The central theme of this study attends to the role of secondary education in relation to two broad categories of specific aptitudes (psychomotor and spatial abilities). Utilising type of secondary education (incorporating subject choice) could be a crucial selection mechanism for high-volume, entry-level technical positions.
The objective of this research was to investigate whether the type of secondary education (incorporating subject choice) could be used as a proxy for psychomotor (dexterity and coordination) and/or spatial (ability to mentally assemble representations and spatial perception 2-D and 3-D) aptitudes in the selection of operators for an automotive plant in South Africa.
The motivation for this study arose from the evident gap in academic literature as well as the selection needs of the automotive industry.
A quantitative approach with a cross-sectional research design was used with a convenience sample (
Statistically and practically significant relationships were found between type of secondary education (incorporating subject choice), eye–hand coordination and spatial visualisation. Broad performance levels in the five aptitude instruments employed in this study were significantly associated with the type of matriculation certificate held by applicants. Specifically, types of secondary education that included mathematics and/or science as subjects were associated with higher levels of performance in the five specific aptitudes.
The type of secondary education (incorporating subject choice) held by applicants could be regarded as a key predictor variable in human resource selection. The study makes a case for a multiple-hurdles approach to selection and proposes a cost-effective preliminary screening method for low-level technical positions.
The study provides information to improve upon selection practices within the South African automotive industry. It could also assist human resource practitioners in designing selection processes for similar entry-level employees in other working contexts. The study makes a case for a multiple-hurdles approach to selection and highlights the reciprocal relationship between education and specific cognitive abilities in the science, technology, engineering and mathematics fields.
In their pursuit of optimising the human capital in organisations, South African (SA) human resource management practitioners are facing the challenges of a volatile, complex and ambiguous environment. Increased digitisation, amplified technological change, an increased focus on knowledge creation and globalisation means that a new set of competencies is required from employees (Ajith,
Gardner’s (
The relationship between these multiple intelligences measured by tools of various abilities, representing psychological concepts, as well as the impact of differing teaching strategies on academic achievement have been broadly investigated. Varying degrees of correlation between these constructs have been found (Carretta & Ree,
An important question regarding human capital therefore pertains to the relationship between education, training and cognitive skill formation (Brinch & Galloway,
Education could be an efficient resource in the selection of potential employees for STEM-related positions.
Advancement through the STEM fields underpins national wealth and is critical to the international competitiveness of countries. It serves as the foundation for research and development, innovation and the generation of a pool of sustainable entrepreneurs and business leaders (Harlan,
However, international and national educational systems are not adequately preparing youth with the skills required to advance within the STEM fields. SA participates in three main cross-national assessments of educational achievement. In comparison to all the other participating middle-income countries, SA has the worst education system. In fact, SA performs worse than many low-income African countries in these educational achievement assessments (Spaull,
Science, technology, engineering and mathematical-specific educational instruction has been found to influence students’ interest and achievements in STEM fields. The implementation of various forms of hands-on STEM activities was found to raise or maintain positive STEM interests amongst students at a secondary school level (Christensen, Knezek & Tyler-Wood,
The importance of spatial and psychomotor abilities in real work settings is evident in the literature. Studies have verified that level of aptitude and skill in these areas can be influenced by situational factors such as experience, education and training (Adanez,
The value of psychological aptitude tests therefore lies in their ability to successfully identify individuals with potential and those who are trainable in specific abilities (Foxcroft & Roodt,
It is with this in mind that this study sought to investigate the relationship between the technically oriented aptitudes and the forms of SA secondary education (incorporating subject choice). The secondary objectives of the study were stated as follows:
To determine whether there is a relationship between level of eye–hand coordination and type of secondary education (incorporating subject choice) attained; To determine whether there is a relationship between the ability to mentally assemble representations and the type of secondary education (incorporating subject choice) attained; and To determine whether there is a relationship between candidates’ spatial perception and the type of secondary education (incorporating subject choice) attained.
