Scholarly article on topic 'Formulation in Evaluating the Technical Skills of Engineering Graduates'

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Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — Yuzainee Md Yusoff, Mohd. Zaidi. Omar, Azami Zaharim, Azah Mohamed, Norhamidi Muhamad

Abstract This paper present a formula to measure technical skills of engineering graduates in the hiring process for the post of engineer in Malaysia. The coefficient obtained for the equation was gathered from the survey on employers’ preference for engineering employability skills. Responses were obtained from a random sample of 301 employers of the Malaysian engineering industries located in Kelang Valley. These industries comprise of 12 nature of business. Although, the initial purpose of the survey was to assess the perception and the expectation of the employers on employability skills, the research also addressed a number of main questions regarding the level of requirement of engineering employability skills according to the needs of their industries. This study focus on technical skills as the skills is significant skills in engineering professionals. The findings show that the weight obtained from the level of requirement of skills initiate a coefficient for the equation of employability score. The paper suggests a pertinent tool for employers and undergraduates to measure technical skills performed by engineering graduates. Furthermore, employers who are facing a problem to have a quality evaluation for the interview process might find this method provides useful evidence for the good evaluation.

Academic research paper on topic "Formulation in Evaluating the Technical Skills of Engineering Graduates"

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Social and Behavioral Sciences

Procedia - Social and Behavioral Sciences 60 (2012) 493 - 499

UKM Teaching and Learning Congress 2011

Formulation in Evaluating the Technical Skills of Engineering

Graduates

Yuzainee Md Yusoff , Mohd. Zaidi Omarb, Azami Zaharimb'*, Azah Mohamedb,

Norhamidi Muhamadb

aCollege of Engineering, Universiti Tenaga Nasional (UNITEN), Malaysia bCentre for Engineering Education Research, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia

ELSEVIER

Abstract

This paper present a formula to measure technical skills of engineering graduates in the hiring process for the post of engineer in Malaysia. The coefficient obtained for the equation was gathered from the survey on employers' preference for engineering employability skills. Responses were obtained from a random sample of 301 employers of the Malaysian engineering industries located in Kelang Valley. These industries comprise of 12 nature of business. Although, the initial purpose of the survey was to assess the perception and the expectation of the employers on employability skills, the research also addressed a number of main questions regarding the level of requirement of engineering employability skills according to the needs of their industries. This study focus on technical skills as the skills is significant skills in engineering professionals. The findings show that the weight obtained from the level of requirement of skills initiate a coefficient for the equation of employability score. The paper suggests a pertinent tool for employers and undergraduates to measure technical skills performed by engineering graduates. Furthermore, employers who are facing a problem to have a quality evaluation for the interview process might find this method provides useful evidence for the good evaluation.

© 2011PublishedbyElsevierLtd. Selection and/orpeer reviewedunderresponsibilityofthe UKMTeachingand LearningCongress 2011

Keywords: Technical skills; engineering graduates; employers; employability score

1. Introduction

The employability skill of a graduate portrays graduate's attributes, knowledge, capabilities and abilities often unobservable. However, new graduates have to demonstrate their mastery of employability skills. Furthermore, leaders in government and organisations wanted the newly graduates be able to 'know-how' to solve real-world problems. In view of that, higher education provider need to ensure that all graduates are qualified to succeed in work and life in this new era of the global economy (Zaharim et al. 2010). As pointed out by Zaharim et al. (2010), the higher education provider, employers and government need to have a common understanding on the set of skills

* Corresponding author. Tel:+6-03-8921-6466; fax:+6-03-8925-2546. E-mail Address:azami.zaharim@gmail.com.

1877-0428 © 2011 Published by Elsevier Ltd. Selection and/or peer reviewed under responsibility of the UKM Teaching and Learning Congress 2011 doi: 10.1016/j.sbspro.2012.09.413

should be owned by engineering graduates. Hence, few studies had been conducted to determine the set of employability skills that suit industries locally (DEST 2002; Zaharim et al. 2009; Zaharim et al. 2010) and a numbers of frameworks represent the set of employability skills were proposed. Zaharim et al. (2010) proposed a framework of engineering employability skills for Malaysian namely Malaysian Engineering Employability Skills (MEES). The framework shows an integrated of technical and nontechnical skills that comply with the requirement of accreditation body and employers needs. However, standing in the way of integrating such skills is about measurement of the skills. The measuring skills are difficult, and different definitions and methods have been used (Borghans et al. 2001). Measuring a student's knowledge is discrete facts but measuring a student's skills and ability to apply knowledge is subjective. Elena Silva (2009) reported that these types of higher-order skills were argued could be measured in reliable, cost-effective, or scalable ways.

