Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia

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1 International Journal of Management Science 2017; 4(1): ISSN: Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia Ahmad Othman 1, *, Evenie Dwin 2 Keywords Students Intention, Attitude, Subjective Norm, Perceived Behavior Control Received: March 15, 2017 Accepted: March 23, 2017 Published: June 6, Kolej Universiti Poly-Tech MARA Kuala Lumpur, Malaysia 2 Graduate in Bachelor of Business Administration, University College of Technology Sarawak, Sibu, Sarawak, Malaysia address ahmadbo@kuptm.edu.my (A. Othman) * Corresponding author Citation Ahmad Othman, Evenie Dwin. Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia. International Journal of Management Science. Vol. 4, No. 1, 2017, pp Abstract This paper explores the intention of public college students to enroll into degree program at private university in Sibu Malaysia. A total of 190 questionnaires were distributed by hand to public college students in Betong where 183 questionnaires were returned for further analysis, yielding a response rate of 96.3 percent. Data were analyzed using factor analysis to determine the factors that influence students intention as dependent variable. There were three factors that met the criteria and were accepted for further analysis, namely: attitude, subjective norm and perceived behavior control. Further analysis was carried out using multiple linear regression to determine the factors that significantly influencing students intention to pursue their study. From this study, the coefficient values revealed that the students intention to pursue their study is influenced by their attitude towards the university (β = 0.445) and perceived behavior control (β = 0.271). This study also found that subjective norm did not have significant impact on students intention, as the values p>0.05. In summary, the student s intention to pursue study at private university in Sibu is associated with their attitudes (such as to gain academic knowledge, to have opportunity to interact with academic staff, to continue study at higher level, to develop good study habits, self-discipline and self-satisfaction) and perceived behavior control (influence of parents, siblings, counseling teachers, friends and classmates). 1. Introduction Higher education is mainly to assist students in creating necessary awareness to the world and also it helps them to understand the relationship between the complicated economic, social and also environmental process [1]. Besides, higher education also not only provide the specific skills but also contribute to the educational and also value of the democracy [2]. Nowadays, in Malaysia, there is a greater opportunities for students especially secondary school students to attend colleges and universities. Besides, students will be able to choose and select their preference from a large pool of universities and colleges regardless whether they are public or private institutions, local or overseas. Until now, there are 20 public universities and more than 50 private universities operating in the country. With the existence of these institutions of higher learning, providing wide opportunities to holders of certificates and diplomas to study at a higher level. They have

2 14 Ahmad Othman and Evenie Dwin: Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia the option to either go to public universities that provide education at a subsidized fees, or go to private universities at full fees. Obviously, the number of students enrolled in public Table 1. Student Enrolment into HEIs in Malaysia, higher institutions scored better than private institutions with a compound annual growth rate (CAGR) of 14.4% and 2.6% respectively. See Table 1. Category Year CAGR (%) Public 87,390 98, , , , , Private 165, , , , , , Source: Lau Sear Haur (2009) [3] Due to the increasingly competitive and dynamic educational environment, universities are becoming more aware of the importance of student satisfaction. By focusing on the student satisfaction, it not only help the universities to re-organize the organization but at the same time will help the organizations to establish a system that will monitor the efficiency and effectiveness of the services to meet the student needs. Thus, it is very important for the higher education institutions to know and identify the factors that influence the intention of the students to choose certain universities for their further studies. This study, therefore, would like to find out about the factors influencing public college s students to pursue their study at private university in Sibu, Sarawak. This study utilized the Theory of Planned Behavior Model. 2. Literature Reviews Theory of planned behavior (TPB) has been applied in various studies that essentially study about consumer behavior especially in the field of marketing [4]. Generally, TPB is known as cognitive model of human behavior that concentrates in predicting and understanding the clearly defined behaviors, subjective norms and perceived behavioral control [5]. Intention is an attitude towards the behavior where it is related to the extent of individuals where they have a positive or negative evaluation of the behavior [6]. A subjective norm is a social element which is referring to perceived social pressures whether to perform or not to perform the behavior [7]. Perceived behavioral control refers to the perception regarding whether the performances of the behavior is easy or difficult [6]. A summary of the literature reviews for all three behaviors under this model are shown in Table 2, 3 and 4. Source: Adapted from Ajzen (1991) [8]. Figure 1. The Planned Behavior Model. Table 2. Summary of literature reviews on attitudes. Variables Author Author Author Author Author Author Krishnan and Vrcelj Seng and Chong and Mokhtar Dora et al., (2009)[12] (2009)[9] Paulo (2008)[10] Lattimore (2012) (2013)[14] Sicat (2011)[11] Environmental quality Factors of choosing Students expectation [13] Greater level of Students having is one of the significant program of study is based on quality Perception of the interaction and Attitudes some problem when element so that the (personal interest, teaching, respond or students towards association as well as adapting to the new students feel secure relevance of feedback of the the atmosphere of more engagement and culture. emotionally and program, reputation university. the campus is psychological support physically of the faculty). spacious by the academic staff.