In order to address and expand on the abovementioned research objectives, the five primary research questions underpinning the project were:
Is there a significant relationship between the type of secondary education (incorporating subject choice) obtained and hand–eye coordination ability? Is there a significant relationship between the type of secondary education (incorporating subject choice) obtained and one-hand–eye coordination? Is there a significant relationship between the type of secondary education (incorporating subject choice) obtained and the ability to mentally assemble representations? Is there a significant relationship between the type of secondary education (incorporating subject choice) obtained and 2-D spatial perception ability? Is there a significant relationship between the type of secondary education (incorporating subject choice) obtained and 3-D spatial perception ability?
In the section that follows, a literature review of the theoretical frameworks underpinning the study is provided alongside a review of the empirical literature in the research field.
The structure and mechanisms of human intelligence have been researched for more than 100 years (Foxcroft & Roodt,
Notably, a multiple perspective of intelligence was proposed by Vernon (
The focus of this study was on aspects of Vernon’s (
The different forms of intelligence appear to be differentially affected by environmental factors such as age, education and training (Carretta & Ree,
Currently, there is significant appreciation of spatial ability in general terms. However, there is still a gap in the literature pertaining to the attainment and development of SI in educational settings and the impact thereof on the occupational field (Johnson & Bouchard,
Psychomotor and dexterity testing have also been increasingly used within the human resource management context (Foxcroft & Roodt,
The SA manufacturing sector requires high-level competencies in order to keep abreast of global competitiveness, the associated technological improvements and a significant increase in the prevalence of lean manufacturing practices (Mahembe,
The dilemma within the SA context is the selection hindrance created by the current inefficacy of the SA secondary education system (Deloitte,
The SA automobile industry has traditionally centred its recruitment and selection of entry-level employees on individuals with a technical education (Schafmeister,
For ease of reference, secondary education is understood as collectively referring to technical high schools, academic high schools and FET institutions. The terms ‘secondary education’, ‘Grade 12 qualification’ and ‘matriculation’ are hence used interchangeably. In this article, five forms of secondary education are named and defined as follows:
A Grade 12 education with mathematics and science as subjects in a secondary education qualification obtained through an academic high school. A matriculation inclusive of mathematics as a subject in a secondary education qualification achieved at an academic high school. A Grade 12 qualification with science as a subject in a secondary education acquired at an academic high school. A technical-type matriculation, inclusive of mathematics and science as subjects, as attained through a technical high school or FET institution. A general type secondary education which does not include mathematics and science as Grade 12 subjects and is obtained at an academic high school.
The quantitative research design and methodology utilised is outlined in the section that follows, as well as the study’s findings. Based on these findings, conclusions, recommendations and limitations of the research are provided.
A quantitative research methodology was followed to achieve the research objectives using a cross-sectional design. With a cross-sectional design, numerous individuals are examined at a specific point in time (Bryman,
This research formed part of a sizeable recruitment drive at a SA automobile plant. The target population was pre-screened according to two criterion employed by the organisation. Firstly, the candidates had obtained a Grade 12 qualification and had achieved a minimum stanine score of three on the general cognitive aptitude abilities (namely, verbal reasoning and non-verbal reasoning) previously assessed. As a result of these selection hurdles, a sampling frame of 1566 potential operator applicants remained within the databank. Given that the sampling frame was readily available to the researcher, a non-probability convenience sampling technique was employed, thus utilising the entire sampling frame within this study.
The majority (65.7%) of this study’s sample was male. A significant portion (45.3%) of the study’s participants were aged between 25 and 29 years, with the second largest group (22.8%) of respondents within the 30- to 34-year age category. Over 80% of the candidates surveyed were black candidates, 16.8% were mixed race, 0.5% were Indian and 0.9% were white candidates. A sizeable proportion (44.4%) of the sample have achieved an academic-type secondary education with mathematics and science as subjects. The second highest category (25.1%) was the general academic-type of matriculation with neither mathematics nor science as subjects in Grade 12. Applicants who completed their academic Grade 12 qualification with mathematics as a subject were the third highest category at 19.2%. A technical-type matriculation, inclusive of mathematics and science as subjects, was completed by 7.3% of the sample. The remaining 3.9% of the candidates had completed an academic Grade 12 with science as a subject.
