Structure Of Professional Competence In Vocational Education
Empirical results about the structure of professional competence in vocational education are rare. Some studies have shown that, in many occupations, professional competence can be divided in professional problem-solving competence and content knowledge (Nickolaus, 2011, p. 334; Nickolaus, Geißel, Abele, & Nitzschke, 2011, pp. 86–90; Gschwendtner, 2008, p. 106). In the occupations of mechatronics and electronics technicians, the professional problem-solving competence is predominantly operationalized as trouble-shooting in technical systems. For the occupation of electronics technician, besides the analytical dimension “trouble-shooting”, a constructive dimension of professional problem-solving competence is assumed, but not yet tested. The study of Leutner, Fleischer, Wirth, Greiff, and Funke (2012) and Kallies, Hägele, & Zinke, 2014) support the assumption. In accordance with these findings, studies about the structure of professional competence showed that the content knowledge has the highest influence on problem-solving competence (Jonassen, 2000; Nickolaus, Abele, Gschwendtner, Nitzschke, & Greiff, 2012, pp. 265–267; Scherer, 2012, pp. 40–42 and S. 16).
Following the theoretical framework of problem-solving of Jonassen (2000) Walker, Link, and Nickolaus (2015) specified the structure of professional competence for the occupation of electronics technicians for automation technology. There is an assumption about a direct influence of the general fluid cognitive ability on both problem-solving competences and the content knowledge. Furthermore, the content knowledge has a direct influence on both problem-solving competences, which are assumed to be two separate but correlated dimensions of the problem-solving competence.
The core question of our study is whether analytical and constructive problem-solving competence are two separate dimensions, as assumed. The second research question addresses the influence of content knowledge and general fluid cognitive ability on the problem-solving competence.
Analytical and constructive problem-solving competence: The approach to measuring analytical and constructive problem-solving competence was a set of realistic problems with the focus on professional activities such as programming (constructive problem-solving) and troubleshooting a programmable logic controller (PLC) (analytical problem-solving). The development of the items was based on the structure of the control program based on Benda (2008, p. 145). Following this approach for both problem-solving competence, items regarding the operating mode, the step chain and output routine were developed. In total, eight troubleshooting scenarios and eight programming scenarios were generated per problem-solving competence. To measure the analytical problem-solving competence, we used a simulation (Walker et al., 2016). The reliability of the analytical problem-solving instrument is SEM-Reliability =.75. In the constructive problem scenario, the apprentices had to program a certain part of the control programme of a PLC in a complex automation system where parcels were transported by a belt conveyor, measured by sensors and sorted by a pick-and-place unit with a vacuum gripper (Link & Geißel, 2015). The reliability of the constructive problem-solving instrument is SEM-Reliability=.83.
Content knowledge: In accordance with van Waveren and Nickolaus (2015) the items of the content knowledge test represent a three-dimensional content specific structure, consisting of the dimensions of automation/PLC (AT/PLC), electrical engineering (EE) and basic principles of electro-technology (BP) (van Waveren & Nickolaus, 2015, pp. 73–76). The latent correlations between the subdimensions are high (EE and BP is r=.89, between AT/PLC and BP r=.87 and between r=.83) but standalone. The reliability of the test is about EAP/PV-Reliability=.72 across all dimensions.
General fluid cognitive ability: We measured general fluid cognitive ability only with part one of the CFT 20-R (Weiß, 2006), i.e., the subset of continuing logical progressions, classifications, matrices and topologies were administered. The related loss of reliability from rtt=.95 (part one and two together) to rtt=.92 (only part one) seems acceptable considering the reduction of the test duration (Weiß, 2006, p. 48).
*Method and Results*
Based on the theoretical conception of the two problem-solving competence, (analytical/constructive) two diagnostic approaches for their measurement are presented and discussed in terms of their validity (Kane, 2013). Next, structural equation models (SEM) are estimated to analyze the relationship of the analytical and constructive problem-solving competence alone and under the control of content knowledge and general fluid cognitive ability. At first, a two dimensional SEM was computed, where the correlation between the analytical and constructive problem-solving competence was estimated. Secondly, a unidimensional SEM was computed which can be seen as equivalent to a two dimensional SEM with fixed correlation to one between the two facets of the problem-solving competence. These models were compared based on the likelihood of ratiotest and fit statistics (e.g. delta CFI).
The sample size in total is 373 apprentices attending the 3rd and 4th year of the German dual apprenticeship track of electronics technicians for automation technology.
The analyses confirmed our hypotheses and showed that analytical and constructive problem-solving competence are two separate but correlated dimensions. The fit of the two dimensional SEM was significantly better than the unidimensional. The latent correlation between the analytical and constructive dimension is r≈.80. After integration of the general fluid cognitive ability and the content knowledge in the model, the correlation between the two problem-solving competence decrease (r≈.60). In accordance with the reported studies of Nickolaus et al. (2012) and Schreiber (2012), content knowledge has the highest predictive value (β≈.50-80) for the two problem-solving competence.
*Significance of the study*
The results document a two-dimensional structure of problem-solving competence, which is represented through both an analytical and a constructive subdimension. These subdimensions remain stable even if general fluid cognitive ability and the three-dimensional content knowledge were integrated. In view of the fact that these two problem-solving dimensions are empirically separable but correlated, these results have implications for designing the final examination at the end of the apprenticeship. To ensure the evidence for validity based on test-content of the final exam, both subdimensions of problem-solving competence have to be included in an appropriate amount. The high influence of context-specific knowledge dimensions on analytical and constructive problems emphasizes the importance of content knowledge for problem-solving. Practical implications for teaching structures can also be drawn from the two-dimensional problem-solving structure in a manner that both dimensions have to be supported during the teaching process. Furthermore, it is important to ensure that the context-specific knowledge has also been taught. In perspective, the simulation for measuring analytical problem-solving could also be integrated in the teaching process. As reported, it is possible to represent industrial PLC and automation systems via the simulation authentically. Despite of the correlation between the analytical and constructive problem-solving competences and the similar context (problem-solving in an industrial automation system), the underlying process for solving analytical and constructive problems seems to be disjunctive.
With regard to the transferability of the results concerning the two-dimensional structure of problem-solving into other vocational domains, a differentiated consideration is necessary. We assume that the structure of problem-solving competence depends on the domain-specific tasks. For vocational domains, which are more closely related to the occupation of electronics technicians for automation technology, e.g. mechatronic technicians or electronics technicians for industrial engineering, a two-dimensional structure of problem-solving seems to be likely.
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