3 International Journal of Management Science 2017; 4(1): Table 3. Summary of literature reviews on subjective norms. Variables Author Author Author Author Chu Man Yee, et.al (2015) [15] Chu Man Yee, et.al (2015) [15]. Shawn (2009)[16]. Students Dauber (2013)[17]. Parents Subjective Decision to enter higher institution Parents will act as information decision on the selected higher become the consumers to Norms influenced by family members, providers that will give students about education based on the family choose the higher education relatives and friends the higher education institutions. background institutions Table 3. Continue. Variables Author Author Author Author Andrius & Palmira (2014)[18]. Pimpa (2004)[19]. Peers and Phang (2013)[20]. Digital Rebecca (2011)[21]. Spread of There is strong parental education agents acts as an channels include social new technology and information Subjective Norms influence in the undergraduate advisor that can influence networks such as Facebook and also the growth of the students when deciding on the study destinations. students to choose higher education institution. and Twitter to seek for the information. Internet as a tool to persuade student s to study. Table 4. Summary of literature reviews on perceived behavior control. Variables Author Author Author Author Author Meleddu & Pulina (2016)[22]. Ming-Shan Hsu Kelleher et.al (2016)[24]. Mueller et.al Pownall (2012)[26]. Control beliefs ultimately (2012)[23]. Flexibility and length of the (2015)[25]. Perceived Behavioral Group teaching as determine the intention and action Suitability of the program and the entry Intrinsic life Control consideration in that set the deals with the presence program is the requirements of the program seem aspirations as one influencing class. or absence or requisite resources. important factor to be most important criteria. of the factors. Table 4. Continue. Variables Author Author Author Author Brennan (2001)[27]. Peng & Perry (2000)[28]. Fuller & Delorey (2016)[29]. Ivy (2001)[30]. Admission criteria as a proxy Program evaluation is Students compare programs Reputation and image of Perceived Behavioral for quality are potentially conceptualized as the offered with those promoted by institution are formed from Control more important than the consumer s attitude towards competing institutions in order word of mouth, past experience program offering. targeted programs. to check their suitability. and the marketing activities. 3. Objectives of Research The objective of this research is to explore the intention of public college students to enroll into degree program at private university in Sibu Malaysia. Specifically, the objectives were three threefold, namely: (i) to identify factors that may influence students intention to pursue their study at private university in Sibu, (ii) to determine the significant relationship between the factors, and (iii) to identify the significantly influenced factors of intention among diploma students to pursue degree program at private university in Sibu. Questionnaire Design The instrument used for the study drew heavily from the literatures reviewed. The instrument was divided into two components. The A component had the demographic variables such as: gender, ethnicity, origin, educational level and parents occupation. The B component contained the major constructs in the study such as: students intention to pursue their study, their attitude towards private university, subjective norms and perceived behavior controls. This component comprised 20 items. The Likert scales was used in designing the variable measuring scale with 1 representing strongly disagree and 7 representing strongly agree. Reliability The reliability of the measure indicates the extent to which it is without bias and hence ensures consistent measurement across time and across the various items in the instrument [31]. In other words, the reliability of a measure is an indication of the stability and internal consistency of items [32]. Internal consistency of