HUMAN CAPITAL IN STEM: THE INFLUENCE OF ATTITUDE, SUBJECTIVE NORM AND PERCEIVED BEHAVIOURAL CONTROL ON CAREER CHOICE
Tiny Chiu Yuen Tey1
Priscilla Moses2
Phaik Kin Cheah3
1,3Universiti Tunku Abdul Rahman Perak.
2Universiti Tunku Abdul Rahman Kajang.
ttcyuen456@gmail.com
Abstract
Malaysia is facing a shortage of human capital in the science, technology, engineering and mathematics (STEM) fields due to low number of school students committing into the STEM stream. The country's goal is to attain 60% of secondary school students enrolling in the STEM stream in upper secondary education instead of the non-STEM stream. The setting of this target is intended to increase the proportion the workforce who are trained in STEM fields. The alarming issue indicates the necessity to reinstate the importance of STEM career choice intention at school level to better address and overcome the challenges in support of nurturing STEM talent pool. Hence, this study aimed to explore the factors that influence secondary school STEM stream students' career choice intention in STEM using the Theory of Planned Behaviour (TPB). A total of 340 Form Four STEM stream students in Malaysia participated in a quantitative survey consisting of 43 seven-point Likert scale items. The data was analysed using standard multiple regression. Through TPB, the results suggested that attitude (beta=.42, p<.0005) was the most significant factor that influenced Form Four science stream students' career choice intention in STEM, followed by perceived behavioural control (beta=.38, p<.0005) and subjective norm (beta=.09, p=0.26). The findings of this study could be considered for the planning of STEM initiatives to reinforce STEM development in Malaysia align with the aspiration to produce the in-demand STEM talents for the workforce.
Keywords: Career choice intention, STEM, theory of planned behaviour
MODAL INSAN DALAM STEM: PENGARUH SIKAP, NORMA SUBJEKTIF DAN KESEDARAN KAWALAN TINGKAHLAKU TERHADAP PILIHAN KERJAYA
Abstrak
Kekurangan modal insan dalam bidang sains, teknologi, kejuruteraan dan matematik (STEM) di Malaysia adalah disebabkan oleh kekurangan bilangan pelajar sekolah yang memilih aliran STEM. Matlamat negara adalah untuk mencapai 60% pelajar sekolah menengah yang mendaftar dalam aliran STEM dalam pendidikan menengah atas dan bukan sebaliknya. Penetapan sasaran ini bertujuan untuk meningkatkan nisbah tenaga kerja yang terlatih dalam bidang STEM. Isu yang membimbangkan ini menunjukkan perlu adanya pemupukan niat keinginan memilih kerjaya dalam STEM di peringkat sekolah bagi memupuk lebih banyak bakat dalam STEM untuk mengatasi cabaran tersebut. Oleh itu, kajian ini bertujuan untuk meneroka faktor-faktor yang mempengaruhi keinginan pemilihan kerjaya dalam bidang STEM di kalangan pelajar sekolah menengah melalui Theory of Planned Behaviour (TPB). Seramai 340 pelajar aliran STEM Tingkatan Empat di Malaysia mengambil bahagian dalam kajian ini. Kajian kuantitatif ini mengandungi 43 item yang diukur menggunakan skala Likert tujuh mata dan data kajian dianalisis menggunakan regresi berganda standard. Hasil kajian menunjukkan bahawa sikap (beta = .42, p <.0005) adalah faktor yang paling signifikan dalam mempengaruhi keinginan memilih kerjaya dalam bidang STEM di kalangan pelajar Tingkatan Empat, diikuti dengan kesedaran kawalan tingkahlaku (beta = .38, p <.0005) dan norma subjektif (beta = .09, p = 0.26). Dapatan kajian ini boleh dipertimbangkan untuk membantu dalam perancangan pelan dan strategi untuk memperkukuhkan pembangunan STEM di Malaysia sejajar dengan aspirasi negara untuk menghasilkan bakat STEM yang diperlukan bagi tenaga kerja.
Kata Kunci: Keinginan memilih kerjaya, STEM, Theory of Planned Behaviour
INTRODUCTION
Quality human capital is essential to support the growth and competitiveness of a country.
