【附錄 14】
Empirical Study between Students’ Career Belief and Creative Thinking
Instruction of Career Planning in Technological and Professional College
*Chin-Mou Cheng
*Fooyin University, Kaohsiung, Taiwan
ABSTRACT: The main purpose of this study was to compile a Questionnaire of Career Planning and Satisfaction (QCPS), to survey the differences in diverse programs, gender, and departments of technological and professional college students concerning the career belief, planning capacity and career satisfaction. Moreover, we compile the Self Creative Thinking Scale (SCTS), Creative Thinking Test (CTT) to evaluate the differences between creative thinking instruction and traditional instruction existing among career belief, planning capacity and career satisfaction; and among fluency, openness, flexibility, originality, elaboration, heading and total creative scores. In order to achieve the goals, we adopted two methods: surveying the 2068 subjects and then planning a quasi-experiment design of the control section with unequal prior and post test (experimental group, 50 subjects; control group 52 subjects). According to Pearson correlation, ANOVA, etc., we discovered that the programs, gender and departments were significant differences in the career belief, planning capacity and career satisfaction. The experimental group students who received creative thinking instruction of career planning course obtained more significant gains in fluency, openness, flexibility, originality, elaboration, heading and total creative scores than the control group students who received traditional instruction. There were some significant correlations between SCTS and CTT in some items mentioned above. Finally, suggestions were proposed for educational administration and liberal teaching and career counseling agencies, technological and professional college teachers and future researchers.
I NTRODUCTION
Higher technological and professional education in Taiwan has over expanded, and as a result students face competition in job searches. The graduates of technological colleges supply outstrips demand. The effects of economic recession has also lead to unemployment rate escalating above 5% in 2004. Therefore, the students of technological colleges worry that their graduation is considered as the start of unemployment, making career planning difficult. In other words, the individual career belief system faces to future that is bleak. Career is the interwoven process of one’s whole life among occupation, work and livelihood [16], including the gender difference occupation choice and satisfaction of future career planning [4]. The shift of college students’ career beliefs regarding career as occupation, no occupation as no career. In fact, Super [18] modified career developmental tasks through the life span, from growth to decline of life stage, including playing roles in works and livelihood. It is a broad definition that career comprises the occupation / work and non-occupational activities, such as healthy, marriage, interpersonal relationship, managing finances, and leisure journey, etc. [2]. According to the serial reports of career guidance, college students demand urgently the precise career belief and career planning skills [9, 14, 17,20]. Moreover, the career planning course is respected recently in universities, if the students have the precise career belief, or take an elective career planning course through instruction ahead of graduation, they can comprehend the real meaning of career, possess the career planning capacity, and result in career satisfaction. This shows that the career belief, planning capacity, and career satisfaction are connected with one another.
This paper is based on the experiences of career planning teaching and research, and is reinforced with creative education which the Ministry of Education advocated and regarded as a focus of educational reform in 2002 and planed a cultivating creative manpower schedule of college students in 2004. We strengthened the creative thinking ability of students through a creative instruction to prepare them for their occupation, and to
promote their career ability and satisfaction. There are few survey and experiment mixed studies concerning the creative career of college students. Therefore, we are very concerned about creative instruction. If we adopt creative thinking instruction which differs with traditional instruction and helps students to develop their critical thinking and problem-solving ability [12], the students can enhance their career planning competence, such as decision-making skills, maintaining a positive self concept, etc. [21]. A new trial was conducted to compare the differences between the creative and traditional instruction with cognitive and affective factors in the career belief, planning capacity and career satisfaction.
RESEARCH PURPOSES
One purpose of this study was to compile a Questionnaire of Career Planning and Satisfaction (QCPS), and we used QCPS to survey the differences in manifold programs, gender, and departments of technological and professional college students concerning the ideas of career and career planning capacity and career satisfaction. A second purpose was to project a serial of Creative Thinking Teaching Material and Self Creative Thinking Scale (SCTS), and we applied the SCTS and Creative Thinking Test (CTT) to evaluate the differences of students performance between creative thinking instruction and traditional instruction among career belief, planning capacity and career satisfaction. For achieving these purposes, two methods were adopted: survey and quasi-experiment.
