Microsoft Word - c8900 Full Issue 12Dec.docx Journal of Education, 2022 Issue 89, http://journals.ukzn.ac.za/index.php/joe doi: http://dx.doi.org/10.17159/2520-9868/i89a06 Online ISSN 2520-9868 Print ISSN 0259-479X Influence of selected social factors on career decision- making of grade 12 learners in township secondary schools in South Africa Oluwakemi B. Ajayi Wits School of Education, University of the Witwatersrand, Johannesburg, South Africa Kemiajayia@gmail.com https://orcid.org/0000-0002-1446-2906 Moeniera Moosa Wits School of Education, University of the Witwatersrand, Johannesburg, South Africa Moeniera.Moosa@wits.ac.za https://orcid.org/0000-0002-6231-9370 Peter JO Aloka Wits School of Education, University of the Witwatersrand, Johannesburg, South Africa Peter.aloka@wits.ac.za https://orcid.org/0000-0002-4298-9211 (Received: 18 October 2021; accepted: 7 June 2022) Abstract Career decision-making is a challenge to most learners in secondary schools in South Africa. In this study, we examined the influence of selected social factors (influence of older siblings, peer influence, teachers’ influence, and career information services) on career decision-making of Grade 12 learners in township secondary schools in South Africa. We adopted a correlational survey research design. The sample size of 260 learners was obtained using the stratified random sampling technique. The questionnaire that included reference to peer influence, teachers’ influence, career information service, influence of older siblings, and career decision- making was used to collect data. We used Cronbach’s alpha coefficient analysis to measure the internal consistency of the questionnaire; all sub-scales had excellent internal consistent reliability. We used the Kaiser- Meyer-Oklin measure of sample adequacy (KMO Index) and the Bartlett’s Test of Sphericity to confirm internal validity. We analysed quantitative data using inferential statistics such as Pearson Product Moment Correlation, linear, and multiple regression analysis. According to the findings, the strongest correlation was between teacher influence and career decision-making (r=.643, n=204, p.01), followed by the relationship between career information services and career decision-making (r =.607, n=204, p.01) while peer influence had the least relationship to career decision-making (r (204) =.514, p.01. The influence of older siblings also had a significant direct relationship with career decision-making among the Grade 12 learners (r=.566, n=204, p<.01). We recommend that teacher counsellors adopt a multifaceted approach in developing career decision making programmes for learners in secondary schools. Keywords: social factors, decision making, career, grade 12, secondary school, township schools 106 Journal of Education, No. 89, 2022 Introduction Secondary school learners confront a significant barrier in making career decisions throughout their lives. Career development is an important component of psychological and social development and is an important element of human growth (Baglama & Uzunboylu, 2017). A career is a set of work functions that a person encounters throughout the course of their life (Super, 1980). Career development is any activity made in the career decision- making process, whereas career choice is the start of a certain occupation or vocation (Baruch et al., 2015). A person’s lifestyle, as well as personal and professional fulfilment, have an impact on career choices (Betz & Taylor, 2006). A process-oriented approach that explores how people decide is defined as career decision-making along with the events that lead to professional choices (Levin et al., 2020). Gati (1996) pointed out that the career decision- making process has some distinct characteristics, such as the fact that an individual can choose from a wide range of career options and that there is a wealth of information available for each career option. Furthermore, various aspects of the profession should be considered. The South African education system is in the process of modernising and correcting the educational disparities created by the apartheid era. During this transitional time, all learners in South African secondary schools are expected to obtain a quality and equitable education that will serve as a basis for future career development. Township learners in South African secondary schools are currently choosing careers in a shrinking economy in which unemployment is rising and affirmative action initiatives aimed at reversing prior inequities in employment prospects to allow for systemic equity are shaky (Karlsson & Moberg, 2013). Personal desires, rather than the needs of the people, drive South African society and this is at odds with African traditions (Maree & Van der Westhuizen, 2011). A suggestion from the Third International Mathematics and Science Study, in which South Africa came in last, underlined the need to improve the subject choices of South African students (Reddy et al., 2016). The South African Department of Higher Education encourages school and parent engagement in secondary school students’ subject choices and suggests that more research be done on the factors that