Original Research

Investigating career guidance implementation between historically advantaged and disadvantaged schools

Petronella Jonck, Eben Swanepoel

Received: 12 Nov. 2018; Accepted: 25 July 2019; Published: 25 Sept. 2019

Copyright: © 2019. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This study examined school learner views on career guidance processes and outcomes contrasting historically advantaged and disadvantaged schools in the Free State province, South Africa. The study comprised 430 learners from seven schools located in the Mangaung area (females = 63.9%, black people = 47.4%, mean age = 15.85, SD = 0.77). A survey was completed underscoring career guidance service delivery, personal growth, career path knowledge and subject satisfaction. Multivariate analysis of variance was computed to examine differences in learners’ perception of the career guidance they received, emphasising school type, besides controlling for selected demographic variables. Results indicated that school type statistically significantly influenced career guidance service delivery, personal growth and career path knowledge gained from career guidance, but not subject satisfaction. Moreover, a statistically significant interaction for type of school with gender and race as covariates, and personal confidence and subject satisfaction as dependent variables, emerged.

Keywords: Segregated schools; career guidance; life orientation; type of schools; comparative analysis.

Introduction

Career guidance in the South African context currently forms part of the National Curriculum Policy Statement (CAPS). This policy document details the skills and knowledge to teach and assess within the various learning areas in South African schools. One of these learning areas, which is often scrutinised as to the overall effectiveness thereof within the South African curriculum, is Life Orientation (Jonck 2015). The aim of life orientation as compulsory subject at secondary school level, is to create a platform to promote the harmonious transitioning of learners into society and their subsequent roles within the community and workplace (Adewumi 2012; Francis & Reygan 2016). The component of life orientation that specifically underscores career guidance comprises of 28-h classroom instruction in the Senior Phase (Grade 7 to Grade 9) of which 3-h explicitly focus on subject selection. After the completion of Grade 9, learners are expected to select subjects which would inform future career choices and access to institutions of higher learning (RSA Department of Basic Education 2011). Career guidance was initially made mandatory in 1967 to white South African learners and to other South African racial groupings 14 years later, that is, during 1981 (Bholanath 2007).

For the sake of clarity, career guidance subsumes services and activities aimed at assisting individuals at any point in their lifespan to make educational, training and career decisions as a means to ultimately manage their chosen profession (Lewin & Colley 2011). Discourse on the aforesaid is mostly subject to perspectives centred on academic sub-disciplines including vocational psychology, educational sociology, education or social work (Weber et al. 2018). Specifically, within the educational context, the eminence of career guidance is driven by an increased awareness of the pivotal role thereof in the school-to-further-education and workplace needs of secondary school learners (Ho & Leung 2016). The said authors furthermore note that the educational policy imperative to infuse career-related elements in educational systems internationally, and the subsequent support towards career guidance, was a response to generic challenges including youth unemployment and skills shortages (Ho & Leung 2016).

Career guidance in South Africa is still challenged by historical and socio-political impediments created through apartheid, which altered the inclusive nature of successful transitioning from school to the vocational environment (Horn 2006; Spaull 2012). Life orientation is further challenged by a lack of training to optimally teach the subject area, as well as teachers who lack the experience to teach the subject holistically (Francis & DePalma 2015). Furthermore, the provision of career guidance often draws on Euro-centric frameworks (Watson 2009), creating a need for multicultural inclusive approaches aimed at previously excluded population groups. Currently, there is a strong thrust by national education bodies and the student population for an African Renaissance in educational discourse propagating that transformative educators should embrace an indigenous socio-cultural and epistemological framework (Higgs 2013).

The most predominant educational reforms in the post-apartheid period subsumed the desegregation of schools, the development of a National Qualifications Framework, the adoption of new language policies for education and the implementation of outcomes-based curricula (Vandeyar & Killen 2007) to ‘redress past injustices in educational provision’ (RSA Department of Basic Education 1996:1). However, it appears that little has changed in relation to transformation of the school systems to reduce the impact of historical disadvantage in quality and intensity of educational resources (Branson et al. 2012; Vandeyar & Killen 2003).