Having strong foundation to constantly produce human capital to the science, technology, engineering and mathematics (STEM) workforce is the key to building a skilled and knowledge-intensive nation for sustainable nation growth in the global marketplace (Academy of Sciences Malaysia, 2018; Ministry of Economic Affairs, 2018). According to
Academy of Sciences Malaysia (2016), many advanced countries comprise approximately 30% of STEM workforce out of the respective total workforce. In contrast, the current STEM workforce in Malaysia only constitutes around 15% of its total labour market (Academy of Sciences Malaysia, 2018). It was also reported that Malaysia will need eight million workers in the STEM labour force by the year 2050 to meet market demands. In view of the current pool of STEM talents, it is expected that Malaysia will not be able provide the in-demand human capital to the workforce (Shahali, Ismail, & Halim, 2017).
Recent years, the growth STEM talent pool has been a priority to accelerate STEM human capital development for the workforce in Malaysia (Academy of Sciences Malaysia, 2018; Ministry of Economic Affairs, 2018). One of the major initiatives taken was the adoption of the Standard Curriculum for Secondary Schools (Kurikulum Standard Sekolah Menengah, KSSM) to replace the Integrated Secondary School Curriculum (Kurikulum Bersepadu Sekolah Menengah, KBSM) since 2017 (Ministry of Education [MoE], 2013, 2016a). Through the implementation of KSSM, STEM elective subjects have been introduced to the curriculum at the upper secondary school level (MoE, 2013, 2016a, 2016b). After students complete lower secondary school at Form Three, they are given the chance to choose either STEM or non-STEM stream at the upper secondary level, hence the beginning of their subsequent academic and career pathway (Academy of Sciences Malaysia, 2018).
Besides, under the first National Science and Technology Enrolment Policy, the target ratio of 60:40 science-to-non-science students in schools has been in place since the 1970s to ensure a rich supply STEM talents to the labour pool (Academy of Sciences Malaysia, 2016;
Curriculum Development Division, 2016; MoE, 2013). Despite having implemented the policy for half a century, the goal has yet to be achieved because non-STEM students have always outnumbered STEM students. The ratio of STEM to non-STEM was reported to have gradually dropped in since the year 2010. The ratio was 48:52 in 2010, 45:55 in 2011 (MoE, 2013), 47:53 in 2014 (Academy of Sciences Malaysia, 2016; Chin, 2017), 42:58 in 2016 and 41:59 in 2017 (Curriculum Development Division, 2016; Educational Planning and Research Division, 2017; Hamid, 2017; MoE, 2013).
It is evident that are gaps along the STEM talent supply from schools to the actual workforce. The undesirable trend shrinks the STEM talent pool for subsequent STEM training at tertiary education and hinders the human capital supply along the pathway to STEM careers
(Academy of Sciences Malaysia, 2018). Besides, the Ministry of Economic Affairs (2018) also highlighted the importance to focus on the urgent need to match the demand and supply between the education system and actual STEM workforce. Therefore, the main objective of this study was to investigate the factors that influence secondary school STEM stream students' career choice intention in STEM.
LITERATURE REVIEW
Past studies discussed career choices involving a wide range of factors and predictors such as academic performance, monetary reward, interest, social status, social-cultural influence, as well as biological and contextual influence (Wang & Degol, 2013; Shahali, Halim, Rasul, Osman, & Zulkifeli, 2017; Xu, 2013).
In Malaysia, various studies were conducted to identify the factors that influence career choice among students in the educational context. Among the popular variables in discussions were attitude toward the behaviour (Ambad & Damit, 2016; Mohd, Salleh, &
Mustapha, 2010), subjective norm (SN) (Faitar & Faitar, 2013; Hsiao & Nova, 2016; Wahid, Suhairom, Zulkifli, & Nasir, 2018; Zhang & Huang, 2018) and perceived behavioural control (PBC) (Ambad & Damit, 2016; Autio, Keeley, Klofsten, Parker, and Hay, 2001). These variables are reflected in the Theory of Planned Behaviour (TPB) (Ajzen, 1991) which entails attitude toward the behaviour with SN and PBC as the antecedents of behavioural intention.
