replication, Redefinition, Reconstruction, and Reinitiation. CSEQ was applied to study 900 students from three colleges (Engineering, Architecture and Information Technology) of NEUST for testing: H1o: There are significant relationships between the selected student demographic variables, namely: age, gender, study preference, year of study, GPA, student reasons for studying their program, and student’s linguistic ability with the eight creativity elements; H2o: There are significant relationships between the selected family demographic variables, namely: parental family status, family income, and family educational background with the eight creativity elements. Definition of Terms The definition of terms was provided for the purpose facilitating a clearer understanding. NEUST refers to Nueva Ecija University of Science and Technology which is publicly funded and is located in Cabanatuan city, Philippines. CSEQ refers to the Creativity Selected Elements Questionnaire. Positive Psychology was envisioned by Seligman and Csikszentmihalyi (2000) as a means to motivate a change in the fixation with repairing the “worst things in life to building positive qualities.” Strengths and Virtues refer to the six domains of core virtues, namely: Wisdom & Knowledge; Courage; Humanity and Love; Justice; Temperance and Transcendence. Selected Creativity Elements refers to the eight innate and external elements of creativity namely: Originality, Ingenuity, Resolution, Synthesis, Replication, Redefinition, Reconstruction, and Reinitiation. Propulsion model refers to the external criterion as proposed by Sternberg, Kaufman & Pretz (2002). Innate creativity refers to creativity elements of Originality, Ingenuity, Resolution and Synthesis. External creativity refers to creativity elements of Replication, Redefinition, Reconstruction, and Reinitiation. Originality was defined by Stokes (1999) as a kind of novelty that was useful, valuable and generative. Ingenuity, refers to smartness, originality and innovative in generating one-of-kind solutions for problems and needs (Peterson and Seligman, 2004). Resolution allows for the creation of something which is valuable, logical, useful, and understandable (Besemer & O’Quin, 1987). Synthesis refers to links that are constructed between two or more apparently separate ideas (Sternberg, Kaufman & Pretz, 2002). Replication refers to the known which is transferred to a new setting” (Sternberg, Kaufman & Pretz, 2002). Redefinition refers to the known which is extended in a new direction (Sternberg, Kaufman & Pretz, 2002). Reconstruction refers to the new life that is breathed into an approach previously abandoned (Sternberg, Kaufman & Pretz, 2002). Reinitiation refers to the thinking that begins at a radically different point from the current one and takes off in a new direction (Sternberg, Kaufman & Pretz, 2002). Literature Review In the literature review, the researcher examined the theoretical justifications for: 1) Contribution of positive psychology through the six strengths and virtues domains to the study of creativity (Peterson & Seligman, 2004); 2) The selection of eight creativity elements used for the development of CSEQ derived from the “Creative Product Semantic Scale” by Besemer & Quin (1987) and the “Propulsion Model” by Sternberg, Kaufman, & Pretz (2002); 3) The use of each of the eight elements of creativity (Originality, Ingenuity, Resolution, Synthesis, Replication,
  • 3. 3 Redefinition, Reconstruction, and Reinitiation) derived from (Sternberg, Kaufman & Pretz, 2002); 4) The study of the demographic variables of the two hypotheses (Piers, 1968; Kuhn & Holling, 2009). Method Research Design The current study is a causal comparative research that incorporates descriptive and inferential analyses methodology to achieve its objectives. Participants A total of 900 participants from three colleges (Engineering, Architecture and Information Technology) of NEUST comprised the study sample. The breakdown of student demographics consisted of 65.3% (n=588) male students and 34.7% (N=312) females. Their ages ranged from 15 to 32 years, with a mean age of 19 years. The samples for study preferences included abstract, social sciences, religion, science, arts, technical and math. In terms of ethnicity, they were all Pilipino and this was why ethnicity was not included as a variable in the demographics as statically it would be meaningless. A purposive sampling technique was utilized for data collection as the research was targeted for the three colleges with seven study preferences. Participants gave informed consent prior to answering the questionnaires which were voluntary and involved no compensation. Strict confidentiality was observed to protect privacy Instrumentation CSEQ was divided into two sections: demographics and question items. The demographic sections were further divided into: 1) Student; 2) Family; 3) Family Education Background; 4) Reasons for Choosing the Program and 5) Student’s Linguistic Ability categories. The questions items section consisted of a Likert scale of 40 items with a five point responses (1 – Not At All, 2- Seldom, 3 – Uncertain, 4 – Often, 5 – All the Time). The item coding consisted of five items for each of the eight scales of: Originality (items 2, 4, 18, 14, 23); Ingenuity (items 5, 17, 32, 28, 36); Resolution (7, 21, 25, 19, 34); Synthesis (8, 24, 12, 37, 27); Replication (items 9, 31, 38, 16, 33); Redefinition (items 10, 29, 35, 22,39); Reconstruction (items 6, 40, 13, 26, 30); and Reinitiation (items 11, 15, 20, 3, 1). Data Collection Procedures The data collection process was carried out in two stages: the pilot study and the actual data collection. The pilot study of 100 % (n=300) cases was conducted on forty items. A Cronbach alpha of .886 (.89) was obtained which confirmed the participant’s comprehension of the scale items. Actual Data Collection For the actual data collection, a total of 1,050 CSEQ questionnaires were distributed to the three colleges, each receiving 350 copies. Out of the 1,050 CSEQ questionnaires were distributed, only 920 were returned to the researcher. The rest (130 questionnaires) were either lost or unaccounted for at the time of the collection. When the 920 questionnaires were individually inspected for errors, 20 questionnaires were found to be non-usable due to respondents’ error in answering. Only 900 valid questionnaires were utilized for data analysis. Data Analysis
  • 4. 4 The valid 900 questionnaires (n= 900) were statistically analyzed for Frequency, Percentile, Reliability, Pearson Correlation, MANOVA gender differences output. Results Demographic Analysis The demographics profile of respondents consisted of two categories namely, student demographics backgrounds and family demographics backgrounds. In terms of student demographics backgrounds, the sample consisted of 900 students; 65.3% (n=588) male students and 34.7% (N=312) females. Their ages ranged from 15 to 32 years, with a mean age of 19 years. In terms of ethnicity, they were all Pilipino and this was why ethnicity was not included as a variable in the demographics as statically it would be meaningless. Their study preferences in an ascending order were as follows: 3.4% (N=31) abstract, 14.4% (N=130) social sciences, 6.7% (N=60) religion, 14.4% (N=130) science, 16.6% (N=149) arts, 25.7% (N=231) technical and 28.8% (N=259) math. In terms of year of study in ascending order, there were: 18.2% (N=164) 1st year, 22.4% (N=202) 2nd year, 27.8% (N=250) 3rd year, 21.4% (N=193) 4th year, 9.7% (N=87) 5th year and .4% (N=4) 6th year students. For GPA in ascending order: 6.3% (N=57) were 1.0, 8.0% (N=72) were 1.25, 8.2% (N=74) were 1.50, 8.8% (N=79) were 1.75, 16.1% (N=145) were 2.0, 16.4% (N=148) were 2.25, 19.0% (N=171) were 2.50, 16.4% (N=148) were 2.25, 19.0% (N=171) were 2.50, 12.7% (N=114) were 2.75, 4.1 (N=37) were 3.0 and .3% (N=3) were 5.0. Their reasons for their choice of programs were: 26.1% (N=235) considered them to be their field of interest, 15.8% (N=142) had related basic knowledge / experience, 19.1% (N=172) were graduates in those programs, 26.0% (N=234) saw them as an opportunity to study and work abroad, 10.8% (N=97) saw them as opportunity to begin and manage their own businesses and 2.2% (N=20) chose because they felt they couldn’t find jobs for lesser qualifications. In terms of linguistics, for spoken languages: 2.3% (N=21) spoke 1, 65.0% (N=585) spoke 2, 9.1% (N=262) spoke 3, 1.3% (N=12) spoke 4 and 2.2% (N=20) spoke 5. In terms of linguistics, for written languages: 3.8% (N=34) wrote 1), 68.0% (N=612) wrote 2, 24.4% (N=220) wrote 3, 1.9% (N=17) wrote 4, 1.8% (N=16) wrote 5 and .1% (N=1) wrote 6. For family demographics backgrounds, the areas covered were parental family status in ascending order: 91.0% (N=819) were married, 6.9% (N=62) were separated, .2% (N=2) were divorced, 1.6% (N=14) were remarried and .3% (N=3) were orphaned. For family income in pesos in descending order: 11.4% (N=103) earned >25,000.00, 14.0% (N=126) earned 20,000 to 25,000.00, 17.0 (N=153) earned 15,000.00 to 20,000.00, 19.7% (N=177) earned 10,000.00 to 15,000.00, 22.1% (N=199) earned 5,000.00 to 10,000.00, 15.8% (N=142) earned < 5000.00 and .1% (N=1) earned 64.00. In terms of family educational backgrounds for fathers: 5.1% (N=46) were elementary levels, 3.9% (N=35) were elementary graduates, 8.0% (N=72) were high school levels, 20.9% (N=188) were high school graduates, 27.4% (N=247) were college levels and 34.7% (N=312) were college graduates. For family educational backgrounds for mothers: 4.3% (N=39) were elementary levels, 4.4% (N=40) were elementary graduates, 7.7% (N=69) were high school levels, 24.9% (N=224) were high school graduates, 20.2% (N=182) were college levels and 38.4% (N=346) were college graduates. Reliability Analyses Prior to computing the eight scales of CSEQ, Reliability analysis was conducted on