Therefore, this study intent to develop a formulation to measure technical skills based on the framework presented in MEES (Zaharim et al. 2010) and the finding in a study conducted by Yuzainee et al. (2011).

2. Literature review

Employability skills emphasises the need for graduates to create their own profile to prepare for today's highly competitive market place for graduate jobs. The employability skills refer to the required skills to acquire, keep and doing well on a job (Robinson 2000). Skill is an ability to perform a specific task (DEST, 2006) and employability is about having the capability to gain initial employment, maintain employment and obtain new employment if required (Hillage, 1998). Liz Reisner explained that there is a way to measure some of these skills (Elena, 2009). He said that "it might be possible to assess decision-making skills by analyzing the middle school participants' selection of high-quality college preparatory high schools". A report by Elena Silva, a Senior Policy Analyst, revealed that the skills "can be measured accurately and in a common and comparable way" (Elena, 2009). Studies on employability skills differed with regards to direct or indirect measurement depend on occupational title, qualification and level of education, years of work experience and numbers of training (Ashton & Green, 1996). Measuring the employability skills is subjective and depends on the perception of evaluators. Evaluator(s) will give score depend on his perception and expectation on the skills performed by candidates. The employability scores are determined by the particular combination of soft skills, technical skills and personal knowledge of the individuals.

3. Methodology

The data used in this study is a part of the data collected from engineering industries in the Kelang Valley, Malaysia funded UKM's research on identifying and observing employability skills of engineering graduates in Malaysia. The survey focuses on technical and soft (nontechnical) skills in an engineering discipline (Yuzainee et al. 2010). In this paper, the focus is on data that were obtained from questionnaires regarding the level of requirement of technical skills. The responses were collected from a random sample of 500 potential employers of engineering graduates around Kelang valley, Malaysia in September 2009 to January 2010. There were fifty attributes used to examine the required employability skills as valued by employers when hiring fresh engineering graduates. These fifty attributes grouped into ten skills that are communication skills (EES1), teamwork (EES2), lifelong learning (EES3), professionalism (EES4), problem solving and decision-making skills (EES5), Competency (EES6), knowledge of science and engineering principles (EES7), knowledge of contemporary issues (EES8), engineering system approach (EES9) and competent in specific engineering discipline (EES 10) (Zaharim et al. 2010). The technical skills selected for statistical testing in this study are the technical skills required by employers (DEST 2002; Lee 2003; Hassan et al. 2006; Zaharim et al. 2009; Zaharim et al. 2010). Based on previous study, the tangible skills such as EES6, EES7, EES8, EES9 and EES10 are defined as technical skills and the other are soft skills (DEST 2002; Lee 2003; Hassan et al. 2006; Zaharim et al. 2009).

Personal interview and questionnaire were the instrument used. About 337 out of 500 engineering's employers responded and only 301 usable responses were analyzed. The respondents were limited to high-rank officers in the companies to assure accurate results. The data collected was analyzed using basic statistical method to present profile of respondents involved in this study. They are attached to six levels of position in the organisation, and twelve types of industry's nature of business as presented in Table 1. The highest numbers of respondents are from field of Engineered Materials (18.3%) followed by Built Environment (14.6%) and Communications and IT (14%).

Table 1. Profile of respondents based on position in company and nature of business.

Nature Chairman Chief Officer Director Manager Senior Engineer Others Total %

N1 0 0 0 2 3 1 6 2.0

N2 0 0 0 3 1 2 6 2.0

N3 0 1 0 7 10 1 19 6.3

N4 0 0 1 4 8 0 13 4.3

N5 2 1 4 18 15 2 42 14.0

N6 0 0 0 2 1 0 3 1.0

N7 0 0 1 9 12 0 22 7.3

N8 0 0 1 9 11 2 23 7.6

N9 0 2 1 25 21 6 55 18.3

N10 0 0 0 16 14 0 30 10.0

N11 0 1 1 20 21 1 44 14.6

N12 0 1 6 13 15 3 38 12.6

Total 2 6 15 128 132 18 301

% 0.7 2.0 5.0 42.5 43.9 6.0 100

N1 - Healthcare and Social; N2 - Leisure and Entertainment; N3 - Education; N4 -Commerce,Trade and Finance; N5 -Communications and IT; N6 - Defence and Security; N7 - Transport; N8 - Agriculture and Food; N9 - Engineered Materials; N10 -Energy and Natural Resources; N11 - Built Environment; N12 - Consulting.