The literature revealed that TPB has been employed expansively by researchers to predict various types of intention and behaviour (Teo & Lee, 2010; Mishkin, Wangrowicz, Dori, & Dori, 2016). TPB has been used to examine intention and behaviour in relation to career choice (Akmaliah & Hisyamuddin, 2009; Krupat, Camargo, Strewler, Espinola, Fleenor, & Dienstag, 2017), and in the context of STEM education (Lin & Williams, 2016;
Mishkin et al., 2016). In recent literature, it was reported that attitude, SN and PBC in TPB were influential predictors of students' career choice intention (Ambad & Damit, 2016; Krupat et al., 2017). As such, this study aimed to examine the factors that influence STEM career choice intention among STEM stream secondary students with TPB as the theoretical framework.
Theory of Planned Behaviour
According to Ajzen (1991), TPB (as shown in Figure 1) explains an individual's decision- making processes via the individual's intention to execute a specific behaviour. Intention is the most powerful predictor of actual behaviour in TPB (Ajzen, 1991; Teo, 2011). In essence, an individual's intention to execute choice and behaviour can be predicted by intention which are determined by attitude toward the behaviour, SN and PBC (Ajzen, 1991; Mishkin et al., 2016;
Teo, 2011).
Figure 1. Theory of Planned Behaviour (Ajzen, 1991)
Intention is an indication of how hard an individual is willing to try, and how much effort the individual attempts to perform the behaviour (Ajzen, 1991; Teo, 2011). Ajzen (1991) also proposed that intention is the immediate antecedent and behavioural disposition to a particular behaviour. Attitude, SN and PBC function independently to form behavioural intention, and intention is the most proximal determinant that will lead to a behaviour (Ajzen, 1991, 2002; Kyle, White, Hyde, Osborne, & Albert, 2014). In line with the scope of the present study, intention is operationalised to career choice intention (CCI) which refers to a secondary school student's willingness and plan to choose a career in STEM.
On the other hand, attitude toward the behaviour in TPB refers to the behavioural beliefs about the consequences towards the execution of a particular behaviour or choice (Ajzen, 1991). Attitude toward the behaviour is the degree to which an individual reflects a favourable or unfavourable evaluation towards performing a certain behaviour (Ajzen, 1991,
2002; Kyle et al., 2014; Mishkin et al., 2016). According to Ajzen (1991, 2002), attitude toward the behaviour is guided by behavioural beliefs. This salient which takes into the considerations on beliefs about the expected consequences of a particular behaviour. In this study, attitude toward the behaviour is specified as attitude toward career choice (ACC) align with the scope of study. Thus, ACC refers to a secondary school student's favourable or unfavourable evaluation towards choosing a career in STEM.
Ajzen (1991, 2002) defined SN as perceived social influence associated with normative beliefs which lead to the intention to perform a behaviour. SN is a social factor oriented term which is defined as an individual's perceived social pressure from important others to perform or avoid a certain behaviour (Ajzen, 1991, 2002; Kyle et al., 2014; Mishkin et al., 2016). SN is resulted from normative beliefs which are related to the normative expectations of other people (Ajzen, 1991, 2002). SN in the present study indicates the social pressure and influence perceived from important people, namely teachers, parents and peers by a secondary school student whether to choose a career in STEM or not.
PBC in TPB is influenced by an individual's control beliefs that facilitate or hamper the execution of a behaviour. Intention refers to how much of effort an individual plans to execute a particular behaviour (Ajzen, 1991, 2002). According to Ajzen (1991), PBC refers to the extent of perceived ease or difficulty of performing a certain behaviour, as well as an individual's ability and control over a particular behaviour based on the individual's experience and anticipated challenges and obstacles (Ajzen, 1991, 2002; Kyle et al., 2014;
Mishkin et al., 2016). Control beliefs which constitute the basis of PBC explain the presence of factors that facilitate or hinder the occurrence of certain behaviour (Ajzen, 1991). Hence, PBC in the present study refers to a secondary school student's confidence, ability, control and perception whether it is easy or difficult to choose a career in STEM.
In this study, behaviour in the TPB indicates students' actual career choice, was not measured because this study focused on the influence of ACC, SN and PBC on CCI in STEM among students who are yet to join the actual workforce. Therefore, the following hypotheses were proposed align with the objective of this study:
H : Attitude toward career choice (ACC) has a significant influence on career choice O1
intention (CCI.)