influence these choices and, eventually, career decisions (Department of Higher Education, 2012). Enache and Matei (2017) emphasised the importance of organised activities between and among the government, parents, and schools to provide learners with the necessary resources and an environment that supports and motivates learners to make the right career decisions. Theoretical framework John Krumboltz’s Social Learning Theory of Career Choice influenced this research. This theory explains how social elements such as the environment, learning experiences, and task approach abilities influence children’s career choices (Krumboltz et al., 1976; Schofield, 2017). Environmental factors include education, culture, economic standing, and political inclination, all of which may be associated with decision-making (Schofield, 2017). While task approach skills are learned, learning experiences are the role models that are crucial to forming the individual’s perspectives about careers and their own professional path Ajayi et al.: Influence of selected social factors on career decision-making . . . 107 (Schofield, 2017). According to this theory, the goal of career counsellors should be to assist individuals in identifying their career views and understanding how social factors influence them (Krumboltz et al., 1976). This theory fills the void left by Holland’s career choice theory that focused solely on personality traits and influenced the current study because it considers factors like environment, learning experiences, and task approach skills to be significant when one is making career decisions, whereas social factors like parental influence, peer influence, teacher influence, and the influence of older siblings are included in the three broad factors of social learning theory. Literature Review Literature on teachers’ influence on career choices exists but with varied points of view. In Pakistan, for example, Khan et al. (2012) found that students regard their instructors as role models and place a high value on their career advice and counselling. In a study conducted in South Africa by Shumba and Naong (2012), educators were found to be major influences on learners’ job choices and goals. In Kenya, Njeri (2013) found that teachers as role models had the greatest influence on career aspirations. In contrast, Mungahu (2013) reported that students were of the opinion that teachers’ influence did not affect their career choices at university. In Nigeria, Akinjide and Sehinde (2011) found that teachers play a major role in influencing learners towards attaining career choice preparedness. Moreover, Georgiana (2015) added that teachers need to carry the responsibility of guiding learners towards career choice preparedness. According to Knefelkamp and Slepitza (1976), a teacher educator might find it advantageous to require students to engage in the investigation of alternative vocations that still have a teaching component, such as coaching, tutoring, administrating, or counselling. In South Africa, Abe and Chikoko (2020) discovered that educators may help students make decisions that reflect students’ values and experiences by understanding students’ perspectives on career decision-making. Furthermore, learners’ career choices and aspirations are influenced by the support of their families and teachers. Literature indicates that parents influence the career decisions of learners. Bojuwoye and Mbanjwa (2006) discovered that factors like high parental expectations of children and appropriate family communication, as well as factors like the prestige status of some occupations, school curricular subjects, academic performance, teacher influences, and peer pressure all had sturdy positive influences on career choices. Tillman (2015) found that children of educators had slightly more parental influence on their profession choices than children of non-educators. According to Akosah-Twumasi et al. (2021), students had a significant need to acquire parental approval, and regardless of whether this approval was obtained early or later, prioritising family responsibilities and commitments was the main focus for all participants. Allowing students to negotiate or even override their parents’ preferences in choosing a career path may exacerbate the already difficult career decision-making process of young people, particularly if their parents are adamant about maintaining their heritage cultural practices (Akosah-Twumasi et al., 2018). Similarly, Kumar (2016) discovered that parents have a considerable influence on their children’s choices of a profession. The impact of a father’s influence on a student’s decision 108 Journal of Education, No. 89, 2022 about a profession choice was found to be greater than that of the mother. Whiston and Keller (2004), however, found that the influence was indirect, owing to factors such as student occupational expectations that influenced career choice. According to some scholars, learners’ career decisions are influenced by their peers. In Zimbabwe, for example, Mtemeri (2020) found that students are impacted by their peers in a variety of ways while they are selecting careers. Peer advice, encouragement, and