A Study on the Decision-Making of Effective S/W Education based on Opinion Mining Analysis

 
 
 
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  • Abstract


    The Currently, along with the advent of the web 2.0 era, due to the continuous expansion of social media service infrastructures, the shares of conventional public opinion evaluation functions have been gradually shifting from the existing mass media to social media. This phenomenon is attributable to the two-way communication and convenience unique to social media and social media are now in charge of an axis of public opinion evaluation standards. In particular, since diverse interests conflict in education policies and countless conflicts of opinions occur in the process of setting up policy agendas, in establishing education policies, accurately analyzing reputations among the public, who are the targets of education policies, in order to set up effective policy agendas, is the most important issue. Therefore, in this study, the resultant values of huge unstructured data on the positive and negative reputations of past policy agendas related to the mandatory software education that has been organized as a regular curriculum of middle/high schools from 2018 in Korea, which have been addressed by the Ministry of Education, the Ministry of Science, ICT and Future Planning, and the Korea Foundation for the Advancement of Science and Creativity, felt and judged by the general public on social media such as blogs and Twitter and on online media including  portal news were visualized through opinion mining analysis techniques to derive more effective software education related policy agendas. In addition, based on the foregoing, a Korean style software education system that fits circumstances was constructed and the system is expected to become an important measure that provides guidelines for setting mid/long-term road maps for the fostering of creative and convergent talented persons equipped with international competitiveness and software education in Korea.

     

     


  • Keywords


    S/W Education Policy, Opinion Mining, Social Media, Unstructured Data

  • References


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Article ID: 21769
 
DOI: 10.14419/ijet.v7i4.16.21769




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