The respondents answered to level of requirement for each skill using a five-point Likert-scale. The scale assigned as "1" indicates "Extremely Not Required", "2" indicates "Not Required", "3" indicates "Slightly Required", "4" indicates "Required" and "5" indicates "Extremely Required". The weight, Normalised Skill Weight (NSW), index and level of requirement of skills were analyzed using the multi-attribute value technique (MAVT) adapted from Fishburn (1967) dan Keeney and Raiffa (1976). The result has been presented in EDUC0N2011 as shown in Appendix. This paper is an extension of the study presented by Yuzainee et al. (2011) with the intention to propose a new mathematical formula to give score for technical skills performed by engineering graduates. The technical skills have been identified in the study presented by Zaharim et al. (2010).

4. Data Analysis and Computation of Results

The Normalised Skills Weight (NSW) of five technical skills (coded EES6-EES10) calculated using the weight of skills obtained from a report presented by Yuzainee et al. (2011). The NSW determined by Equation 1, adopted from Fishburn (1967) dan Keeney and Raiffa (1976). To evaluate the score for engineering job applicant, Equation 2 was derived using NSW.

NSWn x 100 (1)

Total Employability Score = ^ x Sn ) (2)

NSW - Normalised Skill Weight Xn - Weight of skill

Cn - Coefficient (Value of Normalised Skill Weight) Sn - Score of skill obtain by applicant (Mn /50) i - Number of skills ( i = D5) n - nth term

For this study, the calculation using Equation 2 illustrated as following:

Total Employability Score = (20.65) Sj + (20.36) S2 + (19.83) S3 + (19.46) S4 + (19.69) S5

Table 2 shows an example of employability score obtained by three applicants using Equation 2 compared to percentage and average score.

Table 2. Example of Score for three applicants

Skills Code Weigh t NSW Full marks Candidate 1 Candidate 2 Candidate 3

C ^n Mn Mn Mn Mn

1. Competency EES6 0.1011 20.65 50 20.65 30 12.4 25 10.3 45 18.6

2. Knowledge EES7 0.0997 20.36 50 20.36 35 14.3 30 12.2 40 16.3

of science

engineering

principles

3. Knowledge EES8 0.0971 19.83 50 19.83 45 17.8 35 13.9 35 13.9

contemporary

issues

4. Engineering EES9 0.0953 19.46 50 19.46 40 15.6 40 15.6 30 11.7

system

approach

5. Competent in EES 10 0.0964 19.69 50 19.69 25 9.8 45 17.7 25 9.8

specific

engineering

discipline

0.4885 100 250 100 175 69.9 175 69.7 175 70.3

Percentage 100 70 70 70

Average 50 35 35 35

5. Results and Discussion

The evaluators of job interview judge the candidate according to a different level of preference (eg: 1-50 points). According to Ryan and Hughes (1997) and agreed by Vick and Scott (1998) that the level of preference should be realistic and informative to make it competitive choices. In addition, the range of levels of preference should provide enough variation. The positive level of preference should be used because it does not seem appropriate for

candidates with negative levels of preferences. Table 2 shows the example of employability score for five technical skills owned by three candidates. Total mark, percentage, and mean score have equal values for these three candidates though they have different abilities. However, using Equation 2, the equation for employability score gives different value for these three candidates based on the NSW, the coefficients of each skill. The coefficient shows that Competency (20.65) is the skill with the strongest effect on the candidates, and it considered being most influential and required technical skills for the candidates. Based on the coefficients of NSW, Knowledge of science and engineering principles (20.36) ranked as second, and Knowledge of contemporary issues (19.83) as third required skills, while Competent in specific engineering discipline (19.69) and Engineering system approach (19.46) are considered relatively least important for the candidate of engineer professionals. The example illustrated in Table 2 shows that Candidate 3 is the first choice with score 70.3, followed by Candidate 1 as a second choice with 69.9 to succeed in a job interview. Candidate 3 shows better competencies in Competency and Knowledge of science and engineering principles compared to the other two candidates. This makes Candidate 3 a better chance to get the job.

