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International Journal of Technology and Engineering Education

Editors in Chief Ray Y. M. Huang National Cheng Kung University, Taiwan

Associate Editors Chi-Cheng Chang National Taiwan Normal University, Taipei, Taiwan

David F. S. Chen National Changhua University of Education, Changhua, Taiwan

Joseph C. Chen Iowa State University, Iowa, U.S.A.

Colin U. Chisholm Glasgow Caledonian University, Scotland, UK

Chih-Feng Chuang National Changhua University of Education, Changhua, Taiwan

Assistant Editors

Richard C.H. Liu Hsing Kuo University of Management, Tainan, Taiwan

Vincent Tai Iowa State University, Iowa, U.S.A.

Publication Committee Chien Chou National Chiao Tung University, Hsinshu, Taiwan

Lance N. Green The University of New South Wales, Australia

Norbert Grünwald Wismar University of Technology, Business and Design, Germany

Jeou-Shyan Horng De Lin Institute of Technology, Taipei, Taiwan

Yoau-Chau Jeng National Changhua University of Education, Changhua, Taiwan

Min Jou National Taiwan Normal University, Taipei, Taiwan

Ming H. Land Appalachian State University, North Carolina, U.S.A.

Shi-Jer Lou National Pingtung University of Science and Technology, Pingtung, Taiwan

Derek O. Northwood University of Windsor, Windsor, Ontario, Canada

Zenon J. Pudlowski Monash University, Melbourne, Australia

Fuh-Sheng Shieu National Chung Hsing University, Taichung, Taiwan

Sam Stern Oregon State University, Corvallis, Oregon, U.S.A.

Chuen-Tsat Sun National Chiao Tung University, Hsinshu, Taiwan

Shir-Tau Tsai National Taiwan Normal University, Taipei, Taiwan

Kuo-Hung Tseng Mei-Ho Institute of Technology, Pingtung, Taiwan

Clyde A. Warden National Chung Hsing University, Taichung, Taiwan

Copyright © 2011 Association of Taiwan Engineering Education and Management (ATEEM) All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior written permission of Association of Taiwan Engineering Education and Management (ATEEM). Published on June 30, 2011.

International Journal of Technology and Engineering Education 2011, Vol.8 No.1

Contents

Articles Fuzzy Logic based Student Performance Evaluation Model for Practical Component of Engineering Institution Subjects By Rajiv Bhatt & Dr Darshana Bhatt..…...………………………………………………… 1 The Study of Construction of the Core Competencies in the Precision Casting Industry By Chin-Guo Kuo, Ching-Ho Huang, & Huey-Jen Tsay........................................................... 9 Pros and Cons of Effective Training for Engineering Personnel By Gandure Jerekias, Kommula Venkata Parasuram, & Venu Madhav Kuthadi……….…....... 17 PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges By Chien-Yun, Dai, Wan-Fei, Chen, Mu-Hui, Lai, & Yu-Hsi, Yuan…………..………...……... 23 Authors Index ……..……………..…………..…………..…………………..………..….. 37 Submission Guidelines ……..………..…………..…………….………….…...………..… 39



Articles


Int. J. Technol. Eng. Educ. Copyright 2011, ATEEM 2011, Vol.8, No.1

Fuzzy Logic based Student Performance Evaluation Model for Practical Component of Engineering Institution Subjects

Rajiv Bhatt* & Dr Darshana Bhatt**

*Civil Engineering Department, A.D.Patel Institute of Technology, New Vallabh Vidyanagar, Gujarat, India

**Structural Engineering Department, Birla Vishvakarma Mahavidyalaya, Vallabh Vidyanagar, Gujarat, India

Abstract Students’ evaluation in practical component of different subjects in engineering institutes follows constant mathematical rule. Alternatively fuzzy logic based evaluation can be more flexible and realistic. In this paper, fuzzy logic based model is developed for evaluation of practical component (50 marks out of total 150) and result of 20 students is worked out with it. The results are compared with classical method. Comparison of the results showed variations between the classical and fuzzy logic method. It is found that fuzzy based evaluation provides certain advantages particularly to the students having low score. The fuzzy logic based evaluation is complex and needs MATLAB software, but still it is quite attractive as the rules are editable by the teacher in the beginning of the academic term as per his / her choice.

Keywords: Student evaluation, Fuzzy logic, MATLAB Software version 7.8 INTRODUCTION Students play vital role in growth of any institute. The ranking of the institute depends on results of the students as well as their placements and quality of the faculty working with the institute. In the era of tight competitiveness among the various institutes, every college focuses on how to improve the performance of the student as well as how to evaluate the student fairly. In engineering institutes student’s performance is evaluated by different means: External examination, internal examination and laboratory work done by the student during the course work of the subject. Evaluation of laboratory work includes 50 marks out of total 150 in engineering institutions of Gujarat Technological University, India. Gujarat Technological University is one umbrella under which more than 90 degree engineering institutes of Gujarat state are covered. Evaluation scheme for 50 marks of practical work of the subject is to be decided by the subject teacher in the beginning of the academic session and needs to be declared to the students. The marks are generally distributed among attendance, term work (carrying out the experiment, entering readings in the laboratory manual, working out the conclusions) and assignments submissions. Arithmetical and statistical methods have been used for aggregating information from these assessment components. Evaluation of student depends upon number of judgments often based on imprecise data. This imprecision arises from human (teacher) interpretation of human (students) performance. (Yadav & Singh, 2011) As per the current classical evaluation approach, educational success or failure is based on separation via certain scoring thresholds. This classical approach of evaluation is the rigid one. Especially in laboratory applications, evaluation of student performance based on rigid scoring criteria may not be appropriate. In this paper for practical component evaluation of 50 marks of subjects of engineering institutes, fuzzy logic based flexible approach is

suggested.

LITERATURE REVIEW Fuzzy logic theory has emerged in the twentieth century and by the beginning of the twenty-first century it was predicted to be applied extensively in many fields. (Altrock, 1995) One of the applications of the fuzzy logic theory is the measurement and evaluation in education system. Samarakou Maria et al. used fuzzy logic for student evaluation for lab-based examinations. They found the new system effective to improve student performance and evaluation efficiency. Hameed I.A.F.A (2010) studied application of fuzzy logic in student evaluation by doing combination with classical student evaluation approach. His developed architecture of student evaluation found easy to be understood by student and teachers and it overcame the problem of ranking of students with the same score. He noted that fuzzy approach can be easily applied for other evaluations like project work evaluation, learning management system evaluation etc. Baba et al. (2009) used fuzzy decision support system to assess students’ performance in projects of engineering education. Results of his study reveal that fuzzy logic has been influential in increasing the quality of education facilities, motivation, reliability and consistency. Hwang & Yang. (2008) applied fuzzy logic to assess students’ attentiveness and found that it can prevent erroneous judgments associated with a single term and will help the teachers to control the students. Gokmen et.al (2010) used fuzzy logic to evaluate student performance in one of the course of Electrical, Electronics and Computer division of Marmar University, Turkey and found the difference in outcome of results between classical method and fuzzy logic method. Saxena and Saxena (2010) used fuzzy logic to develop a model for student evaluation based on his/her attendance and marks obtained. Goodarzi & Amiri (2009) used fuzzy logic to evaluate difficulty, importance and complexity of the

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subject for student evaluation and found it simple, transparent and easy to implement. Basaran et al (2011) proposed novel hybrid method of student evaluation by combining Conventional Content Analysis (CCA) and Fuzzy Rule Based Systems (FRB). They found it more suitable for verbal data obtained from teaching questionnaires. They applied this approach for evaluation of 138 junior students from Gazi University, Turkey. Bai & Chen (2006) presented a new method for evaluating students’ learning achievement using fuzzy membership functions and fuzzy rules. Rasmani and Sen (2005) classified student academic performance using fuzzy techniques. Yang et al. (2010) applied fuzzy theory for adaptive learning diagnosis system (FADS). They applied it on 200 fourth-grade students and found that use of FADS enabled the students in the experimental group to perform better than the two other groups. Othman et al. (2008) used the combination of qualitative methods using fuzzy set theory in analyzing multi criteria teaching quality. Baba et al (2009) developed Fuzzy Group Decision Support Systems (FGDSS) software for the purpose of performance assessment of research assistants at Marmara University, Turkey. Ma & Zhou (2000) presented a fuzzy set approach for the assessment of student-centered learning. Khan et al (2011) used fuzzy logic for evaluation of teachers’ performance and found it useful for decision-makers for writing annual confidential reports for them in an organization. Fuzzy logic nicely handles uncertain and qualitative knowledge of the problem domain by integration of expert system technology with fuzzy logic concept. Cole & Persichitte (2000) developed Fuzzy Cognitive Mapping (FCM) for study of educational organization settings. They noted that FCM framework has tremendous potential for contribution to the development of useful cognitive tools. The literature reveals that there is a vast potential of fuzzy logic application in education as general and for performance assessment, as a particular application.

In this study, the fuzzy logic model is developed and compared with classical model of present student evaluation system for the practical component of subjects offered in degree engineering institutes of Gujarat state in India.

METHODS

Study Group The study group comprised 20 students of one batch of first year under graduate engineering branch students at A.D.Patel Institute of Technology, New Vallabh Vidyanagar, Gujarat state of India. The study used attendance percentage which was converted in marks out of 10, students’ marks in term work (out of 20) and marks of assignments (out of 20) after completing the laboratory work of the ‘Elements of Civil Engineering’ subject during the first semester of Bachelor of Engineering programme during A.Y. 2010-11.

Aim of the study

Aim of the present study is to find whether there is any difference in evaluation between the classical method and fuzzy logic approach and how far the new fuzzy approach can be useful for the students’ fraternity.

Fuzzy Logic The fuzzy logic set was introduced in 1965 as a mathematical way to represent linguistic vagueness (Zadeh, 1965). Fuzzy logic is a technique which allows us to map an input space to an output space. The importance of fuzzy logic derives from the fact that most modes of human reasoning and especially common sense reasoning are approximate in nature. (Ramot, et al, 2002) The main principle of Fuzzy Logic relates to the use of fuzzy sets, which are classes with non sharp boundaries, with no crisp boundaries. The modeling of many systems involves the consideration of some uncertain variables. There also exists non-statistical uncertainty associated with many variables. This form of uncertainty can be handled in a rational framework of ‘fuzzy set theory’. There are two concepts within fuzzy logic which play a central role in its applications: Linguistic variables and fuzzy if-then rules. Fuzzy logic uses variables like “low”, “high” in place of “yes/no” or “true/false”. According to Zadeh (1975) variables words or sentences as their values is called linguistic variables and the variables that represents the gradual transition from high to low, true to false is called fuzzy variables and a set containing these variables is the fuzzy set. If-then rule is the one in which the antecedent and consequent are propositions containing linguistic variables. Fuzzy sets are determined by membership functions. One of the basic limitations of classic logic is that it is restricted to two values, true or false and its advantage is that it is easy to model the two-value logic systems and also we can have a precise deduction. The real world is an analogical world not a numerical one. We can consider fuzzy logic as an extension of a multi-value logic, but the goals and application of fuzzy logic is different from multi-value logic since fuzzy logic is a relative reasoning logic not a precise multi-value logic. The membership function of a fuzzy set is expressed as µA(x) and membership degree of its fuzzy set is determined as a number between 0 and 1. If variable definitely belongs to set A, µA(x) is ‘1’ and if it is definitely does not belong to set A, then µA(x) is ‘0’. While traditional sets can be characterized by only one membership function, fuzzy sets can be characterized by numerous membership functions (Sen & Cenkci, 2009). Fuzzy logic can be incorporated into expert system to enhance the performance and reliability of expert system in decision making process. It is expected that reasoning based on fuzzy models will provide and alternative way of handling various kinds of imprecise data, which often reflects the way people think and make judgments.

PERFORMANCE EVALUATION BY FUZZY LOGIC Application of fuzzy logic model comprises of three stages:

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Rajiv Bhatt & Dr Darshana Bhatt

1. Fuzzification of 3 inputs: Attendance %, term work marks and assignment marks

2. Determination of if-then rules and inference method

3. Defuzzification of performance value: To calculate the final output with the help of suitable defuzzification method.

Practical component of each subject in study of engineering is divided in to three sub-components: Attendance % (10 marks), Term work (20 marks) and Assignments (20 marks). All these marks are summed up

to give total marks out of 50 for each student as per the present system of evaluation. Fuzzy logic based evaluation model will comprise of 3 inputs and one output, which is shown in Figure 1 below. The development of such a fuzzy decision making system is easily implemented using the MATLAB software (version 7.8). MATLAB is menu-driven software that allows the implementation of fuzzy constructs like membership functions and a database of decision rules. The software is easy to use and it is user friendly. (Dweiri & Kablan, 2006) It has fuzzy logic toolbox for building fuzzy inference system as .fis files.