  • 5. 5 the items that represented these scales. The Cronbach alpha coefficients were: Originality (.48), Ingenuity (.50), Resolution (.50), Synthesis (.37) and four external creativity elements of Replication (.44), Redefinition (.49), Reconstruction (.35), and Reinitiation (.32). The computed Cronbach’s alpha coefficients for all eight scales were a low to high and ranged from .32 to .50. This was expected given the small number of items representing each scale. The computed Cronbach’s alpha coefficient for the eight scales of CSEQ was .84. Items are considered internally consistent if their corrected item- total correlations (I-T) are ≥ .33 which represent approximately 10% of the variance of the total scale accounted for in the analysis. The corrected item - total correlations (I-T) were from a low (.47) to high (.64) which clearly proved internal consistency of the eight scales of CSEQ that justified its use. Hypothesis Testing The results of the two hypotheses testing were as follows: H1o: There are significant relationships between the selected student demographic variables, namely: age, gender, study preference, year of study, GPA, student reasons for studying their program, and student’s linguistic ability with the eight creativity elements. A Correlational analysis of the selected student demographic of: age, study preference, year of study, GPA, student reasons for studying their program, and student’s linguistic ability with the eight creativity elements found that: 1) Age had positive significant relationship with Replication (r=.088, p<.05); 2) Year of Study had an inverse significance relationship with originality (r=-.077, p<.05) and redefinition (r=-.076, p<.05); 3) Student reasons for studying their program had positive significant relationship with Synthesis (r=.067, p<.05); 4) Student’s linguistic ability (spoken and written language) had positive significant relationship with Synthesis (r=.067, p<.05), (r=.075, p<.05) and Reinitiation (r=.087, p<.05); A multivariate analysis of variance (MANOVA) was employed to test for gender difference among the eight creativity elements. The analysis yielded significant overall gender effect among the eight creativity elements, multivariate Pillai F Pillai F (8,890)=2.71, p<.05. However, follow-up tests of between-subject effects yielded significant male gender effects for the creative element of originality F(1,897)=4.91, p<.05; ingenuity (1,897)=4.70, p<.05; Replication F(1,897)=7.50, p<.05 and Reconstruction F(1,897)=11.11, p<.05. H2o: There are significant relationships between the selected family demographic variables, namely: parental family status, family income, and family educational background with the eight creativity elements. A Correlational analysis of the selected family demographic variables, namely: parental family status, family income, and family educational background with the eight creativity elements found that: 1) Family educational background (mother’s background) had a significant positive relationship with resolution (r=.084, p<.05) and Redefinition (r=.074, p<.05). 2) Family income had a significant inverse relationship with ingenuity (r=-.071, p<.05); resolution (r=-.077, p<.05); redefinition (r=-.073, p<.05). Discussion The researcher will divide the discussion of the findings into: 1) Findings from the
  • 6. 6 Demographic analysis; 2) Findings on gender difference; 3) Findings from Hypothesis one and 4) Findings from Hypothesis two of this research. Demographic Findings The notable highlight from the demographic findings is the students’ mean age. The students’ ages ranged from 15 to 32 years, with a mean age of 19 years. What does the mean age indicate? According Stang & Story (2005), the students are in the adolescent period that emphasizes on biological, psychosocial and cognitive changes. And how does the transitional stage affect adolescence creativity? Wai, Lubinski, & Benbow (2005) reports in their longitudinal study that spans from age 13 to 33, that adolescence are prone to qualitative accomplishments when creativity is paired with their preferences. Thus, the opportunity to inculcate the students Engineering, Architecture and Information Technology within NEUST for qualitative accomplishments by pairing creativity with their preferences is open by the status of the students’ mean age. Discussion of Findings Of Hypothesis 1 Age had positive significant relationship with Replication (r=.088, p<.05). What has age to do with creativity element of replication? Researches related to age and creativity has pointed out that creativity can decline or increase with age. (McCrae, Arenberg, & Costa, 1987). And the creativity element of replication in which the known is extended in a new direction, can also decline or increase with age. In the field of music, it was found that classical composers were able to extend their known knowledge in new directions in terms of “melodic originality, melodic variation, repertoire popularity, aesthetic significance, listener accessibility, performance duration, and thematic size” as they aged (Simonton, 1991b). Thus, the students from the colleges of Engineering, Architecture and Information Technology within NEUST have the potential to extend their creativity abilities and skills in new directions as they mature with age. Year of Study had an inverse significance relationship with originality (r=-.077, p<.05) and redefinition (r=-.076, p<.05). This specific finding indicates that an increase in students’ year of study have a decrease (inverse) in their creativity element of originality (novelty / generative) and redefinition (the known is extended in a new direction) creativity elements. Why? A possible explanation can be found in an article by Maisuria (2005) who noted the demise of creativity (originality / replication) in the national curriculum of England and Wales due to the demands of “standardization, centralization, and vocationalization of education” that focused on business-education orientation rather than a student-centered learning experience. Depending on the year of study, the students from the colleges of Engineering, Architecture and Information Technology within NEUST whose exposure (lesser / greater) to the demands of standardization, centralization, and vocationalization of education may similarly focus on business-education-orientation and passing of examinations resulting in the decline of creativity (originality / redefinition). Thus, as an institution it is necessary to strategize towards a balance between creativity and bureaucratic demands. Student reasons for studying their program had positive significant relationship with Synthesis (r=.067, p<.05). Student reasons for the choice of their programs were positively associated with the
  • 7. 7 creativity element of synthesis. Why? Synthesis involves linking between two or more apparently separate ideas (Sternberg, Kaufman & Pretz, 2002). When a student chose a program, he/she had to determine between multiple reasons in which each reason might have multiple advantages and disadvantages. In making a final decision, the student had to link (synthesize) the various reasons, advantages and disadvantages to derive to a specific reason to support their final choice. Thus, it is natural for the student to endorse the creativity element of synthesis. Student’s linguistic ability (spoken and written language) had positive significant relationship with Synthesis (r=.067, p<.05), (r=.075, p<.05) and Reinitiation (r=.087, p<.05). Why was there a positive relationship between student’s linguistic ability (spoken / written language) and creativity element of synthesis? The explanation may be found in the research done on spoken and written language. Olofin & Olusoji (2013) concluded that written and spoken languages are two different things and requires two different skills. The students endorsement of synthesis highlights the fact that different and separate ideas and skills had to be linked together to bring about comprehension in communication (written & spoken). Thus, it was natural for the students to find a relationship and thereby endorse their linguistic abilities (written & spoken) with creativity element of synthesis. Another important point is that spoken language in linguistics is always a blending within a social-cultural background that gives meanings to words that are used in shared communications (Samovar & Porter, 1987). When the students found a positive relationship between their spoken language and the creativity element of Reinitiation – they were endorsing their willingness to explore shared ideas and meanings in a different social-cultural linguistic platform than the one they were in currently. In short, they are willing to explore new starting points and directions in their lives (Sternberg, 2006). Findings On Gender Difference There was overall gender effect among the eight creativity elements, multivariate Pillai F (8,890)=2.71, p<.05. The follow-up tests of between-subject effects also yielded significant male gender effects for the creative element of originality F(1,897)=4.91, p<.05; ingenuity (1,897)=4.70, p<.05; Replication F(1,897)=7.50, p<.05 and Reconstruction F(1,897)=11.11, p<.05. This finding raises the issue for the need to develop the female students of the three colleges who lag behind in the creativity elements. It is not unusual as females still live in a ‘Patriarchy world’ (male ruled) in which the female gender suffers from discriminations, exploitations and inequalities which is not helpful for creative psychological developments (Walby, 1990). Findings on Hypothesis 2 Family educational background (mother’s background) had a significant positive relationship with resolution (r=.084, p<.05) and Redefinition (r=.074, p<.05). It is interesting to note that the family educational background of the fathers had no significance relationship with the eight creativity elements. While the family educational background of the mothers had significant positive relationships with the eight creativity elements namely, resolution and Redefinition. Fasko (2000-2001) in his article entitled “Education and Creativity” had pointed out that creativity can be developed through education as creative activities are
