Factor analysis of english communication competency among Malaysian technology undergraduates

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This paper aimed to determine factors influencing English communication competency among Malaysian university undergraduates from technology departments at Universiti Tun Hussain Onn Malaysia (UTHM).

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 808–817, Article ID: IJMET_10_03_084 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed FACTOR ANALYSIS OF ENGLISH COMMUNICATION COMPETENCY AMONG MALAYSIAN TECHNOLOGY UNDERGRADUATES Sarala Thulasi Palpanadan, PhD Centre for Language Studies Universiti Tun Hussein Onn Malaysia ORCID # 0000-0001-9140-3937 Iqbal Ahmad, PhD Faculty of Education, University of Malakand, Pakistan Venosha K.Ravana Faculty of Language and Linguistics Universiti Malaya ABSTRACT This paper aimed to determine factors influencing English communication competency among Malaysian university undergraduates from technology departments at Universiti Tun Hussain Onn Malaysia (UTHM). A survey was administered to a random sample of 102 undergraduates. Factor analysis was applied to determine the underlying dimensions that influence English competency among the students. The findings revealed four critical factors: mother tongue interference, lack of confidence, lack of practice, and home environment. Thus, students need to be encouraged to communicate in English at the university and home to provide wider language practice opportunities to master communication skills in English and perform well in the technology courses. Key words: English competency, exploratory factor analysis, communication skills, technology courses. Cite this Article: Sarala Thulasi Palpanadan, Iqbal Ahmad, Venosha K. Ravana, Factor Analysis of English Communication Competency among Malaysian Technology Undergraduates, International Journal of Mechanical Engineering and Technology 10(3), 2019, pp. 808–817. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3 http://www.iaeme.com/IJMET/index.asp 808 editor@iaeme.com
Sarala Thulasi Palpanadan, Iqbal Ahmad, Venosha K. Ravana 1. INTRODUCTION The two areas of English language and technology are inseparable where they complement each other very much. Having a good grasp of English language and technology skills facilitate the learning skills to obtain more knowledge (Ahmadi, 2018). English is becoming popular day by day all over the world including the technology field. It is used as an international lingua franca (Ahmad, 2016). English is an important language to have better job employment opportunities in all fields (Suryasa et al., 2017; Swales & Feak, 2004). Thus, mastering English in our daily life has become essential (How et al., 2015; McKay, 2002). Meanwhile, technology also plays a crucial role in bringing about changes in people’s perception, association and style of lives (Salehan, Kim & Lee, 2018). Technology is a tool utilized by everyone, especially engineers to uphold the development and improvement of the world so that everyone can benefit from it. Technological determinism theory (TDT) supports the idea that the development of a nation based on its societal and cultural values depend on its progression of technology (Howells, 1997). Thus, it is very important to study the challenges of English instruction in technology integrated courses among the Malaysian undergraduates who are pursuing technology and engineering based courses at the universities. Malaysia is a multi-race country and Malay is the national language. Malay language is often used as the language of instruction, administration and employment in government and non-government sectors (Mahir et al., 2007). Malay is the language that is used most frequently for communication among people who are not proficient in English in the Malaysian context. English is usually used for some specific occasions and events at English Departments in government institutions and some private sectors. As a matter of fact, many Malaysians still use Malay widely in their daily communication without having to worry about their incompetency in English as it is easily understood by the majority. Apparently, the Malaysian education system has promoted bilingualism and multilingualism school system with three different mediums as instruction, such as Malay, Tamil and Mandarin language mediums. This is to let Malaysians to have a chance to learn their own mother tongue according to their own races (Benraghda et al., 2017). Various languages have benefits for Malaysian students and allow them to get further understanding about the importance of English language (How et al., 2017). However, as English is still not widely used in Malaysia, this might affect the mind sets of the people that English language is not the most important language and therefore, they need not focus in using English in their daily lives (Heriansyah, 2012; Pandian, 2002). Consequently, people may gradually ignore the importance of English language in their daily activities. This is a very serious matter that has to be investigated and discussed as many graduates scored good grades in the examination but they tend to face difficulties in finding jobs due to the lack of fluency in English language (Kirkpatrick, 2012; Nunan, 