Modelling university students’ preferences and interconnectedness among various careers/occupations in Ghana

Abstract

The incongruity between academic programmes pursued and the career path among graduates in recent times suggests that career path does not always lead to programme choice and vice versa. Different occupations/professions not directly found in the area of academic programmes pursued could appeal to graduates. This study sought to examine how the various occupations/professions in Ghana appeal to university graduates. This study modelled university students’ preferences and interconnectedness among various careers/occupations in Ghana. The descriptive survey design was used. The census technique was used to capture all 144 final-year university students pursuing a BED accounting programme with a university in Ghana. Data were collected using an adapted Occupational Inventory Profile ((OIP) and data were analysed with the Partial Least Square Structural Equation Model (PLS-SEM). The study found that technological activities, mathematical computation activities, managerial-clerical activities, scientific research activities, persuasive-enterprising activities, and fine art activities significantly predicted mechanical-technological occupation, mathematical computation occupation, managerial-clerical occupation, science research occupation, persuasive-enterprising occupation, and fine art occupation. Additionally, there was also strong interconnectedness between the six various occupations among BED Accounting students in Ghana. Though the career path of BED accounting students does not generally agree with the realistic and artistic personality type, the study found that these students have a significant interest in activities and occupations in line with these personality types. This suggests that the personality of university students studied had an interest in several occupations not trained for, suggesting that they had a combination of personality types in varying degrees for the various occupations studied. Therefore, it was recommended that teaching pedagogies should vary and the government should create more employment opportunities to better prepare graduates to pursue careers outside what they were trained for. Graduates should also be equipped with skills and resources to be able to create their own jobs in their areas of interest outside or along their professional training. The theoretical and other practical implications of the findings of the study have also been adduced.

Keywords:

• Career
• Occupations
• Activities
• University Students
• Preferences
• Interconnectedness

1. Introduction

Every individual makes career decisions (what one wants to do or become in life) leading to occupational choices (selection of a particular job) at one time or another). Students go through this stage in life when choosing academic programmes of study leading to their future careers (Nyamwange, 2016; Yim, 2018). During this stage of making career decisions , students are assisted with information by key stakeholders (parents, teachers, career counsellors or officers, and psychologists) in their daily lives (Nyamwange, 2016). The relevance of career choice among students is that it significantly influences an individual’s standard of living, status in society, income, emotional health, and social network (Agbo et al. 2021; Khattab et al., 2022). Making the right career choice leads to an avoidance of wastage of time and financial resources. More importantly, most career decisions affect individuals’ lives, suggesting that one can enjoy life if the right career decisions are made or vice versa (Tillman, 2015; Tsui et al., 2019). For this reason, individual students require the right career guidance services and timely information to make career decisions (Sharf, 2010). Meanwhile, making career decisions is a daunting and complicated task (Chui et al., 2022; Ferry, 2006; Nyamwange, 2016 Agbo et al, 2021)

The main factors contributing to the complication in career decisions for students are categorised into intrinsic and/or extrinsic (Hassan et al., 2022; Hewitt, 2010). Apart from the financial or affordability of academic programmes, studies have found other extrinsic factors responsible for students’ career decisions, including the availability of the right information, role models, choice of subject, different job characteristics, and ethnic background (Kobia-Acquah et al., 2020). Lee et al. (2022) and Nyamwange (2016) further added other extrinsic factors such as relatives, parents, friends, peers, teachers and career counsellors, greatly influenced career choices among students. Other key intrinsic factors also include self-concept, cultural identity, attitudes, and individual personality (McQuaid & Bond, 2003). Though professions of parents or parents’ preferred professions highly influence the individual career choice (Hewitt, 2010), other studies have confirmed the influence of educational achievements and preference for careers that give higher allowances, holidays and salary benefits on career decisions among students (Nyamwange, 2016; Parola & Marcionetti, 2022). It is, therefore, clear that there is an interconnectedness between the influence of extrinsic and extrinsic factors on career choice.

Most students making career decisions in Ghana begin at the basic school level when they lack adequate information on various careers, and for that matter, their perception of the ideal job, courses and information from career counsellors influence their choice of secondary and university education and programmes (Albert & Luzzo, 1999; Pulliam, 2014). There are times when the grade obtained by students at the basic and secondary schools also influence their career choice and university programme of study in Ghana (Nyamwange, 2016). Earlier studies by Essel-Anderson et al. (2018), Kobia-Acquah et al. (2020), Arhin (2018), and Turkson (2021) have identified precursors of career choices among university students in Ghana. These precursors were employability, financial benefits, information on career opportunities, and academic performance.

Thus, several factors are responsible for the incongruity between career choices and academic programmes pursued by graduates and vice versa in recent times. Different career options could attract the interest of graduates though they might not necessarily have pursued academic programmes in those areas. This study, therefore, examines how university graduates perceive the various occupations in Ghana and how these occupations relate to each other. Knowledge of how different occupations in Ghana appeal to graduates could influence broader teaching pedagogies at the tertiary level to better prepare graduates for different kinds of jobs rather than what is in vogue. Addressing incongruity between career choices and academic programmes will also reduce the unemployment rate among university graduates.

Additionally, the level of the influence of both intrinsic and extrinsic factors could largely depend on individual personality in terms of being realistic, investigative, artistic, social, enterprising or conventional. The case of BED Accounting students is that they are either trained to teach accounting courses in the classroom or practice as accountants in organisations. Thus, the personality type of university students could have an impact on their preference for several careers or occupations apart from what one is being professionally trained for, suggesting interconnectedness among these occupations in Ghana. That notwithstanding, there are limited empirical studies on the influence of personality type influencing the preferences and interconnectedness among various careers/occupations in Ghana. Within this background, the present study was undertaken to examine university (BED Accounting) students’ preferences for various occupations in Ghana and to establish relationships or interconnectedness among these various careers/occupations in Ghana. The eleven hypotheses that guided this study were:

2. Hypotheses of the study

H1: There is a statistically significant relationship between Mechanical- Technological Activities and Mechanical- Technological Occupation among university students.