Figure 1: Student performance evaluation model based on fuzzy logic

Fuzzification of results and performance value Fuzzification of result for each sub-component of practical component was carried out using input variables and their membership functions of fuzzy sets. There are 3 input variables. Each variable is having 3 membership functions. The fuzzy sets of all 3 inputs are given in Table 1, 2 and 3 and Figures 2, 3 and 4. For converting attendance % in to equivalent marks following rule is followed: 80% to 100% - 10 marks, 75% to 80% - 9 marks, 70% to 75% - 8 marks, 60% to 70% - 7 marks, 50% to 60% - 5 marks and below 50% - 0 marks. Low, average and high 3 fuzzy sets are prepared here after discussion with senior academicians in various engineering institutes of Gujarat. For ‘Term work’ variable ‘Average’ fuzzy set is kept at 50% level of achievement. Marks range for this variable is 0 to 20. Low, average and high three fuzzy sets are taken as triangular shaped as shown in figure 3. For ‘Assignment’ variable ‘average’ fuzzy set is kept at 50% achievement level. Membership functions of ‘Assignment’ variable are shown in figure 4. The output variable, which is the result of student in practical component, has 3 membership functions. Figure 5 shows its fuzzy sets. Table 1: Fuzzy set of input variable – Attendance

Linguistic Expression Type of set Interval Low Trapezoidal (5, 5, 5.5, 7.5)

Average Triangular (6.5, 7.5, 8.5) High Trapezoidal (7.5, 9.5, 10, 10)

Figure 2: Membership functions for input variable

‘Attendance’

Table 2: Fuzzy sets of input variable – Term work Linguistic Expression Type of set Interval

Low Triangular (0, 0, 10) Average Triangular (6, 10, 14)

High Triangular (10, 20, 20)

Figure 3: Membership functions for input variable ‘Term

work’ Table 3: Fuzzy sets of input variable – Assignments

Linguistic Expression Type of set Interval Low Triangular (0, 0, 10)

Average Triangular (6, 10, 14) High Triangular (10, 20, 20)

Figure 4: Membership functions for input variable

‘Assignment’

Figure 5: Membership functions of Output Variable

‘Result’

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Table 4: Fuzzy sets of output variable – Result

Linguistic Expression Type of set Interval Poor Triangular (0, 0, 25)

Average Triangular (15, 25, 35) Excellent Triangular (25, 50, 50)

Rules and Inference Next step in fuzzy logic model development is to decide the If-then rules. The maximum number of fuzzy rules is calculated multiplying the number of fuzzy sets of all inputs. As we have 3 inputs with 3 fuzzy sets in each input, total If-then rules will be 27. The rules are prepared after discussion with senior professors who were having long experience of academics. These rules are as given below:

1. If attendance is low, term work is low and assignment is low, then result is poor.

2. If attendance is low, term work is low and assignment is average, then result is poor.

3. If attendance is low, term work is low and assignment is high, then result is average.

4. If attendance is low, term work is average and assignment is low, then result is poor.

5. If attendance is low, term work is average and assignment is average, then result is average.

6. If attendance is low, term work is average and assignment is high, then result is excellent.

7. If attendance is low, term work is high and assignment is low, then result is average.

8. If attendance is low, term work is high and assignment is average, then result is average.

9. If attendance is low, term work is high and assignment is high, then result is excellent.

10. If attendance is average, term work is low and assignment is low, then result is poor.

11. If attendance is average, term work is low and assignment is average, then result is average.

12. If attendance is average, term work is low and assignment is high, then result is average.

13. If attendance is average, term work is average and assignment is low, then result is average.

14. If attendance is average, term work is average and assignment is average, then result is average.

15. If attendance is average, term work is average and assignment is high, then result is average.

16. If attendance is average, term work is high and assignment is low, then result is excellent.

17. If attendance is average, term work is high and assignment is average, then result is excellent.

18. If attendance is average, term work is high and assignment is high, then result is excellent.

19. If attendance is high, term work is low and assignment is low, then result is poor.

20. If attendance is high, term work is low and assignment is average, then result is average.

21. If attendance is high, term work is low and

assignment is high, then result is excellent. 22. If attendance is high, term work is average and

assignment is low, then result is average. 23. If attendance is high, term work is average and

assignment is average, then result is average. 24. If attendance is high, term work is average and

assignment is high, then result is excellent. 25. If attendance is high, term work is high and

assignment is low, then result is excellent. 26. If attendance is high, term work is high and

assignment is average, then result is excellent. 27. If attendance is high, term work is high and

assignment is high, then result is excellent. In the situation of several rules being active for the same output membership function, it is necessary that only one membership value is chosen. Several authors, including Mamdani, Takagi-Sugeno and Zadeh have developed a range of techniques for fuzzy decision-making and fuzzy inference. In this research, Mamdani method of inference is chosen which is given in Equation (1). (Semerci, 2004)

( ) max[min[ ( ( )), ( ( )), ]], 1, 2........c A Bky input i input j k rμ μ μ= =

(1)

Above Equation (1) gives an output membership function value for each active rule of our fuzzy decision making system. When one rule is active, an AND operation is applied between different inputs. The smaller input value is chosen and its membership vale is determined as membership value of the output for that rule. This method is repeated, so that output membership functions are determined for each rule. To sum up, AND (min) operations are applied between inputs and OR (max) operations are used between outputs. Determination of Result Defuzzification is the process of converting a fuzzy number in to a crisp value. In this study, centroid (centre of area) technique is used, as it is one of the most common methods of defuzzification. (Padhy, 2005) The proposed Fuzzy Expert System tested 20 student’s marks obtained during first semester of A.Y. 2010-11. For each student, all three input scores were fuzzified by membership functions. Active membership functions were calculated according to rule table, using the Mamdani Fuzzy Decision Techniques. The output was calculated and then defuzzified by calculating the center of the resulting geometrical shape. This sequence was repeated using the performance score of student in all three sub-components of practical component. Figure 6 shows all 27 active rules and result of one of the student. The crisp output is calculated with the formula as given below in Equation (2):

Z = ( )

( )c

c

z x dz

z dz

μ

μ

× ×

×∫∫

(2)

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Figure 6: Active rules and result of student with Attendance 7 marks, Term work 15 marks and Assignments 08 marks

Table 5: Comparison of student evaluation by two methods for practical component

Student No Attendance Term work Assignment

Result as per classical

method

Result as per fuzzy

logic approach

1 10 18 16 44 40.8 2 9 18 18 45 41.4 3 9 19 18 46 41.4 4 9 18 18 45 41.4 5 10 18 18 46 41.5 6 9 19 19 47 41.4 7 9 18 18 45 41.4 8 8 16 16 40 40.4 9 5 12 13 30 34 10 7 15 8 35 36.8 11 8 20 12 40 40.4 12 8 14 20 42 39.9 13 10 16 10 36 40.8 14 8 15 15 38 40.4 15 10 18 13 41 39.4 16 10 19 19 48 41.7 17 8 20 11 39 40.4 18 5 10 11 26 27.5 19 10 19 20 49 41.7 20 10 18 15 43 40.4

Arbitrary student 6 10 8 24 25

Figure 7: Surface Viewer of Result based on ‘term work’ and ‘assignments’

Above Table 5 shows all 3 input values and their result by classical method and by fuzzy logic method for 21 students (including one arbitrary) of first year B.E. at A.D.Patel Institute of Technology, New Vallabh Vidyanagar, Gujarat, India. Figure 7 shows change of result with respect to change of marks obtained in assignments and term work by the student. DISCUSSION Table 5 shows comparison between classical method and fuzzy method for student evaluation in practical component of 50 marks. From last two columns, it is proved that there is a linear relationship between the classical approach and fuzzy approach. If a student is excellent as per classical approach, then he or she is also excellent as per fuzzy approach of evaluation. For students having less than 40 marks as per classical method, they are getting more marks as per fuzzy method. Like, student with 30 marks (5, 12 and 13) in classical method is getting 34 marks in fuzzy approach and student with 36 marks (10, 16 and 10) in classical method is getting 40.8 marks in fuzzy method. However, for students with more than 41 marks, performance by fuzzy method is lesser than the classical method. As for example, student with 46 marks (9, 19 and 18) in classical method is getting 41.4 marks in fuzzy method. In practical component minimum passing level is 50% that is 25 marks out of 50. For arbitrary student who gets 24 marks by classical method, he gets 25 marks in fuzzy method. Hence, by classical method he is considered as fail, but by fuzzy method he could clear the practical component exam. The classical method adheres to a constant mathematical rule but evaluation with fuzzy logic has great flexibility. The main advantage of fuzzy evaluation lies in flexibility of rules. At the initial stage of application, course-conveners can edit rules and membership functions to obtain various performance values which should be common to all the students in the same group. It is also necessary for fuzzy approach to

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inform students in advance regarding rules of evaluation. For fuzzy evaluation to implement, a committee can be formed comprising seniors from education board who shall seat together and come to an agreement on rules and membership functions. Proposed fuzzy method of student evaluation is not suggested to completely replace the current traditional method of evaluation, but it can strengthen the present system by providing additional information to be used for decision making by the users.

CONCLUSION In this paper, a fuzzy logic based new approach for students’ evaluation of practical component of subjects of engineering institutes is shown. When the student’s performance in three sub-components is evaluated by fuzzy logic approach, a difference in outcome is observed between the classical and proposed fuzzy logic approach. While the classical method follows a constant mathematical rule, fuzzy logic based evaluation approach provides flexibility as well as reliability. For total scores less than 30 mark out of 50, fuzzy logic approach gives more marks. The fuzzy logic based evaluation is complex and needs MATLAB software, but still it is quite attractive as the rules are editable by the teacher in the beginning of the academic term as per his / her choice. As a future research, one can combine techniques of fuzzy logic and artificial neural networks, called as Neuro-Fuzzy Systems for students’ academic performance evaluation. It is concluded that fuzzy logic approach can be adopted in laboratory evaluation of students in engineering institutes. It can be also further applied for theoretical subject evaluations of students as well as for distance education courses offered by different Universities. REFERENCES Altrock V.C. (1995). Fuzzy Logic Applications in Europe.

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AUTHORS

Rajiv Bhatt-Corresponding author:

Qualification: M.E. Civil (Construction Engineering & Management) (Gold-Medalist), Ph. D pursuing in Civil Engineering from SVNIT, Surat, India.

Experience : 13 years at professional level and 9 years in academics

Publications: 24 research papers published in International / National Journals and Conferences.

Present Affiliation: Head and Associate Professor in Civil Engineering Department of A. D. Patel Institute of Technology, Vallabh-Vidyanagar, Gujarat, India.

Research interests: Sustainable Building Assessments, Analytic Hierarchy Process and Fuzzy logic applications in Civil Engineering, Construction project management

E-mail ID: [email protected] Dr Darshana R Bhatt:

Qualification: M.E.(Structural Engineeirng), Ph.D. in Structural Engineering

Experience: 16 years in academics

Publications :15 research papers published in International / National Journals and Conferences

Present Affiliation: Working as Associate Professor in Structural Engineering Department of Birla Vishvakarma Mahavidyalaya (BVM) at Vallabh-Vidyanagar, Gujarat, India.

Research Interests: Geotechnical Engineering, Steel structures, Fuzzy logic applications in Civil Engineering

E-mail ID: [email protected]

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8


The Study of Construction of the Core Competencies in the Precision Casting Industry

Chin-Guo Kuo*, Ching-Ho Huang**, & Huey-Jen Tsay***

*Department of Industrial Education, National Taiwan Normal University, Taipei, Taiwan **Taipei Municipal Nangang Vocational High school, Taipei, Taiwan

*** Center Of General Education, Kao Yuan University, Taipei, Taiwan

Abstract The main purpose of this study is to investigate the higher level human resource needs in a precision foundry and analyze the core competencies of the industry for promoting the human resource of the precision foundry. This study first reviewed the reference for finding the content of core competencies in precision foundry, second used the method of professional counseling, visits and interviews with 10 industries, and last used 12-bit Delphi expert survey to investigate the gap between the precision foundry courses in colleges and universities of technology and precision casting. The results of this study were indicated as follows: a. There are 10 items in main functions and 25 items in sub functions in the contents of precision casting industry. b. The interviewees thought that it needs to strengthen the university and industry liaison system of precision casting.

The suggestions of this study were indicated as follows: a. The results of this study could provide the basis for the designing of precision casting courses in colleges and

universities of technology and development of precision casting. b. There are many differences in human resource needs of upstream, midstream, and downstream casting industries, so

the follow-up researchers could sort the human competency accurately by needs of every casting industry. Keywords: precision foundry, core competencies INTRODUCTION ‘Casting’ is a link that cannot be ignored in the field of metal industry. With the advancement and development of the precision technology, the traditional casting can no longer satisfy demands of the current high-tech industry. Therefore the elevation of precision casting technology and the nurture of innovative talents are taken as goals to go for by the casting industry.

For many years, to enhance the competitiveness of the domestic precision casting industry, relevant suppliers have been working on aspects such as automatic production, high precision degree, and delicacy. In addition to the improvement of the hardware, another key point is the quality of professional talents. Therefore, how to nurture professionals who can satisfy the demands of the industry has become the common goal of the industry, the government, and the academia.

Technical and vocational education is considered efficient as long as it meets the needs of the students and the industry. Students need quality education in order to meet competency levels required by the workplace (Yildirim & Simsek, 2011). It is important and necessary to develop curriculum that can meet industry needs. The priority is to construct the industry-oriented core competencies so as to cultivate students with the industry-oriented realization and competencies needed by the industry, and facilitate their immediate joining in this profession.

The subject of this study was the precision casting industry. As universities and colleges are cradles which nurture talents, this study aimed to discuss the core

competencies of precision casting in order to offer the data upon which the curriculum development of the precision casting in colleges and universities of technology can be based. We hope that graduates from colleges and universities of technology can have the professional competencies that satisfy the needs of the industry and enable them to ‘go into the industry immediately after graduation’; we also aimed to inspire the industry to look for human resources and to cultivate professionals of precision casting in the campus, therefore enhancing the long-term development of the economy in the country. This is the major motivation for this study.