education were the most important predictors. Students, however, disputed that they seek peer approval for their career choices. In China, Yi-Hui (2006) discovered that student contacts with peers having various interests, and being of different races and origins can promote reflection, knowledge, and beliefs that lead to new ways of thinking about the world, other peers, and eventually, about themselves. Similarly, in Finland, Kiuru (2008) highlighted the significance of peer contact when he noted that the academic direction of the individual teenager’s career path may be influenced in the long run by the peer group to which they belong. In Kenya, Okiror and Otabong (2015) stated that students seek mentorship, information, and guidance on professional concerns from peers who have had comparable experiences, especially when traditional routes such as school career guidance are not functioning well. Peer interactions were shown to be a crucial component in helping students choose jobs in a Nigerian study by Bankole and Ogunsakin (2015). Peers and friends influence career choice making regarding professional careers, job selection, employment prospects, and earning tendencies (Naz et al., 2014). In the social sciences, however, Alika (2011) found no significant association between peer group influence and career choice. Conger and Little (2010) found that older siblings serve as role models for younger siblings in terms of how to navigate these transitions successfully, and that younger siblings gain from their older siblings’ positive and negative experiences, as well as information about the nature of these transitions. According to Mileksky (2005), those who have sibling back-up have higher life contentment and sense of worth as well as lower rates of depression and loneliness. Sibling social support is also a powerful compensation for low peer and parental support. Peer attachments also influence learners’ self-efficacy in making career decisions, according to Wolfe and Betz (2004). Furthermore, according to Spudich (2014), the quality of the relationship between twins who chose the same job path reflected affection and intimacy. The comfortable and reassuring aspect of their relationship was similarly beneficial in leading them to the same occupation, according to participants. For Schultheiss et al. (2002), social support, comprised of emotional support, social integration, esteem support, and information support, is heavily influenced by the most important sibling, i.e., the one who is considered closest. Literature also indicates that career information in schools influences the career decisions of learners. For example, Datar and Ahmad (2019) showed that career information services can help students better comprehend their options. This suggests that, if the career information service is introduced, learners’ understanding of careers will improve. Moreover, Muttaqin et al. (2017) concluded that one of the benefits of career information services is to improve students’ career understanding. Similarly, Oats and Rukewe (2020) revealed that the dynamic Ajayi et al.: Influence of selected social factors on career decision-making . . . 109 nature of the job choosing and planning process influences students’ career decisions, and that, as a result, students want career counselling and information in order to make educated and prudent decisions. Witko et al. (2005) revealed that students in all grades acknowledged the presence and importance of career counselling services but desired more information about available courses, post-secondary education, and other support for career planning. Similarly, Bloxom et al. (2008) confirmed the availability of career development programs that did not meet students’ needs and called for effective career and life planning educational programs. In contrast, Mesa (2013) found that students, to a large extent, do not have access to career information to make realistic plans for their future, while some are unaware of career and guidance training opportunities at various levels of post-secondary school education. Mekgwe (2010) concluded that limited time, lack of trained personnel, lack of key career exploration activities and resource materials in schools hindered effective career service delivery. Amoah et al. (2015) reported that students strongly agreed that all forms of career guidance and counselling provided by their school influenced their decisions. Dabula and Makura (2013), in South Africa, revealed that such a programme helped students overcome their fears, confusion, and lack of confidence in the process of making career choices in their respective schools. In Kenya, Getange and Sagwe (2016) reported that students received little or no career guidance because of the inadequate training of the teachers, too few career guidance sessions, and, in some schools, none at all. Moreover, Ojiah et al. (2015) found that guidance and counselling services are not available in all schools and recommended that stakeholders in education should make efforts to extend the services to all schools and ensure, through regular monitoring, that counsellors are doing their jobs. Many learners