A crucial link between education and inequality in South Africa is the role of education in unemployment (Branson et al. 2012). Branson, Leibbrandt and Zuze (2009) indicate that the completion of secondary and tertiary education substantially improves the probability of employment. Education furthermore plays a pivotal role in human capital development, which can be seen as the attainment of knowledge and intellectual stock intended for the expansion of productivity, efficiency, performance and output to ultimately increase fiscal revenue for all stakeholders (Akinyemi & Abiddin 2013; Jonck & Minnaar 2015). Horn (2006), however, asserted that only 10% of secondary school learners transition to the vocational environment successfully, raising questions as to the effectiveness of education. Consequently, there is a greater need for learners to proactively engage with their prospective career developmental needs (Coetzee & Esterhuizen 2010). As such, career guidance has gained prominence to facilitate the match between supply and demand factors in the labour market, to reduce unemployment and to address prevailing social exclusion, defined as the process of societal detachment (Jonck 2014a; Lundahl & Nilsson 2009; Randolph, Ruming & Murray 2010). As a means to accommodate the need for employability that surpasses mere knowledge, career guidance is foundational to provide learners with dynamic, internationally competitive skillsets (Rooth 2005; Van de Venter 2006), especially in relation to the current workforce that is characterised by a need for technologically driven skills and globalisation, where self-efficacy is principal to vocational adaptability (Patton 2005).

Previous research underscores the importance of career guidance services in economic development (Jonck 2014a), specifically because the lack of access to career guidance for diverse population groups (Bernes, Bardick & Orr 2007; Du Toit 2005), the lack of academic provision (Van Schalkwyk 2007) and the lack of career guidance in secondary schools have been identified as factors that infringe on skills development (Dabula & Makura 2013), thereby hampering economic growth. Additionally, Singaravelu, White and Bringaze (2005) indicate that developing countries, such as South Africa, in the early stages of economic development should direct individuals into professions that benefit the national economy, particularly in light of the fact that skills shortages are deemed endemic in the South African context (Jonck 2014b; Sharp 2011). To this end, the Organisation for Economic Co-operation and Development confirmed the need for countries to recognise career guidance systems as part of their active labour market policies (Watts 2010).

In light of the foregoing discussion, the primary aim of this study was to ascertain whether previously advantaged, marginally advantaged and disadvantaged schools differ in career guidance outcomes from the perspective of the learners themselves. As such, learner differences in career guidance outcomes by school between and within school types were examined focusing on service delivery, personal development and growth, career path knowledge and subject satisfaction. The primary research question subsumes: Do school learner views on career guidance processes and outcomes differ in relation to type of school? The secondary aim of the study included investigating the influence of race and gender on the aforementioned correlation which was investigated by means of the following research question: Do gender and or race statistically significantly influence school learner views on career guidance processes and outcomes per school type?

Historical developmental disparities and experiences, diverse experiential perceptions and future expectations might influence the self-efficacy of learners, which, in its turn, would impact the individual interests and eventually determine career choices (Jonck 2014a; Lent, Brown & Hackett 2000). Learner evaluations are often secondary if at all taken into account (Dabula & Makura 2013), while research is predominantly focussed on evaluating other stakeholders’ perceptions (Mittendorf, Den Brok & Beijaard 2010). To bridge the gap between successful career guidance at theoretical level and ultimately instilling practical change that leads to proactive and sustainable career development for all South African citizens (Jacobs 2011), the perspectives of learners become crucial. Taking these disparities into account, the effectiveness of how career guidance is received in accordance with the current theoretical framework of Holland’s Career Choice theory (Stead & Watson 2006) can be further critiqued as South African development does not show analogous developmental paths, contrary to the core assumption of the theoretical framework used during career education at curriculum level.