H2: There is a statistically significant relationship between Mathematical Computation activities and Mathematical Computation Occupations among university students.

H3: There is a statistically significant relationship between Managerial- Clerical Activities and Managerial- Clerical Occupation among university students.

H4: There is a statistically significant relationship between Science Research Activities and Science and Research Occupations among university students.

H5: There is a statistically significant relationship between Persuasive- Enterprising Activities and Persuasive- Enterprising Occupation among university students.

H6: There is a statistically significant relationship between Fine Art activities and Fine Art Occupations among university students.

H7: Mechanical- Technological Occupation statistically and significantly relates to Mathematical Computation Occupation.

H8: Mathematical Computation Occupation statistically and significantly relates to Managerial- Clerical Occupation.

H9: Managerial- Clerical Occupation statistically and significantly relates to Science Research Occupation.

H10: Science Research Occupation statistically and significantly relates to Persuasive- Enterprising Occupation.

H11: Persuasive- Enterprising Occupation statistically and significantly relates to Fine Art Occupation.

3. Literature review

3.1. Theoretical perspective on career aspiration

Holland’s theory of vocational types guides this study. Holland (1966) propounded a typology theory based on the premise that career choices are expressions of the total personality of an individual and that people tend to search for a working environment that will match their personality types. The satisfaction, thus, derived from a career chosen depends on the compatibility of a person’s work situation and personality style. Holland’s theory of career choice states that job satisfaction and achievement are highest when personality types are matched with a compatible work environment. He emphasised that people must have adequate knowledge of themselves and occupational requirements to make informed career decisions (Holland, 1973; Stead et al., 2022). In his theory, Holland gave six different types of personalities and career types that can be matched. These personality and career types are presented in what he termed the hexagon of career types. The six personality and career types are realistic, investigative, artistic, social, enterprising and conventional personality types. Each type has specific characteristics that describe people who fit the type. Thus, when a person with particular characteristics gets a job, there will be a match.

Holland provides a criterion that people can use to determine their career decisions by checking which personality type matches their interests and best describes them. Individuals need to be aware of aspects of their personality (self-knowledge) in order to determine where they fall. Therefore, one must be able to match their personality and compatibility with the work environment to ensure a successful and satisfactory career. Holland believed that career success largely depended on the congruency between the person’s personality and the work environment (Holland, 1973; Suh & Flores, 2022; Suryadi et al., 2020).

Holland’s theory has been tested and re-tested. One of the focus areas has been that of congruency, which can be described as reflecting the degree to which an individual’s personal qualities match environmental demands in chosen careers (Miller, 2006; Wang & Jiao, 2022). Several studies conducted to test the congruency hypothesis (Gottfredson & Holland, 1966; Swanson & Hanson, 1998) have indicated congruency between preferences and occupational characteristics of individuals is positively related to occupational satisfaction. Using the vocational preference inventory to assess congruency, studies have shown significant positive correlations between congruency with the stability of career choices (Miller, 2006). In essence, Holland’s theory predicts that individuals will choose careers that are consistent with their personal characteristics. However, a lack of self-knowledge and career information might impede career choices, leading to individuals making career choices that lie outside and individual’s dominant personality domains, resulting in poor personality/occupational fit (Bandura, 2001; Budge et al., 2010).

The theory is relevant among contemporary career-development professionals’ thinking about the world of work and methods of promoting clients’ career aims. It is among the most widely researched and applied vocational choice theories. Its longevity and appeal likely relate to its parsimony, thereby making it appropriate for consideration in the current study. Regardless, even though Holland’s theory has stood the test of time over the years for its view on how specific personalities can be matched with specific careers, recent challenges to the theory’s applicability include assertions that research has failed to find a strong link between congruence and outcomes, such as satisfaction and performance (Vulcan, 2017). Other reviews of Holland’s theory have cited limitations that include problems inherent in trait factor theories, including the possibility that people can change themselves and their environments. The occupational and individual traits theory attempts to match are variable and subject to modification.

The implication of the theory in the study is that every occupation has a work environment which must be compatible with the personal orientation of students. Students’ career aspirations should be guided by their personality type and the job environment to ensure satisfaction for the individual, the community and the nation at large. An instance where students are pursuing accounting as a programme but have a higher preference for science-related careers such as becoming medical or agricultural officers, gives a strong indication for a mixed match and its related challenges, which may affect the individual’s work output and national productivity in general.

3.2. Conceptual perspective on personality type and occupational choice

Six personality types from the theoretical review are explained further here under the conceptual review of this study. These six personality types (RIASEC) are realistic (R), investigative (I), artistic (A), enterprising (E), and conventional (C) (Gottfredson & Holland, 1966). Realistic (R) individuals are described as stable and active people who love practical or physical activities, such as mechanics, building, athletics, and machinery operation (Vulcan, 2017).Thus working with gadgets instead of ideas and working with plants and animals are preferred among realistic individuals. Communication style among realistic individuals is characterised by frankness and a direct manner (Vulcan, 2017). Realistic individuals are weak in human relations but very strong in mechanical and physical activities, technical competencies, and work that produces tangible results. Thus, they may be found in occupations such as electrician, engineer, veterinarian, and the military in Ghana.

The investigative personality (I) type describes observant, intellectual and analytical individuals who are very comfortable with scientific, mathematical, and research activities (Miller, 2006). Investigative individuals also solve abstract and complex problems through logic and introspective analysis (Rojewski, 2005). They are weak in leadership roles and persuasive skills but are comfortable working autonomously and mostly see themselves as intellectuals with scientific and mathematical capabilities (Miller, 2006). Examples of investigative careers in Ghana include biologists, medical technologists, chemists, and systems analysts.

Artistic (A) individuals, the third personality type, are creative, innovative, and intuitive and enjoy creative activities, including painting, writing, drawing, directing stage productions and self-expression through artistic creation (Peters & Büchel, 2011). Artists are repugnant to conformity and convention but are comfortable with ambiguity, flexibility, impulsiveness, and emotions. Artistic is very expressive and communicates in an open manner (Miller, 2006). Though artistic individuals might lack clerical or organisational skills, they are very strong in dramatic, musical, aesthetic and writing skills (Miller, 2006; Owusu et al., 2018). Example of artistic occupations in Ghana include musicians, reporters and interior decorators.