H : SN has a significant influence on career choice intention (CCI).O2
H : PBC has a significant influence on career choice intention (CCI).o3
METHODOLOGY
This study employed a quantitative approach to test the research hypotheses. A survey questionnaire was used to examine the influence of ACC, SN and PBC on CCI among Form Four STEM stream students. A panel of three experts in relevant research areas reviewed the questionnaire for its face and content validity. The questionnaire was then improved.
Prior to data collection, cognitive interviews were conducted to assess the quality of the draft questionnaire and determine if the items generated the information align with research objectives (Beatty & Willis, 2007). A total of fifteen Form Four STEM stream students participated in the cognitive interviews and provided feedback on the draft questionnaire. The questionnaire was subsequently revised based on the results from the cognitive interviews prior to data collection.
As a result, the self-report questionnaire consisted of Part A and Part B. The respondents were required to fill out their demographic information in Part A such as date of birth, and name of school. Part B comprised 43 items measuring ACC, SN, PBC and CCI respectively. Each item was measured on a seven-point Likert scale with 1= Disagree to 7=
Agree.
A total of 340 questionnaires were collected from Form Four STEM stream students from Selangor, Perlis, Perak, as well as federal states Kuala Lumpur and Putrajaya from October 2018 to January 2019.
Table 1 shows the Cronbach's Alpha values for all the constructs ranged from .72 to .93, which were above 0.7, suggesting the constructs had good internal consistency within the sample of this study.
Table 1
Instrument reliability
FINDINGS
The data was analysed using standard multiple regression (SMR) with Social Science Statistical Package (SPSS) 23. A SMR analysis was conducted to examine the influence of ACC, SN and PBC on CCI. Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity and homoscedasticity.
As shown in Table 2, ACC, SN and PBC explained 56.2% (R Square=.562) of the variance in CCI in the TPB. Besides, Table 3 shows the model in this study reached statistical significance at p<.0005.
Table 2
Model summaryb
a. Predictors: (Constant), PBC, SN, ACC b. Dependent Variable: CCI
Table 3 ANOVAa
a. Dependent Variable: CCI
b. Predictors: (Constant), PBC, SN, ACC
The results in Table 4 suggest that ACC (beta=.42, p<.0005) had the strongest significant factor that influenced Form Four science stream students' career choice intention in STEM, followed by PBC (beta=.38, p<.0005) and SN (beta=.09, p=0.26).
Table 4 Coefficientsa
a. Dependent Variable: CCI
Table 5 is a summary of the research results according to the hypotheses proposed in this study. In sum, all hypotheses in this study were supported by the statistical results in findings. Figure 2 depicts the research model of this study with ACC, SN and PBC as statistically significant antecedents that predict secondary school students' CCI in STEM.
Table 5
Summary of results
* p<.05
Figure 2. Theory of Planned Behaviour for STEM Career Choice Intention among Secondary School Students in Malaysia
DISCUSSION AND CONCLUSION
The aim of this study was to investigate the STEM stream secondary school students' CCI in STEM through TPB. Since there is an urgent need to bridge the gap between the Malaysian education system and its STEM workforce, it is important to identify the factors that influence secondary school students' career choices in STEM. Overall, the findings evidenced that ACC, SN and PBC had statistical significant influence on CCI among STEM stream secondary school students in Malaysia. This study also found that the combination of all the
three predictors in TPB, namely ACC, SN and PBC explained 56.2% of the variance in CCI.
From the results, it can be concluded that TPB is a powerful theoretical model to predict STEM stream secondary school students' career selection in Malaysia.
First, ACC is a significant predictor of students' CCI in STEM. This finding is consistent with Ambad and Damit (2016) which also found that attitude had significant influence on students' intention. As ACC refers to the students' favourable or unfavourable evaluation towards choosing a career in STEM, thus it is suggested that students' ACC, the greater their intention to choose a career in STEM. Second, this study has a similar finding to Faitar and Faitar (2013), Hsiao and Nova (2016), Wahid et al. (2018), and Zhang and Huang (2018) that SN had significant influence on CCI. SN in this study refers to influence perceived from teachers, parents and peers, hence it can be concluded that teachers, parents and peers had significant influence on students' choice of career in STEM. Third, PBC showed significant influence on students' CCI in STEM. It could be suggested that students' intention to choose a career in STEM can be influenced by their confidence, ability, control and perception whether it is easy or difficult to choose a career in STEM. This finding echoes with the finding in Autio et al. (2001) which reported that PBC was a strong determinant of intention.