SURVEY METHOD
Subjects
In this survey questionnaire method, a stratified random and cluster sampling method were adopted with 2068 students from 4 technological universities, 13 technological institutes and 4 junior colleges (sampled from the 13 technological universities,
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54 technological institutes, and 18 junior colleges ) in Taiwan participated as subjects and finished by April 2002. Four subregions of schools in Taiwan were distinguished, and the cluster samples were from one technological university and three technological institutes and one junior colleges of the northern district and middle district, too, two technological universities and four technological institutes and one junior colleges of the southern district, and three technological institutes and one junior colleges of the eastern district according to proportion of schools. Simultaneously, the random stratified samples were from different departments of natural science, engineering and technology, medicine and nursing, language, management, art, agriculture, etc., and from different grades (1-5). Moreover, it took into account that the equilibratory distribution of schools was from urban or rural district. These samples included 598 four-year collegiate program students (28.92%), 459 two-year collegiate program students (22.19%), 516 five-year associate degree program students (24.95%), and 495 two-year associate degree program students (23.94%), comprised 735 male (35.54%) and 1333 female (64.46%).Instruments / Materials
A Questionnaire of Career Planning and Satisfaction (QCPS) was compiled, and draft plan was amended three times from Nov 2001 to Mar 2002 through prior test, items analysis, reliability and validity analysis. A correlation coefficient was used to assure the reliability of this instrument. The results of correlation coefficient, after deducting 13 low correlation items, obtained a Cronbach’s α of .727. A factor analysis was applied to determine how many factors were involved in students’ responses on the questionnaire. There were 60 items in this finished questionnaire, including 36 items with a positive valence, and 24 items with a negative valence. Students were asked to rate their degree of agreement for each item on QCPS with career belief items 1-39, planning capacity items 40-50, and career satisfaction items 51-60, ranging from strongly disagree (1) to strongly agree (5). Concerning reliability analysis, the results indicated that the internal correlation of questionnaire was very consistent through two tests, and correlation coefficient was very significant (p＜.01) by Pearson correlation. In accordance with Career Beliefs Inventory [10], and the Career Belief Check List [8] was adopted to analyse the validity, and found the significant positive and negative correlations between two career scales, and the correlation coefficient was significant (p＜.05) by Pearson correlation in criterion content validity.
Results and Discussion
Concerning data processing, the survey data were handled by SPSS10.0 for Window. Using one-way ANOVA, multiple-way ANOVA, and a posteriori comparison, we tested the differences in manifold programs, gender, and departments of technological and professional college students among career belief, planning capacity and career satisfaction.
Three one-way ANOVAs were conducted to verify if there were any main effects between programs, gender, or departments (independent variables) and career belief, planning capacity, career satisfaction (dependent variables). The results indicated that there were two main effects (see Table 1).
Table 1 One-way ANOVA of program on career items
Source SS df MS F Sig. Career SSb belief SSw SSt 1619.008 355150.325 356769.333 3 2064 2067 539.669 172.609 3.316 .025* Planning SSb Capacity SSw SSt 155.804 39673.014 39828.818 3 2064 2067 51.935 19.221 2.702 .044* Career SSb satisfaction SSw SSt 222.235 69130.838 69353.073 3 2064 2067 74.078 33.494 2.212 .085 Total SSb score SSw SSt 1332.561 674386.240 675718.801 3 2064 2067 444.187 326.738 1.359 253 *p<.05
In Table 1, two main effects or significant differences were found between the program and career belief, planning capacity, and then found four-year collegiate and two-year collegiate program students all above two-year associate degree program students in career belief when using Scheffe and LSD posteriori comparison; four-year collegiate program and five-year associate degree program students all above two-year collegiate program students. We inferred the reason that the programs of colleges should adapt to competition of occupational career. Another two main effects or significant differences were found between the gender and career belief, total scores (see Table 2 ), and female exceeded male in two main effects. We inferred the cause that the career beliefs of female were more positive and deliberate than male.