2003). Employers claim that the graduates’ lack of communication skills was one of the reasons of the increasing unemployment rate in Malaysia (Shanmugam, 2017). In addition, high unemployment rate among Malaysia graduates in the private sector is often attributed to lack of English proficiency and communication skills (Ting et al., 2017). In order to ensure that people can communicate well in English language, several continuous processes need to be involved in their daily routine (Rashid & Hashim, 2008; Thirusanku & Yunus, 2014). Effective communication and understanding are among the important processes that are involved in peoples’ daily lives which can lead to good grasp of English. In addition, university students and the surrounding community should consciously work towards improving the ability to speak in English fluently. Therefore, this research was carried out at UTHM to determine the reasons that deter effective English communication http://www.iaeme.com/IJMET/index.asp 809 editor@iaeme.com
Factor Analysis of English Communication Competency among Malaysian Technology Undergraduates skills among the undergraduates of technology courses. It was perceived that the local students seldom communicated with each other in English due to their own preferences within the campus compound. Students often used their own mother tongue to communicate with friends from the same races and use Malay language to communicate with friends from different races. English language was neither their favourite choice nor a case for stern learning. Thus, there is a strong reason to study and overcome this phenomena. 2. PROBLEM STATEMENT Many studies were conducted on how the integration of technology could facilitate the English language learning (Ince, 2014; Ahmadi, 2018). However, not many studies show how English language could facilitate the technology based courses at universities. As a matter of fact, many researchers stated that the local university students in Malaysia are still grappling with to communicate effectively in English (Musa et al., 2012; Ting et al., 2010). In addition, many engineering and information technology graduates often remain jobless in the job market due to the poor command of English language and lack of confidence to converse in English (Ibrahim & Mahyuddin, 2017). The low English language proficiency among Malaysian graduates is a serious issue that needs to be discussed and addressed. The current research was conducted to determine the factors influencing English communication skills among the undergraduate students from three technology departments at UTHM Malaysia. The Malaysian universities are offering various technology courses where most of the lectures are conducted in English. Furthermore, the notes and resources are mostly available in English Language. Therefore, as much as the mastery of technology is concerned, the undergraduates’ challenges and ability to process all the information in English has to be addressed as well. This study is important so that the problem in communicating in English among the students of the technology courses can be identified that can help the universities to produce professional and competent graduates in future. 3. RESEARCH OBJECTIVES The main objectives of this study are:  To explore factors influencing English communication among the technology students at the university.  To suggest strategies for the promotion of English language communication skills among the technology students at universities. 4. METHODS 4.1. Participants This exploratory study was conducted to explore potential factors influencing English language communication skills among the students taking the technology courses and programs at UTHM. The sample consisted of 102 students selected from three departments: Faculty of Computer Science and Information Technology, Faculty of Technical and Vocational Education and Faculty of Technology Management and Business. A self- developed 20 items questionnaire was distributed among the participants for data collection. The first part of the questionnaire consisted of demographic features including races and gender and second part items concerning English language speaking skills. http://www.iaeme.com/IJMET/index.asp 810 editor@iaeme.com
Sarala Thulasi Palpanadan, Iqbal Ahmad, Venosha K. Ravana 4.2. Reliability and Validity The questionnaire was tested for internal consistency using Cronbach’s alpha. The content and face validity was checked by expert review and literature review. The statements of the questionnaire were refined grammatically based on the feedback from three language experts. The questionnaire was piloted on 30 respondents. Based on the inter item consistency analysis, only those items which were above .40 were retained (Hinkin, 1995). The internal consistency test showed an alpha of .75 for nineteen items which is considered very good as an alpha value (Hinkin, 1995). The reliability of the questionnaire items was confirmed through scale statistics and item statistics. Table 1: Scale Statistics Mean Variance Std. Deviation N of Items 63.71 94.958 9.745 19 Table 1 shows the scales statistics indicating a total mean 63.71, variance 94.95 and standard deviation 9.74 for 19 items questionnaire. Table 2: Item-Total Statistics Scale