The empirical findings would contribute to the understanding of STEM career choices among the secondary school students in Malaysia. As this study identified the factors that influenced the students' career choices in STEM, it would be able to provide meaningful data about secondary students' choices of career in STEM who are currently under the support of the present Malaysian education system. The research findings would be useful for the MoE, policy makers, educators, researchers and stakeholders to better prepare effective strategies and approaches to produce the highly in-demand STEM workforce in Malaysia.
There are a number of limitations in this study. First, this study was scoped to upper secondary school students. However, this study only focused Form Four students due to restrictions in terms of access. Researchers were advised against involving Form Five students in this study to avoid distracting them from their Malaysian Certificate of Education (SPM) exam preparations. For this reason, the representativeness of the study was affected, thus the findings can only be generalised to Form Four STEM stream students in Malaysia.
Besides, the data was collected through a self-report survey which could have caused common method variance. A qualitative approach such as focus group interview and grounded theory study could potentially provide more in-depth details and underlying factors that are yet to be explored. Future studies may explore other potential variables to examine students' career choices in STEM or integrate the additional relevant predictors to TPB for theory advancement.
REFERENCES
Academy of Sciences Malaysia. (2016). Science outlook 2015: Action towards vision, executive summary 2015. Kuala Lumpur, Malaysia: Academy of Sciences Malaysia.
Academy of Sciences Malaysia. (2018). Science outlook 2017: Converging towards progressive Malaysia 2050. Kuala Lumpur, Malaysia: Academy of Sciences Malaysia.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665-683.
Akmaliah, L. P. Z., & Hisyamuddin, H. (2009). Choice of self-employment intentions among secondary school students. Journal of International Social Research, 2(9), 539-549.
. http://dx.doi.org/10.1016/S2212-5671(16)30100-9
Beatty, P. C., & Willis, G. B. (2007). Research synthesis: The practice of cognitive interviewing. Public Opinion Quarterly, 71(2), 287-311.
http://dx.doi.org/10.1093/poq/nfm006
Chin, C. (2017, July 23). Fewer women opt for STEM. The Star Online.
https://www.thestar.com.my/news/nation/2017/07/23/fewer-women-opt-for-stem-malaysia- records-low-female-enrolment-in-science-stream/
Ambad, S. N. A., & Damit, D. H. D. A. (2016). Determinants of entrepreneurial intention among undergraduate students in Malaysia. Procedia Economics and Finance, 37, 108- 114
Autio, E., H. Keeley, R., Klofsten, M., Parker, G. G. C., & Hay, M. (2001). Entrepreneurial intent among students in Scandinavia and in the USA. Enterprise and Innovation Management Studies, 2(2), 145-160.
Curriculum Development Division, Ministry of Education Malaysia. (2016). Sharing malaysian experience in participation of girls in STEM education. Geneva, Switzerland, UNESCO International Bureau of Education (IBE). Retrieved 10 January 2018 from http://unesdoc.unesco.org/images/0024/002447/244714e.pdf
Educational Planning and Research Division. (2017). Malaysia educational statistics.
Putrajaya, Malaysia: Ministry of Education.
Faitar, G. M., & Faitar, S. L. (2013). Teachers' influence on students' science career choices.
American International Journal of Social Science, 2(5), 10-16.
Hamid, A. J. (2017, August 20). Why do kids avoid the STEM route? New Straits Times.
https://www.nst.com.my/opinion/columnists/2017/08/270000/why-do-kids-avoid-stem-route Hsiao, J., & Nova, S. P. D. C. C. (2016). Generational approach to factors influencing career
choice in accounting. Revista Contabilidade & Finanças, 27(72), 393-407.
Krupat, E., Camargo, C. A., Strewler, G. J., Espinola, J. A., Fleenor, T. J., & Dienstag, J. L.
