스마트 학습을 위한 웹 콘텐츠들의 적응화 기법에 관한 연구

Abstract

The development of information and communication technology has brought the conversion of e-learning contents as consisting of a learner-centered, without the constraints of time and space away from the unilateral and passive classroom between teacher and learner. According to wide supply of various smart devices, it has been needed an open, personalized and customized education and training systems such as smart learning and mobile learning systems. In this thesis, we discuss about the status of the smart teaching and learning systems and analyze the characteristics and structure of the web contents for smart education and training systems by use of smart devices. And we propose a method how to block web contents, to extract them, and adapt personalized segments of web contents by adaptive algorithm. We extract blocks from the web contents based on the smart device information and the preference information of the learners from a desktop-based web contents without the hassle of learners environment. After specifying a block priority from the extracted web contents by the adaptive segment algorithm, it can be displayed directly to the screen to fit the individual learning progress of the learners.