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Professional Competencies of Building Trade Apprentices After Their First Year of Training

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Competence Assessment in Education

Part of the book series: Methodology of Educational Measurement and Assessment ((MEMA))

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Abstract

The study presented here (DFG Ni 606 7-1) focuses on the professional competencies of building trade apprentices after their first year of training. Its main objectives are (1) to examine the dimensional structure of the apprentices’ professional competence and (2) to provide a description of their actual competencies by defining different competency levels. For this purpose, empirical data on 273 building trade apprentices (carpenters, tilers and plasterers) were collected. Confirmatory factor analyses and chi-square difference tests, corresponding to theoretical assumptions, show that a four-dimensional solution provides the best model fit—the four dimensions being technical drawing, basic technical mathematics, professional knowledge, and professional problem-solving. As was expected, all four dimensions show high latent correlations (r > .71). As previous studies have reported, the competency level of building trade apprentices is generally rather low. Major differences exist between apprentices of the different professions: on average, carpenters perform significantly better than do tilers or plasterers. A closer look at the competency levels in professional problem-solving reveals that almost two-thirds of the tilers and plasterers score at the lowest level (below level 1) and do not reach the curricular goals of the first year of training.

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Notes

  1. 1.

    Most of the studies mentioned here concentrated on cognitive aspects of professional competence; effects of motivation or volition were usually not considered, or were analyzed separately, as suggested by Klieme and Leutner (2006).

  2. 2.

    It has to be pointed out that the works cited here do not share a common concept of complexity. While some studies employ global ratings of complexity, other research approaches make use of indicators such as the number or interconnectedness of elements (see Nickolaus 2014).

  3. 3.

    It is important to know that the students in these schools have already signed a pre-agreement for an apprenticeship with an employer or firm. It is part of this agreement that the apprentices attend one day per week (or several weeks per year) at the employer’s workplace.

  4. 4.

    The importance of these basic requirements for building-related tasks is reflected not least in the fact that all three were taught as individual subjects before curricular reform introduced the learning fields in 1999 (see KMK 1999).

  5. 5.

    Unidimensionality was evaluated in Conquest 2.0 (Wu et al. 2007) by comparing alternative unidimensional and multidimensional models. Model evaluation criteria included Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and conditional Akaike Information Criterion (cAIC).

  6. 6.

    Item fit was evaluated according to the following criteria: (1) correct order of threshold parameters, (2) appropriate item-total correlation (≥.3), (3) appropriate weighted-t fit statistics (≤1.9), (4) homogeneity of parameter estimates between subsets of data (r ≥ .9), and (5) differential item functioning (DIF) for apprentices of different occupations.

  7. 7.

    The sizes of the subsamples corresponded approximately to the distribution of apprentices in the respective occupations in the state of Baden-Württemberg (cf. Statistische Berichte Baden-Württemberg 2014). Mean differences, as reported in Sectns. 13.6.2 and 13.7, are not biased by unequal sample size.

  8. 8.

    Following Prenzel et al. (1996), different types of motivation were distinguished in the questionnaire. Yet, due to time and space constraints, only the following four types were included: amotivation, extrinsic, identified, and interested motivation. Additionally, data was collected on a selection of social-contextual conditions, facilitating or forestalling positive motivational development: perceived difficulty, feeling of competence, perceived relevance, and teacher’s feedback.

  9. 9.

    The numeracy test scale consisted of 11 items. Test reliability (based on weighted likelihood estimates, WLE) was acceptable (.72). As the variance of the latent ability distribution was 2.59, the test differentiated well between the subjects. The average standard error of the WLE person parameter estimates was comparably high (0.84), due to the relatively small number of items for a wide range of ability.

  10. 10.

    The test of prior knowledge included 16 items. WLE reliability was acceptable (.73); the variance of the latent ability distribution (1.23) indicated a good differentiation between subjects. The average standard error of the WLE person parameter estimates (0.62) pointed to a balanced distribution of persons’ abilities and item difficulties.

  11. 11.

