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Proceeding Paper

Intention to Choose Education Course in UiTM Using Theory of Planned Behaviour (TPB) †

by
Muhammad Saiful Anuar Yusoff
1,
Wan Nazihah Wan Mohamed
1,*,
Zulkifli Mohamed
2 and
Norhaiyati Abdul Muin
3
1
Akademi Pengajian Bahasa, Universiti Teknologi MARA (UiTM) Cawangan Kelantan, Machang 18500, Malaysia
2
Faculty of Business Management, Universiti Teknologi MARA (UiTM) Cawangan Kelantan, Kota Bharu 15050, Malaysia
3
Independent Researcher, Machang 18500, Malaysia
*
Author to whom correspondence should be addressed.
Presented at the International Academic Symposium of Social Science 2022, Kota Bharu, Malaysia, 3 July 2022.
Proceedings 2022, 82(1), 40; https://doi.org/10.3390/proceedings2022082040
Published: 14 September 2022
(This article belongs to the Proceedings of International Academic Symposium of Social Science 2022)

Abstract

:
In line with the offering of a Master’s of Education as a new course in UiTM Kelantan, this study was conducted to investigate the willingness of the community to enrol into the course based on the Theory of Planned Behaviour (TPB). The influences of attitude, subjective norms and perceived behavioural control towards intention were studied. A total of 347 data elements were obtained from employees working in both public and private sectors in Kelantan and Terengganu. The data were analysed using SmartPLS. The findings reveal a significant influence of attitudes, subjective norms and perceived behavioural control on the intention of the respondents to enrol into an education course offered at UiTM. The findings of this study are expected to contribute to identify the factors that influence the intentions of the community members, in particular public servants, to choose courses offered at UiTM Kelantan.

1. Introduction

The importance of education in increasing the productivity of individuals, workplaces and countries is undeniable since education is an ongoing process throughout a person’s life. The learning process is not confined to only children and the working groups, but it also covers other community members including housewives, retirees, the disabled and the elderly. The ultimate goal of education is to improve the life quality of individuals and society; thus, the country is in dire need of knowledgeable human capital. Knowledge needs to be updated in order to produce human beings that are relevant to the progress and development of the nation [1]. A study by the United Nations Educational, Scientific and Cultural Organization (UNESCO) found that educational programs provided to all community members in the developing countries has fostered progress in the respective countries’ development. As such, lifelong education has been recognized by the United Nations (UN) as the key to human resource development. Subsequently, the government has taken proactive measures in the education system to produce high quality human capital that can move towards the global economy era of knowledge-based communities [2]. All of these measures are designed to fulfil the country’s aspirations to produce balanced, high quality and knowledgeable human capital from all angles.
The rapid growth of education has indirectly created many opportunities for school students and workers in both public and private sectors to pursue studies into higher education. As a result, the process of selecting higher education institutions and courses is increasingly difficult due to the existence of various public and private institutions of higher learning that offer a wide selection of quality and competitive programs [3]. This has created intense challenges and competitions among public and private institutions of higher learning to attract the public in choosing the courses offered. As such, there is a need to understand the tendency of the public and private employees to pursue higher education and to identify the factors influencing the intention to continue their studies. In addition, the absence of studies conducted to determine the community’s interest in pursuing education-related courses at UiTM Kelantan makes this study very significant. Therefore, this study is conducted to provide an accurate and recent perspectives of their intention to choose educational courses offered at UiTM Kelantan.

2. Literature Review

2.1. Intention to Enrol in Course

In social science, intention is an important indicator of an individual’s readiness to accept a behaviour [4,5]. It is an aspect of motivation that affects one’s behaviour and an indication of the willingness to perform an action or plan the effort required to perform an action [6]. In addition, a person’s tendency to perform an action increases with the strength of one’s intention [7].
This study involved the variables of attitude, subjective norm and perceived behavioural control as factors that determine one’s intention to perform an act or behaviour. The choice of these three factors is based on the Theory of Planned Behaviour. The theory postulates that the more important one’s intention to do something is, the higher the probability of an action being taken. With the support of previous studies, it is expected that attitude, subjective norm and perceived behavioural control will influence the intention to choose an education course at UiTM Kelantan.