Social (S) personality relates to individuals who are concerned with the welfare of others, idealistic and humanistic (Gottfredson & Holland, 1966; Issa and Nwalo (2008). They enjoy solving interpersonal problems and social activities as well as helping, training or teaching, counselling, and developing others. Thus human relations are very dear to social personality type individuals (Vulcan, 2017). These individuals dislike the systematic use of equipment or machines (weak in mechanical ability) but are very comfortable with working in a team and using interpersonal skills to solve problems. They are also very persuasive, warm, and tactful in their communication (Vulcan, 2017). Typical examples of occupations under the social personality type in Ghana include teachers, counsellors, and social workers. BED Accounting students in Ghana generally fall under this personality type.

Sociable, self-confident, ambitious, adventurous, and energetic characteristics describe enterprising (E) individuals (Gottfredson & Holland, 1990). This category of individuals do not like systematic or routine activities but are highly outstanding in persuading others through sales and leadership roles that bring about economic gains and organisational goals (Gottfredson & Holland, 1966). Enterprising individuals are very sociable, good public speakers, and are seen as very domineering (Peters & Büchel, 2011). Though they lack scientific skills, they are very self-confident, forceful, and good at leadership, speaking, selling, power and status. Examples of enterprising occupations in Ghana include salespeople, business executives and managers.

The last personality type is the conventional (C) personality type. Conventional individuals are conforming, efficient, organised, careful, and conscientious (Vulcan, 2017). These individuals dislike ambiguity and lack creativity but prefer operating office equipment, well-defined instructions, organising schedules, and maintaining and manipulating data (Vulcan, 2017). Conventional individuals also have weak leadership skills but are very efficient, orderly, and good at numerical and clerical abilities (Gottfredson & Holland, 1990). These abilities make them comfortable with organisational activities such as record-keeping and data management. Examples of occupations in this category in Ghana include accountant, secretary and banker. Thus, if BED Accounting students decide not to teach but to practice as accountants, then they can be classified under this category.

3.3. Operationalisation of the personality types in this study

The operationalisation of these personality types in this study is that realistic individuals is represented by mechanical-technological activities termed ACTSC1. Investigative individuals is also represented with mathematical-computation activities (related to BED Accounting career path) captioned as ACTSC2, and Social personality type related to science research activities and were denoted with ACTSC4. Artistic personality type was represented with Fine Art activities termed as ACTSC6; enterprising individuals were also represented with persuasive- enterprising activities (related to the BED Accounting career path) called ACTSC5. The last personality type- conventional (C) was represented by managerial-clerical activities, also termed as ACTSC3. The conceptual review of the variables of this study is portrayed in Figure 1, highlighting the interconnectedness of these variables of interest and the hypotheses of this study.

Figure 1. Conceptual framework showing the relationship between activities and their corresponding occupation in Ghana.

ALT TEXT: Twelve rectangular images used to represent six groups of activities leading to their specific six groups of occupations and the interrelationship between them.

Source: Authors’ constructs based on the review of literatureKey: ACTSC1 = Mechanical- Technological Activities, ACTSC2 = Mathematical Computation activities, ACTSC3 = Managerial- Clerical Activities, ACTSC4 = Science Research Activities, ACTSC5 = Persuasive- Enterprising Activities, and ACTSC6 = Fine Art activities.OCCSC1 = Mechanical- Technological Occupation, OCCSC2 = Mathematical Computation Occupation, OCCSC3 = Managerial- Clerical Occupation, OCCSC4 = Science Research Occupation, OCCSC5 = Persuasive- Enterprising Occupation, OCCSC6 = Fine Art Occupation.

4. Methodology

The descriptive survey design was adopted for this study from the positivist paradigm (Gravetter et al., 2020; Segbenya et al., 2021). A census technique was used to sample the entire population of 144 final years (BED Accounting) university students for the study. The BED Accounting students were selected for this study because they have benefited from a career counselling course and services and being in the final year put them in a better position to be able to respond to the adopted instrument (questionnaire) of the study. Additionally, the BED Accounting programme did prepare graduates to either teach in the classroom or for the industry as counsellors or guidance coordinators. Thus, this category of graduates bridges the gap between both graduates being prepared to only teach and those prepared for the industry only. The data collection instrument was an adopted questionnaire of Occupational Interest Profiles (OIP) from Essuman (1988). The purpose of the occupational interest profile or inventory is to help to find out the job or activities one is interested in and finds comfortable doing. Part one of the OIP listed ninety-six job-related activities, and part two indicated ninety-six occupations with their descriptions. Part one was further grouped into twelve distinctive activities that pointed toward a particular occupation, and part two was also further grouped into twelve notable occupations in Ghana. However, this study focused on the first six distinct activities and their occupations in Ghana for this paper (and the remaining six categories will be dealt with in subsequent papers). These distinctive activities considered in this present study are Mechanical- Technological Activities (ACTSC1), Mathematical Computation activities (ACTSC2), Managerial- Clerical Activities (ACTSC3), Science Research Activities (ACTSC4), Persuasive- Enterprising Activities (ACTSC5) and Fine Art activities (ACTSC6). The six main occupations out of the twelve occupations this paper investigated based on the activities enumerated earlier were Mechanical- Technological Occupation (OCCSC1), Mathematical Computation Occupation (OCCSC2), Managerial- Clerical Occupation (OCCSC3), Science Research Occupation (OCCSC4), Persuasive- Enterprising Occupation (OCCSC5) and Fine Art Occupation (OCCSC6).

The data collection instrument in a hardcopy form was distributed to respondents in a face-to-face mode. Participants were required to indicate the extent of their likeness for each activity and occupation on a four-point Likert scale type such as strongly agree, agree, disagree, and strongly disagree for each activity. Apart from the distinct activities and the various occupations captured on the OIP, the demographic profile of respondents was also captured in part three of the profile in terms of gender, and age, among others.