items was measured using item analysis with reference to the Cronbach Alpha value. According to Hair et al. (2006), in determining the reliability of the instrument, a general rule is that the indicators should have a Cronbach s alpha of 0.6 or more. The closer the value is to 1 indicates that the instrument is more reliable and shares a high internal consistency [33]. The Cronbach s alpha values obtained in this study range between and Since the Cronbach s alpha values for all constructs are greater than 0.6, therefore, none of the item is excluded. Table 5 shows that the value of Cronbach s alpha for workplace needs attributes and total rewards. Table 5. Reliability Analysis (n=183). Construct Total items Cronbach s Alpha Attitude Subjective norms Perceived behavior control Intention to pursue study Overall Data Analysis and Results A total of 190 questionnaires were distributed by hand to students at a public college in Betong, of which 183 were returned for further analysis, yielding a response rate of 96.3 percent. There were 25.7% of male and 74.3% of female involved in this survey. Majority of them came from Sarawak

4 16 Ahmad Othman and Evenie Dwin: Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia (82.0%) followed by Sabah (10.9%), and Peninsular Malaysia (7.1%). Close to half belongs to Dayaks ethnic (48.6%) followed by Malay (31.7%), Chinese (7.1%) and others. Refer Table 6. Table 6. Demographic profiles of the respondents. Profile Description Frequency Percentage Male Gender Female Dayaks (Iban, Bidayuh, Orang Uu) Melayu Ethnicity Cina Indian Melanau Others Sarawak Origin Sabah Peninsular Malaysia Diploma Educational Certificate level Parents occupation Service sector Transportation sector Agriculture sector Unemployed / self-employed Factor Analysis (for Objective No.1) With a total of 183 respondents obtained in this study, the data was examined using principal component analysis as the extraction technique and Varimax as the method of rotation. Hair et.al (1998) suggest the factor loading cut-off of 0.40 is acceptable for sample size of 180 or more [33]. Tabachnick and Fidell (2013) suggest that for something to be labelled as a factor it should have at least 3 variables [34]. The result of factor analysis shows that the factors that influence the intention of public college students to pursue their study at private university have been factorized into 3 components namely attitude, subjective norms and perceived behavior control. The result consistent with the extensive review of literature discussed earlier. Refer Table 5. Correlations between Independent Variables and Dependent Variables (for Objective No.2) The result of correlation matrix indicates that all the factors that influence the intention of college students to pursue their study at private university in Sibu are moderately related at p-value of (p<0.05) for two factor, namely, attitude and perceived behavior control with correlation value of and respectively. As for subjective norms, there is also positive relationship with students intention to enroll with a correlation value of which is rather weak relationship. See Table 9. Table 7. Summary of Factor Analysis. Factors Factor1 Factor 2 Factor 3 Attitude Subjective Norms Perceived Behavioral.677 Control Table 8. KMO and Bartlett's Test. Kaiser-Meyer-Olkin Measure of Sampling Adequacy..839 Approx. Chi-Square Bartlett's Test of Sphericity df 105 Sig..000 Spearman's rho Factor1 Factor2 Factor3 DV Table 9. Correlation matrix of all factors (IVs and DV). Factor1 Factor2 Factor3 DV Correlation Coefficient Sig. (2-tailed). N 183 Correlation Coefficient.272 ** Sig. (2-tailed).000. N Correlation Coefficient.214 **.375 ** Sig. (2-tailed) N Correlation Coefficient.453 **.176 *.400 ** Sig. (2-tailed) N r 0.20 (very weak relationship), 0.21 r 0.40 (weak relationship), 0.41 r 0.60) (moderate relationship), 0.61 r 0.80 (strong relationship), r 0.81 (very strong relationship) (McBurney, 2001). *Correlation is significant at p<0.05 (2-tailed). **Correlation is significant at p<0.01 (2-tailed