Table 2 One-way ANOVA of sex on career items
Source SS Df MS F Sig. Career SSb belief SSw SSt 3652.567 353116.766 356768.333 1 2066 2067 3652.57 170.918 21.37 .000** Planning SSb Capacity SSw SSt 13.358 39815.459 39828.817 1 2066 2067 13.358 19.272 .693 .405 Career SSb satisfaction SSw SSt 15.623 69337.450 69353.073 1 2066 2067 15.623 33.561 465 .495 Total SSb score SSw SSt 3616.677 672102.123 675718.800 1 2066 2067 3616.68 325.316 11.12 001** **p<.01
And three main effects or significant differences were found between the department and career belief, satisfaction, and total scores (see Table 3), and then found that the departments of medicine, nursing, and language were more excellent than departments of machine, engineering, etc., when used the posteriori comparison. We inferred the cause that the graduate of departments about medicine, nursing, and language had more healthy career belief and occupational vision than other departments.
Table 3 One-way ANOVA of department on career items
Career SSb belief SSw SSt 8280.903 348488.430 356769.333 6 2061 2067 1380.15 169.087 8.162 000** Planning SSb Capacity SSw SSt 224.160 39604.658 39828.818 6 2061 2067 37.36 19.216 1.944 .070 Career SSb satisfaction SSw SSt 555.684 68797.390 69353.073 6 2061 2067 92.614 33.381 2.774 .011* Total SSb score SSw SSt 9038.788 666680.013 675718.801 6 2061 2067 1506.46 323.474 4.657 .000** *p<.05 **p<.01
Moreover, three two-way ANOVAs were conducted to verify if there were any interactive effects between two independent variables and 4 dependent variables. The results indicated that there were two interactive effects between program, gender and career belief (.050*); program, gender and career satisfaction (.043*) (see Table 4). However, results indicated that no significant interactive effect between gender, department and career belief, etc.
Table 4 Two-way ANOVA of program, gender on career items
Items III SS Df MS F Sig.
Belief 1328.179 3 442.726 2.610 .050* Capacity 54.422 3 18.141 .943 .419 Satisfaction 272.727 3 90.909 2.720 .043* Total 825.262 3 275.087 .847 .468 *p ＜.05
There were three interactive effects between department, program and career belief (.000**), planning capacity (.001**), and total scores (.001**) (see Table 5).
Table 5 Two-way ANOVA of department, program on career items
Items III SS df MS F Sig.
Belief 5895.259 12 491.272 2.947 .000** Capacity 616.389 12 51.366 2.703 .001** Satisfaction 518.772 12 43.231 1.298 .213 Total 10666.876 12 888.906 2.777 .001** **p＜.01
As for three-way ANOVA, result indicated that there was no significant interactive effect between program, gender, department and career belief, etc.
Meanwhile, this study was found that 557 students who learned career planning course gained more scores than 1511 students who learned not career planning course in career belief (.014*), planning capacity (.040*), career satisfaction (.045*), and total scores (.003**) (see Table 6). As the branch cannot bear fruit of itself unless it abides in the vine, so neither can student learn unless they receive career planning course.
Table 6 One-way ANOVA of learning and non-learning career planning course
Source SS df MS F Sig. Career SSb 1047.808 1 1047.81 6.086 .014* belief SSw SSt 355721.525 356769.333 2066 2067 172.179 Planning SSb Capacity SSw SSt 80.900 39747.917 39828.818 1 2066 2067 80.90 19.239 4.205 .040* Career SSb satisfaction SSw SSt 135.335 69217.738 69353.073 1 2066 2067 135.335 33.503 4.039 .045* Total SSb score SSw SSt 2808.753 672901.048 675718.801 1 2066 2067 2808.75 325.707 8.624 .003** *p<.05 **p<.01
For understanding the correlations among career belief, planning capacity, career satisfaction, and total career scores, it found that they were very significant relationship by Pearson correlation (see Table 7 ).
