Toward a multidimensional conceptualization of motivation to transfer training: Validation of the transfer motivation questionnaire from a self-determination theory perspective using bifactor-ESEM

Gegenfurtner, Andreas; Quesada-Pallarès, Carla

doi:10.1016/j.stueduc.2021.101116

Cited by 15 publications

(22 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In line with Ajzen's (2020) model, transfer intentions were measured with a single scale, conceptualizing intention to vary in size, not in quality. As a remedy, further research can adopt a multicriterial and multicontextual approach to assess transfer intentions and transfer of training (Testers et al, 2015;Gegenfurtner and Quesada-Pallarès, 2022). Moreover, the findings reported in this study are limited to the population of non-traditional students and should not be generalized blindly to other trainee populations with different levels of workplace affordances (Brand-Gruwel et al, 2014;Hodge et al, 2017), autonomy (Siewiorek and Gegenfurtner, 2010;Cheng, 2016), or supervisor support (Quesada-Pallarès, 2012;Froehlich and Gegenfurtner, 2019;Testers et al, 2019).…”

Section: Discussionmentioning

confidence: 93%

Transfer of training among non-traditional students in higher education: Testing the theory of planned behavior

Gegenfurtner

Testers

2022

Front. Educ.

Self Cite

View full text Add to dashboard Cite

This study tested the predictive validity of Ajzen’s theory of planned behavior with a sample of 182 non-traditional students in higher education to develop our understanding of non-traditional students’ intentions to transfer trained knowledge and skills from university courses to the workplace. After completing their courses, a survey measured behavioral, normative, and control beliefs, transfer attitudes, perceived social norms, transfer self-efficacy, and transfer intentions. One year later, a follow-up survey measured transfer of training. Partial least squares-based structural equation modeling (PLS-SEM) revealed that behavioral beliefs were positively associated with transfer attitudes, normative beliefs were positively associated with social norms, and control beliefs were positively associated with self-efficacy. Transfer attitudes and transfer self-efficacy predicted transfer intentions. Social norms, however, were non-significantly associated with intentions. Transfer intentions and transfer self-efficacy predicted transfer 1 year after training. These findings are discussed in terms of their predictive validity of Ajzen’s theory and their educational implications for non-traditional students enrolled in higher education programs.

show abstract

Section: Discussionmentioning

confidence: 93%

Transfer of training among non-traditional students in higher education: Testing the theory of planned behavior

Gegenfurtner

Testers

2022

Front. Educ.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Organizations that want to ensure transfer success need to understand how to boost the presence of these essential drivers of transfer. Although motivation to transfer received ample research interest (e.g., Bates et al, 2007, 2012; Gegenfurtner & Quesada‐Pallarès, 2022; Gegenfurtner et al, 2009; Massenberg et al, 2017), the investigation of how opportunity to transfer can be fostered in the organizational environment was relatively neglected and only a few studies considered it (e.g., Ford et al, 1992; Nijman, 2004; Quiñones et al, 1995). Consequently, the current study aims to investigate whether and how these essential factors in the transfer process can be influenced by individual and environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

The positive gain spiral of job resources, work engagement, opportunity and motivation on training transfer

Salamon

Blume

Tóth‐Király

et al. 2022

Int J Training Development

View full text Add to dashboard Cite

According to previous studies, general environmental characteristics and job‐related factors influence employees' transfer of learned skills to the job. However, among job‐related variables, the role of work engagement in connection with transfer motivation, opportunity and training transfer has not received much research attention. Building upon the theoretical background of the Job Demands‐Resources Model, the present study investigated the relationship between job resources/demands and training transfer through work engagement, transfer motivation and opportunity to transfer. Based on data from 311 working adults who participated in soft skill training programmes, job resources were associated with higher levels of training transfer through increased work engagement, motivation and opportunity to transfer. In contrast, job demands had negative relationships with transfer via work engagement and opportunity to transfer. The findings supported the assumption of the positive gain spiral in the transfer context. We conclude that companies should prioritize the development of job resources to provide a better environment for training transfer.