in township schools in South Africa are assumed to lack adequate information about career options, so their choices are deeply rooted in their perception of the ideal vocation, the subjects they choose in Grade 10 in secondary school, and the factors that may be related to social ones, that influence them. Furthermore, there is very little literature in South Africa relating to studies on learner career decision-making. As a result, the purpose of this study was to look into the social elements that influence Grade 12 learners’ career decisions in township secondary schools in Gauteng, South Africa. The present study This study examined the influence of selected social factors on the career decision-making of Grade 12 learners in township secondary schools in South Africa. Research hypotheses The following research hypotheses were proposed and tested: Ho1: There is no significant peer influence on career decision-making among the Grade 12 learners. Ho2: There is no significant teachers’ influence on career decision-making among the Grade 12 learners. 110 Journal of Education, No. 89, 2022 Ho3: There is no significant influence of career information service on career decision-making among the Grade 12 learners. Ho4: There is no significant influence of older siblings on career decision-making among the Grade 12 learners. Methods Research design We collected and analysed data using a correlational survey study approach. The statistical test used to detect the tendency or trend for two (or more) variables or sets of data to fluctuate consistently is known as correlation (Creswell, 2012). For this study, a correlational design was best since it allowed two variables to indicate whether they had a positive or negative association. This design aids in the prediction of scores and the explanation of the link between factors. Study participants The study’s target demographic was 720 male and female learner responders, 120 from each of the six schools chosen. The participants were chosen using a stratified random selection procedure. As a result, 260 learners were chosen as the sample size for this study, based on the population (720) proposed by Krejcie and Morgan (1970). Furthermore, by taking into account criteria such as the sex of the Grade 12 learners, stratification contributed to obtaining a suitable and equitable number of participants. As a result, this sampling approach was employed to ensure that each school in the sample size for this study was appropriately represented. Research tools We used questionnaires to collect data on the social factors and career decision-making among learners. The social factors contained in the questionnaire as constructs included peer influence, teachers’ influence, career information service, and influence of older siblings. The two items on the peer influence questionnaire were “I take important decisions without being influenced by my friends’ suggestions” and “I like to choose a career of my own, irrespective of my friends’ advice.” Two items on the teachers’ influence questionnaire were “Information I got from my teacher helped me to choose a career” and “My teacher informs me about different opportunities.” Two items on the career information service questionnaire were “School career days influenced my career choice” and “I spoke to a career counsellor at my school about a career.” Two items on the influence of older siblings’ questionnaire were “I often go to my older sibling(s) for support and advice” and “My older sibling(s)’ career choice(s) influence my career direction.” The responses on social factors are indicated in a 5- point Likert scale, Strongly Disagree (1), Disagree (2), Neutral (3), Agree (4), and Strongly Agree (5). The dependent variable, career decision-making, was also measured using 18 items on the career decision-making scale of which some were “I have decided on a career Ajayi et al.: Influence of selected social factors on career decision-making . . . 111 and feel comfortable with it”, “Several careers have equal appeal to me. I’m having a difficult time deciding among them” and “If I had the skills or the opportunity, I know what I would be but this choice is really not possible for me. I haven’t given much consideration to any other alternatives.” The responses on social factors are indicated in a 4-point Likert scale, Exactly like me (1), Very much like me (2), Only slightly like me (3), and Not at all like me (4). The internal consistency of the questionnaire was measured using Cronbach’s alpha coefficient analysis that is the most consistent test of inter-item consistency reliability for Likert scaled or rating scaled questionnaires. Table 1 Internal Consistency: Cronbach’s Alpha Results for the Questionnaires Scale No. Items Cronbach’s Alpha Item (s) deleted Conclusion (Reliable/Unreliable) • Peer Influence 3 .737 None Good • Teacher Influence 3 .701 None Good • Career Information Service 3 .736 None Good • Influence of Older Siblings 6 .792 None Good Career Decision-Making 5 .842 None Excellent Furthermore, while the Cronbach’s alpha values for the social factor sub-scales varied, all the values showed sufficient internal consistent reliability, with