LITERATURE DISCUSSION Casting is one of the major process methods in machinery manufacturing. It is the technology with the longest history in metal processing, and is also the most flexible approach in making complex parts. It can be regarded as the mother of the machinery industry, with a wide application in making daily industrial supplies, medical supplies, transportation and machinery equipments. Even the high precision aerospace defense industry requires it to make relevant parts. According to the newest “Industrial Statistics Survey Report of Taiwan Area” published by the Ministry of Economic Affairs in 2010, the number of companies in the casting industry in 2006 is 160, which, in comparison with that of 2001, has an increase of 46 companies (40.35 %, as indicated in table 1). It indicates that the precision casting industry is growing, and the nurture of talents and R&D in this industry can be good investments.

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Table 1 Companies of the casting industry from 2001 to 2006 Unit: company Year Industry 2001 2002 2003 2004 2005 2006

Steel Casting Industry 47 101 124 73 98 87

Aluminum Casting industry 42 52 56 56 51 44

Copper Casting Industry 12 10 22 12 24 11

Other Basic Metal Casting Industry 13 20 27 24 22 18

Total 114 183 229 165 195 160

Source: Industry, Commerce, and Services Census Report of Taiwan Area (2010), arranged by this study

In recent years, products of the casting industry have been manufactured towards the goal of high precision and delicacy, which necessitated the precision process technology and professional persons (Chang, 1996a). In the pursuit of miniaturization of parts and systems in the future, the development of MEMS technology undoubtedly opened a wider space for the precision casting industry: the development towards ‘fine precision’ (Chang, 1996b). For this purpose, how to nurture professionals with ‘fine precision’ technology in order to cope with the industry’s requirement of human resources in the assembly line should be the important topic of universities and colleges when they design

curriculum of precision casting courses. According to the search result of ‘the Network of University Curriculum Resource in Ministry of Education’, there are, in total, 20 universities and colleges and 24 departments which offer casting relevant courses (as illustrated in table 2). The time gap between the education of students in colleges and the need of talents in the industry has created serious problems of graduate employment and the lack of employees in the industry. How to bridge the gap between graduates’ learning and its application, and how to foster a close relationship between the industry and the academia, have become important topics in the cultivation of human resources.

Table 2 A list of casting related courses offered by universitues and colleges in academic year 2009 in Taiwan

University (Department) Course Title Required/Selective Credits

National University of Kaohsiung (Traditional Crafts and Creative Design Department) Wax Carving and Metal Casting Selective 2

National Taiwan University (Department of Mechanical Engineering) Foundry Technology Selective 3

National Taipei University of Arts (Fine Arts Department) Foundry TechnologyⅠ Required 2 National Taipei University of Arts (Fine Arts Department) Foundry TechnologyⅡ Required 2 National Taiwan Normal University (regardless of department) Art Glass Casting Selective 2

National Taiwan University of Arts (Crafts and Design Department) Metal Dewax Casting Selective 2

National Taiwan University of Arts (Crafts and Design Department) Dewax Casting Selective 2

Feng Chia University (Materials Science Department) Foundry Technology Selective 3 Feng Chia University (Mechanical Engineering Research Institute) Advanced Foundry Technology Selective 3

Feng Chia University (Mechanical and Computer Aided Engineering Department) Foundry Technology and CAE applications Selective 3

Fu Jen University (Textiles and Clothing Department) Jewelry Casting Wax Carving Selective 2 National Taipei University of Technology (Department of Mechanical Engineering) Foundry Engineering Selective 3

National Taiwan University of Technology (Department of Mechanical Engineering) Casting Welding Practice Required 1

National Taiwan University of Technology (Department of Mechanical Engineering) Advanced Foundry Technology Selective 3

National Kaohsiung University of Applied Sciences (Mold and Engineering Department) Precision Casting Selective 3

National Kaohsiung University of Applied Sciences (Mold and Engineering Department) Foundry Technology Selective 3

National Kaohsiung University of Applied Sciences (Mold and Engineering) Department Casting Special Topics Selective 3

National Chin-Yi University of Technology (Department of Mechanical Engineering) Precision Casting Selective 3

Tainan University of Technology (Product Design Department) Wax Carving and Casting Selective 3

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Chin-Guo Kuo, Ching-Ho Huang, & Huey-Jen Tsay

Chienkuo Technology University (Department of Mechanical Engineering) Precision Casting Selective 3

Nankai University of Technology (vehicle technology services industry spring semester) Precision Casting and Practice Selective 3

St. John's University of Technology (Mechanical and Computer Aided Engineering Department) Precision Casting Selective 3

Lunghwa University of Science and Technology (Department of Mechanical Engineering) Precision Casting Selective 3

Chung Chou Institute of Technology (Mechanical and Computer Aided Engineering Department) Precision Casting and Practice Selective 3

Tung Feng Institute of Technology (Fashion Design Department) Glass dewax Casting Method Selective 2

Tung Feng Institute of Technology (Fashion Design Department) Glass Molding Technique Selective 2

Nanya Institute of Technology (Department of Mechanical Engineering) Foundry Engineering Selective 3

Source: the Network of University Curriculum Resource in Ministry of Education (2010), arranged by this study

Hong (1992) defined levels of technological human resources according to different occupational requirements, ‘operation, maintenance, applied design, and R&D’: with only operational skills, the employee is categorized as a skilled worker; with capabilities of solving problems happening in work with his/her own knowledge and experience, the employee is categorized as a maintenance worker; those who need to seek knowledge and experiences outside their own to solve the problem are regarded as designing workers, but they still belong to the level of trouble shooting worker; those who need to establish hypothesis, test, and create new concept to solve problems are regarded as creative workers. People unusually set up a hierarchy of these levels, but in fact technical staffs of every level differ only in places and fields they work, not in terms of superiority or inferiority. To casting related departments, their curriculum and teaching should be based on the knowledge and skill needed by the industry, in order to prepare students for similar competencies. RESEARCH APPROACH ● Design of Research The study began first by means of discussing the literature on casting related courses offered by colleges and universities, and competency analysis of precision casting industry. They were further supported by approaches such as panel discussions, expert meetings, field works in precision casting industry, and Delphi survey to explore the topic of this study. A detailed explanation is shown as follows:

a) Literature analysis The plan assembles a huge amount of literature on precision casting related courses in domestic colleges and universities, on basic competencies, vocational development theories, competency analysis method and theories, and reports on the development of casting industry or precision casting industry, and their manpower needs. It analyzed collected materials and arranged them into a draft of ‘the core competencies in the precision casting industry’ as the basis for further development of this study.

b) Expert meeting On 29th January year 2010 this study held an expert meeting which invited 5 persons from the precision casting industry, and 3 professors from universities and institutes to review and confirm the draft content, structure, and usage of ‘the core compencies in the precision casting industry’, editing its formal questionnaire which includes 10 working items and 25 missions.

c) Field interview There were 10 representatives of the precision casting industries selected from ‘Taiwan Association of Casting Industry’, which include precision machine tools and equipment industry (equipment end), industry that provides precision casting materials (material end), precision casting production industry (product end that includes producers of heads of golf clubs, aviation technology, decorative lamps). Since 23rd February year 2010 we had begun field visiting to observe and collect potential capability demands, and also interviewed which, from the perspective of employers, focus on the core technical demand of the employee in the precision casting industry.

d) Delphi technique The Delphi technique avoids many factors of traditional decision making process in which participants discuss face to face to reach the agreement. By filling the questionnaire separately, experts have a sense of full participation and are not interrupted (Rowe, Wright & Bodger, 1991). Therefore 12 persons from the precision casting industries were selected as representatives, and since 22nd March year 2010 had been repetitively collecting, analyzing, and arranging experts’ opinions obtained in three written documents until their opinions reached an agreement.

e) Data processing The SPSS17.0 statistic software was adopted to analysis and process data. We compared the content of the three questionnaires filled by the 12 persons from the precision casting industry in terms of times, percentages, and average numbers.

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● Research Object The study used the criterion sampling method to select research objects. The criterion sampling method ensures that all the samples selected meet certain standard, and thus guarantees the quality of research. Before sampling, this study set up certain conditions to sieve research objects. The two conditions are: 1. Persons currently work in the precision casting industry, and have a working experience of more than 10 years in this industry. 2. Persons who have been executives and have at least 5 years’ managing experience, and who understand deeply this industry and the possible difficulties which might happen in the work. ● Research Tool The qualitative part of this study used the researchers ourselves as the tool for collecting materials. The researchers designed half structural interview questionnaire according to literature discussions and our qualitative research experience. We recorded depth interviews with research objects who were informed of the purpose of the interview, and after consent, given interview questionnaire and agreements designed according to respondents’ experience description and research ethics.

As to the questionnaire validity, the study adopted the method of expert validity to ensure its representativeness and relevance. We invited experts in related fields on 29th January year 2010 to view this questionnaire, whose opinions become important references when we edited the formal questionnaire.

ANALYSIS AND DISCUSSION This study discovered the competencies demand in the high-level personnel of the precision casting industry and developed its core competencies by going through literature discussion, field interview, and expert consultation. After the questionnaire interview of the representatives in the industry, the definition of the core competency is leveled up from 1 to 5 points: 5 means very important; it means the precision casting industry thinks that it’s important for employees to have this expert knowledge and skill. And vice versa. The results and discussions are listed below: ● The Analysis of relevant contents From table 3 it can be seen that professionals in the precision casting industry thinks unanimously that ‘shell mold design’, ‘shell mold making’ and ‘metal casting’ are very important, and credit them with 5 points. The second are ‘mold design’, ‘wax making’, and ‘process design’, with the average score of 4.92 points. Respondents differ in opinions on ‘molding’ and ‘post-processing and inspection of castings’, and with further analysis, we found that persons in the equipment end of the precision casting industry all regarded the two as items of less importance.

This study adopted Delphi survey to collect opinions of

12 experts (N=12) from the precision casting industry on items and professional competencies, which, after being analyzed by SPSS 17 statistical software experts, have results listed below:

a) Mold design: 6 respondents think ‘mold flow analysis’ very important, another 6 think important. In terms of ‘mold design’, 11 respondents think this very important; only 1 respondent thinks it important. And after further investigation, we find that this respondent comes from the material end of the precision casting industry.

b) Shell mold design: in ‘casting drawing’, opinions of respondents diversify. After further enquiry, we find that precision casting factories are not able to develop the mold, which is assigned to be done by other mold drawing companies. Therefore they give less importance to this. In the ‘design of casting flow system’, 11 respondents think it very important. Only 1 thinks it important, who, after further investigation, comes from the equipment end of the precision casting industry.

c) Wax mold production: 4 respondents think ‘melting wax’ very important; 2 think it important; and the other 6 think it of common importance. In terms of ‘wax injection’, 11 find it very important; only 1 thinks it of common importance. After further investigation, we find that this respondent comes from the product end of the precision casting industry. At last in ‘group wax tree’, 7 think it very important; only 5 think it important.

d) Shell mold production: all respondents think unanimously ‘pulp dipping and sand pouring’ very important. In ‘dewaxing’ 9 think it very important; 1 thinks it important, and 2 think it of common importance. Finally in ‘sintering’ 10 think it very important, and 2 think it important.

e) Process design: 11 respondents think the ‘design of process parameters’ very important; 1 thinks it important. In ‘QC design’, 11 think it very important, and 1 thinks it important. After further investigation we find that this respondent comes from the product end.

f) Mold making: 8 respondents find that ‘mold making’ is very important, and 4 think it of common importance.

g) Metal melting: here all respondents unanimously think ‘melting’ very important. And in ‘pouring’ 10 think it very important; 2 think it important. After further investigation we find them come from the material and product ends of the precision casting industry.

h) Castings post-processing and inspection: 3 respondents think ‘casting post-processing’ is very important; 8 think it is important and 3 think it of common importance. In ‘heat treatment’, 9 think it is very important; 3 think it is important. Finally in ‘casting inspection’, 10 think it is very important; 2

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think it is important.

i) Equipment maintenance: 4 respondents think that ‘principles of precision casting equipment maintenance’ is very important; 3 think it is important; 5 think it of common importance. And in ‘precision casting equipment maintenance operations’, 11 respondents think that it is very important, and only 1 think it is important.

j) Among them 9 respondents th ink ‘qual i ty management system’ is very important. 3 think it is important. In ‘Project Management Professional

(PMP)’, 9 think it very important, and 3 think it important. After further investigation we find they all come from the equipment end of the precision casting industry. In terms of ‘customer complaint of quality abnormalities’, 9 respondents think it is very important; 2 think it is important, and 1 thinks it of common importance. And in ‘concept of accounting cost’, 4 respondents think it is very important; 5 think it is important; 3 think it of common importance. At last, in terms of ‘mechanical process’, 7 respondents think it is very important, while another 5 think it is important.