In terms of ethical consideration, all ethical standards were ensured, including the freedom to participate and withdraw at any stage of the study, anonymity, informed consent, confidentiality, and avoidance of harm to research participants. Specifically, several steps were taken to obtain informed consent from respondents. Firstly, the researchers obtained an introductory letter to introduce the study’s purpose and the benefits therein to respondents and obtain explicit permission from them in class. Secondly, a Consent Form for Adults from IRB was issued and explained to all respondents to solicit for their consent. Thirdly, consented individuals were issued hard copies of the questionnaires under anonymity and were asked not to indicate their names and index numbers on the questionnaire. The researchers explained every detail of the instrument and educated respondents on what was expected of them. All filled anonymized questionnaire were then retrieved at a later date upon several follow-ups. The reliability and validity results were above the minimum thresholds (See, Table 1 and 2), suggesting that the instrument was good to be used. Ethical clearance (ID—UCCIRB/EXT/2022/24) was therefore granted by the Institutional Review Board of the University of Cape Coast for carrying out this study. Data were analysed with Partial Least Square-Structural Equation Modelling (PLS-SEM) to test the hypotheses. The main steps that guided the methodology and data analysis from a theoretical perspective were:

1. Choosing the research design: The quantitative approach and the descriptive survey design were adopted for this study from the positivist paradigm due to the study’s topic and focus.

2. Choosing a sample based on the population of the study: This study adopted the census technique to capture all the subjects in the population because of the number of the entire population.

3. Data collection using data collection instrument: Quantitative data were collected with the use of an adopted questionnaire of Occupational Interest Profiles (OIP) from Essuman (1988).

4. Data cleaning, coding and entry of data into the SPSS database

5. Converting SPSS data into comma-separated versions in excel format for analysis purposes.

6. Choosing the appropriate model for the analysis: characteristics of the data and assumptions of the PLS-SEM were examined for a match before the PLS-SEM was finally selected.

7. Identification and selection of hypotheses to be tested: The nature of the hypotheses and how they were stated were examined. It was resolved that all eleven hypotheses qualified to be tested using the PLS-SEM model.

8. Preliminary data analysis. The preliminary analysis was based on checking values obtained for Cronbach’s Alpha, rho A, Composite Reliability and Average Variance Extracted (AVE), discriminant validity, and Multicollinearity met the basic criteria.

9. Main data analysis using the PLS-SEM model: The main analysis was to test the hypotheses guiding the study upon the preliminary analysis, and confirm that the data met the suggested criteria.

10. Presentation of results and writing of the research report: The results of the study were presented in Tables and Figures, and interpretations were assigned to them as well as how they were linked to previous studies.

Table 1. Demographic characteristics of respondents

Demographic characteristics	Frequency	Percent
Age
21–25 years	100	69.4
26–30 years	38	26.4
31–35 years	6	4.2
Total	144	100
Gender
Male	95	66.0
Female	49	34.0
Total Level 400	144 144	100 100

Source: Field data (2022)

Table 2. Construct reliability and validity

Constructs	Cronbach’s Alpha	rho_A	Composite Reliability	Average Variance Extracted (AVE)
ACTSC1	0.821	0.830	0.882	0.651
ACTSC2	0.840	0.848	0.893	0.677
ACTSC3	0.601	0.605	0.815	0.687
ACTSC4	0.872	0.872	0.901	0.568
ACTSC5	0.661	0.695	0.814	0.597
ACTSC6	0.833	0.850	0.881	0.599
OCCSC1	0.801	0.801	0.909	0.834
OCCSC2	0.775	0.795	0.855	0.597
OCCSC3	0.603	0.605	0.829	0.708
OCCSC4	0.875	0.885	0.909	0.668
OCCSC5	0.734	0.747	0.854	0.664
OCCSC6	0.898	0.905	0.919	0.620

Source: Field survey (2022)

5. Results

5.1. Demographic data

The preliminary analyses of the results focused on the respondents’ demographic characteristics in terms of gender, age, and level of university students. Table 1 shows the results for the demographic characteristics of respondents of the study. From the results, most of the respondents were aged between 21–25 (69.4%) and were males (66.0%). All respondents (100%) were also final-year university students (level 400) pursuing BED Accounting.

5.2. Measurement of model

The internal consistency of the model was first determined with the use of the PLS algorithm for confirmatory factor analysis. The measurement was done on individual items forming the constructs of the study, as found in the reflective model presented in Figure 2. Figure 3 compared to Figure 2, has all the items or questions measuring their respective study constructs. However, the results suggested that not all items in Figure 3loaded with a .700 minimum threshold, and for that matter, such items scoring below the .700 minimum threshold were removed from the model. Thus, the results in Figure 2 show only items loaded with the minimum loading of 0.70 and above (suggested by Hair et al., 2017) for each item measuring the study’s variables.

Figure 2. An algorithm for confirmatory factor analysis

Twelve circle images representing six groups of activities and six occupations in Ghana and how they correlate with each other as well as the values for the specific items used to form the individual variables/occupations.

Source: Field survey (2022)Key: ACTSC1 = Mechanical- Technological Activities, ACTSC2 = Mathematical Computation activities, ACTSC3 = Managerial- Clerical Activities, ACTSC4 = Science Research Activities, ACTSC5 = Persuasive- Enterprising Activities, and ACTSC6 = Fine Art activities.OCCSC1 = Mechanical- Technological Occupation, OCCSC2 = Mathematical Computation Occupation, OCCSC3 = Managerial- Clerical Occupation, OCCSC4 = Science Research Occupation, OCCSC5 = Persuasive- Enterprising Occupation, and OCCSC6 = Fine Art Occupation.

Figure 3. Bootstrapping resultsfor path analysis.

Twelve circle images representing six groups of activities and six occupations with their specific items used to form them and the performance of these items or questions.

Source: Field survey (2022).