Of the 2463 respondents who completed the first selection phase, 1618 were successful in meeting the qualifying screening criterion set for this phase and were therefore invited to attend the second phase of the selection process. A total of 49 candidates, evenly spread across all groups, were lost because of attrition for a variety of reasons prior to the commencement of the second phase of the assessment process. Therefore, a total of 1569 applicants were expected to complete phase two of the assessment process. However, three candidates were requested to exit the assessment process because they did not adhere to the prescribed assessment regulations. Consequently, a total number of 1566 respondents (63.6%) were actually assessed in the second phase of the assessment process. This was conducted over six assessment sessions.
The reliability of the various sub-tests within the TRAT battery was determined by the Kuder–Richardson formula 21 (K-R 21). The reliability coefficients of three of the TRAT sub-tests used in this study, namely the assembly, spatial perception 2-D and 3-D sub-tests, range from 0.72 to 0.92 and are regarded as being satisfactory. The dexterity and coordination measures are speed tests and the K-R 21 formula is therefore not applicable (Taljaard,
Data were collected over a period of several months. Following an in-house initial pre-screening process, candidates were required to participate in a multiple-hurdle selection process comprising two assessment phases. Those successful in phase 1, the general aptitude tools, were requested to complete phase 2, the technical aptitude sub-tests.
Answer sheets were manually scored using a scoring stencil, except for the dexterity and coordination measures, which were scored according to the psychological test manuals’ scoring instructions. In adherence to standard psychometric assessment practice, raw scores were converted to stanines, using the Grade 8 to Grade 10 norm table. This is in line with previous research done in the field (Lohman & Lakin,
Statistical analysis of the data was conducted using the SPSS 20 statistical package. Descriptive and inferential statistics were calculated. The descriptive statistics were intended to present a snapshot of the data, and the Chi-square test of independence was used to evaluate the relationship between secondary education (incorporating subject choice) and the five aptitudes assessed.
In preparation for the execution of the inferential statistics, the aptitude sub-tests results were tabulated into three categories: a low-, moderate- and high-scoring category. The low-scoring category included stanine scores ranging from 1 to 3, the moderate category comprised the stanine scores 4 to 6, whilst the stanine scores 7 to 9 were designated to the high-scoring category. Inferential statistics were then performed on these three scoring categories. Bivariate statistical analysis was carried out on the two variables within each hypothesis to establish either covariance or independence between the dependent and independent variables (Bryman & Bell,
Permission was obtained from the automotive plant’s head office to collect data in the organisation. All research respondents were also thoroughly informed of the assessment process and each participant voluntarily completed a specifically designed informed consent form.
Medians and modes of Trade Aptitude Test Battery sub-tests.
Sub-tests | Mdn | Mo |
---|---|---|
Dexterity | 3 | 3 |
Coordination | 5 | 5 |
Assembly | 6 | 6 |
Spatial perception 2-D | 7 | 9 |
Spatial perception 3-D | 7 | 7 |
Mdn, median; Mo, mode.
Note: The distribution of the data is recorded in stanine format.
Chi-square tests of independence were completed to scrutinise the relationship between the form of secondary education (incorporating subject choice) and the stanine scores achieved in the five aptitude tests, grouped according to low, moderate and high scores.
Contingency table of observed frequencies for the dexterity sub-test.
Dexterity | Stanine scores | Type of secondary education |
Total | ||||
---|---|---|---|---|---|---|---|
Mathematics and science | Mathematics | Science | Technical | General | |||
Low | Count | 389 | 162 | 27 | 64 | 205 | 847 |
% within group | 54 | 49 | 46 | 62 | 60 | 54 | |
Moderate | Count | 329 | 170 | 32 | 39 | 133 | 703 |
% within group | 45 | 51 | 54 | 38 | 39 | 45 | |
High | Count | 8 | 1 | 0 | 1 | 6 | 16 |
% within group | 1 | 0 | 0 | 0 | 1 | 1 | |
Note:
Contingency table of observed frequencies for the coordination sub-test.