2.2. Attitude

Attitude is an internal factor of an individual which is defined as the positive or negative level of a person’s feelings towards a particular desire or behaviour [4]. According to [8], the students’ perceptions of a domain often influence their choice of a particular subject. This means that students with negative attitudes toward a particular subject will avoid choosing it while positive students will have a positive commitment towards the subject. In relation to this study, attitude is required in the decision-making process so as to continuously and consistently choose the course offered.
Previous studies have proven the influence of positive attitude on the choice of various courses such as language [9,10], accounting [11] and entrepreneurship [12,13,14]. The analysis of these studies found that attitude towards certain subjects has a significant relationship with the formation of behavioural intention. Considering these findings, it is expected that a positive attitude towards an education course will also reflect the same effect on the intention to choose an education course at UiTM Kelantan. As such, the first hypothesis is presented as:
H1. 
Attitude positively influences the intention of choosing an education course at UiTM Kelantan.

2.3. Subjective Norm

Subjective norm is a part of external motivation that plays a role in persuading a person to do an important action. It also refers to a person’s perception of social pressure placed on them from a particular parent, friend or community so as to perform or not to perform the desired behaviour [15]. In the context of this study, this represents a person who has the impression that individuals influence him or her, such as family, employers, friends and community, and may encourage him or her to make a choice and be motivated to do the action. In other words, subjective norm determines an individual’s action.
The results of previous studies support subjective norm as one of the important factors in choosing a college or university course. Social factors which consist of family and peers are seen to be the major factors influencing the selection of a course [16,17]. A study by [17] on student selection at a university in Indonesia found that the family factor is one of the five important factors besides funding fees, reputation, distance factor and career prospects. Therefore, individuals are expected to choose the course offered at UiTM Kelantan if they are encouraged by the important individuals around them. This leads to the second hypothesis which is:
H2. 
Subjective norm positively influences the intention of choosing an education course at UiTM Kelantan.

2.4. Perceived Behavioural Control

Perceived behavioural control is an individual’s perception according to which performing a behaviour is within his or her control and is often assessed by the ease or difficulty of performing the behaviour [18]. It is an internal motivation that influences one’s intention and action which then enables a person to set goals for action [18]. In this study, a person with high expectations for his or her behaviour will be more likely to choose a course of action despite facing various problems such as lack of interest, course information or confidence in his or her own ability and limited economic resources.
Findings of previous studies on the choice of accounting and entrepreneurship courses showed the influence of perceived behavioural control on the intention to choose such courses [12,14]. The study of [14] showed that a student’s self-confidence is one of the major sources of motivation to choose an accounting course and pursue a career in that field. As such, one is expected to choose an education course offered at UiTM Kelantan if he or she has the confidence to face various difficulties. In relation to that, the third hypothesis is written as:
H3. 
Perceived behavioural control positively influences the intention of choosing an education course at UiTM Kelantan.

3. Research Framework

The selection of Theory of Planned Behaviour (TPB) [18] as the model of this study is based on the ability of this theory to explain the intention of choosing an action or behaviour. Several previous studies using the Theory of Reasoned Action (TRA) have provided strong empirical support on the two variables of attitude and subjective norm [15]. Nevertheless, this initial theory (TRA) was criticized by scholars for its lack of factors that could explain one’s self-control in performing an action [18]. Furthermore, the variable perceived behavioural control is included in the model which describes the person’s actual intention and behaviour. The rationale for choosing this variable is due to the fact that a person’s behaviour is usually influenced by one’s confidence in the ability to perform an action. The higher the expectation for behavioural control, the higher the intention to do an action which leads to high performance [18]. In particular, attitude, subjective norm and perceived behavioural control are expected to be positively related to the intention to choose an education course offered at UiTM Kelantan.

4. Methodology

This study used a quantitative research approach through simple random probability sampling technique. The population of the study was employees working at public and private sectors in Kelantan and Terengganu. The number of the study sample was accurately described using the G*power software [19] (Version 3.1.9.6, University Kiel, Germany) which resulted into a minimum of 77 samples required for this study.
Data were obtained through questionnaire distribution using a 7-point Likert scale. A preliminary test was performed to confirm the item reliability of the study. The analysis found that the values of Cronbach’s alpha for all variables exceeded 0.6, which were beyond the level suggested by [20]. Data collection was completed with a total of 355 questionnaires obtained from 400 questionnaires distributed to the respondents in the states of Kelantan and Terengganu. However, after the data cleaning process, a total of 347 data elements were usable for analysis in this study. The strength of the analysis was further enhanced by using two stages of Partial Least Square Structural Equation Modelling (PLS-SEM) analysis, namely measurement model and structural model.