  • 8. 8 instances of learning. This findings together with the proposal of Fasko establishes that females living in a Patriarchy world (male- ruled) can develop creativity through education. In short, learnings and education empowers females to be creative (Robinson, 2001). Family income had a significant inverse relationship with ingenuity (r=-.071, p<.05); resolution (r=-.077, p<.05); redefinition (r=- .073, p<.05. Kiernan & Mensah (2011) have clearly shown in their research that parenting styles and persistent poverty is detrimental to children’s’ development including creativity. It is interesting to note in the current research that an increase in family income (economics) has an inverse impact on the creativity of children. How can this be explained? Despite the abundance of economic resources, children may decline in ingenuity (smartness, originality and innovative in generating one- of-kind solutions for problems and needs) if they are exposed to poor parenting styles (Ermisch , Iacovou & Skew, 2011). In short, though persistent poverty affects creativity - economic abundance with poor parenting styles also may lead to a decline in creativity. Conclusions The findings of this current research have at least three immediate uses: 1) It can be used for new student orientation for assessment of student strengths that would enable the development of student leadership activities, projects and programs; 2) It can be used in the design, implementation and assessment of creative educational content, methods, strategies and presentations within university environments; 3) It can be used in developing a creative-centered experimental hubs for creative designs within a university environment for those identified with creative strengths. Limitations of the Study The researcher would like to list five limitations of this study: 1) The single ethnicity of the sample (Pilipino) only could limit the objectivity of a wider possible responses; 2) The CSEQ questionnaire is a type of self-report measurement which is dependent on the participants’ truthfulness in responding to the question items that cannot be realistically validated. The honesty of the respondents is accepted in good faith; 3) The question items can be rephrased and redesigned according different social-cultural perspectives that may affect the responses of the participants. 4) There is the possibility of additions of more than eight creativity elements which may prove the present research to be limited in its coverage of the scope of creativity elements; 5) There could be a limitation factor in the findings through the lack of execution of the CSEQ in other languages. Delimitations The researcher would like to list two delimitations of this study. 1) CSEQ was designed for measuring the eight creativity elements and therefore it cannot be generalized for other forms of study (i.e., personality); 2) The current study was designed for student population (university level) and therefore caution must be exercise in generalizing to other age groups (i.e., high school). Due to the above limitations and delimitations, the findings of this research should be interpreted with caution. However, regardless of the above limitations and delimitations, the study of CSEQ is a new psychological instrument for measuring the eight creativity elements but is based on the
  • 9. 9 strong theoretical foundations of established researches. Recommendations The recommendations based on this study are: 1) Validation of CSEQ instrument within a multi-cultural population In order to counter the points of one, three and five in Limitations, it is recommended that future research of CSEQ be conducted within multi-cultural populations. 2) Future studies with different demographic parameters for generalization purposes. In order to counter the point 2 in Delimitations, it is recommended that future researches would be designed to include different demographic parameters (age groups) for wider generalizations. Since this research utilizing CSEQ as a psychological assessment instrument is new, this research is only meant to be a pilot or exploratory study for more substantial research in the area of the eight creativity
  • 10. 10 Reference Besemer, S.P., & O’Quin, K. (1987). Creative product analysis: Testing a model by developing a judging instrument. In S. G. Isaksen (Ed.), Frontiers of creativity research: beyond the basics (pp. 367-389). Buffalo, NY: Beraly. Ermisch, J., Iacovou, M & Skew, A. J. (2011).Family Relationships, in Understanding Society, ed. McFall, S. ESRC, Swindon, UK. Fasko, D. Jr., (2000-2001). Creativity and Education. Creativity Research Journal, 2000–2001, Vol. 13, Nos. 3 & 4, 317–327. Kiernan, K.E. and Mensah, F.K. (2011), Poverty, family resources and children’s early educational attainment: the mediating role of parenting, British Educational Research Journal 37(2) 317-336. Kuhn, J.-T., & Holling, H. (2009). Measurement invariance of divergent thinking across gender, age, and school forms. European Journal of Psychological Assessment, 25, 1-7. doi: 10.1027/1015-5759.25.1.1 Maisuria, A., (2005). The Turbulent Times of Creativity in the National Curriculum. Policy Futures in Education, Volume 3, Number 2. McCrae, R. R., Arenberg , D. , & Costa, P. T. Jr. (1987). Declines in divergent thinking with age: Cross-sectional, longitudinal, and cross-sequential analyses . Psychology and Aging, 2,130-137. Olofin, Olusoji A., (2013). The Spoken and the Written Language: Confusion between English Sounds and Letter, Greener Journal of Art and Humanities, Vol. 3 (1), pp. 009-018. Philip E. Vernon. P. E., (1973). Creativity: A Current Bandwagon. The Canadian Psychologist Vol. 14, No. 1, January 1973. Palmon, R. R., (2011). Introduction to Special Issue: The Psychology of Creativity and Innovation in the Workplace. © 2011 American Psychological Relationship, 1931- 3896/11/$12.00 DOI: 10.1037/a0018586. Peterson, C. & Seligman, M. E. P. (2004). Character strengths and virtues: A handbook and Classification. Washington, D.C.: American Psychological Relationship. PIERS, E. V. Adolescent creativity. In J. F. Adams (Ed.), Understanding adolescence. Boston: Allyn & Bacon, 1968. Pp. 159-182. Robinson, Ken., (2001) Out of Our Minds: Learning to be Creative. Chichester: Capstone Publishing Limited. Samovar, L. A., & Porter, R. E. (Eds.). (1997). Intercultural communication: A reader (eighth ed.). Belmont, Ca: Wadsworth Publishing Company.
  • 11. 11 Setigman, M. E.P., & Csikszentmihalyi, M., (2000). Positive Psychology, the American Psychological Relationship. lnc. 0003-066X/00/$5.00, Voh 55. No. 1. 5 14 DOI: 10.1037//0003- 066X.55.1.5 Simonton, D. K. (1991b). Emergence and realization of genius: The lives and works of 120 classical composers. Journal of Personality, and Social Psychology, 61, 829–840 Strenberg, R. J., Kaufman, J.C., & Pretz, J.E. (2002). The creativity conundrum: A propulsion model of kinds of creative contributions. New York: Psychology Press. Stokes, P.D. (1999). Novelty. In M.Runco & S. Prtizker (Eds), Encyclopedia of creativity, Vol. 2 (pp. 297-304). NY:Academic Press. Sternberg, R. J., The Nature of Creativity. Creativity Research Journal, 2006, Vol. 18, No. 1, 87–98 Vernon, P. E. 1978. “Review of Creativity Attitude Survey.” See Bachman & Tuckman 1978, pp. 361–62. Walby, Sylvia, Theorising Patriarchy, Basil Black Well, Oxford, London 1990. Wai, J., Lubinski, D., & Benbow, C. P. (2005). Creativity and occupational accomplishments among intellectually precocious youths: An age 13 to age 33 longitudinal study. Journal of Educational Psychology, 97, 484-492.
  • 13. 13 APPENDIX A: CREATIVITY SELECTED ELEMENTS QUESTIONNAIRE (CSEQ)
  • 14. 14 CREATIVITY: SELECTED ELEMENTS QUESTIONNAIRE (CSEQ) Dear Participants, The researcher is currently conducting a research on “Sustainable Educational Development: Identifying, Describing and Comparing Selected Elements of Creativity that may Promote Educational Excellence,” and gratefully thank you for your voluntary participation in answering this questionnaire. All information collected will be kept confidential and secured. DEMOGRAPHICS Student’s Demographics Age Gender Study Preference Year of Study in College GPA Fill in, ________yrs Check relevant, Male__ / Female__ Check relevant, Arts:___/ Science: ____ / Math: ___ / Technical: ___ / Abstract: ___ / Social Sciences: ___ / Religion: ___ Check relevant, 1st :___ 2nd : ___ 3rd : ___ 4th : ___ 5th : ___ Fill in the correct answer on the line below, 1.0 / 1.25 / 1.50 / 1.75 / 2.0 / 2.25 / 2.50 / 2.75 / 3.0 / 5.0 / Inc / D
  • 15. 15 Family Demographics Parental Family Status Married (M) / Separated (S) / Divorced (D) / Remarried (R) / Orphaned (O) Family Income 1: 25,000 > / 2: 20,000 – 25,000 / 3: 15,000 – 20,000 4: 10,000 – 15,000 / 5: 5,000 – 10,000 / 6: 5,000 < Strike off the irrelevant, M / S / D / R / O Circle your selection, 1: / 2: / 3: / 4: / 5: / 6: Family Educational Background Mother Check, Father Check Elementary Level Elementary Level Elementary Graduate Elementary Graduate High School Level High School Level High School Graduate High School Graduate College Level College Level College Graduate College Graduate
  • 16. 16 Reasons for Choosing the Program Check relevant, My field of interest I have basic knowledge / experience related to this program Graduates in this program are in demand Opportunity to study / work abroad Opportunity to begin and manage my own business I can’t find jobs for lesser qualifications Student’s Linguist Ability Number of Spoken Language Circle number, Number of Written Languages Circle number, 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9 / 10 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9 / 10
  • 17. 17 Answering Questions Please answer all questions by checking your relevant choice in the blank space below the choices, 1. Have you tried travelling on a different route to reach a same destination? 1 - Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 - All the Time 2. Have you ever chosen an entirely new solution to solve an old repetitive problem? 1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time 3. Have you ever tried changing your hair style to have new look? 1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 - All the Time 4. Have you chosen an old solution to solve an entirely new problem? 1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time 5. Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? 1 – Not At All 2 - Seldom 3 - Uncertain 4 - Often 5 – All the Time 6. Have you ever considered analyzing a problem by viewing it under different scenarios? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 7. Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 18. 18 8. Have you tried generating a new idea using two existing ideas? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 9. Have you ever wondered whether the performance of the pop group “KARA” can be replicated in your own country? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 10. Have you tried using “H2o” rather than “water” in your daily conversation? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 11. Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 12. Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 13. Have you ever tried using bamboo to make arrows, planks for flooring and a spear? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 14. Have you risked venturing into a new and unknown project or business? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 15. Have you considered studying an entirely new course in the event you fail your present course? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 19. 19 16. Have you considered that a replicated version of a hit song can be equally valuable in price and quality? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 17. Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 18. Have you supported any law or a group that protects an original work of art, authorship or music? