Decision Tree Attribute Selection Measures for Improving Technical Vocational Skills Competency Training and Assessment under ICT Sector

摘要

Embracing the non-formal education or the technical vocational education is one of the continuing approach in the Philippine Educational System. Technical Vocational seems to progress in terms of delivering competency based training, learning at your own pace, achieving specific learning objectives and both the institutional and national competency assessment. This study focused mainly in improving technical vocational skills competency which includes training and assessment under information and communication technology strand. In order to improve the said criteria, implementation of decision tree along with its attribute selection measures such as entropy, information gain, gain ratio and gini index have taken place. Level and impact of skills competency training and assessment through computations of the attribute selection measures have yielded to a more conclusive and detailed improvements in the field of information and communication technology. Likewise, this study gives an idea to the Technical Education and Skills Development Authority (TESDA) and majority of the training center and institutions on how to deliver the competency based training and at the same time to absorbed the enumerable criteria accustoming the main stream of skills. Decision Tree considered to be the most widely used algorithm have rendered the most satisfying outputs and have provided an accurate results based on the given parameters.