Table 3 Competency Content of Professionals in the Precision Casting Industry (N=12) Minimum Maximum Average Standard

Deviation

1 Mold Design 4 5 4.92 .289

1-1 Mold Flow Analysis 4 5 4.50 .522

1-2 Mold Design 4 5 4.92 .289

2 Shell Mold Design 5 5 5.00 .000

2-1 Casting Drawing 3 5 4.00 .426

2-2 Casting Flow System Design 4 5 4.92 .289

3 Wax Mold Production 4 5 4.92 .289

3-1 Melting Wax 3 5 3.83 .937

3-2 Wax Injection 3 5 4.67 .778

3-3 Group Wax Tree 4 5 4.67 .492

4 Shell Mold Production 5 5 5.00 .000

4-1 Pulp Dipping and Sand Pouring 5 5 5.00 .000

4-2 Dewaxing 3 5 4.58 .793

4-3 Sintering 4 5 4.83 .389

5 Process Design 4 5 4.92 .289

5-1 Process Parameters Design 4 5 4.83 .389

5-2 QC Design 4 5 4.92 .289

6 Mold Making 3 5 4.75 .622

6-1 Mold Making 3 5 4.33 .985

7 Metal Melting 5 5 5.00 .000

7-1 Melting 5 5 5.00 .000

7-2 Pouring 4 5 4.83 .389

8 Castings Post-Processing and Inspection 3 5 4.75 .622

8-1 Castings Post-Processing 3 5 4.17 .577

8-2 Heat Treatment 4 5 4.75 .452

8-3 Castings Inspection 4 5 4.83 .389

9 Equipment maintenance 3 5 4.50 .798

9-1 Principles of Precision Casting Equipment Maintenance 3 5 3.83 .937

9-2 Precision Casting Equipment Maintenance Operation 4 5 4.33 .492

10 Other relevant technologies 4 5 4.67 .492

10-1 Quality Management System 4 5 4.75 .452

10-2 Continual Improvement of PMP 4 5 4.75 .452

10-3 Customer Complaint of Quality Abnormalities 3 5 4.67 .651

10-4 Concept of Accounting Cost 3 5 4.08 .793

10-5 Mechanical Process 4 5 4.58 .515

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● Analysis of Field Interviews

a) Precision machine tool and equipment industry

1. New comers cannot adapt themselves to the long working hours in a high temperature environment of the precision casting industry.

2. New comers lack pragmatic experience and require a period of training to get started.

3. Lacking foreign language abilities; cannot negotiate the business with foreign suppliers.

b) Material suppliers of the precision casting industry

1. The lack of human resources caused by the fact that old masters are of the retiring age while newcomers need a long period of training to get started.

2. There is a difference between the materials used in the academia and those used in the industry.

3. Do not understand clearly the quality of wax and shell mold, and their recycle.

4. Newcomers lack the competencies of innovation and development.

c) Precision casting production industry

1. Graduates from universities are good at theories, but those from universities of technology are familiar with equipments and software analysis. We need to nurture employers who have both skills.

2. Unable to estimate the viability of casting products, which stagnates the production in the factory.

3. With little pragmatic experiences, and cannot detect the flaw of products.

4. Newcomers are often careless in pouring, and cause damage to the factory.

● Talent demand a) Precision machine tool and equipment industry Precision machine tool and equipment industry is the foundation of a country’s industries. Every country strives for the development of precision equipment industries in order to cope with the demand and development of other industries. It’s urgent to nurture talents who design and develop the equipment system for industries. In this stage these talents must have abilities of mechanical design and circuit wiring. Respondents

suggest that school students attend courses of applies mechanics, mechanisms, circuit wiring, and innovation and development. This industry in general selects and evaluates graduates from electrical engineering or electrical engineering related departments.

b) Material suppliers of the precision casting industry Material industry is the basis of all processing industries. As early as in 1978, ‘material’, ‘information’, ‘energy’, and ‘automation’ were listed as key technologies of the country. Taiwan’s traditional metal material industry in the 60s had successfully offered materials needed by the steel casting industry, precision casting industry, mechanical component industry, and the mechanical industry. Now in this stage, talents must understand properties of materials and also have analytical abilities. Respondents think that they have to attend classes such as material science introduction, mechanical material, material properties and analysis and metallurgy. In general this industry chooses people from departments of material or mechanical engineering.

c) Precision casting production industry The precision casting production industry is necessary for the development of high precision machinery and automobile industry. To coordinate with the industrial development, the precision casting production industry has to renew itself in aspects of technology elevation, QC, and product management by strengthening the R&D and by applying high technology to reduce the cost of refining the product while elevating its quality. At this moment it needs people with casting relevant background to join in. CONCLUSION AND SUGGESTIONS The conclusion of the above analysis and results, and the suggestion offered by this study is shown as follows:：

● Research Conclusion a) The core competencies of the precision casting

industry include 10 items and 25 missions.

The study reached the following results after literatures discussing, field interviews and expert meetings: the core competencies of the precision casting industry include 10 working items and 25 missions (as indicated in table 4).

Table 4 Core competencies of the precision casting and the relevant technological contents Item Mission

1.Mold design Mold Flow Analysis, Mold Design 2. Shell mold design Casting Drawing, Casting Flow System Design 3. Wax mold making Melting Wax, Wax Injection, Group Wax Tree 4.Shell mold making Pulp Dipping and Sand Pouring, Dewaxing, Sintering 5.Process design Process Parameters Design, QC Design 6.Mold making Mold Making 7.Metal melting Melting, Pouring 8.Castings Post-Processing and

Inspection Castings Post-Processing, Heat Treatment, Casting Inspection

9.Equipment maintenance Principles of Precision Casting Equipment Maintenance, Precision Casting Equipment Maintenance Operation

10.Other relevant technologies Quality Management System, Continual Improvement of PMP, Customer Complaint of Quality Abnormalities, Concept of Accounting Cost, Mechanical Process

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b) In the current stage the nurture of talents in the precision casting industry still requires the cooperation between the academia and the industry.

Questions proposed by respondents, such as ‘newcomers cannot adapt themselves to the industry’, ‘lack of pragmatic experience’, ‘the lack of human resource’, ‘the difference between the materials used in the industry and those used in the academia’, and ‘unable to evaluate the viability of casting products’, indicate the gap between the content of courses offered in universities and institutes and the employees needed by the precision casting industry. To enable students to join the industry directly after graduate and contriubute their learning there, it is necessary to adopt the ‘practical application’ approach of talent cultivation realized by the cooperation between the industry and the academia. ● Research Suggestions a) This study result mainly concerns the industry, and

can be referred to by vocational institutes, related enterprises, vocational training units when they design courses and teaching materials of precision casting. Universities of technology can adopt the competency indicators of employees in the precision casting industry concluded in this study to design courses and evaluation approaches, thus realizing the ‘practical application’ policy of the Ministry of Education. Each school can also coordinate with local industry group and arrange basic curriculum according to their demand.

b) Main industries of precision casting initially selected by this study include the material end, the equipment end, and the product end of the precision casting. 10 precision casting suppliers are chosen as representatives to be interviewed and visited. Respondents indicated that talents required by every industry vary greatly: those of the material end need to know the properties of material and to have analytical competencies. In general they should be graduates from the material or mechanical engineering departments. The equipment end need people who understand mechanical structure and have circuit wiring skills. Basically these are people from the electrical engineering department. The product end needs employees who understand precision casting process, QC control, and product refinement, and here people with precision casting background are needed. Therefore we suggest that future researchers make finer divisions of the precision casting industry in order to explore competencies requirements of each industry.

REFERENCES DGBAS. (2008). Industry, Commerce, and

ServiceCensus Report of the Taiwan area in 2006. RetrievedOctober 30, 2010, from http://www.dgbas. gov.tw/public/Attachment/07301044771.pdf

Chang, J. C. (1996a). Where to fine human resources with casting technology-strengthen the cooperation

between the industry and the academia to create a win-win future. Casting Monthly, 87, 14-17.

Chang, J. C. (1996b). An analysis of expertise knowledge items of staffs in the precision casting industry in Taiwan. Taipei: Chuan Hua Technology Books.

Hong, J.C. (1992). The thinking system of problem shooting of skilled worker, maintenance, design worker, application worker and creative worker.

Rowe, G., Wright, G. & Bolger, F. (1991). Delphi: A reevaluation of research and theory. Technology Forecasting and Social change, 39(3), 235-251

University Curriculum Resource Network in the Ministry of Education. (2010). Retrieved October 30, 2010, from http://ucourse.tvc.ntnu.edu.tw/NEWWEB/index.html

Yildirim, Ali & Simsek, Hasan (2011). A qualitative assessment of the curriculum development process at secondary vocational schools in Turkey. Retrieved August 22, 2011, from http://scholar.lib.vt.edu/ejournals/JCTE/v18n1/pdf/yildirim.pdf

AUTHORS

Chin-Guo Kuo, Doctor of Philosophy for Department of Materials Science and Engineering of National Chiao Tung University, serves as associate professor in Development of Industrial Education of National Taiwan Normal University. His current research interests are casting industry, solar

energy, and technological and vocational education. Corresponding Author: e-mail: [email protected].

Ching-Ho Huang, Doctor of Philosophy for Department of Industrial Technology Education of National Taiwan Normal University, serves as a teacher in Taipei Municipal Nangang Vocational High school. His current research interests

are mechanical engineering, technological and vocational education, and technology education. His e-mail is [email protected]

Huey-Jen Tsay, Master for the Institute of Mainland China Studies of National Sun Yat-Sen University, serves as Lecturer in Center of General Education of Kao Yuan University. Her current research interests are special education, history education, and technological and vocational education.

Her e-mail is [email protected]

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Pros and Cons of Effective Training for Engineering Personnel

Gandure Jerekias*, Kommula Venkata Parasuram*, & Venu Madhav Kuthadi**

*Department of Mechanical Engineering, University of Botswana, Gaborone, Botswana. **Department of BIT, University of Johannesburg, Johannesburg, South Africa.

Abstract Effectiveness in training personnel in the field of engineering is a task that demands creativity, innovation and commitment. It calls for an integrated approach to “learning through hands-on participation” through scaffolding approach instead of passive listening. This paper presents comparative studies conducted at the Universities of Botswana and Johannesburg to establish effective methods of teaching and learning of two courses namely Computer Aided Drafting and Database Systems for engineering students. The options considered were lectures followed by practical sessions, compared with a combination of lectures and practicals in one session. The later option was overwhelmingly favoured and was adopted as the method for course delivery henceforth.

Keywords: Computer Aided Drafting, Database Systems, Teaching, Learning, Scaffolding. INTRODUCTION Students learn in many ways, and these include seeing and hearing, reflecting and acting, reasoning logically and intuitively, memorizing and visualizing, and drawing analogies and building models. Teaching methods also vary. Some instructors lecture, others demonstrate or discuss, some focus on principles and others on applications, some emphasize memory and others understanding. How much a given student learns in a class depends in part on that student’s ability, prior preparation, and the compatibility of his or her learning style and the instructor’s teaching style. Mismatches exist between common learning styles of engineering students and traditional teaching styles of engineering instructors. In consequence, students become bored and inattentive in class, perform poorly on assessments, get discouraged about the courses, and in some cases end up failing the courses. Active and Reflective Learners The mental processes by which taught information is converted into knowledge can be grouped into two categories, that is, active experimentation and reflective observation. Active experimentation involves doing something in the external world with the information, like discussing it, explaining it or testing it in some way. Reflective observation involves examining and manipulating the information introspectively (Kolb, 1984). An active learner is someone who feels more comfortable with, or is better at, active experimentation than reflective observation. There are indications that engineers are more likely to be active than reflective learners 9Felder, 1993, McCaulley, 1976). Active learners do not learn much in situations that require them to be passive (such as most lectures), and reflective learners do not learn much in situations that provide no opportunity to think about the information being presented (such as most lectures). Active learners work

well in groups, and reflective learners work better by themselves or with at most one other person. Active learners tend to be experimentalists, and reflective learners tend to be theoreticians.

“Active” signifies that students do something in class beyond simply listening and watching, for example, discussing, questioning, arguing, brainstorming, or reflecting. Active student participation thus encompasses the learning processes of active experimentation and reflective observation. A class in which students are always passive is a class in which neither the active experimenter nor the reflective observer can learn effectively. Unfortunately, most engineering classes fall into this category (Lawrence, 1984). As is true of many other learning style dimensions, both active and reflective learners are needed as engineers. The reflective observers are the theoreticians, the mathematical modelers, the ones who can define the problems and propose possible solutions. The active experimenters are the ones who evaluate the ideas, design and carry out the experiments, and find the solutions that work.

Teaching both active and reflective learners demands creativity on the part of the instructor. Ideally, the instructor should alternate lectures with occasional pauses for thought (reflective) and brief discussion or problem-solving activities (active), and should present material that emphasizes both practical problem solving (active) and fundamental understanding (reflective). An exceptionally effective technique for reaching active learners is to have students organize themselves at their seats in groups of three or four and periodically come up with collective answers to questions posed by the instructor (McDowell, 1995). The groups may be given a few minutes to do so, after which the answers are shared and discussed for as much or as little time as the instructor wishes to spend on the exercise. Besides forcing thought about the course material, such brainstorming exercises can indicate material that students don’t understand; provide a more congenial

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classroom environment than can be achieved with a formal lecture; and involve even the most introverted students, who would never participate in a full class discussion. Such short exercises can make the entire class period a stimulating and rewarding educational experience. Scaffolding Theory as a Teaching Strategy The concept of scaffolding (Bruner, 1975) is based on the work of Vygotsky (1962), who proposed that with an adult's assistance, children could accomplish tasks that they ordinarily could not perform independently. Scaffolded instruction is the systematic sequencing of prompted content, materials, tasks, and teacher and peer support to optimize learning (Dickson et. al., 1993). Rosenshine & Meister (1992) defined scaffolding as a process in which students are given support until they can apply new skills and strategies independently.