Mean if Scale Variance Corrected Cronbach's No Statements Item Deleted if Item Deleted Item-Total Alpha if Item Correlation Deleted 1 Fear of mistakes and criticism 60.31 75.664 .733 .704 2 Lack of English speaking platform 60.77 94.167 .631 .770 3 Lack of effective learning strategies 60.28 76.539 .727 .706 4 Lack of English background 60.43 33.884 .596 .799 5 Family background or peer influence 60.17 93.460 .435 .760 6 Lack of practice in using English 60.21 73.762 .778 .697 7 Lack of using English in daily routine 60.32 78.541 .672 .713 8 Mother tongue interference 59.95 87.629 .441 .742 9 No interest in English language 60.33 77.336 .729 .707 10 Weak grammar usage 60.43 78.018 .659 .712 11 Introvert personality 60.47 99.230 .435 .784 12 Lack of confidence 60.63 77.529 .581 .791 13 Poor academic performance 60.36 45.655 .562 .787 14 Job opportunities in future 60.47 80.144 .500 .726 15 Unable to give presentation in class 61.43 88.488 .569 .746 16 Difficult to communicate with others 60.47 76.546 .777 .703 17 Interpersonal relationships 59.67 88.691 .559 .742 18 Cannot go overseas for further study 60.47 76.546 .777 .703 19 Speech anxiety 59.67 88.691 .559 .742 Table 2 shows that all items are above .40 meeting the criterion set for retaining items in the questionnaire. 4.3. Factor Analysis of English Competency among Students Exploratory factor analysis (EFA) was used to identify factors influencing the English language competency among the technology students. The EFA is an analytical process and data reduction that transforms statistical data into linear combination of variables. It is a useful and meaningful statistical method applied to combine large number of data into small factors with minimal loss of information (O'Leary-Kelly & Vokurka, 1998). The Kaiser- Meyer-Olkin (KMO) measure and Bartlett’s Test of Sphericity were used for determining the sample size. Table 3: KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .961 Approx. Chi-Square 15785.116 Bartlett's Test of Sphericity df 210 Sig. .000 http://www.iaeme.com/IJMET/index.asp 811 editor@iaeme.com
Factor Analysis of English Communication Competency among Malaysian Technology Undergraduates Table 3 indicates the KMO and Bartlett’s Test of Sphericity for the current data. The analysis shows the KMO was .96 with Bartlett’s Test of Sphericity significant at .000. This indicated the sample adequacy for conducting the factor analysis. Table 4: Communalities No Statements Initial Extraction 1 Fear of mistakes and criticism 1.000 .800 2 Lack of English speaking platform 1.000 .735 3 Lack of effective learning strategies 1.000 .785 4 Lack of English background 1.000 .642 5 Family background or peer influence 1.000 .622 6 Lack of practice in using English 1.000 .885 7 Lack of using English in daily routine 1.000 .615 8 Mother tongue interference 1.000 .687 9 No interest in English language 1.000 .786 10 Weak grammar usage 1.000 .703 11 Introvert personality 1.000 .435 12 Lack of confidence 1.000 .587 13 Poor academic performance 1.000 .458 14 Job opportunities in future 1.000 .564 15 Unable to give presentation in class 1.000 .697 16 Difficult to communicate with others 1.000 .649 17 Interpersonal relationships 1.000 .779 18 Cannot go overseas for further study 1.000 .493 19 Speech anxiety 1.000 .779 Extraction Method: Principal Component Analysis Table 4 shows that the communalities reveal the amount of variance of all the variables individually. The size of the communality works as an index to assess the amount of variance in an individual variable that accounts for the factor solution. The commonalties are higher ranging from 0.435 to 0.800 as shown in Table 4 above. Table 5: Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative% Total % of Variance Cumulative % 1 8.241 43.376 43.376 8.241 43.376 43.376 2 1.883 9.912 53.288 1.883 9.912 53.288 3 1.378 7.253 60.541 1.378 7.253 60.541 4 1.097 5.772 66.313 1.097 5.772 66.313 5 .923 4.856 71.169 6 .860 4.526 75.695 7 .757 3.982 79.677 8 .697 3.667 83.344 9 .610 3.211 86.555 10 .483 2.543 89.098 11 .457 2.403 91.500 12 .380 2.002 93.503 13 .327 1.722 95.225 14 .280 1.475 96.700 15 .231 1.213 97.914 16 .174 .917 98.831 17 .142 .749 99.579 18 .080 .421 100.000 1.618 8.51 19 100.000 016 016 Extraction Method: Principal Component Analysis. http://www.iaeme.com/IJMET/index.asp 812 editor@iaeme.com
Sarala Thulasi Palpanadan, Iqbal Ahmad, Venosha K. Ravana Table 5 indicates that four factors were extracted based on Eigenvalues greater than 1 using principal component analysis. The first component (mother tongue interference) accounts for 43.37 of the total variance. It is the first influencing factor. The second component (lack of confidence) accounts for 9.91 percent of the total variance being the second influencing factor. The third component (lack of practice) accounts for 7.25 percent of the total variance being the third influencing factor. The fourth component (home environment) accounts for 5.77 percent of the total variance being the fourth influencing factor. The entire four components together accounted for 66.31 percent of the total variance in the scale. Figure 1 Figure 1 also shows the four factors extracted through principal component method (PCA). It shows that the curve tailing off after the four factors. Thus, it allows for retaining four factors as a result of factor analysis. Table 6 Rotated Component Matrix No Component 1 2 3 4 .870 .826 .870 .530 .607 .925 .766 .869 .770 .605 .485 .605 .650 .503 .701 .670 .613 .592 .642 http://www.iaeme.com/IJMET/index.asp 813 editor@iaeme.com