5. Findings

The demographic analysis of the respondents included 248 (71.5%) women and 99 (28.5%) men who are currently working in various public and private sectors in Kelantan and Terengganu. The majority of the respondents (84.7%) were from Kelantan while only 15.3% of them were from Terengganu. A total of 46 respondents (13.3%) were in the age group of 29 years, 106 (30.5%) were aged 30 to 39 years, 111 (32.0%) were aged 40 to 49 years and 84 respondents (24.2%) were over 50 years old. Most of the respondents earned over Ringgit Malaysia RM 6000 per month (43.8%), followed by an income between RM 5000 and RM 6000 (16.7%), RM 4001 and RM 5000 (17.3%), RM 3001 and RM 4000 (7.2%), RM 2001 and RM 3000 (5.8%) and less than RM 2000 (9.2%). The mode of study that the respondents chose was part-time for 209 respondents (60.2) followed by full-time for 138 (39.8%) respondents. The respondent’s choice of education course at UiTM Kelantan was driven by the following reasons: being near to home (72.1%), low costs (62.9), appropriate environment (27.4%), family support (24.4%) and others (8.1%).

5.1. Measurement Model Analysis

The evaluation of the measurement model involves convergent validity and reliability. Convergent validity refers to the level of agreement of several items or indicators in measuring the same concept or construct [21]. The results in Table 1 show that all items exceeded the 0.6 value for item reliability (factor loading) [22], the 0.7 value for rhoA path coefficient [23], the 0.5 value for AVE (Average Variance Extracted) and the 0.7 value for CR (Construct Reliability) [24]. All the values obtained exceeded the minimum requirement of convergent validity [25].
In addition, a discriminant validity test was performed using the Heterotrait-Monotrait (HTMT) criterion. The analysis was performed to detect the presence of a collinearity issue or a cross-loading conflict in the research items. According to [25], HTMT is the latest criterion in SmartPLS software (SmartPLS GmbH, Version 3.3.9, Boenningstedt, Germany) that can accurately determine discriminant validity. Through this test, a construct value greater than 0.85 indicates discriminant validity has been fulfilled [20]. The analysis for this study found that all constructs had values below the HTMT value of 0.85, which is the maximum value for discriminant validity. As such, discriminant validity of all constructs was achieved as presented in Table 2 below.
Figure 1 shows the SmartPLS measurement model results. The R2 value of business success was 0.704, suggesting that 70.4 percent of the course selection intention can be explained by the three independent variables. Once the evaluation of the measurement model was completed, a further analysis was carried out which included structural model analysis for hypothesis testing.

5.2. Structural Model Analysis

Prior to the structural model analysis, a lateral collinearity test was performed. Even though discriminant validity and HTMT ratio showed no collinearity issue for all research constructs, conducting lateral collinearity testing is necessary. This is because the existence of this type of collinearity may impede the research findings, since it has a tendency to disrupt the causal relationship between the predictors and the dependent variables of the research model. This occurs when two variables that are fundamentally related to each other are found to measure the same construct [26].
Table 3 depicts the results for the lateral collinearity test. The Variance Inflation Factors (VIF) values for all independent variables (ATT, SN and PBC) were lesser than five [27], which indicated that lateral collinearity was not an issue in this study.
This study developed three hypotheses in determining the direct relationship between the constructs of the study. According to [24], a research hypothesis can be determined through bootstrapping analysis using 5000 sampling methods in SmartPLS software. The findings show that all three research hypotheses were supported by t values greater than or equal to 1.645 with attitude (ATT) (ß = 0.349, p < 0.01), subjective norm (SN) (ß = 0.177, p < 0.05) and perceived behavioural control (PBC) (ß = 0.381, p < 0.01) positively influenced course selection intention while the number of variance explained by these three variables accounted for 70.4%. Therefore, H1, H2 and H3 were fully supported. The R2 value of 0.704 exceeded the value of 0.26 as proposed by [28] which showed that ATT, SN and PBC influence the intention to choose an education course at UiTM Kelantan. The structural model of hypothesis analysis is presented in Figure 2.
Table 4 shows the results of hypothesis analysis for this research model. The value R2 = 0.704 indicates that 70.4% of the variance in the intention to choose an education course was explained by the three study variables of ATT, SN and PBC. According to [29] on the level of R2 (0.67 = high; 0.33 = medium; 0.19 = low), the value for this study was considered high. In addition, as stated by [28] on the guideline of effect size (f2) (0.02 = small; 0.15 = medium; 0.35 = large), this study had small and medium effect sizes since the values were between 0.023 and 0.166. Perceived behavioural control had a modest effect on the intention to choose an education course while attitude and subjective norm had little effect on the intention to choose a course. Prediction relevance value (Q2) beyond the value of zero suggests that the variable has a predictive ability based on the intention to choose an education course [24]. The acceptable data-model fit is determined through the goodness-of-fit measures (GoFs) [29]. If the average square root value of AVE multiplied by R2 exceeds the value proposed by [30] (GoFsmall = 0.01; GoFmedium = 0.25; GoFlarge = 0.36), the model fit of the study is achieved. The analysis found that the obtained value was high at 0.694, which exceeded the proposed value level.