6. Conclusions

Previous studies on employability skills confirmed the significant of technical and nontechnical skills (DEST 2002; Lee 2003; DEST 2006; Hassan et al. 2006; Zaharim et al. 2009; Zaharim et al. 2010; Yuzainee et al. 2011). Technical skills are close related to skills required in engineering sector. Well-performed skills are the selling values/attributes that employers looking for in the engineering entry level jobs. This study contributes to the discussion on the measurement of technical skills during the job interview in engineering sector. The finding suggests that graduates need to demostrate their competency better than the other four technical skills. Employers in the engineering firm seem to be more interested in graduates who have high level of competency and sufficient knowledge of science and engineering principles. These results can be expected as engineers need to be competent in their technical work. Engineering graduates need to realise that having a good degree is no longer sets them apart from other candidates in today's job hunting. Graduates must be able to market themselves by performing good employability skills especially technical skills.

Acknowledgement

We would like to thank UKM for providing the research grant (UKM-GUP-NBT-08-26-097 and UKM-OUP-NBT-28-131/2011).

References

Ashton, D. N., & Green, F. (1996). Education, training and the global economy. Cheltenham: Edward Elgar.

Borghans, L., Green, F., & Mayhew, K. (2001). Skills measurement and economic analysis: An introduction. Oxford Economic Papers, 53(3), 375-384.

DEST. (2002). Employability skills for Australian industry: literature review and framework development. Employability skills for the future, a report by the Australian Chamber of Commerce and Industry and the Business Council of Australia for the Department of Education, Science and Training, Canberra.

DEST. (2006). Employability skills from framework to practice, an introductory guide for trainers and assessors. A report by the Australian Chamber of Commerce and Industry and the Business Council of Australia for the Department of Education, Science and Training, Canberra.

Elena Silva. (2009). Measuring skills for 21st-Century learning. Phi Delta Kappan, 90(9), 630-634. Fishburn, P.C. (1967). Methods of estimating additive utilities. Management Science, 13(7).

MOHE. (2006). Ministry of Higher Education, Malaysia. The future of engineering education in Malaysia. Department of Institutions of Higher

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Education and Employment (DfEE), London. Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives: Preferences and value tradeoffs. New York: Wiley.

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canterbury.ac.nz/ herdsa03/pdfsref / Y1111. pdf. Ryan, M., & Hughes, J. (1997).Using conjoint analysis to assess women's preferences for miscarriage management. Health Economics, 6, 261273.

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Appendix: Level Of Requirement Of Each Employability Skills

Skills Criteria No. Skills and Criteria Mean Weight Index Rank

EES1 Communication skills 4.25 0.1048 1.0000 [1]

1.1 Speak in clear sentences 4.39 0.2063 1.0000 1

1.2 Give clear direction 4.26 0.2002 0.9704 4

1.3 Listen and ask question 4.27 0.2006 0.9726 3

1.4 Present ideas confidently and effectively 4.37 0.2053 0.9954 2

1.5 Understand and speak English and other languages 3.99 0.1876 0.9096 5

EES2 Teamwork 4.24 0.1043 0.9961 [2]

2.1 Function effectively as an individual 4.25 0.2005 0.9659 3

2.2 Understand the role in a group 4.40 0.2076 1.0000 1

2.3 Function effectively in a group as a team member 4.36 0.2058 0.9917 2

2.4 Accept and provide feedback in constructive and considerate manner. 4.20 0.1981 0.9545 4

(Forming, storming, performing, adjourning)

2.5 Work in a group with the capacity to be a leader. 3.98 0.1880 0.9060 5

EES3 Lifelong Learning 4.01 0.0988 0.9431 [7]

3.1 Recognize the need to undertake lifelong learning 4.06 0.2024 1.0000 1

3.2 Possess and acquire the capacity to undertake lifelong learning 4.01 0.1999 0.9877 3

3.3 Engage in lifelong learning 4.03 0.2008 0.9918 2

3.4 Set their personal learning targets. 3.98 0.1983 0.9795 5

3.5 Plan in achieving their learning goal(s) 3.98 0.1986 0.9811 4

EES4 Professionalism 4.11 0.1013 0.9672 [3]

