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

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Creativity Selected Elements Questionnaire herewith shall be called (CSEQ) as a creative psychological assessment instrument was developed on the theoretical foundations of “Creative Product ...

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: H1) 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; H2) 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.

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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 Document Transcript

  • 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 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 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
  • 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 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 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 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.
  • 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
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  • 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
  • 107 Synthesis Pearson Correlat ion .058 .431** .437** .436** 1 .390** .425** .432** .320** Sig. (2- tailed) .082 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Replicatio n Pearson Correlat ion .008 .439** .440** .249** .390** 1 .462** .381** .299** Sig. (2- tailed) .812 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefiniti on Pearson Correlat ion .074* .470** .500** .356** .425** .462** 1 .466** .368** Sig. (2- tailed) .026 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstru ction Pearson Correlat ion .034 .450** .440** .407** .432** .381** .466** 1 .349** Sig. (2- tailed) .304 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion .038 .428** .307** .291** .320** .299** .368** .349** 1 Sig. (2- tailed) .260 .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).
  • 108 CORRELATIONS BETWEEN FAMILY INCOME AND THE EIGHT CREATIVITY ELEMENTS Fami ly Inco me Origina lity Ingenu ity Resolut ion Synthe sis Replicat ion Redefinit ion Reconstruc tion Reinitiat ion Family Income Pearson Correlat ion 1 -.019 -.071* -.077* -.014 -.019 -.073* -.010 .001 Sig. (2- tailed) .575 .034 .020 .676 .567 .028 .774 .978 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) .575 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Ingenuity Pearson Correlat ion - .071* .452** 1 .378** .437** .440** .500** .440** .307** Sig. (2- tailed) .034 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Resolution Pearson Correlat ion - .077* .411** .378** 1 .436** .249** .356** .407** .291** Sig. (2- tailed) .020 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Synthesis Pearson Correlat ion -.014 .431** .437** .436** 1 .390** .425** .432** .320**
  • 109 Sig. (2- tailed) .676 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Replicatio n Pearson Correlat ion -.019 .439** .440** .249** .390** 1 .462** .381** .299** Sig. (2- tailed) .567 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Redefinitio n Pearson Correlat ion - .073* .470** .500** .356** .425** .462** 1 .466** .368** Sig. (2- tailed) .028 .000 .000 .000 .000 .000 .000 .000 N 900 900 900 900 900 900 900 899 900 Reconstruc tion Pearson Correlat ion -.010 .450** .440** .407** .432** .381** .466** 1 .349** Sig. (2- tailed) .774 .000 .000 .000 .000 .000 .000 .000 N 899 899 899 899 899 899 899 899 899 Reinitiatio n Pearson Correlat ion .001 .428** .307** .291** .320** .299** .368** .349** 1 Sig. (2- tailed) .978 .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).
  • 110 APPENDIX G: CONCEPTUAL FRAMEWORK OF THE STUDY
  • 111 Conceptual Framework of the Study Figure 1. Conceptual framework of the study. Student Demographics Age, Gender, Study Preference, Year of Study in College, GPA, Reasons for Choosing the Program and Student’s Linguistic Ability Eight Creativity Elements Originality, Ingenuity, Resolution, Synthesis, Replication, Redefinition, Reconstruction, and Reinitiation Family Demographic Parental Family Status, Family Income, and Family Educational Background H1o H2o