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  4. Predictors of Collateral Learning Transfer in Continuing Vocational Training
 
Zitierlink URN
https://nbn-resolving.de/urn:nbn:de:gbv:46-00103981-16

Predictors of Collateral Learning Transfer in Continuing Vocational Training

Veröffentlichungsdatum
2014
Autoren
Hinrichs, Anja-Christina  
Zusammenfassung
Against the background of demographic change and skill shortages continuing vocational training is of great significance in Germany. However, the training effectiveness is mostly assessed only at the end of a training program or several months after the training. Since in continuing vocational training the two contexts learning field (training) and performance field (work context) act simultaneously, the presented study investigated whether there are already situations in the work context which allow the application of newly acquired knowledge in parallel with the training. The main focus lies in the identification of predictors of learning transfer that takes place alongside the training participation and in the investigation of their causal relationships. Using structural equation modelling five latent variables were identified which have a significant effect on learning transfer parallel to the training the so called collateral learning transfer. These five predictors explain together 62% of the variance of collateral learning transfer (gathered as performance improvement at work).
Schlagwörter
collateral learning transfer

; 

learning transfer

; 

job performance

; 

vocational training

; 

CVET

; 

structural equation modeling
Institution
Universität Bremen  
Fachbereich
Fachbereich 12: Erziehungs- und Bildungswissenschaften (FB 12)  
Institute
ITB - Institut Technik und Bildung  
Dokumenttyp
Artikel/Aufsatz
Zeitschrift/Sammelwerk
International Journal for Research in Vocational Education and Training (IJRVET)  
Heft
1
Startseite
35
Endseite
56
Zweitveröffentlichung
Nein
Sprache
Deutsch
Dateien
Lade...
Vorschaubild
Name

00103981-1.pdf

Size

543.68 KB

Format

Adobe PDF

Checksum

(MD5):c12d0dfd95fd0c6e02d37a1609372ee3

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