5.0.3. Internal consistency measure for the analysis

Four main indices- Cronbach’s Alpha, rho A, Composite Reliability and Average Variance Extracted (AVE) (Segbenya et al., 2021; Hair et al., 2017) were used to check for the internal consistency measures for the PLS path model in this study. The results, as presented in Table 2, show a Composite Reliability value between 0.814–0.919 for all the variables, a Cronbach’s Alpha value between 0.601–0.898 for all variables, and a rho-A value between 0.605–0.905. This meant that all the variables achieved the minimum threshold recommended by Hair et al. (2017). Additionally, the Average Variance Extracted (AVE) values were between 0.568–0.834, which were above the minimum threshold of 0.50 recommended by Segbenya et al (2021), suggesting that all variables of the model achieved both reliability and validity standards.

5.0.4. Discriminant validity

The uniqueness of each variable in the study was achieved by checking for the discriminant validity using the Fornell-Larcker Criterion, as suggested by Henseler, Ringle and Sarstedt (2015), and the results are displayed in Table 3. All diagonal loadings for the same variable were zero and between variables of the study were below 0.85 thresholds (Henseler, Ringle and Sarstedt, 2015), suggesting that discriminant validity was achieved for the PLS path model.

Table 3. Discriminant validity Fornell-Larcker criterion

	ACTSC1	ACTSC2	ACTSC3	ACTSC4	ACTSC5	ACTSC6	OCCSC1	OCCSC2	OCCSC3	OCCSC4	OCCSC5	OCCSC6
ACTSC1	0.807	0
ACTSC2	0.497	0.823	0
ACTSC3	0.245	0.153	0.829	0
ACTSC4	0.657	0.614	0.227	0.754	0
ACTSC5	0.325	0.298	0.450	0.485	0.773	0
ACTSC6	0.540	0.282	0.264	0.607	0.392	0.774	0
OCCSC1	0.734	0.466	0.155	0.616	0.304	0.506	0.813	0
OCCSC2	0.507	0.612	0.168	0.619	0.409	0.440	0.696	0.772	0
OCCSC3	0.302	0.242	0.335	0.403	0.477	0.380	0.469	0.610	0.841	0
OCCSC4	0.502	0.480	0.220	0.678	0.406	0.475	0.730	0.801	0.628	0.817	0
OCCSC5	0.285	0.310	0.356	0.405	0.599	0.341	0.383	0.614	0.720	0.551	0.815	0
OCCSC6	0.463	0.381	0.257	0.535	0.329	0.684	0.655	0.677	0.560	0.709	0.524	0.788

Source: Field survey (2022)Key: ACTSC1 = Mechanical- Technological Activities, ACTSC2 = Mathematical Computation activities, ACTSC3 = Managerial- Clerical Activities, ACTSC4 = Science Research Activities, ACTSC5 = Persuasive- Enterprising Activities, and ACTSC6 = Fine Art activities.OCCSC1 = Mechanical- Technological Occupation, OCCSC2 = Mathematical Computation Occupation, OCCSC3 = Managerial- Clerical Occupation, OCCSC4 = Science Research Occupation, OCCSC5 = Persuasive- Enterprising Occupation, and OCCSC6 = Fine Art Occupation.

5.0.5. Multicollinearity

According to Fidel and Tabachnick, cited in Segbenya (2021: 43), “multicollinearity refers to where two or more independent variables are highly correlated with each other. Two or more independent variables measure the same thing but in a different way. When this exists, the estimated regression coefficients can oscillate extensively, making it unstable to interpret the coefficients as an indicator of the predictor variable”. For this reason, the existence of multicollinearity, which could affect the validity of the results obtained by the path significance test, was checked with the use of the variance inflated factors (VIF) as suggested by Hair et al. (2017) with threshold values below 3.3 suggesting that the reflective model was a multicollinearity-free model. The results shown in Table 4 suggested no multicollinearity issues since all the inner values were below 3.3 thresholds.

Table 4. Inner VIF values for testing for multicollinearity among the variables

	OCCSC1	OCCSC2	OCCSC3	OCCSC4	OCCSC5	OCCSC6
ACTSC1	1.000
ACTSC2		1.277
ACTSC3			1.029
ACTSC4				1.194
ACTSC5					1.197
ACTSC6						1.132
OCCSC1		1.277
OCCSC2			1.029
OCCSC3				1.194
OCCSC4					1.197
OCCSC5						1.132
OCCSC6						1.000

Source: Field survey (2022)Key: 1. ACTSC1 = Mechanical- Technological Activities, ACTSC2 = Mathematical Computation activities, ACTSC3 = Managerial- Clerical Activities, ACTSC4=Science Research Activities, ACTSC5= Persuasive- Enterprising Activities, and ACTSC6= Fine Art activities.2. OCCSC1 = Mechanical- Technological Occupation, OCCSC2 = Mathematical Computation Occupation, OCCSC3 = Managerial-Clerical Occupation, OCCSC4 = Science Research Occupation, OCCSC5 = Persuasive- Enterprising Occupation, and OCCSC6 = Fine Art Occupation.

5.0.6. Structural model and hypotheses testing

Testing for the significance of the hypotheses for path analysis was done with the Bootstrapping sequence of 5000 samples utilised in the PLS bootstrap procedure as recommended by Hair et al. (2017) and Segbenya et al. (2022). The results can be seen in Figure 4.

Figure 4. AQ10PLS algorithm for allitems measuring the constructsof the study and their performance

Source: Field survey (2022)

5.0.7. Results of path analysis

Table 5 presents the detailed results for the path significance determined from the PLS bootstrapping sequence. The first part of the results highlights the R² values supported by the adjusted R² values, as presented in Table 5. The R² values explained the variance in the dependent variable predicted by the independent variables (Hair et al., 2017). Thus, the structural model explained about 0.539 variances in Mechanical- Technological Occupation (OCCSC1), 0.589 variances in Mathematical Computation Occupation (OCCSC2) and 0.427 variances in Managerial- Clerical Occupation (OCCSC3) among university students. Furthermore, it was also established that the structural model explained 0.610 variances in Science Research Occupation (OCCSC4), 0.472 variances in Persuasive- Enterprising Occupation (OCCSC5), and lastly, 0.564 variance in Fine Art Occupation (OCCSC6).