5 International Journal of Management Science 2017; 4(1): Regression Analysis (for Objective No.3) Multiple linear regression was performed in order to identify the most influencing factors that determine their intention of public college students to pursue study at private university in Sibu, Sarawak. There are several assumptions need to be complied in order to ensure the proven data to be adequate. Table 10. Dublin-Watson Value. Assumption #1: Independence of residuals. This assumption is checked using Dublin-Watson statistics. If the value is between 1.5 and 2.5 then we can assume no problem [33]. By referring to Table 10, the Durbin Watson value of for this study, which shows that it is between the given ranges and therefore free from auto-correlation. Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson a a. Predictors: (Constant), NBD5, CBC1, BBB2, CBC5, BBB3, BBB4, CBC3, NBD2, CBC4, BBB5, BBB1, CBC2, NBD4, NBD3, NBD1 b. Dependent Variable: PBCDVA1 Assumption #2: Linear relationship test using scatterplot. There appears to a linear relationship between dependent variable (intention to pursue study) and independent variables (attitude, subjective norms and perceived behaviour control). Refer Figure 2. Figure 2. Scatter plot of dependent and independent variables. Assumption #3: Homoscedasticity test. The next assumption to be met is homoscedasticity which can be obtained by assessing the output coefficients based on the value of Sig. If the obtained value of sig is greater than 0.05 then it can be concluded that there is no homoscedasticity problem. By referring to Table 11, sig values for all independent variables were greater than Thus no homoscedasticity problem. Assumption #4: Check on multicollinearity. Multicollinearity can be assessed by looking at the value of Tolerance and Variance inflation factor (VIF). Tolerance is an indicator of how much of the variability of the specified independent variable is not explained by the other independent variables in the model [35]. If this value is very small (less than 0.1), it indicates that the multiple correlation with other variables is high (above 0.9), suggesting the possibility of multicollinearity. VIF, on the other hand, is the inverse of Tolerance value (1 divided by Tolerance), which can be guided by the following status of predictors, namely: VIF=1, not correlated; 1<VIF<5, moderately correlated; VIF>5 to 10, highly correlated. As presented in the Table 12, the result of collinearity statistics shows that the Tolerance values for each independent variables are greater than 0.1, indicated that the data has not violated the multicollinearity assumption. This is supported by the VIF values between and which are moderately correlated.

6 18 Ahmad Othman and Evenie Dwin: Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia Table 11. Output Coefficient for Homoscedasticity. Model 1 Unstandardized Coefficients B Std. Error Beta Standardized Coefficients (Constant) BBB BBB BBB BBB BBB CBC CBC CBC CBC CBC NBD NBD NBD NBD NBD t Sig. a. Dependent Variable: PBCDVA1 Table 12. Collinearity Statistics for Independent Variables. Model 1 Unstandardized Coefficients Standardized Coefficients Collinearity Statistics t Sig. B Std. Error Beta Tolerance VIF (Constant) IV IV IV a. Dependent Variable: DV Assumption #5: Check on the absence of outliers. The presence of outliers can be detected whenever the values are more than or lower values calculated, based on the following formulas: Upper=Q3+(2.2x(Q3-Q1)). By referring to Table 13, Upper value can be obtained: Upper=35+(2.2x(35-25)=57. Percentiles Table 13. Percentiles. Lower=Q1-(2.2x(Q3-Q1))=25-(2.2x(35-25))=3. From Table 12, the highest and lowest values, i.e., between 15 and 35, fall within the range of 3 and 57, and thus the data is free from outliers (Q1) (Q3) Weighted Average(Definition 1) DV Tukey's Hinges DV Table 14. Upper and Lower Values. DV Highest Lowest Case Number Value a a. Only a partial list of cases with the value 35 are shown in the table of upper extremes.