6. Discussion

The objective of this study is to investigate the influence of attitude, subjective norm and perceived behavioural control on the intention to choose an education course at UiTM Kelantan. The findings support all the hypotheses of the study which demonstrates that attitude, subjective norm and perceived behavioural control influence the intention to choose an education course. The main perceived contributor is behavioural control, followed by attitude and subjective norm.
It can be seen in this study that all factors collectively influence a person’s intention to perform an action. All factors accounted for 70.4% of the variance in the intention to choose an education course at UiTM Kelantan. However, the strength of the relationship is different. Perceived behavioural control was found to significantly contribute to the intention of choosing education course as compared to the other two factors with a moderate effect size (f2 = 0.166). This result is similar to previous studies that examined the relationship of perceived behavioural control with the intention to select language, accounting and entrepreneurship courses [9,10,11,12,13,14]. In other words, employees involved in this study tend to choose an education course offered at UiTM Kelantan despite facing challenges such as limited economic resources and lack of adequate information on the offered course. However, they are still unsure of their interest and self-confidence in choosing an education course since there is no relationship analysis of these two items with perceived behavioural control.
Positive attitude towards an education course is the second important factor that influences the selection of an education course at UiTM Kelantan. This finding is also parallel to previous studies which showed that attitude is an important factor in influencing respondents’ choice of university courses [9,10,12,13,14]. Based on this result, the offering of an education course at UiTM Kelantan is very much anticipated, and especially at the undergraduate level since such course is not offered at any UiTM campuses, with the exception of UiTM’s main campus in Shah Alam.
The last factor influencing the respondents’ selection of an education course at UiTM Kelantan is subjective norm. The finding of this study corresponds with previous studies that viewed the family factor as a source of motivation for choosing such course [14,16,17]. In this study, the family is seen to be the main motivator for the respondents to choose the course, followed by the community, employers and friends. Family and community are key references in the selection of a course, which may be due to the experience of family members or successful community members in the education field.

7. Conclusions

In conclusion, internal factors such as perceived behavioural control and positive attitude are significant factors that influence the selection of an education course in UiTM Kelantan as compared to external factors such as subjective norm. Despite the obstacles and challenges, the majority of the employees are positive towards choosing this course. Although subjective norm has the least influence within the research model, its influence is still significant since the existence of family members, friends and community is still relevant in the selection of an education course at UiTM Kelantan. Therefore, these three factors need to be taken into account as they greatly influence the intention to choose an education course offered at UiTM Kelantan.

Author Contributions

Conceptualization, Z.M. and N.A.M.; methodology, M.S.A.Y.; validation, Z.M. and N.A.M.; formal analysis, M.S.A.Y.; investigation, M.S.A.Y., W.N.W.M., Z.M. and N.A.M.; data curation, M.S.A.Y.; writing—original draft preparation, M.S.A.Y. and W.N.W.M.; writing—review and editing, W.N.W.M. and N.A.M.; visualization, M.S.A.Y. and W.N.W.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Acknowledgments