show abstract

“…The second domain of motivation and emotion includes the constructs academic motivation (Litalien et al, 2017 ; Guay and Bureau, 2018 ; Gordeeva et al, 2020 ; Howard et al, 2020 ; Kartal, 2020 ; Guay et al, 2021 ; Dierendonck et al, 2022 ), sport motivation (Appleton et al, 2016 ; Milton et al, 2018 ; Stenling et al, 2018 ; Cece et al, 2019 ; Méndez-Giménez et al, 2020 ; Rodrigues et al, 2020 ), work motivation (Burk and Wiese, 2018 ; Calkins, 2018 ; Howard et al, 2018 , 2020 , 2021 ; Gegenfurtner and Quesada-Pallarès, 2022 ), job satisfaction (Sutherland, 2020 ), affective commitment (Perreira et al, 2018 ), work engagement (Gillet et al, 2019 ; Huyghebaert-Zouaghi et al, 2021a , 2022 ), teacher engagement (Perera et al, 2018b ), student engagement (Hoi and Hang, 2021 ; Dierendonck et al, 2022 ; Tomás et al, 2022 ), basic psychological needs (Stenling et al, 2015 ; Sánchez-Oliva et al, 2017 ; Tóth-Király et al, 2018 , 2019 ; Bhavsar et al, 2019 , 2020 ; Garn et al, 2019 ; Burgueño et al, 2020a , b ; Cromhout, 2020 ; Gillet et al, 2020 ; Gucciardi et al, 2020 ; Huyghebaert-Zouaghi et al, 2021b ; Rodrigues et al, 2021 ), subjective task value (Fadda et al, 2020b ; Part et al, 2020 ), flow (Kyriazos et al, 2018b ; Gu et al, 2020 ), interest (Garn, 2017 ), locus of causality (Howard et al, 2020 ), attitudes (Deemer et al, 2014 ), purpose (Summers and Falco, 2020 ), self-efficacy (Barbaranelli et al, 2018 ; Dominguez-Lara et al,…”

Section: Resultsmentioning

confidence: 99%

Bifactor exploratory structural equation modeling: A meta-analytic review of model fit

Gegenfurtner

2022

Front. Psychol.

Self Cite

View full text Add to dashboard Cite

Multivariate behavioral research often focuses on latent constructs—such as motivation, self-concept, or wellbeing—that cannot be directly observed. Typically, these latent constructs are measured with items in standardized instruments. To test the factorial structure and multidimensionality of latent constructs in educational and psychological research, Morin et al. (2016a) proposed bifactor exploratory structural equation modeling (B-ESEM). This meta-analytic review (158 studies, k = 308, N = 778,624) aimed to estimate the extent to which B-ESEM model fit differs from other model representations, including confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), hierarchical CFA, hierarchical ESEM, and bifactor-CFA. The study domains included learning and instruction, motivation and emotion, self and identity, depression and wellbeing, and interpersonal relations. The meta-analyzed fit indices were the χ2/df ratio, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean squared residual (SRMR). The findings of this meta-analytic review indicate that the B-ESEM model fit is superior to the fit of reference models. Furthermore, the results suggest that model fit is sensitive to sample size, item number, and the number of specific and general factors in a model.

show abstract

Toward a multidimensional conceptualization of motivation to transfer training: Validation of the transfer motivation questionnaire from a self-determination theory perspective using bifactor-ESEM

Cited by 15 publications

References 65 publications

Transfer of training among non-traditional students in higher education: Testing the theory of planned behavior

Transfer of training among non-traditional students in higher education: Testing the theory of planned behavior

The positive gain spiral of job resources, work engagement, opportunity and motivation on training transfer

Bifactor exploratory structural equation modeling: A meta-analytic review of model fit

Contact Info

Product

Resources

About