Method

Participants and setting

Participants represented a convenience sample of 430 learners, 47.40% (n = 204) of them from historically disadvantaged and 12.8% (n = 55) from marginally advantaged schools (see Table 1). Of the sample, 274 learners were female and 155 male. The two dominant language groupings that formed part of the composition was Afrikaans (n = 235; 54.7%) and indigenous languages (n = 165; 38.4%), with the remaining 30 learners speaking English as their home language (n = 30; 7%). When considering the racial composition, it was noted that the two dominant racial groupings subsumed black respondents (n = 166; 38.6%) and white respondents (n = 172; 40%), followed by mixed race respondents (n = 74; 17.2%) and those respondents who could not be categorised in the previously stated groups (n = 18; 4.2%). About 39.8% (n = 171) of learners were from previously and predominantly white enrolment (advantaged) schools, 47.4% (n = 204) from previously and predominantly black enrolment (disadvantaged) schools and 12.8% (n = 55) from previously and predominantly mixed race (marginally advantaged) schools.

Instrument

The learners self-reported socio-demographic information including age, gender, language and socio-economic status, in addition to completing a 25-item career guidance questionnaire. The questionnaire covered five categories subsuming: (1) service delivery (e.g. ‘My life orientation teacher teaches us study methods to study more effectively’), (2) personal confidence (e.g. ‘I am confident that I will be able to choose a study field from a list of potential study fields that I am considering’), (3) the completion of personality inventories (e.g. ‘I have done a personality versus job questionnaire’), (4) overall knowledge of career path (e.g. ‘I know what I want to do after school’) and (5) overall satisfaction with subject choices (e.g. ‘I have chosen the correct subjects’). Items were scored on a four-point Likert scale ranging from 1 (representing either always, very confident or strongly agree) to 4 (representing either never, no confidence or strongly disagree). The theoretical range of the measuring instrument was between 25 and 100. Scores from the career guidance questionnaire reached a Cronbach’s alpha reliability index of 0.86.

Procedure

School principals and parents or guardians of the learners subsequently granted consent for participation in the project. Learners completed the survey during normal school hours.

Statistical analysis

Multivariate analysis of variance (MANOVA) was computed to examine differences in reported career guidance outcomes by school type emphasising service delivery, personal confidence, use of personality inventories, career path knowledge and subject satisfaction. In addition, an ANOVA was carried out, and post hoc comparisons using the Tukey’s honestly significant difference (HSD) test with reference to observed statistically significant group differences were performed. A two-way between-group analysis of covariance (ANCOVA) was utilised to determine statistically significant differences between the various school types vis-à-vis the dependent variables while controlling for race and gender.

Ethical consideration

Ethical clearance was obtained from the Department of Education, Free State Province (Ethical Clearance Number: 16/4/1/25-2012).

Results

Table 3 presents the descriptive statistics included in the study. In terms of gender, male respondents from advantaged schools expressed dissatisfaction (mean = 2.76; SD = 0.553) with service delivery, while respondents from disadvantaged (mean = 2.55; SD = 0.458) and marginally advantaged (mean = 2.06; SD = 0.585) schools were somewhat satisfied. With reference to personal confidence, respondents were very satisfied with mean scores ranging between 1.61 and 1.88. As to personality inventory, male respondents from various types of schools were somewhat satisfied, with male respondents from advantaged schools being least satisfied (mean = 2.46; SD = 0.854) and respondents from disadvantaged schools being most satisfied (mean = 2.04; SD = 0.920). Similarly, when considering career path knowledge, the mean scores ranged from 1.25 to 1.96 with male respondents from advantaged schools being less satisfied (mean = 1.96; SD = 0.905) than respondents from disadvantaged (mean = 1.45; SD = 0.920) or marginally advantaged (mean = 1.25; SD = 0.985) schools. The same pattern persisted relating to subject satisfaction with male respondents from advantaged schools (mean = 1.60; SD = 0.650) being less satisfied than male respondents from disadvantaged (mean = 1.57; SD = 0.705) and marginally advantaged (mean = 1.25; SD = 0.622) schools.

