Employee Qualification by Digital Learning Games

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Görke, M.; Bellmann, V.; Busch, J.; Nyhuis, P.: Employee Qualification by Digital Learning Games. In: Procedia Manufacturing 9 (2017), S. 229-237. DOI: https://doi.org/10.1016/j.promfg.2017.04.040

Version im Repositorium

Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/1709

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Summe der Downloads: 296




Kleine Vorschau
Zusammenfassung: 
Global competition and individual customer requirements generate challenges for manufacturing companies. To cope with these challenges, companies require an increased level of flexibility. In the first place, this flexibility has to be provided by the employees, as they are one of the key success factors for mastering change. An essential prerequisite for this is a high level of employee qualification across all areas of the company. The learning factories approach has garnered particular attention in recent years as a playful and efficient way of learning the principles and methods of processes improvement. The drawbacks of this method include the limited, non-holistic perspective of each trainee as well as the non-recurring knowledge transfer. Moreover, this kind of qualification requires the trainees to be in the same place at the same time. These downsides can be successfully countered by supplementing learning factories with a digital learning component depicting the learning environment, as digital learning will enable individual learning routes for all trainees and is accessible at all times and all places. This paper serves to outline the idea of serious learning by using digital learning games along with the attendant benefits. Over and beyond this, it also presents a digital learning game for teaching specific lean production methods. © 2017 The Authors
Lizenzbestimmungen: CC BY-NC-ND 4.0 Unported
Publikationstyp: Article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2017
Die Publikation erscheint in Sammlung(en):Fakultät für Maschinenbau

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Pos. Land Downloads
Anzahl Proz.
1 image of flag of Germany Germany 174 58,78%
2 image of flag of United States United States 53 17,91%
3 image of flag of No geo information available No geo information available 8 2,70%
4 image of flag of China China 7 2,36%
5 image of flag of Russian Federation Russian Federation 6 2,03%
6 image of flag of United Kingdom United Kingdom 5 1,69%
7 image of flag of Peru Peru 4 1,35%
8 image of flag of Italy Italy 4 1,35%
9 image of flag of France France 4 1,35%
10 image of flag of Bulgaria Bulgaria 3 1,01%
    andere 28 9,46%

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