Factor Analysis of English Communication Competency among Malaysian Technology Undergraduates Table 6 reveals the rotated component matrix showing the factor loadings for each of the variables on the main components based on varimax rotation. It also shows the correlation of the components with each other. Values less than .40 were suppressed in the results. Based on the rotated components, seven variables loaded on factor I which was named ‘Mother Tongue Interference’ based on the nature of the items. Five variables loaded on factor 2 which was named ‘Lack of Confidence’ based on the nature of the items. Three variables loaded on factor 3 which was named ‘Lack of Practice’ based on the nature of the items. Four variables loaded on factor four which was named ‘Home Environment’ based on the nature of the items. Table 7: Factor Loading Results for all Factors Item Statements Factor loadings Factor No 1 Fear of mistakes and criticism .870 2 Lack of English speaking platform .826 3 Lack of effective learning strategies .870 4 Lack of English background .530 5 Family background or peer influence .607 Mother Tongue 6 Lack of practice in using English .925 Interference 7 Lack of using English in daily routine .766 8 Mother tongue interference .869 9 No interest in English language .770 10 Weak grammar usage .605 11 Introvert personality .485 Lack of confidence 12 Lack of confidence .605 13 Poor academic performance .650 14 Job opportunities in future .503 Lack of practice 15 Unable to give presentation in class .701 16 Difficult to communicate with others .670 17 Interpersonal relationships .613 18 Cannot go overseas for further study .592 Home environment 19 Speech anxiety .642 5. DISCUSSION The aim of this study was to explore the factors influencing English communication among the technology program students at UTHM Malaysia. The factor analysis highlighted four important influencing factors: Factor 1-mother tongue interference, Factor 2- lack of confidence, Factor 3-lack of practice, and Factor 4- home environment as explained below in detail. Factor 1 (Mother Tongue Interference) is identified as the most powerful influencing factor that affects students’ communication skills. This factor explains 43.37 percent of the total variance. Seven variables loaded on this factor as a result of the principal component analysis with factor loadings ranging from .530 to .870. This factor reveals that mother tongue interference is one of the biggest factors that affect English communication of engineering students in UTHM. This finding also supports previous research studies where mother tongue has been found as a barrier to second and foreign language learning (Gimenez, 2015). Factor 2 (Lack of Confidence) is the second influencing factor. This factor explains 7.25 percent of the total variance. Three variables loaded on this factor based on principal component analysis with factor loadings ranging from .503 to .701. This means that lack of confidence is one of strongest barriers to English language communication among technology http://www.iaeme.com/IJMET/index.asp 814 editor@iaeme.com
Sarala Thulasi Palpanadan, Iqbal Ahmad, Venosha K. Ravana program students at UTHM. This result is in line with previous research that students have lower confidence and cannot communicate with others (Heriansyah, 2012; Souriyavongsa et al., 2013). Consequently, they show poor communication skills and perform low in the language courses and activities. Factor 3 (Lack of Practice) is the third strongest influencing factor. This factor accounts for 9.91 percent of the total variance. Five variables loaded on this factor based on principal component analysis with factor loadings ranging from .485 to .879. This shows that engineering students are unable to find opportunity to practice English language which affects their communication skills in the language. Previous research has also revealed that lack of practice contributes to poor communication skills (Gan, 2012; Stacey & MacGregor, 1991). Factor 4 (Home Environment) is the fourth strongest influencing factor. This factor explains 5.77 percent of the total variance. Four variables loaded on this factor on the basis of principal component analysis with factor loadings ranging from 592 to .670. This reveals that home environment is another barrier for effective English communication for technology program students. Previous studies have also indicated that students who do not find encouraging environment at home regarding second language communication demonstrated low language competency. Normally, such students come from non-English speaking background. Studies have shown that children who do not get encouragement from parents or other elders at their homes show poor speaking performance (Lessing & Mahabeer, 2007; Roopnarine et al., 2006) 6. CONCLUSIONS This study aimed at identifying factors influencing English communication among technology program students at UTHM. Through application of an exploratory factor