Table 5. Path coefficients

	R Square					R Square Adjusted
OCCSC1	0.539					0.535
OCCSC2	0.589					0.584
OCCSC3	0.427					0.419
OCCSC4	0.610					0.604
OCCSC5	0.472					0.465
OCCSC6	0.564					0.557
	Beta	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values	Confidence Intervals		f Square
						2.5%	97.5%
1. ACTSC1 -> OCCSC1	0.734	0.737	0.047	15.771	0.000	0.630	0.815	1.167
2. ACTSC2 -> OCCSC2	0.367	0.369	0.079	4.654	0.000	0.198	0.517	0.257
3. ACTSC3 -> OCCSC3	0.240	0.246	0.062	3.877	0.000	0.124	0.359	0.097
4. ACTSC4 -> OCCSC4	0.508	0.509	0.059	8.661	0.000	0.397	0.620	0.553
5. ACTSC5 -> OCCSC5	0.450	0.464	0.086	5.230	0.000	0.296	0.623	0.321
6 ACTSC6 -> OCCSC6	0.572	0.580	0.057	10.012	0.000	0.467	0.686	0.662
7. OCCSC1 -> OCCSC2	0.524	0.526	0.071	7.378	0.000	0.380	0.672	0.525
	Beta	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values	Confidence Intervals		f Square
8. OCCSC2 -> OCCSC3	0.569	0.570	0.058	9.758	0.000	0.443	0.668	0.550
9. OCCSC3 -> OCCSC4	0.423	0.424	0.059	7.133	0.000	0.303	0.531	0.384
10 OCCSC4 -> OCCSC5	0.368	0.360	0.084	4.407	0.000	0.191	0.512	0.214
11. OCCSC5 -> OCCSC6	0.329	0.330	0.066	4.968	0.000	0.178	0.463	0.219

Source: Field survey (2022) **p < 0.000, *p < 0.05 supportedKey: ACTSC1 = Mechanical- Technological Activities, ACTSC2 = Mathematical Computation activities, ACTSC3 = Managerial- Clerical Activities, ACTSC4 = Science Research Activities, ACTSC5 = Persuasive- Enterprising Activities, and ACTSC6 = Fine Art activities.OCCSC1 = Mechanical- Technological Occupation, OCCSC2 = Mathematical Computation Occupation, OCCSC3 = Managerial- Clerical Occupation, OCCSC4 = Science Research Occupation, OCCSC5 = Persuasive- Enterprising Occupation, and OCCSC6 = Fine Art Occupation.

The second part of the results, as presented in Table 5, also relates to the significance of path analysis results for the study’s variables in terms of testing of hypotheses of the study. The path analysis results suggested that all the eleven hypotheses guiding this study achieved statistical significance. Thus, there was a statistically significant positive relationship between mechanical-technological activities (ACTSC1) and mechanical-technological occupation (OCCSC1) at (β = 0.734, t = 15.771, p = 0.000) for hypothesis one. Also, there was a statistically significant relationship between mathematical computation activities (ACTSC2) and mathematical computation occupation (OCCSC2) among BED Accounting students at (β = 0.367, t = 4.654, p < 0.000) for hypothesis two. The results revealed a positive and significant relationship between managerial-clerical activities (ACTSC3) and managerial-clerical occupation (OCCSC3) for hypothesis three at (β = 0.240, t = 3.877, p < 0.000).

Furthermore, the results for hypotheses four and five of the study revealed that there was a significant positive relationship between science research activities (ACTSC4), and science & research occupation (OCCSC4) among university students at (β = 0.508, t = 8.661, p < 0.000); and between persuasive- enterprising activities (ACTSC5), and persuasive- enterprising occupation (OCCSC5) at (β = 0.450, t = 5.230, p < 0.000) among university students. The last hypothesis testing the relationship between activities and occupations, as captured in hypothesis six, also had a significant relationship between fine art activities and fine art occupations among BED Accounting students at (β = 0.572, t = 10.012, p < 0.000).

The results, as presented in Table 5, also highlighted the relationship between the study’s last five hypotheses (Hypotheses seven to eleven) based on the relationship between the six various occupations selected for this study. Thus, there was a statistically significant positive relationship between mechanical-technological occupation (OCCSC1) and mathematical computation occupation (OCCSC2) at (β = 0.524, t = 7.378, p < 0.000) for hypothesis seven. Hypothesis eight attained a statistically positive and significant relationship between mathematical computation occupation (OCCSC2) and managerial-clerical occupation (OCCSC3) at (β = 0.569, t = 9.758, p < 0.000); and objective nine of the study was also supported because there was a statistically positive significant relation between managerial- clerical occupation (OCCSC3) and science research occupation (OCCSC4) at (β = 0.423, t = 7.133, p < 0.000). The last two hypotheses in Table 5 (Hypotheses ten and eleven) were also supported since there was a statistically positive significant relationship between science research occupation (OCCSC4) and persuasive-enterprising Occupation (OCCSC5) at (β = 0.368, t = 4.407, p < 0.000); and persuasive- enterprising occupation (OCCSC5) and Fine Art Occupation (OCCSC6) at (β = 0.329, t = 4.968, p < 0.000).

6. Discussion of results

The findings of the study that there is a significant positive relationship between mechanical-technological activities and mechanical-technological occupation can be explain further. The results mean that university students who develop interest and pursue mechanical and technological activities will like joining two pieces of metals by welding, repairing a fault in a sewing machine and faulty torchlight, and the use tools like a screwdriver, pliers, and spanners for repairs. Such students could pursue a profession in any of the mechanical technology-related occupations. These occupations include chemical engineering: designing and building chemical plants, and studying and supervising chemical processes in the industry. Other occupations that such individuals could develop an interest in are: becoming an engineer or electronic technician who assembles and repairs equipment like radio, television, tape recorders, etc. Therefore, the findings of this study corroborate the findings of Essuman (1988) that likeness for welding and repairing activities, among others, relate to mechanical-technological occupation.