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 19. Have you tried to understand comprehensively the functions of the products that you bought? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 20. Have you ever considered learning a foreign language for a new vocational move in your life? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 21. Have you used logical reasoning during emotional conflicts? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 22. Have you ever been convinced that a same element can be transformed into water, gas, and ice? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 20. 20 23. Have you bought and used an entirely revolutionary new electronic product that had no performance track record? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 24. Have you thought that a new religion can be created by combining two or more existing religions? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 25. Have you considered the usefulness of the things or products you have bought? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 26. Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 27. Have you ever thought why children became more active after eating more sweets or chocolates? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 28. Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 29. Have you ever tried painting a same picture in water color, charcoal, and oil color? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 30. Have you ever thought that wine can be made out of mango rather than grapes? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 21. 21 31. Have you seen, purchased or owned a replicated art piece? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 32. Have you ever tried to get an income without working, without breaking any laws and without asking anyone for help? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 33. Have you ever tried replicating a successful activity, project, or business? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 34. Have you ever asked yourself that according to your income status, whether buying a hummer is logical? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 35. Have you ever thought that Michael Jackson’s portrait in color is the same when it is in black and white? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 36. Have you ever thought how you can remember a thousand faces without any form of gadget aid? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 37. Have you ever linked your feeling of freshness with the amount of sleep you have had daily? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 22. 22 38. Have you ever tried replicating you friends’ successful study methods and strategies? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 39. Have you ever tried singing a same song in country, rock and hip-hop? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time 40. Have you ever tried to remake a broken toy into a different one? 1-Not At All 2-Seldom 3-Uncertain 4-Often 5-All the Time
  • 23. 23 APPENDIX B: ITEM CODING FOR CREATIVITY: SELECTED ELEMENTS QUESTIONNAIRE (CSEQ)
  • 24. 24 ITEM CODING FOR CREATIVITY: SELECTED ELEMENTS QUESTIONNAIRE No Items Creative Elements 2 4 18 14 23 Have you ever chosen an entirely new solution to solve an old repetitive problem? Have you chosen an old solution to solve an entirely new problem? Have you supported any law or a group that protects an original work of art, authorship or music? Have you risked venturing into a new and unknown project or business? Have you bought and used an entirely revolutionary new electronic product that had no performance track record? Originality
  • 25. 25 5 17 32 28 36 Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? Have you ever tried to get an income without working, without breaking any laws and without asking anyone for help? Have you ever thought that it was possible to eat using your feet while your hands are tied behind your back? Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? Ingenuity
  • 26. 26 7 21 25 19 34 Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? Have you used logical reasoning during emotional conflicts? Have you considered the usefulness of the things or products you have bought? Have you tried to understand comprehensively the functions of the products that you bought? Have you ever asked yourself that according to your income status, whether buying a hummer is logical? Resolution
  • 27. 27 8 24 12 37 27 Have you tried generating a new idea using two existing ideas? Have you thought that a new religion can be created by combining two or more existing religions? Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? Have you ever linked your feeling of freshness with the amount of sleep you have had daily? Have you ever thought why children became more active after eating more sweets or chocolates? Synthesis
  • 28. 28 9 31 38 16 33 Have you ever wondered whether the performance of the pop group “KARA” can be replicated in your own country? Have you seen, purchased or owned a replicated art piece? Have you ever tried replicating you friends’ successful study methods and strategies? Have you considered that a replicated version of a hit song can be equally valuable in price and quality? Have you ever tried replicating a successful activity, project, or business? Replication
  • 29. 29 10 29 35 22 39 Have you tried using “H2o” rather than “water” in your daily conversation? Have you ever tried painting a same picture in water color, charcoal, and oil color? Have you ever thought that Michael Jackson’s portrait in color is the same when it is in black and white? Have you ever been convinced that a same element can be transformed into water, gas, and ice? Have you ever tried singing a same song in country, rock and hip-hop? Redefinition
  • 30. 30 6 40 13 26 30 Have you ever considered analyzing a problem by viewing it under different scenarios? Have you ever tried to remake a broken toy into a different one? Have you ever tried using bamboo to make arrows, planks for flooring and a spear? Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? Have you ever thought that wine can be made out of mango rather than grapes? Reconstruction
  • 31. 31 11 15 20 3 1 Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? Have considered studying an entirely new course in the event you fail your present course? Have you ever considered learning a foreign language for a new vocational move in your life? Have you ever tried changing your hair style to have new look? Have you tried travelling on a different route to reach a same destination? Reinitiation
  • 32. 32 APPENDIX C: FREQUENCIES FOR DEMOGRAPHICS
  • 33. 33 FREQUENCIES FOR DEMOGRAPHICS Statistics Age Gen der Study Prefere nce Year of Stud y in Colle ge GPA Paren tal Fami ly Statu s Fami ly Inco me Father Famil Educati onal Backgro und Mother Famil Educati onal Backgro und Reaso ns for Choos ing Progra m Numbe r of Spoken Langua ges Numbe r of Written Langua ges N Valid 900 900 900 900 900 900 900 900 900 900 900 900 Missi ng 0 0 0 0 0 0 0 0 0 0 0 0 Mean 19.23 56 1.34 67 3.2500 2.832 2 5.360 0 1.133 3 3.743 3 4.6567 4.6756 2.862 2 2.3611 2.3022 Median 19.00 00 1.00 00 3.0000 3.000 0 6.000 0 1.000 0 4.000 0 5.0000 5.0000 3.000 0 2.0000 2.0000 Mode 20.00 1.00 3.00 3.00 7.00 1.00 5.00 6.00 6.00 1.00 2.00 2.00 Std. Deviation 2.137 66 .476 17 1.6149 8 1.252 21 2.198 03 .5036 0 1.596 61 1.38838 1.38932 1.441 06 .66171 .66687 Variance 4.570 .227 2.608 1.5684.831 .254 2.549 1.928 1.930 2.077 .438 .445 Skewness 1.779 .645 .610 .112 -.384 4.841 -.227 -1.050 -.950 .113 1.571 1.619 Std. Error of Skewness .082 .082 .082 .082 .082 .082 .082 .082 .082 .082 .082 .082 Kurtosis 7.048 - 1.58 7 .061 -.902 -.754 26.16 1 - 1.076 .475 .243 -1.125 3.894 4.525 Std. Error of Kurtosis .163 .163 .163 .163 .163 .163 .163 .163 .163 .163 .163 .163 Range 17.00 1.00 6.00 5.00 9.00 4.00 5.00 5.00 5.00 5.00 4.00 5.00 Minimum 15.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Maximum 32.00 2.00 7.00 6.00 10.00 5.00 6.00 6.00 6.00 6.00 5.00 6.00 Percent iles 25 18.00 00 1.00 00 2.0000 2.000 0 4.000 0 1.000 0 2.000 0 4.0000 4.0000 1.000 0 2.0000 2.0000
  • 34. 34 50 19.00 00 1.00 00 3.0000 3.000 0 6.000 0 1.000 0 4.000 0 5.0000 5.0000 3.000 0 2.0000 2.0000 75 20.00 00 2.00 00 4.0000 4.000 0 7.000 0 1.000 0 5.000 0 6.0000 6.0000 4.000 0 3.0000 3.0000 Age Frequency Percent Valid Percent Cumulative Percent Valid 15.00 2 .2 .2 .2 16.00 45 5.0 5.0 5.2 17.00 121 13.4 13.4 18.7 18.00 181 20.1 20.1 38.8 19.00 181 20.1 20.1 58.9 20.00 199 22.1 22.1 81.0 21.00 89 9.9 9.9 90.9 22.00 30 3.3 3.3 94.2 23.00 23 2.6 2.6 96.8 24.00 7 .8 .8 97.6 25.00 7 .8 .8 98.3 26.00 6 .7 .7 99.0 27.00 1 .1 .1 99.1 28.00 1 .1 .1 99.2 29.00 2 .2 .2 99.4 30.00 1 .1 .1 99.6 32.00 4 .4 .4 100.0 Total 900 100.0 100.0
  • 35. 35 Gender Frequency Percent Valid Percent Cumulative Percent Valid Male 588 65.3 65.3 65.3 Female 312 34.7 34.7 100.0 Total 900 100.0 100.0 Study Preference Frequency Percent Valid Percent Cumulative Percent Valid Arts 149 16.6 16.6 16.6 Science 130 14.4 14.4 31.0 Math 259 28.8 28.8 59.8 Technical 231 25.7 25.7 85.4 Abstract 31 3.4 3.4 88.9 Social Science 40 4.4 4.4 93.3 Religion 60 6.7 6.7 100.0 Total 900 100.0 100.0 Year of Study in College Frequency Percent Valid Percent Cumulative Percent Valid 1st Year 164 18.2 18.2 18.2 2nd Year 202 22.4 22.4 40.7 3rd Year 250 27.8 27.8 68.4
  • 36. 36 4th Year 193 21.4 21.4 89.9 5th Year 87 9.7 9.7 99.6 6.00 4 .4 .4 100.0 Total 900 100.0 100.0 GPA Frequency Percent Valid Percent Cumulative Percent Valid 1.0 57 6.3 6.3 6.3 1.25 72 8.0 8.0 14.3 1.50 74 8.2 8.2 22.6 1.75 79 8.8 8.8 31.3 2.0 145 16.1 16.1 47.4 2.25 148 16.4 16.4 63.9 2.50 171 19.0 19.0 82.9 2.75 114 12.7 12.7 95.6 3.0 37 4.1 4.1 99.7 5.0 3 .3 .3 100.0 Total 900 100.0 100.0 Parental Family Status Frequency Percent Valid Percent Cumulative Percent Valid Married 819 91.0 91.0 91.0 Separated 62 6.9 6.9 97.9 Divorced 2 .2 .2 98.1
  • 37. 37 Remarried 14 1.6 1.6 99.7 Orphaned 3 .3 .3 100.0 Total 900 100.0 100.0 Family Income Frequency Percent Valid Percent Cumulative Percent Valid 25000> 103 11.4 11.4 11.4 20000 - 25000 126 14.0 14.0 25.4 15000 - 20000 153 17.0 17.0 42.4 10000 - 15000 177 19.7 19.7 62.1 5000 - 10000 199 22.1 22.1 84.2 5000< 142 15.8 15.8 100.0 Total 900 100.0 100.0 Father Family Educational Background Frequency Percent Valid Percent Cumulative Percent Valid Elementary Level 46 5.1 5.1 5.1 Elementary Graduate 35 3.9 3.9 9.0 High School Level 72 8.0 8.0 17.0 High School Graduate 188 20.9 20.9 37.9 College Level 247 27.4 27.4 65.3 College Graduate 312 34.7 34.7 100.0 Total 900 100.0 100.0
