Big Data Based Decision-making Support System Design for Efficient Analysis of the Performance of Software Education

Abstract

This paper is aimed to analyze the performance of domestic software education that has been implemented thus far centering on the opinion mining visualization analysis technique based on big data related to domestic software education collected over the last five years such as data from portal site news, SNS service, Internet  café, and other performance data and develop a big data based decision-making support system for Korean style software education in order to derive agendas that will be discussed hereafter. In addition, through the prediction of more advanced future-oriented education systems and analysis of performance factors based on the foregoing, solutions for big data based decision-making support prediction analysis can be prepared hereafter in the field of education and measures for cultivation of creative convergence talents and promotion of software education can be sought so that the directions of mid/long-term development of Korean style software education can be accurately set.