Female respondents from advantaged schools expressed dissatisfaction (mean = 2.61; SD = 0.546) with service delivery, while respondents from disadvantaged (mean = 2.48; SD = 0.479) and marginally advantaged (mean = 1.95; SD = 0.443) schools were somewhat satisfied. With reference to personal confidence, female respondents from disadvantaged and marginally advantaged schools were very satisfied with mean scores ranging between 1.60 and 1.74. Female respondents from advantaged schools were somewhat satisfied (mean = 1.96; SD = 0.459). Regarding the variable personality inventory, female respondents from various types of schools were somewhat satisfied, with mean scores ranging from 2.05 to 2.29. Concerning career path knowledge, female respondents from advantaged schools were less satisfied (mean = 2.16; SD = 0.998) than respondents from disadvantaged (mean = 1.49; SD = 0.700) or marginally advantaged (mean = 1.42; STD = 0.730) schools. Concerning subject satisfaction, female respondents in totallity were very satisfied with mean scores ranging from 1.50 to 1.75.

When considering race, black respondents from advantaged schools were very satisfied with service delivery (mean = 1.58; SD = 0.000) opposed to respondents from disadvantaged (mean = 2.48; SD = 0.436) and marginally advantaged (mean = 2.16; SD = 0.238) schools. Pertaining to personal confidence, black respondents from various school types were very satisfied with mean scores ranging between 1.40 and 1.76. Regarding personality inventory, black respondents from various school types were somewhat satisfied, with mean scores ranging from 2.00 to 2.63. As to career path knowledge, black respondents from advantaged schools were less satisfied (mean = 2.00; SD = 0.00) than respondents from disadvantaged (mean = 1.46; SD = 0.686) or marginally advantaged (mean = 1.00; SD = 0.000) schools. Concerning subject satisfaction, black respondents from advantaged schools were dissatisfied (mean = 3.00; SD = 0.000) with subject selection, while respondents from disadvantaged (mean = 1.51; SD = 0.714) and marginally advantaged (mean = 1.38; SD = 0.744) schools were very satisfied.

White respondents from advantaged (mean = 2.67; SD = 0.547) and disadvantaged (mean = 2.72; SD = 0.632) schools were dissatisfied with service delivery. With reference to personal confidence, white respondents from advantaged and disadvantaged schools were somewhat satisfied, with mean scores ranging between 1.92 and 2.05. Regarding personality inventory, white respondents from advantaged and disadvantaged schools were somewhat satisfied, with mean scores ranging from 2.00 to 2.36. As to career path knowledge, white respondents from advantaged schools were less satisfied (mean = 2.08; SD = 0.967) than respondents from disadvantaged schools (mean = 1.50; SD = 0.707). Concerning subject satisfaction, white respondents from advantaged schools were very satisfied (mean = 1.68; SD = 0.692) with subject selection, while respondents from disadvantaged schools (mean = 2.00; SD = 0.00) were somewhat satisfied.

Mixed race respondents from disadvantaged schools (mean = 2.61; SD = 0.612) were dissatisfied with service delivery, while respondents from marginally advantaged schools (mean = 1.95; SD = 0.490) were somewhat satisfied. With reference to personal confidence, mixed race respondents from disadvantaged schools were somewhat satisfied (mean = 1.96; SD = 0.592), while respondents from marginally advantaged schools (mean = 1.63; SD = 0.509) were very satisfied. Concerning personality inventory, mixed race respondents from disadvantaged and marginally advantaged school were somewhat satisfied, with mean scores ranging from 2.14 to 2.17. As to career path knowledge as well as subject satisfaction, mixed race respondents from disadvantaged and marginally advantaged schools were very satisfied.

Respondents who could not be categorised in the stated categories were either somewhat satisfied (viz. disadvantaged schools) or very satisfied with service delivery (viz. marginally advantaged schools). With reference to personal confidence, respondents were very satisfied with mean scores ranging from 1.50 to 1.74. Regarding personality inventory, respondents from disadvantaged schools were very satisfied (mean = 1.88; SD = 0.993), while those from marginally advantaged schools were somewhat satisfied (mean = 2.00; SD = 0.000). As to career path knowledge, respondents from disadvantaged and marginally advantaged schools were very satisfied. Lastly, with reference to subject satisfaction, respondents from disadvantaged schools were very satisfied (mean = 1.41; SD = 0.507), while respondents from marginally advantaged schools were very dissatisfied (mean = 4.00; SD = 0.000).