  • 38. 38 Mother Family Educational Background Frequency Percent Valid Percent Cumulative Percent Valid Elementary Level 39 4.3 4.3 4.3 Elementary Graduate 40 4.4 4.4 8.8 High School Level 69 7.7 7.7 16.4 High School Graduate 224 24.9 24.9 41.3 College Level 182 20.2 20.2 61.6 College Graduate 346 38.4 38.4 100.0 Total 900 100.0 100.0 Reasons for Choosing Program Frequency Percent Valid Percent Cumulative Percent Valid My field of interest 235 26.1 26.1 26.1 I have basic knowledge / experience related to this program 142 15.8 15.8 41.9 Graduates in this program are in demand 172 19.1 19.1 61.0 Opportunity to study / work abroad 234 26.0 26.0 87.0 Opportunity to begin and manage my own business 97 10.8 10.8 97.8 I can't find jobs for lesser qualifications 20 2.2 2.2 100.0 Total 900 100.0 100.0
  • 39. 39 Number of Spoken Languages Frequency Percent Valid Percent Cumulative Percent Valid 1 21 2.3 2.3 2.3 2 585 65.0 65.0 67.3 3 262 29.1 29.1 96.4 4 12 1.3 1.3 97.8 5 20 2.2 2.2 100.0 Total 900 100.0 100.0 Number of Written Languages Frequency Percent Valid Percent Cumulative Percent Valid 1 34 3.8 3.8 3.8 2 612 68.0 68.0 71.8 3 220 24.4 24.4 96.2 4 17 1.9 1.9 98.1 5 16 1.8 1.8 99.9 6 1 .1 .1 100.0 Total 900 100.0 100.0
  • 41. 41
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  • 53. 53 SCALE: RELIABILITY ANALYSIS - PILOT STUDY Case Processing Summary N % Cases Valid 300 100.0 Excludeda 0 .0 Total 300 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .886 .907 40
  • 54. 54 SCALE: ORIGINALITY Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .484 .485 5 Item Statistics Mean Std. Deviation N Have you ever chosen an entirely new solution to solve an old repetitive problem? 3.0800 1.09516 900 Have you chosen an old solution to solve an entirely new problem? 2.9489 1.07848 900 Have you supported any law or group that protects an original work of art, authorship or music? 2.6867 1.26194 900
  • 55. 55 Have you risked venturing into a new and unknown project or business? 2.4122 1.16305 900 Have you bought and used an entirely revolutionary new product that had no performance track record? 2.3667 1.30414 900 Inter-Item Correlation Matrix Have you ever chosen an entirely new solution to solve an old repetitive problem? Have you chosen an old solution to solve an entirely new problem? Have you supported any law or group that protects an original work of art, authorship or music? Have you risked venturing into a new and unknown project or business? Have you bought and used an entirely revolutionary new product that had no performance track record? Have you ever chosen an entirely new solution to solve an old repetitive problem? 1.000 .345 .173 .082 .111 Have you chosen an old solution to solve an entirely new problem? .345 1.000 .148 .047 -.006 Have you supported any law or group that protects an original work of art, authorship or music? .173 .148 1.000 .203 .171 Have you risked venturing into a new and unknown project or business? .082 .047 .203 1.000 .309 Have you bought and used an entirely revolutionary new product that had no performance track record? .111 -.006 .171 .309 1.000
  • 56. 56 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.699 2.367 3.080 .713 1.301 .100 5 Item Variances 1.402 1.163 1.701 .538 1.462 .057 5 Inter-Item Correlations .159 -.006 .345 .352 -53.686 .011 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you ever chosen an entirely new solution to solve an old repetitive problem? 10.4144 8.412 .287 .143 .413 Have you chosen an old solution to solve an entirely new problem? 10.5456 8.951 .204 .131 .463 Have you supported any law or group that protects an original work of art, authorship or music? 10.8078 7.797 .290 .085 .407 Have you risked venturing into a new and unknown project or business? 11.0822 8.218 .279 .120 .416 Have you bought and used an entirely revolutionary new product that had no performance track record? 11.1278 7.931 .245 .117 .441
  • 57. 57 SCALE: INGENUITY Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .499 .558 5 Item Statistics Mean Std. Deviation N Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? 2.6967 1.06736 900 Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? 2.5022 2.17146 900
  • 58. 58 Have you tried to get an income without working, without breaking any laws and without asking anyone for help? 2.4689 1.29778 900 Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? 2.4456 1.17080 900 Have you ever thought how you can remember a thousand faces without any form of gadget aid? 2.4744 1.18030 900 Inter-Item Correlation Matrix Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? Have you tried to get an income without working, without breaking any laws and without asking anyone for help? Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? Have you ever thought how you can remember a thousand faces without any form of gadget aid? Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? 1.000 .063 .093 .196 .173 Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? .063 1.000 .131 .174 .134
  • 59. 59 Have you tried to get an income without working, without breaking any laws and without asking anyone for help? .093 .131 1.000 .225 .252 Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? .196 .174 .225 1.000 .578 Have you ever thought how you can remember a thousand faces without any form of gadget aid? .173 .134 .252 .578 1.000 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.518 2.446 2.697 .251 1.103 .010 5 Item Variances 2.061 1.139 4.715 3.576 4.139 2.240 5 Inter-Item Correlations .202 .063 .578 .515 9.182 .020 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you ever thought that in the absence of any other resources, trying to cross a torrential river on a fallen tree log was a feasible idea? 9.8911 14.531 .181 .046 .493
  • 60. 60 Have you ever thought that you could find a way to cross a field filled with landmines, poisonous snakes and pitfalls? 10.0856 9.820 .192 .041 .575 Have you tried to get an income without working, without breaking any laws and without asking anyone for help? 10.1189 13.006 .262 .082 .450 Have you ever thought how you can remember a thousand contact names and phone numbers without any form of gadget aid? 10.1422 12.118 .448 .357 .351 Have you ever thought how you can remember a thousand faces without any form of gadget aid? 10.1133 12.259 .422 .353 .364
  • 61. 61 SCALE: RESOLUTION Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .497 .510 5 Item Statistics Mean Std. Deviation N Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? 3.2848 1.45274 900 Have you used logical reasoning during emotional conflicts? 3.1156 1.07349 900 Have you considered the usefulness of the things or products you have bought? 3.4067 1.54616 900
  • 62. 62 Have you tried to understand comprehensively the functions of the products that you bought? 3.2300 1.16177 900 Have you ever asked yourself that according to your income status, whether buying a hummer is logical? 2.4478 1.21565 900 Inter-Item Correlation Matrix Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? Have you used logical reasoning during emotional conflicts? Have you considered the usefulness of the things or products you have bought? Have you tried to understand comprehensively the functions of the products that you bought? Have you ever asked yourself that according to your income status, whether buying a hummer is logical? Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? 1.000 .149 .149 .173 .086 Have you used logical reasoning during emotional conflicts? .149 1.000 .255 .309 .144 Have you considered the usefulness of the things or products you have bought? .149 .255 1.000 .340 .032 Have you tried to understand comprehensively the functions of the products that you bought? .173 .309 .340 1.000 .085 Have you ever asked yourself that according to your income status, whether buying a hummer is logical? .086 .144 .032 .085 1.000
  • 63. 63 Inter-Item Covariance Matrix Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? Have you used logical reasoning during emotional conflicts? Have you considered the usefulness of the things or products you have bought? Have you tried to understand comprehensively the functions of the products that you bought? Have you ever asked yourself that according to your income status, whether buying a hummer is logical? Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? 2.110 .233 .336 .292 .153 Have you used logical reasoning during emotional conflicts? .233 1.152 .423 .385 .187 Have you considered the usefulness of the things or products you have bought? .336 .423 2.391 .612 .060 Have you tried to understand comprehensively the functions of the products that you bought? .292 .385 .612 1.350 .119 Have you ever asked yourself that according to your income status, whether buying a hummer is logical? .153 .187 .060 .119 1.478
  • 64. 64 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 3.097 2.448 3.407 .959 1.392 .143 5 Item Variances 1.696 1.152 2.391 1.238 2.075 .279 5 Inter-Item Correlations .172 .032 .340 .308 10.632 .010 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you preferred value in quality over cheapness in cost when making decisions for personal purchases? 12.2000 9.944 .221 .050 .479 Have you used logical reasoning during emotional conflicts? 12.3692 10.472 .354 .140 .400 Have you considered the usefulness of the things or products you have bought? 12.0781 8.829 .311 .147 .414 Have you tried to understand comprehensively the functions of the products that you bought? 12.2548 9.916 .385 .179 .374 Have you ever asked yourself that according to your income status, whether buying a hummer is logical? 13.0370 11.565 .126 .027 .526
  • 65. 65 SCALE: SYNTHESIS Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .374 .386 5 Item Statistics Mean Std. Deviation N Have you tried generating a new idea using two existing ideas? 3.2011 1.66044 900 Have you thought that a new religion can be created by combining two or more existing religions? 2.2878 1.19810 900 Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? 2.2622 1.17450 900 Have you ever linked your feeling of freshness with the amount of sleep you have had daily? 3.1144 1.55765 900