Coordination | Stanine scores | Type of secondary education |
Total | ||||
---|---|---|---|---|---|---|---|
Mathematics and science | Mathematics | Science | Technical | General | |||
Low | Count | 80 | 24 | 5 | 20 | 37 | 166 |
% within group | 11 | 7 | 8 | 19 | 11 | 11 | |
Moderate | Count | 507 | 231 | 41 | 70 | 240 | 1089 |
% within group | 70 | 69 | 69 | 67 | 70 | 70 | |
High | Count | 139 | 78 | 13 | 14 | 67 | 311 |
% within group | 19 | 23 | 22 | 13 | 19 | 20 | |
Note:
Contingency table of observed frequencies for the assembly sub-test.
Assembly | Stanine scores | Type of secondary education |
Total | ||||
---|---|---|---|---|---|---|---|
Mathematics and science | Mathematics | Science | Technical | General | |||
Low | Count | 36 | 20 | 1 | 5 | 29 | 91 |
% within group | 5 | 6 | 2 | 5 | 8 | 6 | |
Moderate | Count | 317 | 143 | 29 | 49 | 205 | 752 |
% within group | 44 | 43 | 49 | 58 | 60 | 48 | |
High | Count | 373 | 170 | 29 | 49 | 110 | 723 |
% within group | 51 | 51 | 49 | 41 | 32 | 46 | |
Note:
Contingency table of observed frequencies for the spatial perception 2-D sub-test.
Spatial perception 2-D | Stanine scores | Type of secondary education |
Total | ||||
---|---|---|---|---|---|---|---|
Mathematics and science | Mathematics | Science | Technical | General | |||
Low | Count | 66 | 27 | 8 | 11 | 64 | 170 |
% within group | 8 | 8 | 14 | 11 | 19 | 11 | |
Moderate | Count | 251 | 119 | 24 | 38 | 136 | 568 |
% within group | 35 | 36 | 41 | 37 | 40 | 36 | |
High | Count | 415 | 187 | 27 | 55 | 144 | 828 |
% within group | 57 | 56 | 46 | 53 | 42 | 53 | |
Note:
Contingency table of observed frequencies for the spatial perception 3-D sub-test.
Spatial perception 3-D | Stanine scores | Type of secondary education |
Total | ||||
---|---|---|---|---|---|---|---|
Mathematics and science | Mathematics | Science | Technical | General | |||
Low | Count | 37 | 11 | 1 | 9 | 32 | 90 |
% within group | 5 | 3 | 2 | 9 | 9 | 6 | |
Moderate | Count | 258 | 106 | 29 | 44 | 169 | 600 |
% within group | 36 | 32 | 49 | 42 | 47 | 38 | |
High | Count | 431 | 216 | 29 | 51 | 149 | 876 |
% within group | 59 | 65 | 49 | 49 | 43 | 56 | |
Note:
The data provided in
Hypothesis 1 was therefore accepted.
The study’s second null hypothesis stated that there would not be a significant relationship between levels of coordination and type of secondary education qualification (incorporating subject choice) obtained. However, as depicted in
Seventy per cent of the respondents with mathematics and science as matric subjects and a general type of secondary education obtained moderate scores in this instrument. A total of 89% of these two forms of qualifications achieved moderate to high category scores. Candidates with mathematics as a subject in their Grade 12 qualification achieved the largest percentage (23%) in the high-scoring category. However,
Hypothesis 2 was therefore accepted.
A significant relationship -
Stanine scores in the high category were associated with candidates who had obtained a matriculation education with either mathematics and science or just mathematics as subjects. For both types of secondary education, more than half (51%) of the applicants attained high stanine scores. Ninety-eight per cent of the candidates with a Grade 12 qualification inclusive of science attained stanine scores of four and above for this tool. However, as depicted in
Hypothesis 3 was therefore accepted.
There was a significant relationship between the type of secondary education (incorporating subject choice) and the spatial perception 2-D sub-test stanine scores,
Hypothesis 4 was therefore accepted.
More respondents with mathematics as a matric subject realised higher scores (65%) in this instrument than candidates with the other types of secondary education. The second highest percentage (59%) of high–stanine category scores was obtained by candidates with mathematics and science as subjects in their secondary education.
Based on the results, Hypothesis 5 was therefore accepted.