As per Table 3, learners from advantaged schools were only dissatisfied with one aspect related to career guidance that being service delivery (mean = 2.67; SD = 0.552), as can be seen in Table 3. Overall, subject satisfaction (mean = 1.69; SD = 0.697) was the aspect respondents were most satisfied with. This was followed by personal confidence (mean = 1.92; SD = 0.477), career path knowledge (mean = 2.08; SD = 0.964) and completion of personality inventories (mean = 2.36; SD = 0.865).

Respondents from disadvantaged schools yielded positive evaluations for all the aspects related to career guidance provided as part of the subject life orientation. Service delivery was the aspect that received the score closest to a negative evaluation, for which respondents were only somewhat satisfied (mean = 2.51; SD = 0.471), followed by personality inventories (mean = 2.05; SD = 0.828). Very positive evaluations were yielded for career path knowledge (mean = 1.48; SD = 0.7), subject satisfaction (mean = 1.53; SD = 0.677) and personal confidence (mean = 1.79; SD = 0.447).

Similarly, respondents from the marginally advantaged schools yielded positive evaluations for all the aspects related to career guidance provided as part of the subject life orientation. Personality inventories (mean = 2.24; SD = 0.860) was the aspect respondents were least satisfied with, followed by service delivery (mean = 1.97; SD = 0.474), while career path knowledge (mean = 1.38; SD = 0.707) was the aspect respondents were most satisfied with. This was followed by personal confidence (mean = 1.6; SD = 0.481) and subject satisfaction (mean = 1.64; SD = 0.890).

To test the primary research hypothesis, a MANOVA test was performed, as illustrated in Table 4.

As indicated in Table 4, the type of school statistically significantly influenced the evaluation of career guidance service delivery. Service delivery, personal confidence, personality inventories and overall career path knowledge specifically were statistically significantly influenced by the type of school on the 99th percentile. Subject satisfaction did not yield a statistically significant result.

An ANOVA test was conducted to further explore the impact of school type on service delivery, personal confidence, personality inventories and career path knowledge, as measured by the measuring instrument.

According to the ANOVA results, as depicted in Table 5, there were statistically significant differences on the 99th percentile between respondents from the different school types in terms of service delivery, personal confidence, personality inventories and career path knowledge. Despite reaching statistical significance, the differences in the mean scores between the groups were small. The effect sizes, calculated using eta squared (η²), were 0.16 for service delivery, 0.05 for personal confidence, 0.12 for career path knowledge and 0.03 for personality inventory. The biggest effect was noted for service delivery.

Post hoc comparisons based on the Tukey’s HSD test were calculated to determine how respondents from the various school types differ in terms of the measured dependent variables. By considering the results depicted in Table 3, it appears that respondents from advantaged schools evaluated service delivery as dissatisfactory, while respondents from the disadvantaged and marginally advantaged schools had a slightly more positive evaluation of service delivery. More specifically, results indicate that respondents from advantaged schools had the most negative evaluation of service delivery (mean = 2.67; SD = 0.552), followed by respondents from disadvantaged schools (mean = 2.51; SD = 0.471) and, lastly, marginally advantaged schools (mean = 1.97; SD = 0.474). In addition, respondents from disadvantaged schools statistically significantly differed from respondents from the marginally advantaged schools.

As per the post hoc results for personal confidence, respondents from the various school types statistically significantly differed from each other. Results indicated that all respondents had a slightly to very positive evaluation with reference to personal confidence (see Table 3). Respondents from advantaged schools had the most negative perception (mean = 1.92; SD = 0.477), followed by respondents from disadvantaged schools (mean = 1.79; SD = 0.447). Respondents from marginally advantaged schools had the most positive perception about their personal confidence (mean = 1.60; SD = 0.481).