Table 7 Correlation among career items
Pearson correlation belief capacity satisfaction total
career belief .352** .300** .908**
planning capacity .352** .299** .595** career satisfaction .300** .299** .611** total career scores .908** .595** .611**
N＝2068 **p＜.001
QUASI-EXPERIMENT METHOD
Subjects
The subjects consisted of 102 students who took an elective career planning course during 2001-2002. They were randomly assigned to one of the two condition groups, one was experimental group (with 50 subjects) who received creative instruction, while another was control group (with 52 subjects) who received traditional instruction. The design of nonequivalent pretest-posttest control group (see Figure 1) was adopted in this study. The experiment group and control group all received pretest (E1, C1), after experimental treatment two months, this two groups all received posttest (E2, C2), then compared the differences for testing the effect of creative instruction.
group pretest experimental treatment posttest experiment group E1 creative instruction E2
control group C1 tradition instruction C2
Figure 1 Nonequivalent pretest-posttest control group design
Instruments / Materials
For the second purpose of this study, the Self Creative Thinking Scale (SCTS) and Creative Thinking Teaching Material were compiled. And adopted the Creative Thinking Test (CTT)[13] and SCTS to evaluate the differences among fluency, openness, flexibility, originality, elaboration, heading and the total scores. CTT was revised from Williams Creative Test in 1994, and consisted of 10 uncompleted figures to test
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the creative differences of students among fluency, openness, flexibility, originality, elaboration, heading and total creative scores. Concerning reliability analysis, the results indicated that the internal correlation of test items were consistent, and correlation coefficient was significant by Pearson correlation. And the validity was found the significant correlations by Pearson correlation in validity between experts each other. The differences of students performance between creative thinking instruction and traditional instruction among career belief, planning capacity, career satisfaction, and total scores would also be evaluated by CTT and SCTS. The author complied the SCTS according to Hong’s Creative Work Value Scale (2000) [7], and the reliability and validity were in line with standardized process. SCTS is composed of two domains: cognition and affection; the cognitive domain consisted of fluency, flexibility, originality, and elaboration; the affective domain consisted of curiosity, adventure, openness, and challenge.The Creative Thinking Teaching Material was composed of eight creative strategies: warm-up encouragement, giving a boost to the intelligence of the troops, discussion, boundless diffusion, classification, analogy and organization, inquisition and hearing about, acting and coming true. These strategies were consistent correlation and effective, and could apply to test the differences of students performance between creative thinking instruction and traditional instruction among career belief, planning capacity, career satisfaction, and total scores.
Results
We used a one-way ANOVA and multiple-way ANOVA to compare the differences in fluency, openness, flexibility, originality, elaboration, heading and total scores between experimental group students who received creative thinking instruction of career planning course and control group students who received traditional instruction.
Pretest results indicated that the experimental group and control group were not significant differences on the Creative Thinking Test in the creative items through one-way ANOVA. It showed that the experimental group equalled approximately the control group in every condition, and then the experimental instruction with creative and traditional forms accorded with the experimental basic spirit.
Posttest results indicated that the experimental group with creative instruction gained more effective performance than the control group with traditional instruction after two months. Two groups reached all significant differences through one-way ANOVA in fluency, openness, flexibility, originality, elaboration, heading, and total creative scores (see Table 8). This showed that various instructional methods were significant differences, nevertheless, the results indicated that the career items reached not all significant differences between two groups, and needed to further research the effectiveness of materials.