the teachers’ influence sub-scale having the lowest coefficient value of .701 and the influence of older siblings’ sub-scale having the highest coefficient value of .792. Similarly, the internal consistent reliability of the career decision-making sub-scale and the problems in career decision sub-scale was excellent, as evidenced by Cronbach’s alpha values of .842 and .911, respectively. The survey data was suitably checked using the Kaiser-Meyer-Oklin measure of sampling adequacy (KMO Index) and the Bartlett’s Test of Sphericity, as shown in Table 2. Table 2: KMO and Bartlett’s Test of social factors Sub-scale Kaiser-Meyer-Oklin (KMO index) Bartlett’s Test for Sphericity Approx. Chi-Square df Sig. Social Factors .761 581.404 45 .000 • Peer Influence .522 76.543 10 .000 • Teacher Influence .714 176.671 10 .000 • Career Information Service .570 97.254 10 .000 112 Journal of Education, No. 89, 2022 Sub-scale Kaiser-Meyer-Oklin (KMO index) Bartlett’s Test for Sphericity Approx. Chi-Square df Sig. • Influence of Older Siblings .657 146.511 10 .000 Career Decision-Making .848 1327.956 153 .000 Table 2 shows that the Bartlett’s test for sphericity is significant (p0.001, p=0.000) and the Kaiser-Meyer-hold Olkin indices are all >.6 for all the questionnaire’s subscales. As a result of the findings, it was reasonable to assume that the data had enough internal validity and hence could be used for further analysis. Procedure This work was first given ethical approval by the University of the Witwatersrand’s Human Research Ethics Committee. We then got ethical permission from the Gauteng Department of Education in order to gain access to the secondary schools that were sampled. After gaining authorisation from the Gauteng Department of Education, the researchers told the principals of the six secondary schools of their intention to conduct the study. This research was conducted in accordance with ethical standards. Because some of the Grade 12 students were minors, they were asked to sign a consent form agreeing to engage in the study, and only those who returned the consent form were eligible to participate. Learners were advised that their participation in the study was completely optional and that they could drop out at any time. Furthermore, given our use of pseudonyms for participants and schools, participant anonymity and confidentiality were preserved at all times. The questionnaires were given out in person in the classroom with the help of the teacher in charge to ensure that the completed questionnaires were returned; they took 30 to 45 minutes to complete. Data analysis Quantitative data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) computer program version 23. Pearson Product Moment is an example of an inferential statistic. The relationship between the research variables was investigated using correlation, linear, and multiple regression analysis, for example career decision-making and self-efficacy. The hypotheses were tested at the 0.05 level of significance. Results The study examined the influence of selected social factors on career decision-making of Grade 12 learners in township secondary schools in South Africa. We present the results for both descriptive and inferential analysis using tables to indicate correlations among tested variables. The hypothesis that stated that “there is no significant relationship between social factors and career decision-making of Grade 12 learners in township secondary schools” was tested. The social factors investigated include the influence of older siblings, peer influence, teachers’ influence, and career information services. The career decision-making was the Ajayi et al.: Influence of selected social factors on career decision-making . . . 113 response variable while social factors constituted the predictor variable. First, the correlation between the aspects of social factors and career decision making was calculated to determine the direction and magnitude of the linear relationships, as shown in Table 3. Table 3 Correlations between Social Factors and Career Decision-Making Correlations 1 2 3 4 5 Career Decision-making (1) 1 .514** .643** .607** .566** Peer Influence (2) 1 .287** .265** .179* Teacher Influence (3) 1 .342** .327** Career Information Service (4) .346** Influence of Older Siblings (5) 1 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). The correlation analysis results in Table 3 show, on the one hand, that there is a general association between social characteristics and career decision-making among Grade 12 learners. The amplitude of the correlations, on the other hand, differs among social factors, while the changes are minor. For example, the strongest correlation was found between teacher influence and career decision-making (r=.643, n=204, p.01), followed by the relationship between career information services and career decision-making (r =.607, n=204, p.01), but peer influence had the least relationship with career decision-making, r (204) =.514, p.01. In Grade 12, the effect of older siblings had a substantial direct link with occupational decision-making (r=.566, n=204, p.01). This implies that there is a general positive relationship