Considering the post hoc results for personality inventories, the only statistically significant result was that respondents from advantaged schools differed statistically significantly (mean = 2.36; SD = 0.865) from those from disadvantaged schools (mean = 2.05; SD = 0.828). With reference to career path knowledge, respondents from advantaged schools statistically significantly differed (mean = 2.08 SD = 0.964) from respondents from both disadvantaged (mean = 1.48; SD = 0.700) and marginally advantaged schools (mean = 1.38; SD = 0.707). Concerning overall career path knowledge, respondents from advantaged schools had a more negative evaluation, whereas respondents from disadvantaged and marginally advantaged schools had a more positive evaluation and did not statistically significantly differ from each other.

A two-way between-group ANCOVA was conducted to explore the influence of gender and type of school on career guidance processes and outcomes (see Table 6).

As per Table 6, the only statistically significant interaction effect yielded was for school type with gender as covariant and personal confidence as dependent variable on the 95th percentile (F = 3.138; p = 0.044*). The effect size was small as evident from the partial eta square (η²) of 0.015. Nonetheless, only school type yielded a statistically significant main effect (F = 7.098; p = 0.001**), while the same for gender was not statistically significant (F = 0.086; p = 0.769).

A statistically significant interaction effect was established for school type with race as covariant and subject satisfaction as dependent variable on the 99th percentile (F = 5.819; p = 0.001*). However, the effect size was small (partial eta square = 0.040). Nevertheless, a statistically significant main effect for school type (F = 4.653; p = 0.010**) as well as race (F = 2.768; p = 0.041*) came to the fore. Post hoc comparisons using the Tukey’s HSD test did not reveal any statistically significant differences between the racial groups.

Discussion

The primary aim of this study was to investigate whether school type (i.e. advantaged, disadvantaged or marginally advantaged) statistically significantly influences the evaluation of career guidance processes and outcomes as part and parcel of the subject life orientation, with specific reference to service delivery, personal confidence, personality inventories, career path knowledge and subject satisfaction. The hypotheses related to service delivery, personal confidence, personality inventory and career path knowledge were accepted. However, the research sub-hypothesis for subject satisfaction was rejected, indicating that school type does not statistically significantly influence the evaluation of career guidance received with specific reference to overall subject satisfaction. The secondary aim of the study was to determine whether gender and race statistically significantly influence the aforementioned correlation. Results indicated that gender as covariant influences the relationship between school type and personal confidence, while race as covariant influences the correlation between school type and subject satisfaction.

Before discussing the results, it is important to again briefly reflect on the use of Holland’s Career Choice theory as the basis for career guidance at curriculum level (RSA Department of Basic Education 2011). The theoretical foundation of aligning personality types of learners with the environment has been critiqued as stagnant when fostering proactive change within the current vocational environment (Stead & Watson 2006). Consequently, when reviewing the curriculum of Life Orientation for Grade 9 learners in South Africa, it is advisable to exclude Holland’s Career Choice theory.

The results further indicate that as the majority of Afrikaans-speaking respondents attended historically advantaged schools and the majority of respondents speaking an indigenous language attended disadvantaged schools, it would appear as if the desegregation of schools as set out by the Department of Basic Education as an educational reform (Vandeyar & Killen 2007) has not materialised at grass-roots level. This finding is in accordance with a statement made by Spaull (2012), who indicated that inequality still plagues the South African education system.

Moreover, the results reflect that service delivery was the facet respondents, for the most part, were least satisfied with. The aforementioned results are corroborated by research findings by Coetzee and Esterhuizen (2010) who questioned the sustainability of career guidance based on current policies, especially in providing future-oriented and skill-based development at a holistic level. These findings are also in line with the research conducted by Rottinghaus et al. (2002), who found that learning environments significantly influence future career aspirations. In South Africa, the contexts of previously segregated schools have influenced the context within which learning and career guidance currently take place (Lindley 2005). The results, however, seem to be contradicting with research done by Dabula and Makura (2013), who noted that South African learners are restricted when making career choices, ascribed to a lack of knowledge and self-efficacy or personal confidence.

