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The interplay between experiential and traditional learning for competency development.

Bonesso S, Gerli F, Pizzi C - Front Psychol (2015)

Bottom Line: Extensive research demonstrated that firms may pursue several advantages in hiring individuals with the set of emotional, social, and cognitive (ESC) competencies that are most critical for business success.Contrary to prior studies, our results provide counterintuitive evidence, suggesting that TL needs to be implemented together, on the one hand, with IEL to achieve a significant effect on emotional competencies and, on the other hand, with SEL to have an impact on social competencies.Moreover, IEL plays a prominent role in stimulating cognitive competencies.

View Article: PubMed Central - PubMed

Affiliation: Department of Management, Ca' Foscari University of Venice Venice, Italy.

ABSTRACT
Extensive research demonstrated that firms may pursue several advantages in hiring individuals with the set of emotional, social, and cognitive (ESC) competencies that are most critical for business success. Therefore, the role of education for competency development is becoming paramount. Prior studies have questioned the traditional methods, grounded in the lecture format, as a way to effectively develop ESC competencies. Alternatively, they propose experiential learning techniques that involve participants in dedicated courses or activities. Despite the insights provided by these studies, they do not take into account a comprehensive set of learning methods and their combined effect on the individual's competency portfolio within educational programs that aim to transfer primarily professional skills. Our study aims to fill these gaps by investigating the impact of the interplay between different learning methods on ESC competencies through a sample of students enrolled in the first year of a master's degree program. After providing a classification of three learning methods [traditional learning (TL), individual experiential learning (IEL), and social experiential learning (SEL)], the study delves into their combined influence on ESC competencies, adopting the Artificial Neural Network. Contrary to prior studies, our results provide counterintuitive evidence, suggesting that TL needs to be implemented together, on the one hand, with IEL to achieve a significant effect on emotional competencies and, on the other hand, with SEL to have an impact on social competencies. Moreover, IEL plays a prominent role in stimulating cognitive competencies. Our research contributes to educational literature by providing new insights on the effective combination of learning methods that can be adopted into programs that transfer technical knowledge and skills to promote behavioral competencies.

No MeSH data available.


Artificial neural network feed forward ANN(5, 2, 1).
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Figure 1: Artificial neural network feed forward ANN(5, 2, 1).

Mentions: To test our research hypotheses, we used the Artificial Neural Networks (Bishop, 1995; Ripley, 1996; Haykin, 1999). More precisely, since the independent variables are the three learning methods (TS, IEL, SEL), we defined three different Artificial Neural Networks (ANNs). This choice is motivated by the consideration that the ANNs are a more flexible model compared with the regression one. The ANNs, in fact, are able to capture both linear and non-linear relationships between variables without a priori definition of the type of relationship. This feature enables us also to delve into the interaction among variables, consistent with our study whose aim is to investigate the impact of the interplay between traditional and experiential learning methods on ESC competencies development. In doing so, we trained different feed-forward neural networks using 80 sample points, whereas the remaining 15 form the validation set. Concerning the structure of the ANN and due to the number of observations, we considered a neural network with one hidden layer with two nodes. To avoid the drawback of a possible arrest of the estimation algorithm at a local minimum, we repeated the estimation 100 times. Among all the estimated ANNs, we chose the one that minimized the Network Information Criterion. The difference among these ANNs is essentially on the number of nodes in the hidden layer: we considered two, three, and four hidden nodes and the choice of the best ANN was based on a penalty function computed on the validation set. Figure 1 depicts the ANN that was selected.


The interplay between experiential and traditional learning for competency development.

Bonesso S, Gerli F, Pizzi C - Front Psychol (2015)

Artificial neural network feed forward ANN(5, 2, 1).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4557282&req=5

Figure 1: Artificial neural network feed forward ANN(5, 2, 1).
Mentions: To test our research hypotheses, we used the Artificial Neural Networks (Bishop, 1995; Ripley, 1996; Haykin, 1999). More precisely, since the independent variables are the three learning methods (TS, IEL, SEL), we defined three different Artificial Neural Networks (ANNs). This choice is motivated by the consideration that the ANNs are a more flexible model compared with the regression one. The ANNs, in fact, are able to capture both linear and non-linear relationships between variables without a priori definition of the type of relationship. This feature enables us also to delve into the interaction among variables, consistent with our study whose aim is to investigate the impact of the interplay between traditional and experiential learning methods on ESC competencies development. In doing so, we trained different feed-forward neural networks using 80 sample points, whereas the remaining 15 form the validation set. Concerning the structure of the ANN and due to the number of observations, we considered a neural network with one hidden layer with two nodes. To avoid the drawback of a possible arrest of the estimation algorithm at a local minimum, we repeated the estimation 100 times. Among all the estimated ANNs, we chose the one that minimized the Network Information Criterion. The difference among these ANNs is essentially on the number of nodes in the hidden layer: we considered two, three, and four hidden nodes and the choice of the best ANN was based on a penalty function computed on the validation set. Figure 1 depicts the ANN that was selected.

Bottom Line: Extensive research demonstrated that firms may pursue several advantages in hiring individuals with the set of emotional, social, and cognitive (ESC) competencies that are most critical for business success.Contrary to prior studies, our results provide counterintuitive evidence, suggesting that TL needs to be implemented together, on the one hand, with IEL to achieve a significant effect on emotional competencies and, on the other hand, with SEL to have an impact on social competencies.Moreover, IEL plays a prominent role in stimulating cognitive competencies.

View Article: PubMed Central - PubMed

Affiliation: Department of Management, Ca' Foscari University of Venice Venice, Italy.

ABSTRACT
Extensive research demonstrated that firms may pursue several advantages in hiring individuals with the set of emotional, social, and cognitive (ESC) competencies that are most critical for business success. Therefore, the role of education for competency development is becoming paramount. Prior studies have questioned the traditional methods, grounded in the lecture format, as a way to effectively develop ESC competencies. Alternatively, they propose experiential learning techniques that involve participants in dedicated courses or activities. Despite the insights provided by these studies, they do not take into account a comprehensive set of learning methods and their combined effect on the individual's competency portfolio within educational programs that aim to transfer primarily professional skills. Our study aims to fill these gaps by investigating the impact of the interplay between different learning methods on ESC competencies through a sample of students enrolled in the first year of a master's degree program. After providing a classification of three learning methods [traditional learning (TL), individual experiential learning (IEL), and social experiential learning (SEL)], the study delves into their combined influence on ESC competencies, adopting the Artificial Neural Network. Contrary to prior studies, our results provide counterintuitive evidence, suggesting that TL needs to be implemented together, on the one hand, with IEL to achieve a significant effect on emotional competencies and, on the other hand, with SEL to have an impact on social competencies. Moreover, IEL plays a prominent role in stimulating cognitive competencies. Our research contributes to educational literature by providing new insights on the effective combination of learning methods that can be adopted into programs that transfer technical knowledge and skills to promote behavioral competencies.

No MeSH data available.