Study on communication of characteristics smart learning from UX perspective

Abstract

Researches on smart learning have so far focused on e-learning contents, infrastructure, and the quality of teaching and learning method. This thesis based on the stance that, as smart learning is mainly practiced through smart devices people carry with them every day, its platform evaluation should go beyond just simple evaluation of content effectiveness but to more diversified aspects such as users' feeling, association, and difference. And such smart learning analysis and evaluation should be connected to subsequent emotional UX management and brand asset management that serve as strategic guidelines for mobile telecommunication op erators' platform business and e-learning content production. This study examined more customized functions of mobile telecommunication operators' smart learning platform services currently available in the market by considering the perspective of the emotional UX. By doing so, this thesis sought to make some strategic approaches to create values. We, for the purpose of this study, selected T-smart learning of SK Telecom, the first South Korean mobile telecommunication carrier to launch a smart learning platform. For case analysis, we employed Yin's theory, adopted the explanation research method to interview involved officials and users and recorded interview details and resulting reports by using the case study method. In addition, based on previous studies and in the perspective of emotional communication rather than technological perspective of Smart Learning, it drew four categories: (1) interdisciplinary, (2) customized management, (3) motivation, and (4) knowledge network. The characteristics of SK T-learning UX factor was interpreted on the basis of Oral-Formulaic Theory by Ong, Walter J (1995). As a result, it was revealed that oral-formulaic characteristics were found in the Smart Learning factor in the smart environment. Also, it was found that the oral-formulaic characteristics were in the same context with the smart characteristic of smart learning. © 2013 SERSC.