Supporting real-world language learning based on ubiquitous learning analytics

Kousuke Mouri, Hiroaki Ogata, Noriko Uosaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a visualization and analysis system called VASCORLL (Visualization and Analysis system for COnnecting Relationships of Learning Logs) in order to link learners in the real world and learning logs that are accumulated in a cyber space by a ubiquitous learning system called SCROLL (System for Capturing and Reminding of Learning Log). Learning materials provided by ubiquitous learning systems are in most cases, prepared by teachers or instructional designers. It makes it difficult to find relationships between a learner and other learners in different contexts. Using VASCORLL, learners can find other contexts where can be applied to their own learning experiences. This paper describes the design, the implementation of VASCORLL.

Original languageEnglish
Title of host publicationDoctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015
EditorsWenli Chen, Gautam Biswas, Xiaoqing Gu, Hiroaki Ogata, Siu Cheung Kong, Feiyue Qiu, Ben Chang, Weiqin Chen
PublisherAsia-Pacific Society for Computers in Education
Pages5-8
Number of pages4
ISBN (Electronic)9784990801496
Publication statusPublished - 2015
Event23rd International Conference on Computers in Education, ICCE 2015 - Hangzhou, China
Duration: Nov 30 2015Dec 4 2015

Publication series

NameDoctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015

Other

Other23rd International Conference on Computers in Education, ICCE 2015
CountryChina
CityHangzhou
Period11/30/1512/4/15

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Education

Fingerprint Dive into the research topics of 'Supporting real-world language learning based on ubiquitous learning analytics'. Together they form a unique fingerprint.

Cite this