between social variables and career choice decision-making, meaning that a stronger tendency to social elements is linked to a speedier career choice decision, and vice versa, among Grade 12 learners. In addition, model summaries and regression equations were created, with the predictor variables being different features of job interest and the dependent variable being career decision-making. The findings of the regression analysis are summarised in Table 4. Table 4 Multiple Regression results on Social Factors and Career Decision-Making Variable B Std. Error Beta t Sig. Part corr. (Constant) 1.34 0.063 21.131 0.001 Peer Influence 0.115 0.016 0.276 7.021 0.006 .260 Teacher Influence 0.108 0.012 0.363 8.767 0.005 .324 114 Journal of Education, No. 89, 2022 Variable B Std. Error Beta t Sig. Part corr. Career Information Service 0.094 0.013 0.309 7.467 0.002 .276 Influence of Older Siblings 0.084 0.012 0.291 7.152 0.004 .265 Adjusted R 2 .722 F-ratio 132.756** df1=4 df2=199 * p-value<.05 ** p-value < .01 and *** p-value < .001 Using the multiple regression entry method, we discovered that social factors explained 72.2 % (Adjusted R Square =.722) of the variation in Grade 12 learners’ career decision-making. This has a significant impact on career decision-making. The model’s significance was determined using a multiple regression Analysis of Variance (ANOVA). As a result, the results were analysed using the null hypothesis that multiple R in the population equals 0, and the study’s findings revealed that the model was statistically significant, F (4, 199) = 132.756, p.01. This implies that among learners in Grade 12, social factors are a strong predictor of job choice. Further investigation of beta values reveals that the extent of the influence of individual aspects of social variables on vocational decision-making varies. For example, out of the four variables, teacher influence had the highest unique contribution of beta =.363, implying that increasing teacher influence by one standard deviation increases learners’ capacity to make career decisions by.363 standard deviations, and vice versa. Similarly, a one-standard- deviation improvement in career information services to learners would result in a.309 (beta =.309) standard-deviation improvement in career decision-making among learners. Similarly, when peer and older sibling influence increases by one standard deviation, career decision- making increases by .276 and .291 standard deviations, respectively. In addition, our research looked into the contribution of each social element to the total R squared. The results suggest that peer influence has a part correlation coefficient of .260, teacher influence has a part correlation coefficient of .324, job information service has a part correlation coefficient of .276, and older siblings’ impact has a part correlation coefficient of .265. Squaring these numbers shows how much of the total variance in professional decision- making is explained by the variable and how much R squared would drop if it were not in the model. For example, teacher influence that contributes the most to the model, explains 10.5 percent of the variance in career decision-making, while peer influence that has the least effect, explains only 6.8 percent. Similarly, job information services and older siblings’ impact account for 7.6 per cent and 7.0 percent of the variation in career decision-making among Grade 12 learners, respectively. When teacher influence, career information service, older sibling influence, and peer influence are not included in the model, R squared drops by 10.5 percent, 7.6 percent, 7.0 percent, and 6.8 percent, respectively. Ajayi et al.: Influence of selected social factors on career decision Finally, the regression equations from Table 4 were used to factors on career decision-making among learners in following generic regression prediction model: Career Decision-Making = β where X1 denotes peer influence, X2 denotes teacher influence, X3 denotes career information service, and X4 denotes older sibling influence. As a result, the predicted optimum degree of career decision learners, given social influences and other variables held constant, was represented by Career Decision-Making + .084 X4 units + The coefficients’ values in the model show how much career decision one of the social factors changes while the others remain constant. However, when all the social elements were increased by one unit, the study a significant impact on career decision teacher influence (B=.108; t =8.767; p =.005), career information services (B=.094, t=7.467; p=.002), and older sibling influence (B =.084; t =7.152, p=.004) are all significant. This suggests that a one considerable rise in career decision statistically significant in general, with F (4, 199) = 132.7 This further supports the model Finally, the null hypothesis was chosen: social influences have no statistically significant effect on career decision-making amon examined null hypothesis, with H1: at least one I0 being the matching alternative hypothesis. The null hypothesis was rejected since all were equal to zero. As a result, the alternative hypothesis that asserts that social