7 International Journal of Management Science 2017; 4(1): Assumption #6: Normality test using P-P Plot. As shown, there is a straight-line relationship between independent variables (attitude, subjective norms and perceived behavior control) with students intention whereby the plots are scattered round a straight line which indicate that data is normally distributed. After fulfilling all the assumptions, further analysis using Multiple Linear Regression was carried out to identify the most influence attributes of IVs (attitude, subjective norm and perceived behavior control) towards students intention to pursue their study at private university in Sibu. The regression analysis yielded a multiple correlation coefficient (R) of which means that there was a moderate relationship between the dependent variable (intention to pursue study) and the set of predictors (attitude, subjective norm and perceived behavior control). See Table 15. Additionally, the coefficient of determination (R 2 ) of indicates that 27.9% of the variation in students intention can be explained by the attributes of planned behaviors. Meanwhile, the residual of 72.1% is explained by other variables out of the model. In general, the analysis yielded a regression model with F value of with p value of (p<0.05). Table 15. Model Summary. R Adjusted R Std. Error of the Model R Square Square Estimate a a. Predictors: (Constant), IV1, IV2, IV3; F = 23.13, Sig.F = Figure 3. P-P Plot of Dependent and Independent Variables. From this study, the coefficient values revealed that the students intention is influenced by their attitude towards the university (β = 0.445) and perceived behavior control (β = 0.271). Please see Table 16. This study also found that subjective norm did not have significant impact in determining students intention to pursue study, as the values p>0.05. Table 16. Multiple Linear Regression Analysis. Model 1 Unstandardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. (Constant) IV IV IV The relationship of these variables can be presented by the following linear equation. y = x x 2 y = Students intention to pursue study x 1 = Attitude x 2 = Perceived behavior control To summarize, it is predicted that the intention of public college students to pursue their study at private university in Sibu is associated with their attitudes (such as to gain academic knowledge, to have opportunity to interact with academic staff, to continue study at higher level, to develop good study habits, self-discipline and self-satisfaction) and perceived behavior control (influence of parents, siblings, counseling teachers, friends and classmates). 5. Conclusions Based on the objectives of this study, the following conclusions have been derived. First, in order to identify the probable component of students intention, a factor analysis was conducted on each item. The result showed that the major attributes of students intention to pursue their study is factorized into 3 factors namely attitude, subjective norms and perceived behavior control. Further analysis was carried out using Linear Regression to find out the most influence factors from among the factors discussed above. From this study, the coefficient values revealed that the students intention is influenced by their attitude towards the university (β = 0.445) and perceived behavior control (β = 0.271). This study also found that subjective norm did not

8 20 Ahmad Othman and Evenie Dwin: Exploring the Intention of Public College Students to Enroll into Degree Program at Private University in Sibu Malaysia have significant impact on students intention, as the values p>0.05. The study found that attitude was the most significant variable with β=0.445 at p=0.000, followed by perceived behavior control (β=0.271, at p= In summary, the student s intention to pursue study at private university in Sibu is associated with their attitudes (such as to gain academic knowledge, to have opportunity to interact with academic staff, to continue study at higher level, to develop good study habits, self-discipline and self-satisfaction) and perceived behavior control (influence of parents, siblings, counseling teachers, friends and classmates). References [1] Duke, C. (2005, October 4-5). The Role Of Higher Education Institutions In Regional Development. Retrieved November 20, 2014, from [2] Millican, J., & Bourner, T. (2011). Student-community engagement and the changing role and context of higher education. Education& Training, 53(2-3), [3] Lau Sear Haur (2009). Higher Education Marketing Concerns: Factors Influencing Malaysian Students Intention to Study at Higher Education Institution. MBA dissertation submitted to University of Malaya. [4] Mishra, S. (2014). Adoption of M-commerce in India: Applying Theory of Planned Behavior. Journal of Internet Banking and Commerce. Vol (19).pp [5] Ajzen, I. and Martin Fishbein (2012). Legacy: The reasoned action approach: Annals of the American Academy of Political and Social Science. Vol.640, No. 1, pp [6] Hsu, M. (2012). A Study of Internship Attitude, Subjective Norm, Perceived Behavioral Control, And Career Planning Of Hospitality Vocational