Glass, Rupert ; Metternich, Joachim (2020)
Method to Measure Competencies - A Concept for Development, Design and Validation.
In: Procedia Manufacturing, 45
doi: 10.1016/j.promfg.2020.04.056
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Production companies face the challenge to adapt their manufacturing processes and technologies to changing market demands and to stay ahead in global competition. To master this challenge successfully competencies at all hierarchical levels are a central success factor. Learning factories have proven to be a successful approach to develop these competencies. Trainings in learning factories are particularly beneficial, when their learning success can be assessed. In order to verify the learning success and to revise trainings afterwards precisely, a method to determine the acquisition of competencies is necessary. This paper addresses the question of how production-relevant competencies can be determined if they can't be assessed directly. An approach on how a measurement can be performed is presented, as well as the direction of further refinement of the method. Among other things, a structural equation analysis will be used to empirically test hypotheses on competency acquisition. Using a variety of different data sources (e.g. written test, observation or self-assessment) diverse parameters will be tested for the determination of competencies with the aim to develop a statistically sound measurement procedure. This will make it possible to compare different approaches with a large dataset created in the learning factory "Center of industrial Productivity'' (CiP) at the Technical University Darmstadt.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2020 |
| Autor(en): | Glass, Rupert ; Metternich, Joachim |
| Art des Eintrags: | Bibliographie |
| Titel: | Method to Measure Competencies - A Concept for Development, Design and Validation |
| Sprache: | Englisch |
| Publikationsjahr: | 2020 |
| Verlag: | Elsevier B.V. |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Procedia Manufacturing |
| Jahrgang/Volume einer Zeitschrift: | 45 |
| DOI: | 10.1016/j.promfg.2020.04.056 |
| Kurzbeschreibung (Abstract): | Production companies face the challenge to adapt their manufacturing processes and technologies to changing market demands and to stay ahead in global competition. To master this challenge successfully competencies at all hierarchical levels are a central success factor. Learning factories have proven to be a successful approach to develop these competencies. Trainings in learning factories are particularly beneficial, when their learning success can be assessed. In order to verify the learning success and to revise trainings afterwards precisely, a method to determine the acquisition of competencies is necessary. This paper addresses the question of how production-relevant competencies can be determined if they can't be assessed directly. An approach on how a measurement can be performed is presented, as well as the direction of further refinement of the method. Among other things, a structural equation analysis will be used to empirically test hypotheses on competency acquisition. Using a variety of different data sources (e.g. written test, observation or self-assessment) diverse parameters will be tested for the determination of competencies with the aim to develop a statistically sound measurement procedure. This will make it possible to compare different approaches with a large dataset created in the learning factory "Center of industrial Productivity'' (CiP) at the Technical University Darmstadt. |
| Freie Schlagworte: | Learning factories, trainings, measurement of competencies, method development |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > CiP Center für industrielle Produktivität |
| Hinterlegungsdatum: | 04 Mai 2020 05:39 |
| Letzte Änderung: | 04 Mai 2020 05:39 |
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