effects have a substantial impact on career decisions chosen. As a result, it was determined that social pressures have a considerable impact on career decision-making among secondary school learners in Discussion The impact of certain social elements on Grade 12 learners in this study. According to the data, the strongest link between teacher influence and career decision-making was found, followed by the link between career information services career decision-making, but peer influence had the weakest link with career decision The influence of older siblings on students in with professional decision-making. This research supports the Soc explains how social elements such as the environment, learning experiences approach skills influence children et al. (2012) found that students regard their lecturers as role models and place a high value on their career advice and counselling. Similarly, Shumba and Naong (2012) discovered that Ajayi et al.: Influence of selected social factors on career decision Finally, the regression equations from Table 4 were used to estimate the influence of social making among learners in Grade 12. The goal was guided by the following generic regression prediction model: Making = β0+β1X1+β2X2 + β3X3+ β4X4 + ε where X1 denotes peer influence, X2 denotes teacher influence, X3 denotes career information service, and X4 denotes older sibling influence. As a result, the predicted optimum degree of career decision-making among Grade 12 secondary school n social influences and other variables held constant, was represented by Making=1.340 units + .115 X1 + .108 X2 units + error values in the model show how much career decision-making varies when one of the social factors changes while the others remain constant. However, when all the social elements were increased by one unit, the study’s findings revealed that all of them had significant impact on career decision-making. Peer influence (B =.115; t=7.021; p=.006), teacher influence (B=.108; t =8.767; p =.005), career information services (B=.094, t=7.467; p=.002), and older sibling influence (B =.084; t =7.152, p=.004) are all statistically significant. This suggests that a one-unit adjustment in each of the social effects leads to a considerable rise in career decision-making among learners in Grade 12. The model was statistically significant in general, with F (4, 199) = 132.756, p.01, and Adjusted R2 = .722. This further supports the model’s role as a predictor of Grade 12 learners’ career choices. Finally, the null hypothesis was chosen: social influences have no statistically significant making among learners in Grade 12. H0: 1=2=3=4=0 was the examined null hypothesis, with H1: at least one I0 being the matching alternative hypothesis. The null hypothesis was rejected since all were equal to zero. As a result, the alternative that social effects have a substantial impact on career decisions . As a result, it was determined that social pressures have a considerable impact on making among secondary school learners in Grade 12. rtain social elements on Grade 12 learners’ career decisions was investigated in this study. According to the data, the strongest link between teacher influence and career making was found, followed by the link between career information services making, but peer influence had the weakest link with career decision lder siblings on students in Grade 12 had a considerable direct association making. This research supports the Social Learning theory explains how social elements such as the environment, learning experiences approach skills influence children’s career choices (Krumboltz et al., 1976). Similarly, et al. (2012) found that students regard their lecturers as role models and place a high value on their career advice and counselling. Similarly, Shumba and Naong (2012) discovered that Ajayi et al.: Influence of selected social factors on career decision-making . . . 115 estimate the influence of social . The goal was guided by the where X1 denotes peer influence, X2 denotes teacher influence, X3 denotes career information service, and X4 denotes older sibling influence. As a result, the predicted secondary school n social influences and other variables held constant, was represented by + .094 X3 making varies when one of the social factors changes while the others remain constant. However, when all the s findings revealed that all of them had making. Peer influence (B =.115; t=7.021; p=.006), teacher influence (B=.108; t =8.767; p =.005), career information services (B=.094, t=7.467; statistically unit adjustment in each of the social effects leads to a . The model was 56, p.01, and Adjusted R2 = .722. career choices. Finally, the null hypothesis was chosen: social influences have no statistically significant . H0: 1=2=3=4=0 was the examined null hypothesis, with H1: at least one I0 being the matching alternative hypothesis. The null hypothesis was rejected since all were equal to zero. As a result, the alternative that social effects have a substantial impact on career decisions was . As a result, it was determined that social pressures have a considerable impact on career decisions was investigated in this study. According