    The fact that our sample consisted of two quite different groups became especially important during item scaling. Analyses of differential item functioning (DIF) were carried out for both test scales (basic numeracy skills and prior knowledge in the professional domain). Items that were differentially more difficult for one of the groups were deleted from the scales.

  12. 12.

    Following Weinert (2001), “competence” is understood as a “system of abilities, proficiencies, or skills that are necessary or sufficient to reach a specific goal.” (ibid., 45). The term “competencies” is used when referring to specific components of the respective system (see ibid.).

  13. 13.

    Following the recommendations of Muthén and Muthén (2012) and Finney and DiStefano (2006), all analyses were run using Mplus’s WLSMV estimator, as the research points to advantages over other estimators when dealing with ordered categorical data and few categories (<3).

  14. 14.

    CFA and the chi-square difference test were carried out using Mplus 6.12 (Muthén and Muthén 2010).

  15. 15.

    For reasons of space, other multi-dimensional solutions, which were either deemed implausible or were discounted due to low model fit, are not discussed and elaborated on here.

  16. 16.

    According to Finney and DiStefano (2006), RMSEA and WRMR (weighted root mean square residual) appear to be the most promising fit indices with ordered categorical data and a low number of categories.

  17. 17.

    The scale of professional problem-solving comprised 25 items. Scale reliability (WLE) and the variance of the latent ability distribution were acceptable (.71 and 0.98 respectively). The average standard error of the WLE person parameter estimates was 0.59: i.e., item difficulties were relatively evenly distributed over the ability range.

  18. 18.

    Item difficulties were transformed to represent a 65 % chance of success in solving the task, instead of the 50 % that is configured in the Rasch standard setting.

  19. 19.

    Complex means here a combination of requirements from the three dimensions PK, TD, and BTM.

  20. 20.

    The number of items corresponding to the competency levels is as follows: N Level A = 9, N Level B = 9, N Level C = 7. Two items correspond to the segment below level A. No item and very few apprentices are located on level D, which is reported here to reflect the high curricular expectations.

  21. 21.

    The three scales (PK, TD, and BTM) consisted of 23, 19, and 19 items respectively. Scale reliabilities (based on WLE) were all satisfactory (≥.75). The variance of the latent ability distribution was the highest for BTM (1.71) and the lowest for TD (1.01); for PK the variance amounted to 1.25. The average standard error of the WLE person parameter estimates was similar for PK and TD (0.58 and 0.59 respectively). The higher average standard error for BTM (0.64) is a result of the higher variance and hints at a more unbalanced distribution of item difficulties and persons’ abilities.

  22. 22.

    Due to space constraints, it is not possible to present the findings on the apprentices’ motivational development in detail here. Another paper will discuss related issues.

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Acknowledgments

The preparation of this chapter was supported by grant Ni 606 7-1 from the German Research Foundation (DFG) in the Priority Program “Competence Models for Assessing Individual Learning Outcomes and Evaluating Educational Processes” (SPP 1293).

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  1. University of Stuttgart, Stuttgart, Germany

    Kerstin Norwig, Cordula Petsch & Reinhold Nickolaus

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  1. Kerstin Norwig
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  2. Cordula Petsch
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Correspondence to Kerstin Norwig .

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Editors and Affiliations

  1. Faculty of Educational Sciences, Department of Instructional Psychology, University of Duisburg-Essen, Essen, Germany

    Detlev Leutner

  2. Faculty of Educational Sciences, Department of Instructional Psychology, University of Duisburg-Essen, Essen, Germany

    Jens Fleischer

  3. German Institute for International Educational Research (DIPF), Frankfurt/Main, Germany

    Juliane Grünkorn

  4. German Institute for International Educational Research (DIPF), Frankfurt/Main, Germany

    Eckhard Klieme

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Norwig, K., Petsch, C., Nickolaus, R. (2017). Professional Competencies of Building Trade Apprentices After Their First Year of Training. In: Leutner, D., Fleischer, J., Grünkorn, J., Klieme, E. (eds) Competence Assessment in Education. Methodology of Educational Measurement and Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319-50030-0_13

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