A novel approach to monitoring and creating significant learning experiences using social tag cloud navigation

Abstract

Prior knowledge learning for increasing the efficiency of the learning processes is an important issue. Traditional studies on prior knowledge generation during language learning have focused on providing additional supplemental materials from reading materials that are manually generated by educators. This is time-consuming and hence personalized prior knowledge recommendation is difficult to perform and monitor. To cope with these problems, we purpose a novel tag-cloud visualization learning approach to automatically monitor running activities and student status. In addition, we incorporate cloud tags into a prior knowledge learning system (TAK), which provides students an engaging way to reinforce meaningful topics, identifies suitable supplementary materials through tag cloud navigation, and helps students reevaluate their reading process. Our experimental results demonstrate that our approach not only significantly improves the efficiency of prior knowledge learning but also helps teachers assist students in improving their reading ability.