The authors wish to thank UiTM Cawangan Kelantan for supporting this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Majlis Pelancaran Pelan Strategi UPM 2001–2010, Etika Kerja UPM dan Anugerah Fellowship Naib Canselor. Available online: www.upm.edu.my/website/koleksi_ucapan/2002 (accessed on 12 January 2022).
  2. Mansor, F.; Tengku Kasim, T.S.A. Pembangunan Modal Insan dari Perspektif Pengurusan Islam. J. Al-Tamaddun. 2008, 3, 85–109. [Google Scholar] [CrossRef]
  3. Dimon, Z.; Azizan, N.I.; Ismail, N.; Bakar, S.A.; Shaharuddin, H.N. Faktor yang mempengaruhi pelajar memilih bidang pengajian Islam: Kajian di Fakulti Pengajian Peradaban Islam, KUIS. Attarbawiy Malays. Online J. Educ. 2017, 1, 50–57. [Google Scholar]
  4. Ajzen, I. Perceived behavioural control, self-efficacy, locus of control, and the theory of planned behavior. J. Appl. Soc. Psychol. 2002, 32, 665–683. [Google Scholar] [CrossRef]
  5. Fishbein, M.; Ajzen, I. Belief, Attitude, Intention and Behaviour: An Introduction to Theory and Research; Addison-Wesley: Reading, UK, 1975. [Google Scholar]
  6. Ajzen, I.; Driver, B.L. Application of the theory of planned behaviour in leisure choice. J. Leis. Res. 1992, 24, 207–224. [Google Scholar] [CrossRef]
  7. Ajzen, I.; Madden, T.J. Prediction of goal directed behaviour: Attitudes, intentions, and perceived behavioural control. J. Exp. Soc. Psychol. 1986, 2, 453–474. [Google Scholar] [CrossRef]
  8. Curran, J.M.; Rosen, D.E. Student attitudes toward college courses: An examination of influences and intentions. J. Mark. Educ. 2006, 28, 135–148. [Google Scholar] [CrossRef]
  9. Yusoff, M.S.A.; Hassan, N.S.I.C.; Nor, N.H.M.; Yusof, N. Pengaruh sikap dan nilai Islam terhadap niat untuk menghadiri program bahasa Inggeris di masjid. e-Acad. J. 2018, 7, 98–108. [Google Scholar]
  10. Bosan, B. The Effects of Role-Play on Students’ Attitude and Motivation to Speak and Interact in the ESL Classroom. Master’s Thesis, Universiti Teknologi Malaysia, Johor, Malaysia, 2013. [Google Scholar]
  11. Hatta, M.; Agustian Riduan, O.H. Niat mahasiswa akuntasi bekarir sebagai akuntan di luar negeri: Pengujian theory of planned behavior. J. Akunt. 2017, 7, 63–68. [Google Scholar]
  12. Potishuk, V.; Kratzer, J. Factors affecting entrepreneurial intentions and entrepreneurial attitudes in higher education. J. Entrep. Educ. 2017, 20, 25–44. [Google Scholar]
  13. Shah, N.; Soomro, B.A. Investigating entrepreneurial intention among public sector university students of Pakistan. Educ. + Train. 2017, 59, 841–855. [Google Scholar] [CrossRef]
  14. dos Santos, E.A.; de Almeida, L.B. To pursue a career in accounting or not: A study based on the Theory of Planned Behavior. Rev. Contab. Finanç. 2018, 29, 114–128. [Google Scholar] [CrossRef]
  15. Ajzen, I.; Fishbein, M. Understanding Attitudes and Predicting Social Behaviour; Prentice-Hall: Hoboken, NJ, USA, 1980. [Google Scholar]
  16. Jafari, P.; Aliesmaili, A. Factors influencing the selection of a university by high school students. J. Basic Appl. Sci. Res. 2013, 3, 696–703. [Google Scholar]
  17. Kusumawati, A. A qualitative study of the factors influencing student choice: The case of public university in Indonesia. J. Basic Appl. Sci. Res. 2013, 3, 314–327. [Google Scholar]
  18. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Processes 1991, 50, 179–211. [Google Scholar] [CrossRef]
  19. Faul, F.; Erdfelder, E.; Buchner, A.; Lang, A.G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav. Res. Methods 2009, 41, 1149–1160. [Google Scholar] [CrossRef] [PubMed]
  20. Kline, R.B. Principles and Practice Of Structural Equation Modeling; Guilford Press: New York, NY, USA, 2011. [Google Scholar]
  21. Malhotra, A.; Schuler, S.R.; Boender, C. Measuring Women’s Empowerment as a Variable in International Development; The World Bank: Washington, DC, USA, 2002. [Google Scholar]
  22. Byrne, B.M. Structural Equation Modeling With AMOS: Basic Concepts, Applications, And Programming; Routledge: London, UK, 2016. [Google Scholar]
  23. Dijkstra, T.K.; Henseler, J. Consistent partial least squares path modeling. MIS Quart. 2015, 39, 297–316. [Google Scholar] [CrossRef]
  24. Hair, J.F.; Hult, T.M.; Ringle, C.M.; Sarstedt, M.A. Primer on Partial Least Square Structural Equation Modeling (PLS-SEM); Sage Publications: Thousand Oaks, CA, USA, 2014. [Google Scholar]
  25. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
  26. Kock, N.; Lynn, G.S. Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. J. Assoc. Inf. Syst. 2012, 13, 546–580. [Google Scholar] [CrossRef]
  27. Hair, J.; Hollingsworth, C.L.; Randolph, A.B.; Chong, A. An updated and expanded assessment of PLS-SEM in information systems research. Ind. Manag. Data Syst. 2017, 117, 442–458. [Google Scholar] [CrossRef]
  28. Cohen, J. Statistical Power Analysis for the Behavioural Sciences, 2nd ed.; Lawrence Erlbaum Associates: Hillsdale, NJ, USA, 1988. [Google Scholar]
  29. Chin, W.W. The partial least squares approach for structural equation modeling. In Modern Methods for Business Research; Marcoulides., G.A., Ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 1998; pp. 295–358. [Google Scholar]
  30. Tenenhaus, M.; Esposito Vinzi, V.; Chatelin, Y.-M.; Lauro, C. PLS path modelling. Comput. Stat. Data Anal. 2005, 48, 159–205. [Google Scholar] [CrossRef]
Figure 1. Measurement model.
Figure 1. Measurement model.
Proceedings 82 00040 g001
Figure 2. Structural model.
Figure 2. Structural model.
Proceedings 82 00040 g002
Table 1. Convergent validity analysis.
Table 1. Convergent validity analysis.
ConstructItemLoadingCronbachrhoACRAVE
ATTD10.9070.9710.9710.9710.847
D20.930
D30.916
D40.918
D50.942
D60.909
SNE10.9540.9560.9560.9560.843
E20.903
E30.896
E40.918
PBCF10.8710.8850.8860.8850.794
F20.911
INTG10.9550.9570.9620.9590.824
G20.945
G30.927
G40.912
G50.791
ATT: Attitude, INT: Intention, PBC: Perceived Behavioural Control, SN: Subjective Norm, rhoA: Reliability indicator, AVE: Average Variance Extracted, CR: Construct Reliability.
Table 2. Discriminant validity analysis.
Table 2. Discriminant validity analysis.
ATTINTPBCSN
ATT
INT0.775
PBC0.7260.781
SN0.8350.7780.808
ATT: Attitude, INT: Intention, PBC: Perceived Behavioural Control, SN: Subjective Norm.
Table 3. Lateral collinearity analysis.
Table 3. Lateral collinearity analysis.
ConstructIntention (VIF Value)
ATT2.93
PBC2.32
SN3.59
VIF ≤ 5.0 [27].
Table 4. Hypothesis analysis.
Table 4. Hypothesis analysis.
HypothesisRelationshipBetaSET ValueResultR2f2Q2GoF
H1ATT → INT0.349 **0.084.352Supported0.7040.1220.5260.694
H2SN → INT0.177 *0.1001.767Supported 0.023
H3PBC → INT0.381 **0.0874.381Supported 0.166
ATT: Attitude, INT: Intention, PBC: Perceived Behavioural Control, SN: Subjective Norm ** p < 0.01, t value > 2.33; * p < 0.05, t value > 1.645.
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MDPI and ACS Style