to the data, the strongest link between teacher influence and career making was found, followed by the link between career information services and making, but peer influence had the weakest link with career decision-making. had a considerable direct association ial Learning theory that explains how social elements such as the environment, learning experiences, and task 1976). Similarly, Khan et al. (2012) found that students regard their lecturers as role models and place a high value on their career advice and counselling. Similarly, Shumba and Naong (2012) discovered that 116 Journal of Education, No. 89, 2022 teachers had a significant impact on learners’ career choices and goals. The findings are also in line with those of Bojuwoye and Mbanjwa (2006), who found that family characteristics such as parental high expectations of children and adequate family communication are important. Furthermore, according to Tillman (2015), children of educators have a slightly stronger parental influence on their profession choices than is experienced by children of non-educators. Furthermore, Akosah-Twumasi et al. (2021) revealed that students had a significant need to acquire parental approval, and that, regardless of whether this permission was obtained early or later, prioritising family demands and commitments was the main focus for all participants. Furthermore, Mtemeri (2020) stated that students are impacted by their friends in a variety of ways when they are making professional decisions. Students’ contacts with peers of other interests, races, and backgrounds, according to Yi-Hui (2006), have the ability to promote introspection, knowledge, and beliefs that can lead to new ways of thinking about the world, other peers, and, eventually, oneself. Peer interactions were identified as a crucial influence in helping students choose vocations, according to Bankole and Ogunsakin (2015). Datar and Ahmad (2019) also agreed that career information services can help students better comprehend their options. In addition, Muttaqin et al. (2017) found that career information services have an impact, one of which is to improve students’ professional comprehension. Similarly, Oats and Rukewe (2020) found that because of the dynamic nature of the job choice and planning process, learners’ career decisions are influenced by a variety of circumstances, and that, as a result, learners want career counselling and information to make educated and prudent decisions. Mesa (2013), however, discovered that many students lack access to the career information needed to create realistic plans for their futures and that others are ignorant of career and guidance training possibilities available at various levels of post-secondary education. Bloxom et al. (2008) validated the availability of career development programmes that did not satisfy their demands and advocated for the development of effective career and life planning educational programmes. Despite the efforts of the South African Department of Basic Education, the Life Orientation course fails to accomplish its objectives in disadvantaged communities when it comes to work and career learning (Kweyama, 2016). Conclusion The findings of this study show that the selected social factors (impact of older siblings, peer influence, teacher influence, and career information services) are a significant predictor of career decision-making among learners in Grade 12. According to the data, the strongest link was found between teacher influence and career decision-making, followed by the link between career information services and career decision-making and peer influence had the weakest link with career decision-making. The study’s only flaw is that personal variables were not taken into account as potential determinants of learners’ career choices. However, the study’s regression model revealed that, in addition to social influences, there may be additional variables that influence learners’ career decisions. Because social variables account for just 72.2 percent of career decision-making, other factors, such as personal ones, could account for the remaining 27.8 percent of career decision making among learners. Ajayi et al.: Influence of selected social factors on career decision-making . . . 117 Consequently, this study revealed that the selected social factors all had a significant influence on career decision-making process of Grade 12 learners. Recommendation The study’s findings have ramifications for teachers, school principals, and teacher counsellors in helping learners make career decisions. According to the findings, teacher counsellors should take a diverse approach to establishing vocational decision-making programmes for secondary school learners. In South Africa, where the unemployment rate is so high, designing programs to prepare high-risk youth for the future is critical. Personal aspects impacting secondary school learners’ career decisions should be investigated in future studies. References Abe, N. E., & Chikoko, V (2020). Exploring the factors that influence the career decision of STEM students at a university in South Africa. 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