analysis, this study revealed that four major factors affected the English language communication skills of the technology program students. These factors were mother tongue interference, lack of confidence, lack of practice, and home environment. Thus, the stakeholders and the respective lecturers will be able to tailor their lesson and learning activities to cater to needs of the students based on the four factors identified in this study. Besides, scholars and lecturers also can suggest to students to discuss with their respective family members to cooperate with them to provide room for them to improve their communication skills based on their own capacities. This would pave ways for the students not only to excel in English but also in their technology courses and programs. RECOMMENDATIONS Based on the results this study provides the following recommendations:  It is important that students should get an environment at UTHM where English communication can be declared mandatory for communication among lecturers and students in the classroom and within the campus. The university management may notice this issue and embed this matter it in the curriculum and policy.  The students should be encouraged by lecturers and management to communicate in English language. Thus, more language enhancement trainings, workshops, seminars, and symposium could be held from time to time where students could participate actively. This would boost up their confidence to speak in second language.  Parents should be positive in creating an environment at home where children find ample opportunity to practice English language. Parents could allow their children to watch English drama, English language tutorials and other supportive channels and programs. This would increase their knowledge of English language and also add to their language vocabulary. http://www.iaeme.com/IJMET/index.asp 815 editor@iaeme.com
Factor Analysis of English Communication Competency among Malaysian Technology Undergraduates  Further research is needed on this issue in the context of English learning among the technology students in Malaysian universities. This would provide new knowledge and insight for language policy development in educational institutions. ACKNOWLEDGEMENT The funding for this publication was provided by UTHM Research Fund (E15501). REFERENCES [1] Adelaar, K. A., and Prentice, D. (1996). Malay: the national language of Malaysia. Atlas of languages of intercultural communication in the Pacific, Asia, and the Americas, 729- 733. [2] Ahmad, S. R. (2016). Importance of English communication skills. International Journal of Applied Research, 2(3), 478-480. [3] Ahmadi, M. R., (2018). The Use of Technology in English Language Learning. International Journal of Research in English Education. 3(2), 115-125 [4] Benraghda, A., Radzuan, N. R. M., and Ali, Z. (2017). Impediments to Delivering Oral Presentations in English among Malaysian ESP Undergraduates. English for Specific Purposes World(53), 1-13. [5] Gan, Z. (2012). Understanding L2 speaking problems: Implications for ESL curriculum development in a teacher training institution in Hong Kong. Australian Journal of Teacher Education, 37(1), 3. [6] Gimenez, S.L. (2015). A Case Study on Oral Corpus: The Use of MotherTongue in Class by Brazilian Teachers of Spanish as Foreign Language. Procedia - Social and Behavioral Sciences, 198, 242-248. [7] Heriansyah, H. (2012). Speaking problems faced by the English department students of Syiah Kuala University. Lingua Didaktika: Jurnal Bahasa dan Pembelajaran Bahasa, 6(1), 37-44. [8] Hinkin, T. R. (1995). A review of scale development practices in the study of organizations. Journal of management, 21(5), 967-988. [9] How, S. Y., Abdullah, A. N., and Chan, S. H. (2017). patterns of dominance of language vitalities among malaysian students in primary national-type and secondary schools. Indonesian Journal of Applied Linguistics, 6(2), 271-287. [10] How, S. Y., Heng, C. S., and Abdullah, A. N. (2015). Language Vitality of Malaysian languages and its Relation to Identity. GEMA Online® Journal of Language Studies, 15(2). [11] Howells, J. (1997). Does Technology Drive History?: The Dilemma of Technological Determinism, Merritt Roe Smith & Leo Marx (Eds), Cambridge, MA, London, MIT Press, 1995, xv + 288 pp., ISBN 0-262-69167-1, Prometheus, 15:1, 144-148, DOI: 10.1080/08109029708632060 [12] Ibrahim, D. H. M., and Mahyuddin, M. Z. (2017). Youth Unemployment in Malaysia: Developments and Policy Considerations. Outlook and Policy, Annual Report. [13] Ince, M. (2014) The Investigation of Instructors’ Views on Using Technology in English Language Teaching. Procedia - Social and Behavioral Sciences. 141,670 – 674. [14] Kirkpatrick, A. (2012). English as an international language in Asia: Implications for language education English as an international language in Asia: Implications for language education (pp. 29-44): Springer. [15] Lessing, A. C., and Mahabeer, S. D. (2007). Barriers to acquiring English reading and writing skills by Zulu-speaking foundation-phase learners. Journal for Language Teaching= Ijenali Yekufundzisa Lulwimi= Tydskrif vir Taalonderrig, 41(2), 139-151. http://www.iaeme.com/IJMET/index.asp 816 editor@iaeme.com
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