In scaffolding instruction, which was used as a tool in this work, an instructor provides scaffolds or supports to facilitate the learner’s development. The scaffolds facilitate a student’s ability to build on prior knowledge and internalize new information. The activities provided in scaffolding instruction are just beyond the level of what the learner can do alone (Olson et. al., 2000). The instructor provides the scaffolds so that the learner can accomplish (with assistance) the tasks that he or she could otherwise not complete (Bransford et. al., 2000). CASE 1 A comparative study was conducted at the University of Botswana to establish an effective method of teaching and learning Computer Aided Drafting course for second year engineering students. This is a large group comprising of students from all engineering disciplines (common year). As such, the teaching of this course was structured to comprise of two parts, lectures and practicals. Lectures were conducted in a conference hall (to accommodate all students) where the instructor would present lectures and demonstrations using multi-media equipment. Due to the large size of the group, students were largely passive listeners with no confidence at all even to ask or answer questions, for fear of being ridiculed by fellow students in case of a non-sensible question or response. The lectures would then be followed, at a later time, by sessions of practicals in the computer laboratory in smaller groups where students would practice what they learnt in the lecture. In almost all cases, most students were unable to do the assigned practical tasks and the instructor had to present the lecture again. This was indicative of the fact that students had not understood the material taught or were not attentive at all.

To address this problem, the instructor devised an alternative method of teaching the course. This approach required that the large group be divided into smaller groups. Each group would then have a single continuous session of a lecture and practical’s per week, conducted

in the computer laboratory. Each student would be having his or her own computer during the entire session, and would be able to try out the demonstrations made by the instructor. A short break would separate the demonstration-packed lecture and the practical session. The practical session was anticipated to be done without much difficulty since students would be fresh from the lecture. Students were taken through one session of this method, and they seemed to enjoy it very much with overwhelming participation.

A survey was then carried out to establish the opinions of students on their preferred method of course delivery. Data was collected from students during a lecture session using a questionnaire drafted as on table 1 below.

Table 1: Questionnaire: Kindly indicate which of the two methods indicated below would you prefer for the teaching of Computer Aided Drafting.

Options Indicate Your Choice By A Tick

1. Lectures in the conference Center, followed by practical sessions in the Labs (Current).

2. Eliminate lectures in the Conference Center and have combined sessions of lectures and practical’s in the Labs (Proposed).

RESULTS Forty-seven (47) students participated in this exercise (partly due to a test for another course which was scheduled at the same time). Out of the 47 questionnaires, 46 chose options 2 while one chose both options (spoiled). Nobody chose option 1 as the preferred method of teaching the course. These results are represented graphically in figure 1 below.

Figure 1: Student opinions

Comparative analysis of assessments Table 2 below shows average scores for Computer Aided Drafting course assessments for the 2009 (old teaching method) and 2010 (new teaching method) streams.

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Gandure Jerekias, Kommula Venkata Parasuram, & Venu Madhav Kuthadi

Table 2: Comparative analysis of assessments

Academic Year Assessment component

2009 2010 Test-1 62.0 71.4 Test-2 59.9 65.5 Assignment 1 81.2 80.4 Assignment 2 63.3 81.5 Final CA 64.6 73.5

The data in table 2 above indicates an improvement in student performance of 15.2% in Test 1, 9.3% in Test 2, 28.8% in Assignment 2, and 13.8% in final course assessment from 2009 to 2010 streams. There was however a 1% drop in performance in Assignment 1. This data largely demonstrates that the new teaching method has the potential to impart a strong learning experience on students that yields good results.

Cognicence is ofcourse taken of the fact that the assessment questions are different from year to year, but efforts were made to ensure that the same content and level of difficulty were maintained as much as possible. There was also a higher demonstration of understanding of the course material during practicals in the 2010 stream than in the 2009 stream. It is anticipated that with repetitive application of this new method by course instructors, the quality of learning outputs will continue to improve.

Figure 2 below shows a graphical representation of the data in table 1 above. On the legends, Series 1 shows average scores for the 2009 stream, and Series 2 shows the average scores for the 2010 stream.

Figure 2: Comparative analysis of continuous assessment

CASE 2 A comparative study was conducted at the University of Johannesburg to establish an effective method of teaching and learning Database Systems (ILS22B3) course for second year engineering students. The experimental study was done during the second semester of 2010. A total number of 89 students were registered for the course and were active. The course has three components in its continuous assessment namely test 1, test 2 and laboratory whose weights are 0.35, 0.35 and 0.3 respectively. The continuous assessment contributes 50% in the final mark and the other 50% is taken from

the final exam mark. In this study, the ‘old’ method of course delivery was applied in the first half of the semester and its impact was assessed through test 1. The ‘new’ method of course delivery was applied in the second half of the semester and its impact was assessed through test 2. Comparative analysis of assessments Table 3 below shows average scores for the course assessments for the two methods of course delivery.

Table 3: Comparative analysis of assessments Assessment component Average score Test-1(old method) 53 Test-2(new method) 77 Final CA 56 Exam Mark 64

The new teaching method shows an average mark improvement of 45%. It also had significant effect on the exam mark. Cognicence is ofcourse taken of the fact that the assessment questions for tests 1 and 2 were different, but efforts were made to ensure that the same amount of content and level of difficulty were maintained as much as possible. Figures 3-6 shows how the individual marks of students are used to show the impact of new method in teaching this course.

Figure 3: Comparison of Test 1 and Test 2.

Figure 3 shows the comparison of marks for tests 1 and 2.

The average mark for test 1 is 53 and the average for test 2 is 77. This implies that the new method improved the pass rate, and thus the average learning, by 45%. Surprisingly, the majority of students scored higher marks in test 2 than in the test1, validating the significance of this method in teaching and learning.

Figure 4: Comparison of CA and Exam marks.

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Figure 4 shows the comparison of continuous assessment mark against the final examination mark. The average mark in the continuous assessment is 56 and the average of final exam marks is 64. A total of 14 students (15%) scored less than 50% in the final exam. A total of 20 students 22%) scored between 40 and 50. Eleven students scored approximately the same score in both continuous assessemnt and final exam.

Figure 5: Comparison of Tests and Final marks.

Figure 6: Comparison of CA, Exam and Final marks.

Figure 5 and 6 show the comparison of individual components of continuous assessment and final mark in the course. DISCUSSION ON RESULTS The results of case study 1 indicate that the method of teaching Computer Aided Drafting that has been used so far was not appropriate for engineering students, who are supposed to be largely active and reflective by nature. Upon exposure to a method based on scaffolding theory and active learning approach to delivery that is more conducive for learning and given the opportunity to decide, virtually everybody decided for the second option (proposed method). The survey results show the significance of new teaching methodology and it was unanimously approved for immediate implementation. The impact of the new approach was validated by the

results obtained after running a pilot stream during the 2009/2010 academic year, second semester. The results indicated an overall improvement in the performance of the students.

CONCLUSIONS The learning styles of most engineering students and teaching styles of most engineering instructors are incompatible in several dimensions. These mismatches lead to poor student performance, professional frustration, and a loss to society of many potentially excellent engineers. Although the diverse styles with which students learn are numerous, the inclusion of a small number of techniques such as scaffolding instruction style as an instructor’s approach should be sufficient to meet the needs of most of the students in any class. This study testifies a substantial improvement in performance of students after the implementation of new approaches to course delivery at the Universities of Botswana and Johannesburg. REFERENCES Bransford, J., Brown, A., & Cocking, R. (2000). How

People Learn: Brain, Mind, and Experience & School. Washington, DC: National Academy Press.

Bruner, J. S. (1975). The ontogenesis of speech acts. Journal of Child Language, 2, 1-40.

Dickson, S. V., Chard, D. J., & Simmons, D. C. (1993). An integrated reading/writing curriculum: A focus on scaffolding. LD Forum, 18(4), 12-16.

Felder R.M; Reaching the second Tier: Learning and teaching styles in college science education; College science teaching, 23(5), 286-290(1993)

Kolb, D.A., Experiential Learning: Experience as the Source of Learning and Development, Prentice- Hall, Englewood Cliffs, N.J., 1984.

Lawrence, G., “A Synthesis of Learning Style Research Involving the MBTI,” J. Psychological Type 8, 2-15 (1984).

Lev Vygotsky, L.S. (1962). Thought and language. Cambridge, MA: MIT Press. (Original work published 1934)

McCaulley, M.H., “Psychological Types of Engineering Students—Implications for Teaching,”Engineering Education, vol. 66, no. 7, Apr. 1976, pp. 729-736.

McDowell l; Effective Teaching and Learning on Foundation and Access Courses in Engineering, Science and Technology; European Journal of Engineering Education; Volume20, Issue 4, 1995, pages 417 – 425

Olson, J. and Platt, J. (2000). The Instructional Cycle. Teaching Children and Adolescents with Special Needs (pp. 170-197). Upper Saddle River, NJ: Prentice-Hall, Inc.

Rosenshine, B. & Meister, C. (1992). The use of scaffolds for teaching higher-level cognitive strategies. Educational Leadership, 49(7), 26-33.

Vygotsky, L. S. (1978). Mind in society. Cambridge, MA:

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Gandure Jerekias, Kommula Venkata Parasuram, & Venu Madhav Kuthadi

Harvard University Press.

AUTHORS

Jerekias Gandure is a Lecturer in the Department of Mechanical Engineering of the University of Botswana. He received his MEng in Industrial and Manufacturing Engineering (MSOM) from the National University of Science &Technology, Zimbabwe. He has more than 10 years of industrial

experience and 3 years in academia. He specialises in Manufacturing Systems and Operations Management, Biofuels and has interest in engineering education. [email protected]

Kommula Venkata Parasuram is a Lecturer in the Department of Mechanical Engineering at the University of Botswana. He received his Master of Engineering in Computer Integrated Manufacturing from the Anna University, Chennai, India. For the past 12 years he has been working

at universities mainly in India, Malaysia and Botswana.

He specializes in engineering Production / Manufacturing/ and teaches courses in this area. He has particular interest in engineering education. [email protected]

Name: Dr Venu Madhav Kuthadi Qualifications: B.Tech (CSE), M.Tech (SE), PhD (CS). Experience: Working as Senior Lecturer at University of Johannesburg, South Africa, for the past 12 years he has been working at various organizations at India, Botswana and South Africa. Area of

Expertise: Data Mining, Databases, Software Engineering, Networks and Engineering Education. [email protected]

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22


PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges

Chien-Yun Dai*, Wan-Fei Chen**, Mu-Hui Lai***, & Yu-Hsi Yuan**

*Department of Applied Electronics Technology, Taiwan Normal University, Taipei, Taiwan

**Department of Industrial Education, Taiwan Normal University, Taipei, Taiwan *** Department of Electronics Engineering, Neihu Vocational High School, Taipei, Taiwan

Abstract In this research through the implement of an experimental teaching, the creative teaching elements were adapted into the professional courses in the experimental group duly, on the other hand, traditional teaching model was adapted into the control group. ANCOVA and MANCOVA were used for comparison analysis, and Kappa and K-S were adopted for teaching results on consistency analysis. According to the result we have discovered that (1) Students in the experimental group are better in the areas such as flexibility, originality, and practical than students in the control group; (2) These four creative teaching elements are capable of increasing the interest and efficiency in learning. By the experimental teaching results and efficiency analysis, to establish electrical and electronic professional course integrated creative thinking teaching model named PDSE.

Keywords: creativity, electrical and electronic, integrated creative thinking teaching, PDSE teaching model INTRODUCTION Creativity promotes the innovation of science, the creation of art, groundbreaking inventions, and the achievements in new social programs (Sternberg & Lubart, 1999). Human thinking and creative thinking remains sustainable in development and expanding, especially in an age of high technology and information. Future generations will deem us ignorant and barbaric, just as how we look at the people in the caverns of time (Torrance, 1995). Apparently this shows how crucial creativity is to the influence on technology and information, as well as the major power on advances in human society. The export value of Taiwan electrical and electronic-related industries (which includes electronic components manufacturing industries, electrical equipment manufacturing industries, computer, electronics, and IT manufacturing, etc.) accounts for 53.42% of the whole industry in 2010, for it reveals the fact that the output value of electrical and electronic-related industries occupies half of the output value of the whole industry in Taiwan, which is the most crucial industry in Taiwan as well (Small and Medium Enterprise Administration of Ministry of Economic Affairs, 2011). In the year of 2010, the number of electrical and electronic-related major students accounts for 47.02% of the entire student population in technology-related majors in colleges (Department of Statistics of Ministry of Education, 2011), which is a significant field for nurturing talents. Owing to the lack of creativity teaching-related researches on electrical and electronic majors in colleges in Taiwan, the research determines to establish electrical and electronic technology creativity integrated teaching model by adding creative thinking elements into professional courses through an experimental teaching, and explore its results and effects. In accordance with the analyzed

result that the teaching and learning efficiency had been verified and proved that the performance of PDSE teaching model was better than traditional teaching model for creativity training in this research.