With regard to the results pertaining to personality inventories, the Health Professions Council of South Africa (HPCSA) stipulated that teachers are not qualified to administer personality tests. Rather, school psychologists or trained psychometrists are required to assist learners with identifying their personal strengths and to foster in-depth insight into optimal individual career path knowledge. Research by Miller and Nickerson (2006) indicated that the type of school significantly predicts the evaluation of career guidance with reference to personality inventories, as different types of schools have different resources to provide such services, if applicable. It should therefore be questioned whether the guidance learners receive on part of personality inventories are consistent across the diverse context of schools in South Africa, while also underscoring that teachers are not authorised or permitted to administer personality tests set out by the HPCSA.

Life Orientation as a subject should ideally provide a basis in which the personal characteristics and backgrounds of learners are also taken into account in order to enhance personal confidence and career path knowledge. Yet, as discussed, this is complicated by the lack of optimal teacher induction to provide holistic career guidance (Jacobs 2011), time and resource constraints (Miller & Nickerson 2006), and a theoretical foundation that is predominantly westernised and lacks significance in the multicultural environment typical of South Africa’s diverse society (Watson 2009). In addition, previous research studies have indicated that teachers are inadequately equipped in supplying career guidance (Magano 2011; Rooth 2005). Often, schools with limited funding utilise currently employed teachers who are not formally trained to teach the subject life orientation, especially in order to deploy resources deemed more important elsewhere.

Limitations of the study

Recipient feedback provides a measure of the perception of the relevance and the value of services rendered with a certain amount of bias. The study thus provides a one-sided view from respondents which forms one part of a system within which career guidance services are rendered. As such, it would be valuable to gain further perspectives from various other stakeholders who form part of the context of career education (such as teachers, principals and parents). Another limitation to the study is that the data reported present only a quantitative perspective, whereas a qualitative view will be needed to gain further understanding, especially related to the specific contexts of the respondents.

Conclusion

South Africa’s apartheid history created an unequal society that has not been sufficiently addressed in the post-apartheid period as the country is facing a deepening of disparity. This is evident in the increase of unemployment, widening of income disparities, continuous employee strikes and problematic transitioning of secondary school learners to the vocational environment. South Africa has one of the most progressive constitutions in the world with the best-developed policies and intentions, but the implementation thereof seems to be problematic. Against this backdrop, the research reported on in this article attempted to investigate one aspect of educational reform, that is the desegregation of schools, with specific reference to career guidance received as part of the subject life orientation. The importance of career guidance is well documented, ranging from economic development to fostering social inclusion, defined in terms of participation in paid employment, which is easier to obtain for those with a tertiary education.

In light of the intention of career guidance, as a component of the subject life orientation which is to instil lasting skills to enable learners to enter the dynamic workforce, it becomes evident that there are still challenges in the South African education system that create a disjuncture between theory and practice. The findings of this research indicate the need for career guidance and education that is aligned with the patterns of disparities that would counteract the historical backdrop of South Africa. Aligned with the Social Cognitive Career Development Theory, the context and background of learners influence their future career choices and expectations. As such, the research indicated that there is a significant difference in how learners evaluate career guidance, dependent on the type of school they attend. Although most respondents evaluated career guidance received as part of the subject life orientation in a positive light, respondents from the advantaged schools yielded the most negative evaluation. Furthermore, the use of a unison theory to provide career guidance at secondary school level is questioned, while a recommendation is made towards teacher induction based on interpreting the curriculum and the tailoring thereof to learners’ contexts.

Acknowledgements

Sincere gratitude is hereby extended towards the Free State Department of Basic Education for the willingness to participate in the research project.

The authors have declared that no competing interests exist.

P.J. conceptualised the project and was responsible for the development of the measuring instrument, data gathering and analysis as well as write up of the article. E.S. assisted with data gathering as well as compiling the article.

The research under study forms part of a larger postdoctoral research project funded by the National Research Foundation.

Data sharing is not applicable to this article as no new data were created or analysed in this study.

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.

References