Table 8 One-way ANOVA of two groups on the posttest
Source SS df MS F Sig. fluency SSb SSw SSt 2.699 23.978 26.676 1 100 101 2.699 .240 11.255 .001** Openness SSb SSw SSt 69.591 1130.497 1200.088 1 100 101 69.591 11.305 6.156 .015* flexibility SSb SSw SSt 40.025 91.122 131.147 1 100 101 40.025 .911 43.924 .000** Originality SSb SSw SSt 104.724 1097.942 1202.666 1 100 101 104.724 10.936 9.538 .003** elaboration SSb SSw SStl 147.672 1193.622 1341.294 1 100 101 147.672 11.936 12.372 .001** heading SSb SSw SSt 89.504 564.349 653.853 1 100 101 89.504 5.643 15.860 .000** total scores SSb. SSw SSt 2319.155 14164.92 16484.08 1 100 101 2319.15 141.649 16.373 .000** **p <.01 *p<.05 IMPLICATION
This paper provides survey questionnaire and experimental data for career belief and creative instruction of career planning. The results also provide career planning course designers or counselor with reference information for college students who face the challenge of a future career. Although there was no significant correlation between creative instruction and career belief, planning capacity, and career satisfaction, then creative instruction of career planning was found to have significant effect on learning career course which students enhanced their creativity. There were resources available to assist college students in learning how to do creative career planning and make career decision for their life. Attention to career belief, planning skill, and career satisfaction can be effective to improve career teaching, so that college students can become foresighted, skillful, prearranged, independent learners for future career development.
CONCLUSION AND SUGGESTIONS
This study successfully compiled a Questionnaire of Career Planning and Satisfaction (QCPS) which could survey the differences in manifold programs, gender, and departments of college students concerning the career belief, career planning capacity and career satisfaction, and to project a serial of Creative Thinking Teaching Material and Self Creative Thinking Scale (SCTS) which could evaluate the differences of students performance between creative thinking instruction and traditional instruction on the career planning course. The main findings were that the students’ career belief, planning capacity, and career satisfaction connected with one another. This means that the students could correct their career beliefs, then could promote their planning capacity, and could achieve their career satisfaction; and should consider the differences of manifold programs, gender, and departments of technological and professional college students. Another main finding was that the career planning course with creative instruction enabled
students to reinforce their creativity more than with traditional instruction. Eventually, we achieved the purposes of this study through survey questionnaire and quasi-experimental methods. The results indicated that the career belief, planning capacity, and career satisfaction of college students showed the significant differences among programs, gender, and departments. Therefore, to regulate the programs is necessary, five-year associate and two-year collegial programs should transform their characters to accord social demands. Concerning the career guidance or counseling, the counselor at a college should understand the career beliefs of students and lead them toward healthful career development [10], enhance their planning skill, and promote their career satisfaction. Another result indicated that the career planning course with creative instruction was superior to traditional instruction, then the career planning course or liberal curriculum should adopt the creative instruction in accordance with cultivating college students’ creative manpower planning of the Ministry of Education in 2004. Finally, suggestions are proposed for educational administration and liberal teaching and career counseling agencies, teachers of technological and professional college and future researchers. In other others, the author drawed up a CREATIVE strategy about career related issues or further researches practicability as below. There were eight suggestions, and the initiative letter of the first word at every suggestion composed a CREATIVE strategy.
1.Compile rigorous scales of students career to survey and compare the present career satisfactory situation of general universities and technological universities.
2.Relate cooperatively among the universities, industries, and government in exploring students future career development and compiling a career handbook for their career direction.
3.Expand the career planning competence of students to integrate or acquire technological expertise connecting with the implement of Web-based instruction [11], and to promote student creativity through Virtual Teams[1] and innovative spirit..
4.Apply the concept of life planning to guide students future career [15], and understand their career needs.
5.Tender the strategies of creative instruction for infusing it into the general curriculum. For example, as pedagogy embedded in educational software design[6], so integrated the creative career to general education.
6.Identify the position of career planning course occupying on the professional dimension in college, and develop the multiple career belief and creativity of students for their career achievement [5].
7.Verify the differences among the students’ career beliefs, planning skills, and career satisfaction about our country and other advanced country.
8.Even up scarcity and superabundance of the quantitative evaluation and qualitative interview about career beliefs. For example, as measurement of perceptual curiosity [3] and psychosocial maturity [19] carried out the quantitative and qualitative research, so progressed in career beliefs step by step.
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