The speech on the subject of “Creativity” given by Guildford in a seminar held by American Psychological Association in 1950, has successfully drawn the attention of the academic circle to think highly of creativity, and the led it to a vigorous development later in time (Kaufman & Sternberg, 2007). Although the composed of creativity is an important and absorbing research subject, however, it is hard to define (Runco, 2007). For many years, the researcher has been trying to offer specific instructions on creativity despite numerous creativity-related control tables, models, and tests were used, the researcher still could not provide a complete explanation of the human brain on creativity (Fisher & Williams, 2004). Early in the literature about creativity, it was discussed basing on “4P” points of views (Rhodes, 1961) including process (Gallagher, 1975), person (Sternberg & Lubart, 1995), product (Amabile, 1997; Sternberg & Lubart, 1996), and environment press/place (Amabile, Conti, Coon, Lazenby & Herron, 1996; Mellou, 1996; Oldham & Cummings, 1996). However, if you want to make a general description of creativity, the researcher then believes creativity is a combination of inventive ability, output ability, and divergent thinking ability, which takes advantages of psychometric methods on estimation of fluency, flexibility, and originality to comprehend the ability of creativity.

Technology is defined as “a set of entities or mental processes which transforms inputs into useful outputs” (Hulin & Roznowski, 1985). Such process should include a physical process after a task is completed (such as physical activities, operations on physical facilities, etc.), and an abstract mental process (such as knowledge,

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thoughts, or mathematic formulas, etc.) (Greenberg & Baron, 1995).

In summary, creativity as a particular in a specific field, makes use of the knowledge and skills in the related areas to generate a process comprised of originality, practical, and appropriateness of products. Similarly, electrical and electronic creativity as a particular in the related areas, makes use of electrical and electronic-related knowledge and skills to generate a process comprised of originality, practical, and appropriateness of products. Comments on creativity Most of the creativity study currently is still based on psychometric written tests, and creativity test indicators continue to use the divergent thinking established by Guilford as its foundation (Cropley, 2000). In education in context, divergent thinking test is the most popular creativity testing skill (Plucker & Runco, 1998). General creative products emphasize the “originality” and “usefulness” (Mayer, 1999). In the field of innovation in science and technology or design, the actual application and practice of knowledge are extraordinarily valued, as well as known as the practical of the product (Jhu, 2005). The researcher used fluency, flexibility, originality, and practical as the score indicators of the electrical and electronic creativity test (Farivar, 1985), which was also the basis of the experimental teaching test on effectiveness. Traditional teaching model Traditional teaching model tends to be partial to one-way mode of teaching model with emphasis on direct teacher explanation, while students are put into a situation where they can listen only. In this learning environment, students tend to become self-enclosed, and lack of flexibility (Syu, Lai, Chen, Jhan & Jhang, 2008). Although the didactic lecture has been so for quite some time, but there should be a set of standard process and procedure. For this reason, a three-stage methods implementation is recommended as the following:

1. Initial summary – the preparation for teaching, including confirming the teaching objectives, gathering materials, composing lesson plans, and analyzing students’ characteristics;

2. Detailed information – to enhance student motivation to learn, generalize a conclusion of clear concepts, complete the instructions of activities in accordance of the content;

3. Final summary – to summarize and integrate the concept and summary of the teaching content, and provide suggestions on course activities (Hoover, 1982).

Therefore, referred to the three-stage methods model proposed by Hoover, the researcher determines to establish electrical and electronic professional course integrated creative thinking teaching model.

Fused teaching model Stemberg and Lubart proposed that cultivating creativity

should use the traditional education measures as the foundation, and further create an environment conductive to the development of creativity to break through the conservative and closed traditional school atmosphere which puts too much emphasis on school regulations and academic (Sternberg & Lubart, 1996). A fused curriculum is a method of combining two or more subjects and merging them into one new subject for which is no longer a sole subject, but an integrated one. However, it is different than the methods to infuse a subject matter into the curriculum (Ben-Peretz, 1975). Curriculum infusion is the process of examination by educators, and the results are later delivered and emerged into an integrated curriculum (Dai, 2004). The research has adopted the infusion curriculum methods by adding the creativity thinking teaching model elements into the electrical and electronic courses. Storytelling teaching model Ever since the language was created by mankind, storytelling has been existed (Geringer, 2003). The definition of storytelling is the conveying of a true or fictitious event in accordance with its sequences or the relations between causes and effects, to reach the state of knowledge transaction (Thomas & Tommy, 1997). Compared to a series of numbers or reports, stories are always able to initiate people’s curiosity, expectations, explorations, surprises, or both positive and negative emotions, etc. thus it is as well very effective on teaching performances ranging from enhancing teaching effectiveness to developing creative thinking ability of students; storytelling teaching model has become one of the most important teaching approaches (Parkin, 2004). In brief, in order to stimulate students’ interest in learning and enrich the curriculum content for the purpose of students motivation and creativity enhancement, integrating storytelling methods into the teaching model is one of the major elements in the creativity thinking teaching model. Creative thinking teaching model Creative thinking involves focuses of originality and value (Sternberg, 2003). A common creativity thinking teaching model usually contains creative problem solving models (Treffinger, Isaksen & Dorval, 1994; Treffinger, Isaksen & Dorval, 2000), Guilford’s theoretical model of the teaching of creative thinking (Guilford, 1967, 1977), and William’s model for creativity thinking in teaching (Williams, 1970, 1972). The researcher believes by adapting William’s cognitive affective interactive teaching model, teachers will be able to exercise the strategies of creative thinking in the area of various subjects and help forming a creativity thinking teaching model by enhancing students’ cognitive, affective, and behavioral abilities. This is the most suitable indicator to establish an electrical and electronic course integrated creativity thinking teaching model in the research of establishing an electrical and electronic course integrated creativity thinking teaching model.

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Chien-Yun Dai, Wan-Fei Chen, Mu-Hui Lai, & Yu-Hsi Yuan

RESEARCH DESIGN Procedure The researcher has developed four creative teaching elements by conferring teaching model-related literature and by holding four experts meeting and inviting experts and instructors in the field of electrical and electronic to join the discussion on the development of establishing and constructing an integrated creativity skill curriculum and teaching model. Before the experimental teaching proceeded, students of the experimental and control groups were given electrical and electronic creativity skill pre-test separately. By eliminating deviations of the designed system and increasing the accuracy of experiment, the scores of the creativity skills among experimental groups were not influenced by the covariant quantity (Jamieson, 2004). The official experimental teaching was put into practice in accordance with the electrical and electronic course integrated creativity thinking teaching model unit, and after a period of twelve weeks of a semester experimental teaching, students of the control group were resulted in not performing creativity thinking teaching, while students in the experimental group were resulted in performing activities including story creation, invention introduction, creative skills teaching, and practice list fulfillment, etc. in class according to the designed and established professional subject. Before the end of semester, students of experimental and control groups were again given the post test on creative skills, and were used to determine the final scores of the creative skills of students in the experimental group. The data obtained from the experimental teaching then used such statistical method for the further analysis and test. Methods a. Quasi-experimental design

The researcher used the quasi-experimental teaching design to study the independent variables based on the experimental variables in the experimental teaching and creativity thinking test; control variables including the confounding factors generated by the experimental teaching, such as teaching methods, curriculum, teaching units, teaching media, etc. were taken into control to form unity. As for the Quasi-experimental design, the researcher decided not to use the nonequivalent pretest-posttest designs considering the experimental condition in the real situation. The researcher was determined to sample electrical and electronic major students from two schools which are alike in academic achievements, and used the pre-test of electrical and electronic creative skills to eliminate the covariate variables before the procedure of the experimental teaching. In the process of experimental teaching, instructors has integrated the creation story (as in Appendix 2), creation introduction (as in Appendix 3), creativity skills and practice list (as in Appendix 4) created and designed by the research group into the experimental teaching of electrical courses of the experimental group, and at last, used the

same test for the post test as the dependent variables for the data information analysis.

b. Research tools

i. Experimental teaching questionnaire The researcher used the effectiveness tracking

questionnaire to investigate the effectiveness of the factors including teachers partaking in the experimental teaching, four creative teaching elements, and teaching time, etc. The content validity of the effectiveness tracking questionnaire was designed and reviewed by experts in the fields of education and creativity, and college instructors who participated in experts meetings. Topic items covered responses of teachers and students towards four creative teaching elements and opinions about integrated teaching time. Data obtained from teachers’ and students’ opinions was used to analyze the consistency, and such result was adopted as indicators of the research on establishing an integrated creative thinking teaching model.

ii. Electrical and electronic creativity test The electrical and electronic creativity test was

published in TSSCI that research tools with an overall good reliability and validity have become the exclusive well-developed electrical and electronic creativity testing tool in Taiwan. The test was applied with the pre-test and post-test, and creativity scoring indicators were comprised of fluency, flexibility, originality, and practical.

Samples In judgmental sampling, the researcher chose the departments of electronic engineering major in electronic devices, systems and applications, internship of electronic engineering and related majors from two universities which are alike in students’ academic achievements in Taiwan. Students (age around 19 to 20 without basic notion of electronic devices, systems and applications) from each school were divided into two experimental groups (n=65, female=7, male=58) for experimental teaching and two control groups (n=66, female=3, male=63) for non-experimental teaching. As for the effectiveness tracking questionnaire, the researcher used a random sampling of approximately 1/3 of students from each experimental group (n=24) and all the instructors participating within the experimental group (n=7) for the fulfillment of the experimental teaching effectiveness tracking questionnaire designed by the researcher. Data analysis Data information of the experimental teaching was determined by adopting multivariate statistical analysis such as MONCOVA and ANCOVA for data calculation and analysis of the examination of the effectiveness of the experimental teaching. Data obtained from the experimental teaching effectiveness tracking questionnaire used Kappa coefficient and Kolomogorov-Smimov one sample test for the

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consistency analysis, and through the discussions over the analysis results among the research group, an integrated creative thinking teaching model suitable for electrical and electronic professional courses was as concluded. RESULT Analysis of the differences in the tests of electrical and electronic creativity

Based on the scores from the test, the electrical and electronic creativity test was used as the covariance variable, the teaching model was used as the independent variable, and the electrical and electronic creativity post-test was used as the dependent variable for the analysis of one-way ANCOVA to understand the differences between both groups on the performance of electrical and electronic creativity test. Analyzed result shown in Table 1.

Table 1 Abstract table of the average and standard deviation of different teaching models of electrical and electronic creativity pre-test and post-test

Pre-test Post-test Group Indicators

M SD M SD Fluency 5.14 3.60 5.42 3.12 Flexibility 2.52 1.23 2.83 1.40 Originality 0.88 1.10 1.57 1.80

Experimental group

(N=65) Practical) 11.46 7.62 12.48 8.98 Fluency 3.33 2.38 4.58 3.30 Flexibility 1.83 0.90 1.91 0.97 Originality 1.02 1.45 0.77 1.48

Control group (N=66)

Practical 7.23 5.02 8.33 4.36

Different teaching models of electrical and electronic creativity test contained remarkable effects (Wilks’ λ=.887, p<.01), data information shown as in Table 2. After a further one-way analysis of variance, we have discovered that there are remarkable differences among

students’ flexibility (F(1,125)=4.62, p<.05), originality (F(1,125)=4.11, p<.05), and practical (F(1,125)=4.03, p<.05) over different teaching models; but no remarkable difference was found on fluency (F(1,125)=.14, p>.05).

Table 2 Abstract table of MONCOVA of different teaching models of electrical and electronic creativity test

Source df SSCP MANCOVA

Wilks’λ ANCOVA

(F) 1.50 2.56 4.36 4.13 7.04 11.36

Between (Teaching method)

1

16.44 28.04 45.23 180.17

.887**

Fluency Flexibility Originality Practical

0.14 4.62*4.11*4.03*

1388.00 201.91 114.15 444.35 84.45 345.71

Within 125

2382.38 463.64 824.47 5589.51

* p<.05; ** p<.01

Table 3 shows the performance of students of the experimental group on flexibility (M-2.57) is better than students of the control group (M=2.17); performance of students of the experimental group on originality

(M-1.50) is better than students in the control group (M=.85); performance of students of the experimental on practical (M=11.69) is better than students of the control group (M=9.11).

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Table 3 Comparison table of the average after the adjustment of different teaching models of electrical and electronic creativity

Experimental Group Control Group Item M Std. Error M Std. Error

Result

Fluency 5.11 0.44 4.88 0.43 n.s.

Flexibility 2.57 0.13 2.17 0.12 experimental group>control group

Originality 1.50 0.22 0.85 0.22 experimental group> control group

Practical 11.69 0.87 9.11 0.87 experimental group> control group

Experimental teaching effectiveness tracking questionnaire The experimental teaching effectiveness tracking questionnaire was developed by the researcher for the confirmation of effectiveness of the experimental teaching. By examining the results of both teachers and students’ scores on the questionnaires, it is helpful to review the opinions of both groups. The questionnaire was comprised of fifteen questions for the first twelve questions were addressed using 5-point Likert type scale; questions from the thirteenth to the fifteenth were surveys of the opinions about the best timing to integrate the four creative teaching elements into the experimental teaching. The following are the different points of views of both groups for consistency testing as a whole and individually.

a. Consistency test of Kappa coefficient

In order to determine whether teachers and students agree with each other’s opinion or not, the researcher used Kappa coefficient for the consistency test as a whole. Table 4 shows the corresponding frequency of opinions from both groups about the fifteen questions.

