Abstract:

The aim of the present research is to evaluate the self-sufficiency and self-efficacy of educational primary and secondary education using computational intelligence methods. The work was based on the Educational Effectiveness Scale, where the electronic version was created and was promoted through the website http://www.cicos.gr. This scale has been built to measure the effectiveness of teachers as perceived by themselves.

It consists of 24 issues pertaining to the evaluation of three factors of effectiveness:
(a) the effectiveness of teaching strategies;
(b) the effectiveness of department management; efficacy for classroom management; and
(c) the effectiveness of the involvement of students - efficacy for student engagement.

The sample of the present work, which was documented by Greek teachers working in public and private structures, in the primary and secondary levels of Education, in regions of the region and the capital. Subsequently, methodologies from the field of Mechanical Learning and Data Mining were used to analyze the data to produce "hidden" knowledge, which is depicted and presented in the form of rules, clusters and correlations. In addition, the parameters of these algorithms were determined, depending on the case of application, in order to produce rules for extracting conclusions.

The results of this research highlight the conjecture of the teacher's beliefs in organizing and coordinating his / her skills with the ultimate goal of functionality and collective effectiveness.

Keywords:

Educational Effectiveness Scale, Self-Efficiency, Machine Learning.