  • 66. 66 Have you ever thought why children became more active after eating more sweets or chocolates? 3.1000 1.25369 900 Inter-Item Correlation Matrix Have you tried generating a new idea using two existing ideas? Have you thought that a new religion can be created by combining two or more existing religions? Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? Have you ever linked yor feeling of freshness with the amount of sleep you have had daily? Have you ever thought why children became more active after eating more sweets or chocolates? Have you tried generating a new idea using two existing ideas? 1.000 .030 .072 .109 .130 Have you thought that a new religion can be created by combining two or more existing religions? .030 1.000 .250 .077 .118 Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? .072 .250 1.000 .039 .058 Have you ever linked your feeling of freshness with the amount of sleep you have had daily? .109 .077 .039 1.000 .236 Have you ever thought why children became more active after eating more sweets or chocolates? .130 .118 .058 .236 1.000
  • 67. 67 Inter-Item Covariance Matrix Have you tried generating a new idea using two existing ideas? Have you thought that a new religion can be created by combining two or more existing religions? Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? Have you ever linked yor feeling of freshness with the amount of sleep you have had daily? Have you ever thought why children became more active after eating more sweets or chocolates? Have you tried generating a new idea using two existing ideas? 2.757 .060 .141 .282 .270 Have you thought that a new religion can be created by combining two or more existing religions? .060 1.435 .352 .143 .177 Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? .141 .352 1.379 .071 .086 Have you ever linked your feeling of freshness with the amount of sleep you have had daily? .282 .143 .071 2.426 .461 Have you ever thought why children became more active after eating more sweets or chocolates? .270 .177 .086 .461 1.572
  • 68. 68 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.793 2.262 3.201 .939 1.415 .225 5 Item Variances 1.914 1.379 2.757 1.378 1.999 .401 5 Inter-Item Correlations .112 .030 .250 .220 8.289 .006 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you tried generating a new idea using two existing ideas? 10.7644 9.393 .148 .027 .366 Have you thought that a new religion can be created by combining two or more existing religions? 11.6778 10.757 .186 .075 .325 Have you ever wondered, what is the common link between Hitler, Jack the Ripper and Nero? 11.7033 10.976 .167 .067 .338 Have you ever linked your feeling of freshness with the amount of sleep you have had daily? 10.8511 9.315 .201 .064 .311 Have you ever thought why children became more active after eating more sweets or chocolates? 10.8656 10.094 .250 .077 .277
  • 69. 69 SCALE: REPLICATION Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .440 .459 5 Item Statistics Mean Std. Deviation N Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? 2.2844 1.53389 900 Have you seen, purchased owned a replicated art piece? 2.4256 1.36621 900 Have you ever tried replicating your friends' successful study methods and strategies? 2.7222 1.18413 900
  • 70. 70 Have you considered that a replicated version of a hit song can be equally valuable in price and quality? 2.4989 1.60471 900 Have you ever tried replicating a successful activity, project, or business? 2.5667 1.21586 900 Inter-Item Correlation Matrix Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? Have you seen, purchased owned a replicated art piece? Have you ever tried replicating your friends' successful study methods and strategies? Have you considered that a replicated version of a hit song can be equally valuable in price and quality? Have you ever tried replicating a successful activity, project, or business? Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? 1.000 .114 .020 .093 .113 Have you seen, purchased owned a replicated art piece? .114 1.000 .169 .123 .301 Have you ever tried replicating your friends' successful study methods and strategies? .020 .169 1.000 .116 .261 Have you considered that a replicated version of a hit song can be equally valuable in price and quality? .093 .123 .116 1.000 .138 Have you ever tried replicating a successful activity, project, or business? .113 .301 .261 .138 1.000
  • 71. 71 Inter-Item Covariance Matrix Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? Have you seen, purchased owned a replicated art piece? Have you ever tried replicating your friends' successful study methods and strategies? Have you considered that a replicated version of a hit song can be equally valuable in price and quality? Have you ever tried replicating a successful activity, project, or business? Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? 2.353 .239 .037 .229 .210 Have you seen, purchased owned a replicated art piece? .239 1.867 .274 .269 .501 Have you ever tried replicating your friends' successful study methods and strategies? .037 .274 1.402 .221 .376 Have you considered that a replicated version of a hit song can be equally valuable in price and quality? .229 .269 .221 2.575 .270 Have you ever tried replicating a successful activity, project, or business? .210 .501 .376 .270 1.478
  • 72. 72 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.500 2.284 2.722 .438 1.192 .026 5 Item Variances 1.935 1.402 2.575 1.173 1.836 .270 5 Inter-Item Correlations .145 .020 .301 .281 14.859 .006 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you ever wondered whether the performance of the pop group "KARA" can be replicated in your own country? 10.2133 11.142 .140 .025 .457 Have you seen, purchased owned a replicated art piece? 10.0722 10.494 .290 .111 .341 Have you ever tried replicating your friends' successful study methods and strategies? 9.7756 11.709 .224 .083 .391 Have you considered that a replicated version of a hit song can be equally valuable in price and quality? 9.9989 10.373 .191 .037 .421 Have you ever tried replicating a successful activity, project, or business? 9.9311 10.736 .340 .148 .315
  • 73. 73 SCALE: REDEFINITION Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .492 .497 5 Item Statistics Mean Std. Deviation N Have you tried using "H2o" rather than "water" in your daily conversation? 2.3022 1.42978 900 Have you ever tried painting a same picture in water color, charcoal, and oil color? 2.6767 1.22493 900 Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? 2.5156 1.40268 900
  • 74. 74 Have you ever been convinced that a same element can be transformed into water, gas, and ice? 2.7167 1.22939 900 Have you ever tried singing a same song in country, rock, and hip-hop? 2.9478 1.23201 900 Inter-Item Correlation Matrix Have you tried using "H2o" rather than "water" in your daily conversation? Have you ever tried painting a same picture in water color, charcoal, and oil color? Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? Have you ever been convinced that a same element can be transformed into water, gas, and ice? Have you ever tried singing a same song in country, rock, and hip-hop? Have you tried using "H2o" rather than "water" in your daily conversation? 1.000 .087 .156 .145 .080 Have you ever tried painting a same picture in water color, charcoal, and oil color? .087 1.000 .201 .159 .270 Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? .156 .201 1.000 .169 .194 Have you ever been convinced that a same element can be transformed into water, gas, and ice? .145 .159 .169 1.000 .190 Have you ever tried singing a same song in country, rock, and hip- hop? .080 .270 .194 .190 1.000
  • 75. 75 Inter-Item Covariance Matrix Have you tried using "H2o" rather than "water" in your daily conversation? Have you ever tried painting a same picture in water color, charcoal, and oil color? Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? Have you ever been convinced that a same element can be transformed into water, gas, and ice? Have you ever tried singing a same song in country, rock, and hip-hop? Have you tried using "H2o" rather than "water" in your daily conversation? 2.044 .152 .313 .255 .141 Have you ever tried painting a same picture in water color, charcoal, and oil color? .152 1.500 .346 .240 .408 Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? .313 .346 1.967 .291 .335 Have you ever been convinced that a same element can be transformed into water, gas, and ice? .255 .240 .291 1.511 .288 Have you ever tried singing a same song in country, rock, and hip- hop? .141 .408 .335 .288 1.518 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.632 2.302 2.948 .646 1.280 .058 5 Item Variances 1.708 1.500 2.044 .544 1.362 .075 5
  • 76. 76 Inter-Item Correlations .165 .080 .270 .190 3.366 .003 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you tried using "H2o" rather than "water" in your daily conversation? 10.8567 10.312 .188 .041 .493 Have you ever tried painting a same picture in water color, charcoal, and oil color? 10.4822 10.288 .292 .105 .421 Have you ever thought that Michael Jackson's portrait in color is the same when it is in black and white? 10.6433 9.542 .297 .089 .415 Have you ever been convinced that a same element can be transformed into water, gas, and ice? 10.4422 10.423 .270 .074 .434 Have you ever tried singing a same song in country, rock, and hip-hop? 10.2111 10.218 .298 .111 .417
  • 77. 77 SCALE: RECONSTRUCTION Case Processing Summary N % Cases Valid 899 99.9 Excludeda 1 .1 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .346 .392 5 Item Statistics Mean Std. Deviation N Have you ever considered analyzing a problem by viewing it under different scenarios? 3.2970 1.31536 899 Have you tried to remake a broken toy into a different one? 3.0189 1.21364 899 Have you ever tried using bamboo to make arrows, planks for flooring and a spear? 2.3526 1.15657 899
  • 78. 78 Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? 2.8621 2.46871 899 Have you ever thought that wine can be made out of mango rather than grapes? 2.6352 1.70494 899 Inter-Item Correlation Matrix Have you ever considered analyzing a problem by viewing it under different scenarios? Have you tried to remake a broken toy into a different one? Have you ever tried using bamboo to make arrows, planks for flooring and a spear? Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? Have you ever thought that wine can be made out of mango rather than grapes? Have you ever considered analyzing a problem by viewing it under different scenarios? 1.000 .112 .058 .008 .039 Have you tried to remake a broken toy into a different one? .112 1.000 .201 .135 .183 Have you ever tried using bamboo to make arrows, planks for flooring and a spear? .058 .201 1.000 .104 .191 Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? .008 .135 .104 1.000 .112 Have you ever thought that wine can be made out of mango rather than grapes? .039 .183 .191 .112 1.000