The research findings for hypothesis two of the study that established that there was a significant relationship between mathematical computation activities and mathematical computation occupation need further deliberation. The results mean that university students develop an interest in mathematical computation activities like guessing the time it takes a man to run on a kilometre, measuring the distance around a football field or measuring the space (volume) of a box by use of a ruler suggest that such university students could become a cartographer (who draws or complies maps or charts). Such students could also become land surveyors, measuring the area of land, the direction of a road, the height of a hill, etc. Becoming a quantity surveyor- calculating the amount and cost of materials needed for a building or any construction work is also a possible profession (Essuman, 1988; Vulcan, 2017).

A further explanation for the findings for hypothesis three, which established a significant relationship between managerial-clerical activities and managerial-clerical occupations. That is the interest of university students have in activities like organising office files for reference purposes, taking typing lessons, and typing letters have a strong linkage to the possibility that such students will become either a legal secretary-handling clerical work for a lawyer or library assistant -checks out books for loaning, organises books in the library. Thus, the assertion of Gottfredson and Holland (1990) that activities organising office files and typing letters predict one’s chances of succeeding in occupations under the managerial-clerical categorisations.

Furthermore, the findings for hypothesis four also supported that there was a significant relationship between science research activities and science research occupations among university students can be explained further. The results suggest that the interest of students for science research activities includes investigating how mirrors form images of objects or how sunlight can be changed into electricity; joining the school science club; observing how butterflies suck nectar (sweet juice) from flowers or how two substances combine to form a new substance. Thus, these activities can help such students to pursue careers in science research occupations. These science research occupations include being a chemist—studies substances and how they change; an entomologist -investigates the nature and life patterns of insects; a meteorologist- studies the weather conditions to foretell what the weather will be; or become a Zoologist -investigate the nature, growth, behaviour, and origin of animals (Essuman (1988); Vulcan (2017).

Several meanings can also be assigned to the findings of hypothesis five of the study, which found that there was a significant relationship between persuasive-enterprising activities and persuasive-enterprising occupations among university students. The findings mean that all students at the university level who express interest and pursue activities like reading the judgment of famous judges, studying the arguments in a court case, and writing adverts for a company have a high possibility of becoming either judge -decides who is right or wrong in a court case; or lawyers -defending people involved in a court case and advises people legally.

The last hypothesis in terms of relating activities to occupation was captured by hypothesis six, and its findings that there was a significant relationship between fine art activities and fine art occupations can also be explained further. The explanation is that students who develop a high level of interest in fine act activities such as drawing and painting pictures, joining the school art and craft club, learning to make statuses from clay, making plates and teacups from the clay, and lastly, studying how to draw and paint animals could pursue careers in fine art. Careers in the fine art that these students could pursue include being architects (designs and draws plans for buildings), fashion designers (designs new fashion in clothes), illustrators (draws and paints pictures in books) or Interior decorators (decorates rooms). Other careers in fine art that these categories of students are likely to pursue include photo engravers -who produce picture blocks for painting purposes; photographers- who take and print pictures of people, animals, and places; sculptors- moulds wood, stone, and metal, concrete into images of people, things etc.

Hypothesis seven was the first hypothesis to test the interconnectedness between two occupations (mechanical-technological occupation and mathematical computation occupation). The findings from this hypothesis that there were significant relations between mechanical-technological occupation and mathematical-computation occupation need explanation. The results suggest that any percentage increase for the likeness of mechanical-technological occupation will lead to the same percentage increase in likeness for mathematical computation occupation. This means that occupations such as engineering, electronic technician, and chemical engineering (OCCSC1) have a strong relationship with being a cartographer, land surveyor or quantity surveyor (OCCSC2). Thus, though these occupations (mechanical-technological occupation and mathematical computation occupation) are distinct. However, this study has found commonalities in terms of BED Accounting students’ interest in both occupations. Additionally, the findings suggest that students with a mathematical computation background can also pursue a career in mechanical-technological fields. Therefore, the findings of this study support that of Kobia-Acquah et al. (2020) and Holland (1966) that there is varied students’ interests in several careers.

Also, the findings of the study, as captured in hypothesis eight, that there was a significant relationship between mathematical-computation occupations and managerial-clerical occupations, can be explained further. University students have an interest in both occupations, which require different clear activities and skills. The results further suggest that a student will need some computation and mathematical skills to manage an enterprise well. Though a student’s mathematical and computation skills requirement might not necessarily be the basis for being employed to manage an institution, such knowledge could aid such students to better understand computation and mathematical issues raised by experts working under them.

Moreso, the findings of hypothesis nine that there was a significant relationship between science research occupation and managerial-clerical occupations also means that students will need some amount of managerial skills in (managerial-clerical occupations) to be able to succeed as a chemist, entomologists, meteorologists, and zoologist (under science-research occupation). The results, therefore, corroborate the findings of Nyamwange (2016) that the varied interest of students suggests their likeness to several occupations.

Furthermore, an explanation can be provided for hypothesis ten which found a significant relationship between science-research occupation and persuasive-enterprising occupation. It can deduce that students who want to pursue a career in a chemist, entomologist, meteorologist, and zoologist (under science-research occupation) have also developed an interest in persuasive -enterprising probable to enable them to present their issues to convince others. The findings further suggest that this category of students could desire to work at the laboratories, teach related courses under science research in academia, or make presentations on their findings to society. Thus, the findings of this study are in tandem with that of Kobia-Acquah et al. (2020) that students’ interests and career choices are not limited to one career.

An explanation is also needed for the findings of the last hypothesis (Hypothesis 11) that there was a significant relationship between Persuasive- Enterprising Occupation and Fine Art Occupation. The results suggest that any percentage increase in students’ interest in persuasive-enterprise occupations will result in the same percentage increase in students’ interest in fine art occupations such as sculpture, photography/photo engraving, illustrator, interior decoration, fashion design and architect. Thus, the results mean that the skills to present issues to convince others are necessary for persuasive -enterprises such as lawyers and judges but was very dear to pursuers of a career in the fine art field. This could mean that persuasive skills are needed to probable convince customers and to be able to present alternatives to customers to choose from. It can also further be conjectured that these students were equally interested in teaching-related courses in the fine art occupation in academia.

