An Experience-Connected e-Learning System with a Personalization Mechanism for Learners’ Situations and Preferences

This paper presents an “experience-connected” e- Learning system that facilitates users to learn practical skills of foreign language by associating knowledge and daily-life experiences. “Experience-Connected” means that the users of this system receive personalized and situation-dependent learning materials automatically. Knowledge associated to users’ daily-life has the following advantages: 1) provides opportunities to learn frequently, and 2) provides clear and practical context information about foreign language usage. The unique feature of this system is a dynamic relevance computation mechanism that retrieves learning materials according to both preference relevance and spatiotemporal relevance. Users of this system obtain appropriate learning materials, without manual and time-consuming search processes. This paper proves the feasibility of the system by showing the actual system implementation that automatically broadcasts the media-data of foreign language learning materials to smart-phones

A Geo-Location Context-Aware Mobile Learning System with Adaptive Correlation Computing Methods

AbstractThis paper proposes a context-aware mobile learning system with adaptive correlation computing methods. This system enables users to enhance their knowledge by correlating it with daily experiences. The proposed system contains a hybrid metric vector space to define the correlation between heterogeneous metadata vectors of the user context and learning material. The system integrates heterogeneous metric vector spaces with definitions of the semantic relations between the vector spaces. The significant feature of this system is a hybrid adaptation mechanism for the calculation of correlation. The adaptation mechanism has multidirectional adaptation functions for various learning materials, situations, and learners. We propose a revise-localize-personalize (RLP) adaptation model. In the adaptation mechanism, users only have to improve the metadata or the relations just in their relevant field. The advantage of the system is that the system reduces the time-intensive efforts required for describing direct relations between user contexts and learning materials. This paper presents the feasibility of the context-aware heterogeneous information provision with the hybrid metric vector space, by implementing an actual mobile application system and examining real-world experiments on data provision