  • 79. 79 Inter-Item Covariance Matrix Have you ever considered analyzing a problem by viewing it under different scenarios? Have you tried to remake a broken toy into a different one? Have you ever tried using bamboo to make arrows, planks for flooring and a spear? Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? Have you ever thought that wine can be made out of mango rather than grapes? Have you ever considered analyzing a problem by viewing it under different scenarios? 1.730 .179 .088 .027 .087 Have you tried to remake a broken toy into a different one? .179 1.473 .282 .406 .378 Have you ever tried using bamboo to make arrows, planks for flooring and a spear? .088 .282 1.338 .297 .376 Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? .027 .406 .297 6.095 .472 Have you ever thought that wine can be made out of mango rather than grapes? .087 .378 .376 .472 2.907 Summary Item Statistics Mean MinimumMaximum Range Maximum / Minimum Variance N of Items Item Means 2.833 2.353 3.297 .944 1.401 .130 5 Item Variances 2.708 1.338 6.095 4.757 4.556 3.967 5
  • 80. 80 Inter-Item Correlations .114 .008 .201 .193 24.564 .004 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you ever considered analyzing a problem by viewing it under different scenarios? 10.8687 16.232 .072 .014 .363 Have you tried to remake a broken toy into a different one? 11.1468 14.762 .267 .082 .243 Have you ever tried using bamboo to make arrows, planks for flooring and a spear? 11.8131 15.301 .230 .070 .270 Have you tried taking a short story and rewriting it to have a different conclusion but with the same characters? 11.3037 10.227 .152 .031 .362 Have you ever thought that wine can be made out of mango rather than grapes? 11.5306 13.191 .212 .064 .258
  • 81. 81 SCALE: REINITIATION Case Processing Summary N % Cases Valid 900 100.0 Excludeda 0 .0 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .320 .389 5 Item Statistics Mean Std. Deviation N Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? 2.0811 1.17779 900 Have you considered studying an entirely new course in the event you fail your present course? 2.2556 1.29825 900 Have you considered learning a foreign language for a new vocational move in your life? 3.1400 1.33005 900
  • 82. 82 Have you ever tried changing your hair style to have a new look? 3.1900 2.61137 900 Have you tried travelling on a different route to reach a same destination? 2.9033 1.38102 900 Inter-Item Correlation Matrix Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? Have you considered studying an entirely new course in the event you fail your present course? Have you considered learning a foreign language for a new vocational move in your life? Have you ever tried changing your hair style to have a new look? Have you tried travelling on a different route to reach a same destination? Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? 1.000 .269 .137 .027 .125 Have you considered studying an entirely new course in the event you fail your present course? .269 1.000 .163 .014 .030 Have you considered learning a foreign language for a new vocational move in your life? .137 .163 1.000 .072 .149 Have you ever tried changing your hair style to have a new look? .027 .014 .072 1.000 .144 Have you tried travelling on a different route to reach a same destination? .125 .030 .149 .144 1.000
  • 83. 83 Inter-Item Covariance Matrix Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? Have you considered studying an entirely new course in the event you fail your present course? Have you considered learning a foreign language for a new vocational move in your life? Have you ever tried changing your hair style to have a new look? Have you tried travelling on a different route to reach a same destination? Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? 1.387 .411 .214 .084 .203 Have you considered studying an entirely new course in the event you fail your present course? .411 1.685 .282 .046 .054 Have you considered learning a foreign language for a new vocational move in your life? .214 .282 1.769 .250 .274 Have you ever tried changing your hair style to have a new look? .084 .046 .250 6.819 .519 Have you tried travelling on a different route to reach a same destination? .203 .054 .274 .519 1.907 Summary Item Statistics Mean Minimum Maximum Range Maximum / Minimum Variance N of Items Item Means 2.714 2.081 3.190 1.109 1.533 .264 5
  • 84. 84 Item Variances 2.714 1.387 6.819 5.432 4.916 5.304 5 Inter-Item Correlations .113 .014 .269 .255 19.828 .006 5 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Have you ever considered moving to a different town or city to restart a same business that has failed in the current venue? 11.4889 15.031 .200 .092 .253 Have you considered studying an entirely new course in the event you fail your present course? 11.3144 14.970 .158 .089 .275 Have you considered learning a foreign language for a new vocational move in your life? 10.4300 14.430 .202 .056 .243 Have you ever tried changing your hair style to have a new look? 10.3800 9.624 .111 .023 .398 Have you tried travelling on a different route to reach a same destination? 10.6667 14.236 .201 .051 .241
  • 85. 85 APPENDIX E: RELIABILTY ANALYSIS OF THE EIGHT SCALES OF CSEQ
  • 86. 86 SCALE: RELIABILTY ANALYSIS OF THE EIGHT SCALES OF CSEQ Case Processing Summary N % Cases Valid 899 99.9 Excludeda 1 .1 Total 900 100.0 a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .840 .842 8 Inter-Item Correlation Matrix Originalit y Ingenuit y Resolutio n Synthes is Replicati on Redefiniti on Reconstructi on Reinitiati on Originality 1.000 .452 .410 .431 .439 .470 .450 .429 Ingenuity .452 1.000 .378 .437 .440 .500 .440 .308 Resolution .410 .378 1.000 .436 .250 .355 .407 .292 Synthesis .431 .437 .436 1.000 .391 .425 .432 .321 Replication .439 .440 .250 .391 1.000 .462 .381 .299 Redefinition .470 .500 .355 .425 .462 1.000 .466 .369
  • 87. 87 Reconstructi on .450 .440 .407 .432 .381 .466 1.000 .349 Reinitiation .429 .308 .292 .321 .299 .369 .349 1.000 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Originality 95.4386 367.017 .639 .412 .814 Ingenuity 96.3463 350.070 .607 .386 .816 Resolution 93.4449 373.145 .511 .297 .828 Synthesis 94.9670 364.517 .589 .357 .819 Replication 96.4397 366.340 .541 .329 .825 Redefinition 95.7723 357.622 .631 .410 .813 Reconstruction 94.7690 345.831 .601 .366 .817 Reinitiation 95.3652 365.711 .473 .244 .835 Scale Statistics Mean Variance Std. Deviation N of Items 108.9347 461.316 21.47828 8 Inter-Item Correlation Matrix
  • 88. 88 Originalit y Ingenuit y Resolutio n Synthes is Replicati on Redefiniti on Reconstructi on Reinitiati on Originality 1.000 .452 .410 .431 .439 .470 .450 .429 Ingenuity .452 1.000 .378 .437 .440 .500 .440 .308 Resolution .410 .378 1.000 .436 .250 .355 .407 .292 Synthesis .431 .437 .436 1.000 .391 .425 .432 .321 Replication .439 .440 .250 .391 1.000 .462 .381 .299 Redefinition .470 .500 .355 .425 .462 1.000 .466 .369 Reconstructi on .450 .440 .407 .432 .381 .466 1.000 .349 Reinitiation .429 .308 .292 .321 .299 .369 .349 1.000 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item- Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Originality 95.4386 367.017 .639 .412 .814 Ingenuity 96.3463 350.070 .607 .386 .816 Resolution 93.4449 373.145 .511 .297 .828 Synthesis 94.9670 364.517 .589 .357 .819 Replication 96.4397 366.340 .541 .329 .825 Redefinition 95.7723 357.622 .631 .410 .813 Reconstruction 94.7690 345.831 .601 .366 .817 Reinitiation 95.3652 365.711 .473 .244 .835 Scale Statistics Mean Variance Std. Deviation N of Items
  • 89. 89 108.9347 461.316 21.47828 8 APPENDIX F: CORRELATIONAL ANALYSES
  • 90. 90 CORRELATION BETWEEN AGE AND EIGHT CREATIVITY ELEMENTS Age Ori gin alit y Ingenu ity Resolut ion Synthe sis Replicat ion Redefinit ion Reconstruc tion Reinitiat ion Age Pearson Correlat ion 1 .05 3 .031 .003 -.018 .088** .005 .045 .033 Sig. (1- tailed) .05 6 .177 .465 .296 .004 .440 .089 .160 N 900 900 900 900 900 900 900 899 900 Originality Pearson Correlat ion .053 1 .452** .411** .431** .439** .470** .450** .428** Sig. (1- tailed) .056 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion .031 .45 2** 1 .378** .437** .440** .500** .440** .307** Sig. (1- tailed) .177 .00 0 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion .003 .41 1** .378** 1 .436** .249** .356** .407** .291** Sig. (1- tailed) .465 .00 0 .000 .000 .000 .000 .000 .000
  • 91. 91 N 900 900 900 900 900 900 900 899 900 Synthesis Pearson Correlat ion -.018 .43 1** .437** .436** 1 .390** .425** .432** .320** Sig. (1- tailed) .296 .00 0 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Replication Pearson Correlat ion .088** .43 9** .440** .249** .390** 1 .462** .381** .299** Sig. (1- tailed) .004 .00 0 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefinitio n Pearson Correlat ion .005 .47 0** .500** .356** .425** .462** 1 .466** .368** Sig. (1- tailed) .440 .00 0 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstruc tion Pearson Correlat ion .045 .45 0** .440** .407** .432** .381** .466** 1 .349** Sig. (1- tailed) .089 .00 0 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion .033 .42 8** .307** .291** .320** .299** .368** .349** 1 Sig. (1- tailed) .160 .00 0 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 **. Correlation is significant at the 0.01 level (1-tailed).
  • 92. 92 CORRELATIONS BETWEEN YEAR OF STUDY AND EIGHT CREATIVITY ELEMENTS Year of Study in Colle ge Origina lity Resolut ion Synthe sis Replicat ion Ingenu ity Redefinit ion Reconstruc tion Reinitiat ion Year of Study in College Pearson Correlat ion 1 -.077* .000 -.049 -.017 -.038 -.076* .032 -.055 Sig. (2- tailed) .021 .998 .141 .606 .254 .022 .331 .100 N 900 900 900 900 900 900 900 899 900 Originality Pearson Correlat ion - .077* 1 .411** .431** .439** .452** .470** .450** .428** Sig. (2- tailed) .021 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion .000 .411** 1 .436** .249** .378** .356** .407** .291** Sig. (2- tailed) .998 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Synthesis Pearson Correlat ion -.049 .431** .436** 1 .390** .437** .425** .432** .320** Sig. (2- tailed) .141 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900
  • 93. 93 Replicatio n Pearson Correlat ion -.017 .439** .249** .390** 1 .440** .462** .381** .299** Sig. (2- tailed) .606 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion -.038 .452** .378** .437** .440** 1 .500** .440** .307** Sig. (2- tailed) .254 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefinitio n Pearson Correlat ion - .076* .470** .356** .425** .462** .500** 1 .466** .368** Sig. (2- tailed) .022 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstruc tion Pearson Correlat ion .032 .450** .407** .432** .381** .440** .466** 1 .349** Sig. (2- tailed) .331 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion -.055 .428** .291** .320** .299** .307** .368** .349** 1 Sig. (2- tailed) .100 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
