The well-fit for the FET model
Learning transfer evaluation is a necessary process for practitioners to assess the effectiveness of training, and the outcomes of training produces in workers' behaviors. In this paper, we explore an alternative way to evaluate transfer: through the study of transfer facilitators and barriers....
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:249674 |
| Acceso en línea: | https://ddd.uab.cat/record/249674 https://dx.doi.org/urn:doi:10.5565/rev/educar.1327 |
| Access Level: | acceso abierto |
| Palabra clave: | Transfer factors Learning transfer Transfer evaluation Confirmatory factor analysis Professional learning Training Education Factors de transferència Transferència de l'aprenentatge Avaluació de la transferència Anàlisi factorial confirmatòria Factores de transferencia Transferencia del aprendizaje Evaluación de la transferencia Análisis factorial confirmatorio |
| Sumario: | Learning transfer evaluation is a necessary process for practitioners to assess the effectiveness of training, and the outcomes of training produces in workers' behaviors. In this paper, we explore an alternative way to evaluate transfer: through the study of transfer facilitators and barriers. Our aim is to validate the Factors to Evaluate Transfer (FET) model in a large sample of Spanish employees using confirmatory factor analysis. We applied the Spanish version of the FET scale to a sample of 2,745 Spanish workers of public service institutions and private companies. The results show a seven-factor model as the best choice according to the adjustment indices presented in the paper. We obtained a shorter version of the instrument, with adequate construct validity as well as good reliability and internal consistency. This model is a step forward in the measurement of indirect transfer and allows keeping working on the FET model to diagnosis transfer factors and increase the probabilities of higher learning transfer levels. |
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