(2017). Factors associated with physicians' choice of a career in research: A retrospective report 15 years after medical school graduation. Advances in Health Sciences Education, 22(1), 5-15. https://doi.org/10.1007/s10459-016-9678-5
Kyle, V. A., White, K. M., Hyde, M. K., & Occhipinti, S. (2014). The role of goal importance in predicting university students' high academic performance. Australian Journal of E d u c a t i o n a l & D e v e l o p m e n t a l P s y c h o l o g y , 1 4 , 1 7 – 2 8 . www.newcastle.edu.au/journal/ajedp/
Lin, K. Y., & Williams, P. J. (2016). Taiwanese preservice teachers' science, technology, engineering, and mathematics teaching intention. International Journal of Science and Mathematics Education, 14(6), 1021-1036. http://dx.doi.org/10.1007/s10763-015-9645-2
Ministry of Economic Affairs. (2018). Mid-term review: Eleventh malaysia plan 2016-2020 new priorities and emphases. Putrajaya: Federal Government Administrative Centre, Malaysia. Retrieved from https://www.talentcorp.com.my
Ministry of Education. (2013). Malaysia education blueprint 2013-2025. Putrajaya: Ministry o f E d u c a t i o n , M a l a y s i a . R e t r i e v e d f r o m https://www.moe.gov.my/index.php/en/dasar/pelan-pembangunan-pendidikan-malaysia- 2013-2025
Ministry of Education. (2016a). Buku penerangan kurikulum standard sekolah menengah ( K S S M ) . P u t r a j a y a : G o v e r n m e n t o f M a l a y s i a . R e t r i e v e d f r o m https://www.moe.gov.my
Ministry of Education. (2016b). Panduan perlaksanaan sains, teknologi, kejuruteraan dan Matematik (STEM) dalam pengajaran dan pembelajaran. Putrajaya: Ministry of Education, Malaysia. Retrieved from https://cms.mrsm.edu.my/cms/index.jsp
Mishkin, H., Wangrowicz, N., Dori, D., & Dori, Y. J. (2016). Career choice of undergraduate engineering students. Procedia-Social and Behavioral Sciences, 228, 222–228.
https://doi.org/10.1016/ j.sbspro.2016.07.033
Mohd, F., Salleh, A. M., & Mustapha, R. (2010). The influence of contextual aspects on career decision making of Malaysian technical students. Procedia-Social and Behavioral Sciences, 7, 369-375. https://doi.org/10.1016/j.sbspro.2010.10.050
Shahali, E. H. M., Halim, L., Rasul, M. S., Osman, K., & Zulkifeli, M. A. (2017). STEM learning through engineering design: Impact on middle secondary students' interest towards STEM. EURASIA Journal of Mathematics, Science & Technology Education, 13(5), 1189-1211. https://doi.org/10.12973/eurasia.2017.00667a
Shahali, E. H. M., Ismail, I., & Halim, L. (2017). STEM education in Malaysia: Policy, trajectories and initiatives. Asian Research Policy, 8(2), 122–133.
http://www.arpjournal.org/usr/browse/list_issues_detail.do?seq=27
Teo, T. & Lee, C. B. (2010). Examining the efficacy of the theory of planned behavior (TPB) to understand pre-service teachers' intention to use technology. In C.H. Steel, M.J.
Keppell, P. Gerbic & S. Housego (Eds.), Curriculum, technology & transformation for an unknown future. Proceedings ascilite Sydney 2010, 968-972.
Teo, T. (2011). Factors influencing teachers' intention to use technology: Model development and test. Computers and Education, 57(4), 2432-2440.
Wahid, N. H. A., Suhairom, N., Zulkifli, R., & Nasir, A. N. M. (2018). The influence of parents ethnicity on agricultural students career choice. Advanced Science Letters, 24(4), 2769- 2772. http://dx.doi.org/10.1166/asl.2018.11055
Wang, M. T. & Degol, J. (2013). Motivational pathways to STEM career choices: Using expectancy-value perspective to understand individual and gender differences in S T E M f i e l d s . D e v e l o p m e n t R e v i e w , 3 3 , 3 0 4 - 3 4 0 . http://dx.doi.org/10.1016/j.dr.2013.08.001
Xu, Y. J. (2013). Career outcomes of STEM and non-STEM college graduates: Persistence in majored-field and influential factors in career choices. Research in Higher Education, 54(3), 349-382. https://doi.org/10.1007/s11162-012-9275-2
Zhang, H., & Huang, H. (2018). Decision-making self-efficacy mediates the peer support–career exploration relationship. Social Behavior and Personality: An International Journal, 46(3), 485-498.