Yusoff, M.S.A.; Wan Mohamed, W.N.; Mohamed, Z.; Abdul Muin, N. Intention to Choose Education Course in UiTM Using Theory of Planned Behaviour (TPB). Proceedings 2022, 82, 40. https://doi.org/10.3390/proceedings2022082040

AMA Style

Yusoff MSA, Wan Mohamed WN, Mohamed Z, Abdul Muin N. Intention to Choose Education Course in UiTM Using Theory of Planned Behaviour (TPB). Proceedings. 2022; 82(1):40. https://doi.org/10.3390/proceedings2022082040

Chicago/Turabian Style

Yusoff, Muhammad Saiful Anuar, Wan Nazihah Wan Mohamed, Zulkifli Mohamed, and Norhaiyati Abdul Muin. 2022. "Intention to Choose Education Course in UiTM Using Theory of Planned Behaviour (TPB)" Proceedings 82, no. 1: 40. https://doi.org/10.3390/proceedings2022082040

APA Style

Yusoff, M. S. A., Wan Mohamed, W. N., Mohamed, Z., & Abdul Muin, N. (2022). Intention to Choose Education Course in UiTM Using Theory of Planned Behaviour (TPB). Proceedings, 82(1), 40. https://doi.org/10.3390/proceedings2022082040

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