7. Theoretical implications

The findings of this study have a clear implication for Holland’s theory of vocational types guiding this study. That is the two pillars of the theory -personality type and environment determine career choices and interest in a particular career type. The first personality type identified was the realistic personality type, described as individuals who are active and stable and enjoy hands-on or manual activities, such as building, mechanics, machinery operation and athletics (This does not agree with the career path of BED Accounting students). They prefer to work with things rather than ideas and people. Thus, some university students’ preference for mechanical and technological occupations in the study supports the theory of vocational type. The second personality type identified in this study was investigated personality type that describes individuals who are analytical, intellectual and observant and enjoy research, mathematical or scientific activities. This second personality type is related to the mathematical and computational occupation as well as the science-research occupation categorisations in this study (Holland, 1973).

The findings of the study also revealed that students’ interest in the fine art occupation means that such students could be classified under the artistic personality type according to the theory of vocational type by Holland. Artistic personality type, as identified in this study, describes original, intuitive and imaginative individuals who enjoy creative activities, such as drawing or painting and acting in or directing stage productions (This does not agree with the career path of BED Accounting students). Additional personality type corroborated in this study was the enterprise personality type. Enterprise personality type relates to energetic, ambitious, adventurous individuals who enjoy activities that require them to persuade others to obtain organisational goals or economic gain. Thus, the students identified with the enterprise personality type were associated with those who had a preference for the persuasive-enterprising occupation category.The study also found the presence of conventional and social personality types. The major theoretical implication of all the findings of the study was that the personality of university students studied had an interest in several occupations suggesting that they had a combination of personality types in varying degrees (Holland, 1973). Thus, though the career path of BED accounting students do not generally agree with the realistic and artistic personality type, this study found the students have a significant interest in activities and occupations in line with these personality types.

8. Practical and managerial implications

The findings of the study equally have practical and managerial implications. The first practical implication for managers is that career counselling is very relevant at the basic school level. This is because major career decisions of students are made at this level, after which little can be done in terms of adjustment. Thus, the importance of career guidance should not be limited to job entrants. Thus, managers of organisations need to take a key interest in supporting building solid career guidance services and centres for basic school pupils in the country. Therefore, this will help provide adequate and up-to-date career guidance services for informed decision-making among learners early in their academic life.

The varied interest in several occupations suggests that the government must take a practical step in provisions for varied employment opportunities for university students to be employed in their preferred occupation. Universities providing academic content knowledge and employability skills should introduce practical sessions or industrial attachments to expose the university students to employability skills in the areas of their interest to prepare them for employment of their interest.

9. Conclusions and recommendation

This study modelled BED Accounting students’ preferences and interconnectedness among various careers/occupations in Ghana. The study found that there was a positive and strong statistically significant relationship between six personality type activities and six categories of occupations in Ghana. Thus, technological activities, mathematical computation activities, managerial-clerical activities, scientific research activities, persuasive-enterprising activities and fine art activities significantly predicted mechanical-technological occupation, mathematical computation occupation, managerial-clerical occupation, science research occupation, persuasive-enterprising occupation and fine art occupation. There was also strong interconnectedness between the six various occupations among university students in Ghana, suggesting that the personality of university students studied had an interest in several occupations suggesting that they had a combination of personality types in varying degrees for the various occupations studied (Holland, 1973). Unlike previous studies that look at how specific academic programmes prepare graduates for professions in areas of academic programmes, this study has revealed that several occupations other than those under mathematical computation appealed to BED Accounting students in Ghana. Also this study has found that academic training in a particular area did not limit university graduates’ ability and desire for other professions outside their academic discipline (interconnectedness). The findings, therefore, suggest the need to increase job availability and vary the teaching methodology to better prepare graduates for different jobs.

Based on the findings, it is recommended that the government of Ghana should create more jobs in the various disciplines to enable BED Accounting university students to be able to pursue their career interests other than what they were professionally trained for. Graduates should also be encouraged and supported to establish their own entrepreneurial businesses in line with their career interests. The National Enterprises Agency (formerly National Board for Small Scale Industries (NBSSI)) could provide support to establish entrepreneurial ventures. This will contribute to employment creation and reduce the current unemployment rate.

The Ministry of Education should also ensure that students at the junior high school level are provided with academic and career counsellors who will guide them to choose their Senior High School programmes after listening to their interests. This is also necessary to cater for pupils whose parents could be illiterate and unable to effectively counsel these pupils on the right academic programmes to select. Embarking on industrial trips and excursions among pupils at the basic level also exposes them to several career options for better decisions.

It is also recommended that existing academic counsellors and school authorities of basic and secondary schools should organise career awareness seminars for parents to enable them to appreciate the need for students to make an informed decisions about their careers. This will expose parents to various career options to help their wards make an informed choice. Additionally, the Ministry of Education should revise its educational curriculum and academic programmes to allow students to offer a common program in the first year of senior high school to help solve students’ being compelled to offer programmes because of the choice of a particular school.

10. Limitations and suggestions for further studies

Considering the widespread career choice issues, the sample size may miss out on some barriers or factors on career choices. The use of only B.ED (Accounting) students may make it difficult to generalise the study’s findings. Thus, to ensure the generalisation of the findings, further studies should expand to cover all other students. The qualitative aspect of the study could serve as a baseline study for a quantitative study on barriers to the development of career aspirations among students.

Abbreviation

ACTSC1: Mechanical- Technological Activities,

ACTSC2: Mathematical Computation activities,

ACTSC3: Managerial- Clerical Activities,

ACTSC4: Science Research Activities,

ACTSC5: Persuasive- Enterprising Activities,

ACTSC6: Fine Art activities.

OCCSC1: Mechanical- Technological Occupation,

OCCSC2: Mathematical Computation Occupation,

OCCSC3: Managerial- Clerical Occupation,

OCCSC4: Science Research Occupation,

OCCSC5: Persuasive- Enterprising Occupation, and

OCCSC6: Fine Art Occupation.

PLS-SEM: Partial Least Squares Structural Equation Modelling

SEM: Structural Equation Modelling

VIF: Variance Inflated Factor

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.