Table 4 Distribution table of the corresponding frequency of opinions from teachers and students

Students’ reactions 1 2 3 4 5

Summary

1 1 0 0 0 0 1 2 0 4 0 0 0 4 3 0 0 2 0 0 2 4 0 0 0 4 0 4

Teachers’ reactions

5 0 0 0 2 2 4 Total 1 4 2 6 2 15

After calculation, the Kappa coefficient of the consistency of opinions of teachers and students towards the experimental teaching was .826, which K value was larger than 0.7 and Z value that reached the remarkable standard was 6.064. This tells us that opinions of both groups have reached a consistency. Data information is shown in Table 5.

Table 5 Distribution table of the Kappa consistency test

Kappa Standard Error Z value Significant

Kappa .826 .114 6.064 .000 Valid items 15

The formula for Kappa value:

f(K)=[P(A)-P(E)] / [1-P(E)] Equation (1)

Where f(K): Kappa coefficient

P(A): Percentage frequency of opinion consistency in fact

P(E): Percentage frequency of expectation

A procedure for calculation is as the following:

1. The percentage frequency when opinions of teachers and students towards the experimental teaching are in consistency: P(A)=13/15=0.8667.

2. The percentage frequency of expectation when teachers and students towards the experimental teaching are in consistency: P(E)=0.2356 (details shown in Table 6).

Table 6 The percentage frequency of expectation when teachers and students towards the experimental teaching are in consistency

Answering options Margin frequency P(E)

5 (1/15) × (1/15) 0.0044 4 (4/15) × (4/15) 0.0711 3 (2/15) × (2/15) 0.0178 2 (6/15) × (4/15) 0.1067 1 (2/15) × (4/15) 0.0356

Total: 0.2356

Opinions of the effectiveness in consistency from teachers and students towards the integration of four creative teaching elements such as “creation story” to the experimental teaching were obtained after the consistency test of the Kappa coefficient. Following up,

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the research continued to work on the consistency test of opinions about individual questions from both groups.

b. K-S the sole sample of the consistency test

In order to determine the consistency of opinions from

both teachers and students towards the experimental teaching effectiveness tracking questionnaire, the researcher has calculated the consistency test of the opinions from both groups separately. Analyzed result shown in Table 7.

Table 7 Collective table of the sole sample of opinions of the consistency test

Teacher group Student group Item No. M SD K-S Test Z Value M SD K-S Test Z Value

1. 4.57 .535 1.512* 4.54 .509 2.654*** 2. 4.57 .535 1.512* 4.42 .504 2.858*** 3. 2.14 .900 1.386* 1.79 .588 2.041*** 4. 1.86 .378 2.268*** 1.83 .482 2.245*** 5. 4.14 .378 2.268*** 4.04 .464 2.041*** 6. 4.57 .535 1.512* 4.42 .504 2.858*** 7. 4.57 .535 1.512* 4.46 .509 2.654*** 8. 2.14 .900 1.386* 1.83 .565 2.041*** 9. 1.86 .378 2.268*** 1.79 .415 3.878*** 10. 4.43 .535 1.512* 4.08 .504 2.041*** 11. 4.14 .378 2.268*** 4.08 .282 4.491*** 12. 4.14 .378 2.268*** 4.17 .381 4.082*** 13. 1.29 .488 1.890** 1.17 .381 4.082*** 14. 2.71 .488 1.890** 2.88 .537 2.041*** 15. 2.71 .488 1.890** 2.96 .550 1.837**

* p<.05; ** p<.01

According to the K-S sole sample test, the z value of both groups have reached the remarkable standard and passed the consistency test, which means opinions of both teachers and students on the integrating the four creative teaching elements such as “creation story” into the experimental teaching is in consistency. According to the answer data of the experimental teaching effectiveness tracking questionnaire via the consistency test based on the Kappa coefficient, and the fact that the sole sample test of each question has reached the remarkable standard, which indicates opinions of the effectiveness of both groups on integrating four creative teaching elements such as “story creation” into the experimental teaching is in consistency.

By looking at the results of the consistency test, the opinions obtained from the questions in the questionnaire attached in Appendix 1 are as following:

1. To present “creation story” in class can increase the learning interest of students on integrated creativity thinking teaching model, and the content of “creation story” is better off to involve any sources related to electrical and electronic professional courses and contemporary technology;

2. To present “creation introduction” in class is helpful in increasing the learning interest of students on integrated creativity thinking teaching model, and the inventions are better off to relate to electrical and electronic professional courses and contemporary technology;

3. It is helpful to increase the learning interest of students on integrated creativity thinking teaching model through applying the skills of “creativity skills” such as brainstorming skills in class;

4. To use “practice list” is helpful in increasing the learning interest of students on integrated creativity thinking teaching model;

5. The first five minutes of each class is the best timing to present “creation story”;

6. The best timing to present “creation introduction” is after the presentation of an unit;

7. To spend eleven to twenty minutes on “creativity skills” application is the best.

Electrical and electronic professional course in colleges integrated creative thinking PDSE teaching model According to the results analyzed from the experimental teaching effectiveness tracking questionnaire, the researcher has proposed the electrical and electronic professional course integrated creative thinking teaching model which are suitable for colleges in Taiwan (shown in Figure 1). The teaching model is integrated with crucial teaching procedures: preparation, development, synthesis, and evaluation, and formed into a complete teaching model comprised of PDSE orders. Key points of activities in each stage are described in the following:

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Fig. 1 Infused creativity thinking into professional course teaching model

a. P: Preparation

Teachers should being preparing the four creative teaching elements during the stage of preparation. Divide students into 5 – 6 groups in the beginning of the semester, and present basic creativity skill practices such as brainstorming skills to enhance the skillfulness.

b. D: Development

Teachers should spend 3 – 5 minutes to present “creation story” to enhance the motivation during the stage of development. After presenting the content of the unit, integrate “creation introduction” into the teaching model, which helps students to understand the principle application of the subject and promotes new creative ideas.

c. S: Synthesis

Teachers should pass out practice lists to each group for group discussion during the stage of synthesis, which can help students to think creatively and generate new ideas. Have each group share their results to the class at the end, which helps students to learn and interact extensively.

d. E: Evaluation

Teachers should present quiz after completing the unit to assure the learning situation of students during the stage of evaluation. Then teachers are supposed to provide comments for each group’s performance with emphasis on the characteristics and innovation of each group.

SUGGESTIONS AND CONCLUSION In view of the results of the consistency test via ANCOVA of Quasi-experimental design and the experimental teaching effectiveness tracking questionnaire, the researcher has come to a conclusion as the following:

a. The performance of the flexibility, originality, and practical of the experimental group on electrical and electronic creativity is better than the control group.

By a further analysis of the experimental teaching

effectiveness tracking questionnaire, the analysis showed that by integrating the four creative teaching elements such as “creation story”, “creation introduction”, “creativity skills”, and “practice list” into the experimental teaching, helps generate scope (which is the flexibility) and depth (which is the originality) of thinking, and as well gives consideration to the practical of the inventions.

b. The purpose of fluency test was focus on counting the quantity of ideas that generated by students but the analysis result of “fluency” was not reached the significant level. Sternberg and Lubart (1995) argued that individual creativity can be cultivated or discovered through a systematically approach, consider the analysis result, therefore, the fluency could be improved by add more creativity training (e.g. brainstorming) through extracurricular activities.

c. Remarkable effectiveness is found regarding the four creative teaching elements

The result of the analysis showed that by adding creative teaching elements such as “creation story”, “creation introduction”, “creativity skills”, and “practice list” into the class, the opinions of both teachers and students are in consistency. It proved that integrating the four creative teaching elements into the teaching model can increase the learning interest of students and enhance the teaching efficiency.

Suggestions on applying PDSE teaching model a. The collected or edited contents of “creation story”

and “creation introduction” should relate to electrical and electronic professional courses and contemporary technology.

b. Present “creation story” within the first five minutes of the class, which can increase the learning motivation of students.

c. The best timing to present “creation introduction” is after the explanation of the content of a unit. In other words, once students are familiar with the basic concepts, adding “creation introduction” helps they understand the theories and concepts of the unit, and such advantage can be extended to practical applications.

d. Use 11 – 20 minutes to present “practice list” (not too long or too short). On one side, it helps students achieve the effectiveness through practices within an appropriate period of time; on the other side, it would not affect the presentation of the regular curriculum.

e. In the integration of creative thinking PDSE teaching model into the electrical and electronic professional courses in colleges, creative teaching elements such as “creation story”, “creation introduction”, “creativity skills”, and “practice list” should be taken into consideration for the greatest effect.

f. Due to this experimental design was focus on professional subject but the material was developed along with course, hence, the experimental process

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was under the limitation of time pressure without add too much activities regarding creativity training. A further research can focus on the assessment of fluency improvement by add more creativity training (e.g. brainstorming) through extracurricular activities.

REFERENCES Amabile, T. M. (1997). Entrepreneurial creativity

through motivational synergy. Journal of Creativity Behavior, 31, 18-26.

Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Herron, M. (1996). Assessing the work environment for creativity. Academy of Management Journal, 39, 1154-1184.

Ben-Peretz, M. (1975). The concept of curriculum potential. Informal Section-Curriculum Theory Network, 5, 151-159.

Cropley, A. J. (2000). Defining and measuring creativity: Are creativity tests worth using? Roeper Review, 23, 72-79.

Dai, S. M. (2004). The interpretation and research study on integrating sex education into Chinese literature curriculum in the junior high school. Graduate Institute of Education, National Kaohsiung Normal University, unpublished Master’s thesis, Kaohsiung, Taiwan.

Department of Statistics of Ministry of Education (2011). Data Base of the information of every school. ‘The year of 2010 – 2011’, 19 October 2011, http://www.edu.tw/files/site_content/b0013/99_sdata.xls.

Farivar, S. H. (1985). Developing a cooperative learning program in an elementary classroom: Cooperative study of innovative and tradition middle teaching and learning strategies. LA: University California.

Fisher, R. ,& Williams, M. (2004). Unlocking creativity: Teaching across the curriculum. London: David Fulton Publishers.

Gallagher, J. J. (1975). Teaching the gifted child (2nd Ed.), Boston, MA: Allyn & Bacon.

Geringer, J. (2003). Stories from the Heart: For Parents Particularly. Childhood Education, 79, 175-76.

Greenberg, J., & Baron, R. A. (1995). Behavior in organizations. NJ: Prentice-Hall.

Guilford, J. P. (1967). The nature of human intelligence. NY: McGraw-Hill.

Guilford, J. P. (1977). Way beyond the IQ. Buffalo, NY: Creative Education Found.

Hoover, W. (1982). Language and literacy learning in bilingual education: Preliminary report, Cantonese site analytic study. Austin, TX: Southwest Educational Development Laboratory. (ED 245 572).

Hulin, C. L., & Roznowski, M. (1985). Organizational technologies: Effects on organizations’ characteristics and individuals’ responses. In L. L. Cummings, & B. M. Staw (Eds.), Research in organizational behavior (Vol. 7, pp. 39-86). Greenwich, CT: JAI Press.

Jamieson, J. (2004). Analysis of covariance (ANCOVA)

with difference scores. International Journal of Psychophysiology, 52, 277 –283.

Jhu, Y. Y. (2005). Quantitative development of the elements that influence the innovation on science and technology of elementary students. Journal of National Taiwan Normal University: Scientific education 50, 29-54.

Kaufman, J. C., & Sternberg, R. J. (2007). Creativity. Change, July/August, 55-58.

Mayer, R. E. (1999). Fifty years of creativity research. In R. J. Sternberg (Ed.), Handbook of creativity (pp.449-460). Cambridge: Cambridge University Press.

Mellou, E. (1996). The two-conditions view of creativity. Journal of Creative Behavior, 30, 126-149.

Oldham, G. R., & Cummings, A. (1996). Employee creativity: Personal and contextual factors at work. Academy of Management Journal. 39, 607-634.

Parkin, M. (2004). Tales for change: using storytelling to develop people and organizations. London: Kogan Page.

Plucker, J. A., & Runco, M. A. (1998). The death of creativity measurement has been greatly exaggerated: Current issues, recent advances, and future directions in creativity assessment. Roeper Review, 21, 36-39.

Rhodes. M. (1961). An analysis of creativity. Phi Delta Kappan, 42, 305-310.

Runco, M. A. (2007). Creativity theories and themes: Research, development, and practice. Oxford, UK: Elsevier Academic Press.

Small and Medium Enterprise Administration of Ministry of Economic Affairs (2011). White Paper of Small and Medium Enterprise. Taipei: Ministry of Economic Affairs.

Sternberg, R. J. & Lubart, T. I. (1995). Defying the crowd: Cultivating creativity in a culture of conformity. NY: Free Press.

Sternberg, R. J. & Lubart, T. I. (1995). Investing in creativity. American Psychologist, 51(7), 677-688.

Sternberg, R. J. & Lubart, T. I. (1996). Investing in creativity. American Psychologist. 51, 677-688.

Sternberg, R. J. & Lubart, T. I. (1999). The concept of creativity: Prospects and paradigms, In R.J. Sternberg (Eds.). Handbook of Creativity (pp.3-15). NY: Cambridge.

Sternberg, R. J. (2003). Creative thinking in the classroom. Scandinavian Journal of educational Research, 47, 325-338.