  • 94. 94 CORRELATIONS BETWEEN STUDENT REASONS FOR STUDYING THEIR PROGRAMS AND THE EIGHT CREATIVITY ELEMENTS Reaso ns for Choosi ng Progra m Origina lity Resolut ion Synthe sis Replicat ion Ingenu ity Redefini tion Reconstru ction Reinitiat ion Reasons for Choosing Program Pearson Correlat ion 1 .000 -.036 .067* .050 .039 .030 .015 .007 Sig. (2- tailed) .988 .274 .044 .134 .238 .373 .661 .829 N 900 900 900 900 900 900 900 899 900 Originality Pearson Correlat ion .000 1 .411** .431** .439** .452** .470** .450** .428** Sig. (2- tailed) .988 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion -.036 .411** 1 .436** .249** .378** .356** .407** .291** Sig. (2- tailed) .274 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Synthesis Pearson Correlat ion .067* .431** .436** 1 .390** .437** .425** .432** .320** Sig. (2- tailed) .044 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900
  • 95. 95 Replicatio n Pearson Correlat ion .050 .439** .249** .390** 1 .440** .462** .381** .299** Sig. (2- tailed) .134 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion .039 .452** .378** .437** .440** 1 .500** .440** .307** Sig. (2- tailed) .238 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefinitio n Pearson Correlat ion .030 .470** .356** .425** .462** .500** 1 .466** .368** Sig. (2- tailed) .373 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstruc tion Pearson Correlat ion .015 .450** .407** .432** .381** .440** .466** 1 .349** Sig. (2- tailed) .661 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion .007 .428** .291** .320** .299** .307** .368** .349** 1 Sig. (2- tailed) .829 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
  • 96. 96 CORRELATIONS BETWEEN STUDENTS LINGUISTIC ABILITY (SPOKEN / WRITTEN AND THE EIGHT CREATIVITY ELEMENTS Numb er of Spoke n Langu ages Numb er of Writte n Langu ages Origin ality Resolu tion Synth esis Replica tion Ingen uity Redefin ition Reconstru ction Reinitia tion Number of Spoken Language s Pearso n Correla tion 1 .655** .064 .041 .067* .018 .017 .055 .034 .087** Sig. (2- tailed) .000 .054 .223 .046 .591 .618 .100 .309 .009 N 900 900 900 900 900 900 900 900 899 900 Number of Written Language s Pearso n Correla tion .655** 1 .027 .001 .075* .024 .008 .047 .045 .048 Sig. (2- tailed) .000 .420 .967 .024 .472 .817 .155 .180 .150 N 900 900 900 900 900 900 900 900 899 900 Originalit y Pearso n Correla tion .064 .027 1 .411** .431** .439** .452** .470** .450** .428** Sig. (2- tailed) .054 .420 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Resolutio n Pearso n Correla tion .041 .001 .411** 1 .436** .249** .378** .356** .407** .291**
  • 97. 97 Sig. (2- tailed) .223 .967 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Synthesis Pearso n Correla tion .067* .075* .431** .436** 1 .390** .437** .425** .432** .320** Sig. (2- tailed) .046 .024 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Replicatio n Pearso n Correla tion .018 .024 .439** .249** .390** 1 .440** .462** .381** .299** Sig. (2- tailed) .591 .472 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Ingenuity Pearso n Correla tion .017 .008 .452** .378** .437** .440** 1 .500** .440** .307** Sig. (2- tailed) .618 .817 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Redefiniti on Pearso n Correla tion .055 .047 .470** .356** .425** .462** .500** 1 .466** .368** Sig. (2- tailed) .100 .155 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 Reconstru ction Pearso n Correla tion .034 .045 .450** .407** .432** .381** .440** .466** 1 .349**
  • 98. 98 Sig. (2- tailed) .309 .180 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 899 Reinitiati on Pearso n Correla tion .087** .048 .428** .291** .320** .299** .307** .368** .349** 1 Sig. (2- tailed) .009 .150 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 900 899 900 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
  • 99. 99 GENERAL LINEAR MODEL (MANOVA) GENDER DIFFERENCE BETWEEN THE EIGHT CREATIVITY ELEMENTS Between-Subjects Factors Value Label N Gender 1.00 Male 587 2.00 Female 312 Box's Test of Equality of Covariance Matricesa Box's M 114.463 F 3.146 df1 36 df2 1419800.525 Sig. .000
  • 100. 100 Multivariate Testsa Effect Value F Hypothesis df Error df Sig. Intercept Pillai's Trace .962 2833.707b 8.000 890.000 .000 Wilks' Lambda .038 2833.707b 8.000 890.000 .000 Hotelling's Trace 25.472 2833.707b 8.000 890.000 .000 Roy's Largest Root 25.472 2833.707b 8.000 890.000 .000 Gender Pillai's Trace .024 2.710b 8.000 890.000 .006 Wilks' Lambda .976 2.710b 8.000 890.000 .006 Hotelling's Trace .024 2.710b 8.000 890.000 .006 Roy's Largest Root .024 2.710b 8.000 890.000 .006 a. Design: Intercept + Gender b. Exact statistic Levene's Test of Equality of Error Variancesa F df1 df2 Sig. Originality .333 1 897 .564 Ingenuity 1.716 1 897 .190 Resolution 1.112 1 897 .292 Synthesis 1.251 1 897 .264 Replication 3.244 1 897 .072 Redefinition .463 1 897 .496 Reconstruction 1.863 1 897 .173 Reinitiation .060 1 897 .806 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + Gender
  • 101. 101 Tests of Between-Subjects Effects Source Dependent Variable Type III Sum of Squares df Mean Square F Sig. Corrected Model Originality 55.974a 1 55.974 4.912 .027 Ingenuity 79.911b 1 79.911 4.675 .031 Resolution 1.387c 1 1.387 .098 .754 Synthesis .081d 1 .081 .006 .939 Replication 111.092e 1 111.092 7.492 .006 Redefinition 25.922f 1 25.922 1.842 .175 Reconstruction 205.707g 1 205.707 11.110 .001 Reinitiation 5.907h 1 5.907 .323 .570 Intercept Originality 146667.837 1 146667.837 12871.942 .000 Ingenuity 127174.905 1 127174.905 7440.472 .000 Resolution 195197.777 1 195197.777 13854.375 .000 Synthesis 159050.537 1 159050.537 11625.532 .000 Replication 124933.250 1 124933.250 8424.913 .000 Redefinition 140008.863 1 140008.863 9949.636 .000 Reconstruction 159991.246 1 159991.246 8640.835 .000 Reinitiation 149469.756 1 149469.756 8179.008 .000 Gender Originality 55.974 1 55.974 4.912 .027 Ingenuity 79.911 1 79.911 4.675 .031 Resolution 1.387 1 1.387 .098 .754 Synthesis .081 1 .081 .006 .939 Replication 111.092 1 111.092 7.492 .006 Redefinition 25.922 1 25.922 1.842 .175 Reconstruction 205.707 1 205.707 11.110 .001 Reinitiation 5.907 1 5.907 .323 .570
  • 102. 102 Error Originality 10220.762 897 11.394 Ingenuity 15331.809 897 17.092 Resolution 12638.059 897 14.089 Synthesis 12271.983 897 13.681 Replication 13301.635 897 14.829 Redefinition 12622.367 897 14.072 Reconstruction 16608.598 897 18.516 Reinitiation 16392.498 897 18.275 Total Originality 174025.000 899 Ingenuity 157875.000 899 Resolution 228339.090 899 Synthesis 187665.000 899 Replication 153769.000 899 Redefinition 168399.000 899 Reconstruction 197215.000 899 Reinitiation 181933.000 899 Corrected Total Originality 10276.736 898 Ingenuity 15411.720 898 Resolution 12639.446 898 Synthesis 12272.065 898 Replication 13412.727 898 Redefinition 12648.289 898 Reconstruction 16814.305 898 Reinitiation 16398.405 898 a. R Squared = .005 (Adjusted R Squared = .004) b. R Squared = .005 (Adjusted R Squared = .004) c. R Squared = .000 (Adjusted R Squared = -.001)
  • 103. 103 d. R Squared = .000 (Adjusted R Squared = -.001) e. R Squared = .008 (Adjusted R Squared = .007) f. R Squared = .002 (Adjusted R Squared = .001) g. R Squared = .012 (Adjusted R Squared = .011) h. R Squared = .000 (Adjusted R Squared = -.001) Estimated Marginal Means Gender Dependent Variable Gender Mean Std. Error 95% Confidence Interval Lower Bound Upper Bound Originality Male 13.678 .139 13.405 13.951 Female 13.154 .191 12.779 13.529 Ingenuity Male 12.806 .171 12.471 13.141 Female 12.179 .234 11.720 12.639 Resolution Male 15.518 .155 15.214 15.822 Female 15.436 .213 15.019 15.853 Synthesis Male 13.961 .153 13.661 14.260 Female 13.981 .209 13.570 14.392 Replication Male 12.751 .159 12.439 13.063 Female 12.013 .218 11.585 12.441 Redefinition Male 13.286 .155 12.982 13.590 Female 12.929 .212 12.513 13.346 Reconstruction Male 14.514 .178 14.166 14.863 Female 13.510 .244 13.032 13.988 Reinitiation Male 13.629 .176 13.282 13.975 Female 13.458 .242 12.983 13.933
  • 104. 104 CORRELATIONS BETWEEN FAMILY EDUCATIONAL BACKGROUND: FATHER AND THE EIGHT CREATIVITY ELEMENTS Father Family Educati onal Backgro und Origina lity Ingenu ity Resolut ion Synthe sis Replicat ion Redefini tion Reconstru ction Reinitia tion Father Famil Education al Backgroun d Pearson Correlat ion 1 -.019 .037 .050 .032 -.026 .025 .000 -.033 Sig. (2- tailed) .559 .269 .133 .342 .444 .446 .994 .326 N 900 900 900 900 900 900 900 899 900 Originality Pearson Correlat ion -.019 1 .452** .411** .431** .439** .470** .450** .428** Sig. (2- tailed) .559 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion .037 .452** 1 .378** .437** .440** .500** .440** .307** Sig. (2- tailed) .269 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion .050 .411** .378** 1 .436** .249** .356** .407** .291** Sig. (2- tailed) .133 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900
  • 105. 105 Synthesis Pearson Correlat ion .032 .431** .437** .436** 1 .390** .425** .432** .320** Sig. (2- tailed) .342 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Replicatio n Pearson Correlat ion -.026 .439** .440** .249** .390** 1 .462** .381** .299** Sig. (2- tailed) .444 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefiniti on Pearson Correlat ion .025 .470** .500** .356** .425** .462** 1 .466** .368** Sig. (2- tailed) .446 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstru ction Pearson Correlat ion .000 .450** .440** .407** .432** .381** .466** 1 .349** Sig. (2- tailed) .994 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion -.033 .428** .307** .291** .320** .299** .368** .349** 1 Sig. (2- tailed) .326 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 **. Correlation is significant at the 0.01 level (2-tailed).
  • 106. 106 CORRELATIONS BETWEEN FAMILY EDUCATIONAL BACKGROUND: MOTHER AND THE EIGHT CREATIVITY ELEMENTS Mother Family Educati onal Backgro und Origina lity Ingenu ity Resolut ion Synthe sis Replicat ion Redefini tion Reconstru ction Reinitia tion Mother Family Education al Backgroun d Pearson Correlat ion 1 -.030 .036 .084* .058 .008 .074* .034 .038 Sig. (2- tailed) .365 .287 .011 .082 .812 .026 .304 .260 N 900 900 900 900 900 900 900 899 900 Originality Pearson Correlat ion -.030 1 .452** .411** .431** .439** .470** .450** .428** Sig. (2- tailed) .365 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion .036 .452** 1 .378** .437** .440** .500** .440** .307** Sig. (2- tailed) .287 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion .084* .411** .378** 1 .436** .249** .356** .407** .291** Sig. (2- tailed) .011 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900