The primary objectives of this study were to investigate the relationship between hand–eye coordination test scores and types of secondary education (incorporating subject choice) and to determine whether the forms of secondary education (incorporating subject choice) were related to the spatial visualisation test scores.
Three conclusions have been derived from the study’s five hypotheses. The first conclusion points to a differing complexity level across the five instruments employed in this study, whilst the second and third conclusions outline the different levels of aptitudes presented by matriculants with different types of secondary education.
In
The second conclusion pertains to the endorsed types of secondary education. Based on the results obtained across the five aptitude measures, three forms of secondary education (incorporating subject choice) are recommended, namely a Grade 12 qualification inclusive of science; a matriculation education with mathematics as a subject; and a secondary education including both mathematics and science subjects. The applicants with the secondary education inclusive of science consistently outperformed the other applicants educated through matriculation type in three of the instruments, namely, dexterity, assemble and spatial perception 3-D. However, in two of the sub-tests, namely coordination and spatial perception 2-D, they were outperformed. Matriculants who studied mathematics and/or science performed consistently better in the five aptitude sub-tests in comparison to the other two types of secondary education. These three forms of secondary education are concluded to have been positively associated with the applicants’ accomplishments in these specific aptitude measures. These forms of Grade 12 qualifications may also have afforded the applicants with exposure to a spatially enriched education as described in the research by Hsi et al. (
Thirdly, the technical and general types of secondary education were not optimal performers in the five aptitude sub-tests. Whilst the technical matriculation applicants performed moderately well in the assembly and spatial perception 2-D sub-tests, they did not perform optimally in the other three sub-tests. It is therefore concluded that these two forms of matriculation (incorporating subject choice) education are not able to reliably provide the technically oriented abilities required of automobile operators. This confirms the abundance of literature indicating the educational crisis that is being experienced in the technical school system, both internationally and nationally. Improved technical training systems should assist in addressing the current technical skills gaps by focusing on the type, relevance and levels of courses being offered (Ramdass,
Overall, the results of this study have highlighted statistically significant relationships between the five technically oriented aptitudes assessed in this study and the type of secondary education (incorporating subject choice) attained. This finding supports previous research that has highlighted the need for changes in curriculum design, teaching and assessment methodologies currently being employed in certain forms of secondary education. Being exposed, through certain forms of schooling, to specific stimuli and activities may have significant associations with specific abilities and hence potential employability.
The contribution of this research study is three-fold. The study has confirmed the applicability and relevance of employing the type of secondary education (incorporating subject choice) obtained as a cost-effective screening tool. Human resource practitioners need to take cognisance of the warning provided by several academics and researchers regarding the poor quality of education stemming from certain forms of secondary education in the country (Ramdass,
Secondly, the study has provided SA research confirming a relationship between education, training and specific cognitive abilities. This is of particular importance given the documented association between spatial aptitudes and achievement in STEM fields. Thirdly, this study’s findings have highlighted the benefits of utilising a multiple rather than a singular selection methodology. This is highly relevant in the SA context where supply exceeds demand in the labour market.
This study’s sample is not in line with either provincial or national data pertaining to age, race or gender as indicated in the 2001 census (Lehohla,
The primary objective of the study was to investigate the relationship between the type of secondary education (incorporating subject choice) obtained and the spatial and psychomotor aptitudes of potential operators within the automotive industry. The key variable to ascertain this relationship was a psychological assessment tool. The central recommendation from this research counsels the automotive industry to focus on applicants with mathematics and/or science as subjects in their academic Grade 12 qualification. The study has confirmed the utility of employing type of secondary education (incorporating subject choice) as a cost-effective initial screening mechanism within a multiple-hurdle selection approach. This has value for human resource managers and practitioners who are seeking to optimise the STEM fields within their organisation whilst not being overly burdened with compliance to the rules and regulations associated with psychological testing.
This research study formed part of a large recruitment process completed by a South African automotive assembly plant. The administration and communication of this research study was conducted by the internal human resource project team.
The authors declare that they have no financial or personal relationship(s) that may have inappropriately influenced them when they wrote this article
N.D. and K.V. were the promoters of J.P. for her master’s dissertation. The article flows from her research in this regard.