College Students. Journal Of Hospitality, Leisure, Sport & Tourism Education, [7] Astuti, R., &Martdianty, F. (2012). Students Entrepreneurial Intentions by Using Theory Of Planned Behavior. Journal of Management, [8] Ajzen, I. (1991). The Theory Of Planned Behavior. Organizational Behavior And Human Decision Processes, [9] Krishnan, S., and Vrcelj, Z. (2009). International Students Expectations And Motivations. [10] Paulo Charles Pimentel Botas (2008). Students perception of quality teaching in higher education in the UK. Thesis submitted for PhD. University of London. [11] Sicat, R. M. (2011). Foreign students cultural adjustment and coping strategies International Conference on Social Science and Humanity. IPEDR, Vol. (5). IACSIT Press Singapore. [12] Dora, M., Ibrahim, N., Ramachandran, S., Kasim, A., &Saad, M. (2009). A Study On Factors That Influence Choice Of Malaysian Institution Of Higher Learning For International Graduate Students. Journal Of Human Capital Development, [13] Seng, E., & Lattimore, C. (2012). Campus Life For International Students: Exploring Students Perceptions Of Quality Learning Environment At A Private University In Malaysia. Higher Education Studies, 2. [14] Chong, P. and Mokhtar, A. (2013). International students learning experiences. Proceeding of the Global Summit on Education. Pp [15] Chu Man Yee, Foong Bi Kai, Lai Chee Liang and Pang Ai Nee (2015). Foreign students enrolment in Malaysian higher education institution. Project report submitted for Bachelor of Marketing degree at Universiti Tunku Abdul Rahman. [16] Shawn Lea Temple (2009). Factors that influence students desires to attend higher education. Dissertation submitted to Seton Hall University for Doctor of Education degree. [17] Dauber, J. (2013). Public V. Private: Parental Choice of Schools and the Reasons [18] Andrius Eidimtas and Palmira Jucevicience (2014). Factors Influencing School-leavers Decision to enroll in Higher Education. Procedia-Social and Behavioral Science. Vol.116, 21 February 2014, pp [19] Pimpa, N. (2004). The Relationship between Thai Students Choices of International Education And Their Families. International Education Journal, [20] Phang, S. (2013). Factors Influencing International Students Study Destination Decision Abroad [21] Rebeca Sawyer (2011). The impact of new social media on intercultural adaptation. Senior Honors Projects. Paper 242. University of Rhode Island. [22] Marta Meleddu and Manuela Pulina (2016). Evaluation of individuals intention to pay a premium price for ecotourism: An exploratory study. Journal of Behavioral and Experimental Economics. Vol. 69, December 2016, pp [23] Ming-Shan Hsu (2012). A study of internship attitude, subjective norm, perceived behavior control, and career planning of hospital vocational college students. Journal of Hospitality, Leisure & Tourism Education. Vol.11, Issue 1, April 2012, pp [24] Kelleher, S., FitzGerald, S., and Hegarty, J. (2016). Factors that influence nursing and midwifery students intentions to study abroad: A qualitative study using the theory of planned behavior. Nurse Education Today. Vol. 44. September Pp [25] Mueller, E. F., Fickinger, M., and Dorner, V. (2015). Knowledge junkies or career-builders? A mixed-methods approach to exploring the determinant of students intention to earn PhD. Journal of Vocational Behavior. Vol. 90. October pp [26] Pownall, I. (2012). Student identity and group teaching as factors shaping intention to attend a class. The International Journal of Management Education. Vol. 10, Issue 2. July pp [27] Brennan, L. (2001). How Prospective Students Choose Universities: A buyer Behavior Perspective. Unpublished Doctoral: dissertation, University of Melbourne, Australia. [28] Peng, Z, Lawley, M. and Perry, C. (2000), Modeling and Testing Effects of Country, Corporate and Brand Images on Consumers Product Evaluation and Purchase Intention, Paper Presented at the ANZMAC 2000 Visionary Marketing for the 21st Century: Facing the Challenge Conference.

9 International Journal of Management Science 2017; 4(1): [29] Fuller, M. A., and Delorey, R. (2016). Making the choice: University and program selection factors for undergraduates management education in maritime. The International Journal of Management Education. Vol.14, Issue 2. July Pp [30] Ivy, J. P. (2001), Higher Education Institution Image: A Correspondence Analysis Approach, International Journal of Educational Management, Vol. 15, No. 6/7, pp [31] Sekaran, U. (2003). Research methods for business. A skill building approach. 4th ed. NY: John Wiley & Sons Inc. [32] Onwuegbuzie, A. J. and Daniel, L. (2002). Uses and misuses of the correlation coefficient. Research in the Schools. 9: [33] Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate data analysis. 6th Edition. New Jersey: Prentice-Hall International Inc. [34] Tabachnick, B. G. and Fidell, L. S. (2013). Using multivariate statistics. 6 th Edition. United States: Pearson. [35] Pallant, J. (2010). SPSS survival manual: A step by step guide to data analysis using SPSS. 4th Edition. New York: McGraw Hill Words count: 4,459.

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