Syu, H. G., Lai, M. H., Chen, D. G., Jhan, B. Y., & Jhang, T. M. (2008). Editorial of Quantitative Chart of the electrical and electronic creativity test. Chinese Electronic Periodical Services, 55, 407-434.

Thomas, T., & Tommy, O. (1997). Stories on spot: introducing students to impromptu storytelling. Childhood Education, 73, 154-155.

Torrance, E. P. (1995). Why Fly? A Philosophy of Creativity. Norwood, NJ: Ablex Publishing.

Treffinger, D. J., Isaksen, S. G., & Dorval, K. B. (1994). Creative Problem Solving: An overview. In M. A. Runco (Ed.), Problem finding, problem solving, and

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creativity. NJ: Ablex Publishing. Treffinger, D. J., Isaksen, S. G., & Dorval, K. B. (2000).

Creative Problem Solving-An Introduction (3rd Ed.). Buffalo: Center for Creative Learning, Creative Problem Solving Group.

Williams , F. E. (1970). Classroom ideas for encouraging thinking and feeling (2nd Ed.). NY: D.O.K. Publishers, Inc.

Williams , F. E. (1972). Encouraging creative potential. NY: Educational Technology Publications.

Appendix 1 Experimental teaching effectiveness tracking questionnaire

【For teacher use only】 Note: All items were not multiple choices.

No. Items

Strong Agree

Agree

Natural

Disagree

Strong Disagree

1. To present “creation story” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

2. The content of “creation story” should be related to electrical and electronic subjects, and the units in the professional courses.

□ □ □ □ □

3. The content of “creation story” should be related to electrical and electronic subjects, but not necessary to the units in the professional courses.

□ □ □ □ □

4. The content of “creation story” does not need to relate to the electrical and electronic subjects.

□ □ □ □ □

5. Whether the content of “creation story” is related to the electrical and electronic subjects or units in the courses or not, it is better to be related to the contemporary technology.

□ □ □ □ □

6. To present “creation introduction” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

7. The content of “creation introduction” should be related to electrical and electronic subjects, and the units in the professional courses.

□ □ □ □ □

8. The content of “creation introduction” should be related to electrical and electronic subjects, but not necessary to the units in the professional courses.

□ □ □ □ □

9. The content of “creation introduction” does not need to relate to the electrical and electronic subjects.

□ □ □ □ □

10. Whether the content of “creation introduction” is related to the electrical and electronic subjects or units in the courses or not, it is better to be related to the contemporary technology.

□ □ □ □ □

11. To apply brainstorming skills in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

12. To use “practice list” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

13. When is the best time to present “creation story” in class? (Use an example of a total of 300 minutes with 6 lesson units)(1) 5 minutes in the beginning of the first class (2) 6 – 1o minutes in the beginning of the first class (3) 11 – 15 minutes in the beginning of the first class (4) Any time in the first class (5) Any time in any class

14. When is the best time to present “creation introduction” in class? (Use an example of a total of 300 minutes with 6 lesson units)(1) After the presentation of “story creation” (2) Before the presentation of the unit in the curriculum (3) After the presentation of the unit in the curriculum (4) Any time in the first class (5) Any time any class

15. How much time should be spent for the presentation of “practice list” and “creativity skills”? (Use an example of a total of 300 minutes with 6 lesson units) (1) Within 5 minutes (2) 5 – 10 minutes (3) 11 – 20 minutes (4) 20 – 30 minutes (5) More than 30 minutes

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【For student use only】 Note: All items were not multiple choices.

No. Items Strong A

gree

Agree

Natural

Disagree

Strong Disagree

1. To present “creation story” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

2. The content of “story creation” should be related to electrical and electronic subjects, and the units in the professional courses.

□ □ □ □ □

3. The content of “creation story” should be related to electrical and electronic subjects, but not necessary to the units in the professional courses.

□ □ □ □ □

4. The content of “creation story” does not need to relate to the electrical and electronic subjects. □ □ □ □ □5. Whether the content of “creation story” is related to the electrical and electronic subjects or units

in the courses or not, it is better to be related to the contemporary technology. □ □ □ □ □

6. To present “creation introduction” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

7. The content of “creation introduction” should be related to electrical and electronic subjects, and the units in the professional courses.

□ □ □ □ □

8. The content of “creation introduction” should be related to electrical and electronic subjects, but not necessary to the units in the professional courses.

□ □ □ □ □

9. The content of “invention introduction” does not need to relate to the electrical and electronic subjects.

□ □ □ □ □

10. Whether the content of “creation introduction” is related to the electrical and electronic subjects or units in the courses or not, it is better to be related to the contemporary technology.

□ □ □ □ □

11. To apply brainstorming skills in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

12. To use “practice list” in class helps increase the learning interest of students on the integrative creative thinking teaching model activities.

□ □ □ □ □

13. When is the best time to present “creation story” in class? (Use an example of a total of 300 minutes with 6 lesson units) (1) 5 minutes in the beginning of the first class (2) 6 – 1o minutes in the beginning of the first class (3) 11 – 15 minutes in the beginning of the first class (4) Any time in the first class (5) Any time in any class

14. When is the best time to present “creation introduction” in class? (Use an example of a total of 300 minutes with 6 lesson units)(1) After the presentation of “story creation” (2) Before the presentation of the unit in the curriculum (3) After the presentation of the unit in the curriculum (4) Any time in the first class (5) Any time any class

15. How much time should be spent for the presentation of “practice list” and “creativity skills”? (Use an example of a total of 300 minutes with 6 lesson units) (1) Within 5 minutes (2) 5 – 10 minutes (3) 11 – 20 minutes (4) 20 – 30 minutes (5) More than 30 minutes

32


Appendix 2 Creation Story Creation Story Data card Serial No.: EES102 Invention: FAX machine Inventor: Alexander Bain The history of FAX technology is fascinating and strange for it was not invented with great intentions on purpose, but a result derived from inventions on digital clocks. In the year of 1842, the Scottish inventor Alexander Bain was working on a timepiece idea, pendulum that could be generated by electricity. During the process, he had discovered and covered the use of the clocks to synchronize the movement of two pendulums so that a message could be scanned line by line, and printed remotely. In the light of such idea, he added a magnetic needle on the pendulum as the windscreen wiper, and made a data board which was generated by another clock; there were text and graphic images on the paper. He put a piece of thermal paper on the data board in the receiving end, and when the indicator stated scanning the paper, black dots began to appear on the paper. When the pendulum moved by electromagnetic impulses, the indicator then touched the connected dots on the data board, an electric current would then occurred. When the data board propelled by the clock movement, it would slightly move upward and transformed the graphic images on the board into the receiving end. This way, the graphic images were kept and recorded on the thermal paper. This is the most primitive fax machine in the history. Data source: I Tian Publications (2007). 100 greatest science inventions of all time. Taipei: Tomorrow International Books.

Appendix 3 Creation Introduction

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Appendix 4 Practice list

AUTHORS

Chien-Yun, Dai Dr. Dai is a professor in the Department of Industrial Education at National Taiwan Normal University. In recent years, his main research areas are technological teacher education, curriculum and instructional designs in new

technology, ICT educational and certification. He received Ph.D. from National Taiwan Normal University and Post Doctor study at University of California, Irvine (UCI). His professions are Software Engineering, System Programming, Artificial Intelligence, and electronic CKT

design. His research field focus on Networking Management, Data mining, E-Learning, electronic control, and E-Learning & E-Testing. His career position list is: Associate Professor of Department of AET and IE, Chairman of Chinese Computer Education Association. His honor list is: Top Ten Talents of Youth Award in Taiwan (1983), Top Ten Talents of Information Award in Taiwan (1984), Bronze Medal of World-wide Invention Show in Swiss (1982), Golden Medal of World-wide Invention Show in New York (1982), Silver Medal of World-wide Invention Show in Brussels (1983). He published academic articles on international journals especially on information technology, information education, vocational education, electronic engineering education, and also the reviewer of internal academic journals from 1980.

34


Mu-Hui, Lai Dr. Lai received the Ph.D. from National Taiwan Normal University in 2009. His backgrounds are focused on majored in Information Technology Education and Electric & Electronic Education. He served as a director in computer center, Nei-Hu Vocational High School,

Taipei, Taiwan. His main fields include information technology education, data mining, electronic design automation, and creativity education etc. In 2009 and 2010 Dr. Lai instructed students and won twice the International School CyberFair PLATINUM AWARD which is verified by Kim’s Record. He published for over 20 expertise books including operating system, data mining, electronic design automation, creativity education, computer auxiliary design and computer education.

Wen-Fei, Chen She received Master degree of Administration from Shih Hsin University. Currently she is the doctoral candidate of Industrial Education, Nation Taiwan Normal University. She is the Assistant Vice President, R&D Taipei Office of Hanlin Publish Co., Ltd. in Taiwan. Her

professional field focus on textbook research and

development, marketing strategy, media communication, information education.

Yu-Hsi, Yuan He received Master degree of Administration from Southern Taiwan University. Currently he is the doctoral candidate of Industrial Education, Nation Taiwan Normal University. He is the instructor of Information Management of Hwa Hsia Institute of Technology, Human Resource Development of Ching Kuo

Institute of Health and Management, Cardinal Tien College of Healthcare & Management in Taiwan. His professional field focus on human resource management and development, research methodology, statistical analysis, information education, industrial hygiene and safety, vocational education. He is the executive editor of Quarterly Journal of Vocational Education. Corresponding Author e-mail: [email protected]

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36

Int. j. technol. eng. educ. Copyright 2011, ATEEM 2011, Vol.8 No.1

Authors Index

Rajiv Bhatt 1 Fuzzy Logic based Student Performance Evaluation Model for Practical Component of Engineering Institution Subjects

Dr Darshana Bhatt 1 Fuzzy Logic based Student Performance Evaluation Model for Practical Component of Engineering Institution Subjects

Wan-Fei Chen 23 PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges

Chien-Yun Dai 23 PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges

Ching-Ho Huang 9 The Study of Construction of the Core Competencies in the Precision Casting Industry

Gandure Jerekias 17 Pros and Cons of Effective Training for Engineering Personnel

Chin-Guo Kuo 9 The Study of Construction of the Core Competencies in the Precision Casting Industry

Venu Madhav Kuthadi 17 Pros and Cons of Effective Training for Engineering Personnel

Mu-Hui Lai 23 PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges

Kommula Venkata Parasuram

17 Pros and Cons of Effective Training for Engineering Personnel

Huey-Jen Tsay 9 The Study of Construction of the Core Competencies in the Precision Casting Industry

Yu-Hsi Yuan 23 PDSE (Preparation, Development, Synthesis, Evaluation): A Developed Creative Thinking Teaching Model for Department of Electrical and Electronic in Taiwan Colleges

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Submission Guidelines International Journal of Technology and Engineering Education (IJTEE) is a biannual journal published in every June and December. Papers to be considered for inclusion in the IJTEE should be submitted directly to the Association of Taiwan Engineering Education and Management (ATEEM). Original papers, not previously published, will be considered for publication on the basis of referee reports from at least two independent international referees. Authors of papers accepted will be required to transfer copyrights to the publisher. All contributions must be in English and adhere to the guidelines published in Publication Guidelines of the American Psychological Association format (APA 5th Edition). Papers will be fully edited and English corrected to ensure standard English form and expression. The publisher reserves the right not to return original manuscripts submitted for publication. Contributions in the form of a paper should comprise a PDF file and an MS Word file on a CD diskette suitable for an IBM PC. In preparing papers, authors are kindly asked to strictly adhere to the instructions for authors. INSTRUCTIONS FOR AUTHORS The ATEEM aims to produce a volume of the International Journal of Technology and Engineering Education with as uniform an appearance as possible and it is therefore requested that you conform to these instructions when preparing your article. These instructions are following APA style. 1. A PDF file and an MS WORD file must both reach ATEEM.

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International Journal of Technology and Engineering Education Process of Paper Evaluation

I. Papers will be evaluated by reviewers come from International Journal of Technology

Engineering Education publication committee and related experts/scholars. II. While receiving submitted paper, editor consults with publication committee about papers’

fields. III. Each academic paper will be evaluated by two reviewers（double-blind）, reviewers will write

down their opinions in the comment paper. IV. International Journal of Technology Engineering Education will send the reviewers’ comment

to the papers’ authors and express accept, modify or refuse paper. V. The process of paper evaluation as following:

Second Reviewer

5 4 3 2 1 Process of Evaluation

Refuse (under 69)

Modify & Re-evaluate

(70-74)

Modify (75-79)

Accept (80-89)

Accept (above 90)

5 Refuse (under 69) Refuse Refuse Third

Reviewer Third

Reviewer Third

Reviewer

4 Modify &

Re-evaluate (70-74)

Refuse Modify (re-evaluate)

Modify (re-evaluate)



3 Modify (75-79)

Third Reviewer

Modify (re-evaluate) Modify Modify Modify

2 Accept (80-89)

Third Reviewer

Modify (re-evaluate) Modify

Modify (will be

published)

Modify (will be

published)

First Reviewer

1 Accept (above 90)

Third Reviewer

Modify (re-evaluate) Modify

Modify (will be

published) Publish

* If two reviewers opinions are too much difference (up to 15 points), the paper will be evaluated by third reviewer.

* Publication committee have right to determine accept, modify or refuse by reviewers comments.

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International Journal of Technology and Engineering Education

Topic: Field: □ Engineering Education □ Vocational Education □ Technological Education

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