Recommendation of the video in a ubiquitous learning environment

Hiroaki Ogata, Toru Misumi, Yoshiki Matsuka, Bin Hou, Mengmeng Li, Moushir El-Bishouty, Noriko Uosaki, Yoneo Yano

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

Abstract

This paper proposes a personal learning assistant called LORAMS (Link of RFID and Movies System), which supports learners with a system to share and reuse learning experiences by linking movies to environmental objects. We assume that every object has RFID tags and mobile devices have a RFID reader and can record a video at anytime and anyplace. By scanning RFID tags of real objects, LORAMS can provide only video segments that include the objects. Also LORAMS recommends the similar videos to be compared. In LORAMS, the video recording and RFID tagging are used purposely to support further teaching or learning rather than "just record it and use it in some day". We think that LORAMS can be applied to various kinds of domains that employ several kinds of real objects and vary the results depending on the combination of the objects; for example, cooking, checking upon cars such as oils, battery, and tires, surgery operations and chemical bioreactor experimentations.

Original languageEnglish
Title of host publicationProceedings of the IADIS International Conference Mobile Learning 2010
Pages93-100
Number of pages8
Publication statusPublished - Dec 1 2010
EventIADIS International Conference Mobile Learning 2010 - Porto, Portugal
Duration: Mar 19 2010Mar 21 2010

Publication series

NameProceedings of the IADIS International Conference Mobile Learning 2010

Other

OtherIADIS International Conference Mobile Learning 2010
Country/TerritoryPortugal
CityPorto
Period3/19/103/21/10

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Software
  • Education

Fingerprint

Dive into the research topics of 'Recommendation of the video in a ubiquitous learning environment'. Together they form a unique fingerprint.

Cite this