DSBuilder-CJS: An Adaptive LMS Fuzzy Inference Powered, Based on Cognitive and Job Skills for Improving Job Effectiveness in a Mexican Local Government

Publication Information

Authors:

  • Raul Quintanar Casillas,
  • Ma Sandra Hernandez Lopez,

Pages:

  • 31-64

Keywords:

  • Artificial Intelligence, Digital Education and Educational Technology, Adaptive learning, Cognitive skills, Job skills

Abstract:

  • This research aims to present an adaptive Learning System for the public servants of the Huixquilucan City Hall which allows the simultaneous development of their cognitive abilities and labor competencies. Among the problems that motivated the development of this research are that the lack of adequate training has stemmed both the development of human resources and the establishment of employees' career plans, resulting in subpar service delivery to citizens and poor staff performance. On the other hand, few works on adaptive learning study the work approach and propose the development of cognitive and work skills. The theoretical framework that supports this work includes the state of the art of adaptive learning from the cognitive approach, fuzzy logic applied to adaptive learning, and cognitive and work skills. The research is of an experimental nature; a quantitative approach is proposed since fuzzy logic is used to measure the different indicators that affect labor effectiveness. The information is collected through tests of cognitive abilities divided into sections for each type of study object applied to 80 individuals. The main result is that the proposed LMS allows, in a greater proportion than other jobs, the development of cognitive and labor skills, and therefore, an improvement in job effectiveness.