4.1 Understand the social responsibilities. (human factors and social issues) 4.07 0.1980 0.9599 4

4.2 Understand the cultural and global responsibilities. (Awareness on 4.02 0.1953 0.9466 5

cultural and nature surrounding)

4.3 Understand the environmental responsibilities. (Aware of environmental 4.08 0.1985 0.9623 3

needs)

4.4 Commit to professional responsibilities. (Be professional as an Engineer). 4.24 0.2063 1.0000 1

4.5 Commit to ethical responsibilities. (Be accountable for their actions) 4.15 0.2019 0.9788 2

EES5 Problem solving and decision making skills 4.11 0.1011 0.9655 [4]

5.1 Undertake problem identification. (identify problem in work place) 4.05 0.1974 0.9658 4

5.2 Implement problem solving. (use experiences to solve problem) 4.09 0.1994 0.9754 3

5.3 Apply formulation and solution. (use science, mathematics or technology 4.05 0.1974 0.9658 5

to solve problem)

5.4 Be creative, innovative and see different points of view in solving 4.20 0.2044 1.0000 1

problems.

Skills Criteria No. Skills and Criteria Mean Weight Index Rank

5.5 Identify the root cause of the problems. 4.14 0.2015 0.9857 2

EES6 Competency 4.11 0.1011 0.9654 [5]

6.1 Use the necessary techniques for engineering practice. 3.99 0.1943 0.9403 5

6.2 Use the necessary skills for engineering practice. 4.04 0.1966 0.9513 4

6.3 Use the modern engineering tools and software. 4.19 0.2039 0.9866 2

6.4 Work toward quality standards and specifications. 4.24 0.2067 1.0000 1

6.5 Assemble equipment following written directions. 4.07 0.1984 0.9599 3

EES7 Knowledge of science and engineering principles 4.05 0.0997 0.9520 [6]

7.1 Continue to acquire knowledge of sciences and engineering fundamentals. 3.93 0.1941 0.9547 5

7.2 Apply the knowledge of engineering fundamentals 4.08 0.2015 0.9911 3

7.3 Select and use proper tools and equipments for particular job/task. 4.12 0.2033 1.0000 1

7.4 Access, analyse and apply skills and knowledge of science and engineering. 4.09 0.2022 0.9943 2

7.5 Understand principles of sustainable design and development. 4.03 0.1989 0.9781 4

EES8 Knowledge of contemporary issues 3.94 0.0971 0.9273 [8]

8.1 Continue learning independently in the acquisition of new knowledge, skills and technologies. 4.02 0.2040 0.9877 3

8.2 Use information technologies. (Computers, networks and electronic) 4.07 0.2066 1.0000 1

8.3 Use communication technologies in the knowledge-based era. 3.98 0.2018 0.9771 4

8.4 Use computing technologies. 4.05 0.2052 0.9935 2

8.5 Read news paper 3.60 0.1824 0.8830 5

EES9 Engineering system approach 3.87 0.0953 0.9097 [10]

9.1 Utilize a systems approach to design operational performance 3.90 0.2018 0.9807 4

9.2 Utilize a systems approach to evaluate operational performance. 3.92 0.2024 0.9841 3

9.3 Design systematically 3.95 0.2040 0.9916 2

9.4 Analyse engineering design 3.98 0.2057 1.0000 1

9.5 Demonstrate a knowledge and understanding of engineering system for management and business practices. 3.60 0.1861 0.9045 5

EES10 Competent in specific engineering discipline 3.91 0.0964 0.9199 [9]

10.1 Continue to acquire in-depth technical competence in a specific engineering discipline. (electrical, highway, structure etc) 3.89 0.1987 0.9774 3

10.2 Apply technical skills in a specific engineering discipline effectively 3.97 0.2031 0.9992 2

10.3 Design and conduct experiments 3.88 0.1985 0.9765 4

10.4 Analyse and interpret data 3.98 0.2033 1.0000 1

10.5 Apply knowledge in multidisciplinary engineering 3.84 0.1965 0.9665 5

Total requirement of employability skills 40.6