IDENTIFICATIONS OF ABSENT FACTORS TO GENERATE SECOND-ORDER CHANGES IN UNDERGRADUATE STUDENTS ABOUT THE FUTURE LABOR MARKET

Year 2019, Volume: 2 Issue: 3, 256 - 278, 29.12.2019

Rubén Chávez , Federico González Beatriz Flores

Abstract

The objective focuses on the identification and development of behavior patterns in the activities of the individual in the organization on the disposition to acquire new competences that allow to generate the change, as well as the formal management of the acquired knowledge are necessary elements to generate the change of second order. In this work we propose a mechanism with cognitive and emotional elements that activate the declarative knowledge (explicit) that is developed from behavioral knowledge (tacit) through the OSAR model, the perceptron type training algorithm is implemented to classify the synaptic weights on the threshold of activation on the cognitive and emotional elements in causal relation with the elements of knowledge management, competence and availability to change. Thus, the neural network allows the generation of the synaptic weights matrix to predict the processes of structural change evaluation and the second order changes (SOC) in order to generate learning in the organization.

Keywords

knowledge change, second order change, cognitive, emotional, neural networks

Supporting Institution

UMSNH

Project Number

UMSNH-CA-180 “Políticas Públicas y Negocios Internacionales”

IDENTIFICATIONS OF ABSENT FACTORS TO GENERATE SECOND-ORDER CHANGES IN UNDERGRADUATE STUDENTS ABOUT THE FUTURE LABOR MARKET

Abstract

The
objective focuses on the identification and development of behavior patterns in
the activities of the individual in the organization on the disposition to
acquire new competences that allow to generate the change, as well as the
formal management of the acquired knowledge are necessary elements to generate
the change of second order. In this work we propose a mechanism with cognitive
and emotional elements that activate the declarative knowledge (explicit) that
is developed from behavioral knowledge (tacit) through the OSAR model, the
perceptron type training algorithm is implemented to classify the synaptic weights
on the threshold of activation on the cognitive and emotional elements in
causal relation with the elements of knowledge management, competence and availability
to change. Thus, the neural network allows the generation of the synaptic
weights matrix to predict the processes of structural change evaluation and the
second order changes (SOC) in order to generate learning in the organization.

Keywords

knowledge management, second order change, cognitive, emotional, neural networks

Project Number

UMSNH-CA-180 “Políticas Públicas y Negocios Internacionales”

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