Recommendation method in the context of real-world language learning

Kousuke Mouri, Hiroaki Ogata, Noriko Uosaki

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

1 Citation (Scopus)

Abstract

This paper explores a recommendation method in the context of real-world language learning based on ubiquitous learning logs. Ubiquitous learning log stands for a digital record of what they have learned in the daily life using ubiquitous technologies. One of the issues of ubiquitous learning analytics is how we should detect or mine effective and efficient learning patterns from many learning data accumulated in a ubiquitous learning system. To tackle this issues, 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). Using VASCORLL, learners can predict their next learning steps and then find learning patterns related to their current learning situation. The initial evaluation was conducted to measure whether VASCORLL can increase learners' learning opportunities and whether the recommended learning patterns are appropriate for learners or not. In this evaluation, we found important criteria for recommending appropriate learning patterns for learners in the real-world language learning. In addition, VASCORLL succeeded in increasing learners' learning opportunities.

Original languageEnglish
Title of host publicationDoctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015
PublisherAsia-Pacific Society for Computers in Education
Pages704-712
Number of pages9
ISBN (Electronic)9784990801496
Publication statusPublished - 2015
Event23rd International Conference on Computers in Education, ICCE 2015 - Hangzhou, China
Duration: Nov 30 2015Dec 4 2015

Other

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

Fingerprint

Visualization
language
learning
Learning systems
systems analysis
visualization
learning situation
evaluation

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Education

Cite this

Mouri, K., Ogata, H., & Uosaki, N. (2015). Recommendation method in the context of real-world language learning. In Doctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015 (pp. 704-712). Asia-Pacific Society for Computers in Education.

Recommendation method in the context of real-world language learning. / Mouri, Kousuke; Ogata, Hiroaki; Uosaki, Noriko.

Doctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015. Asia-Pacific Society for Computers in Education, 2015. p. 704-712.

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

Mouri, K, Ogata, H & Uosaki, N 2015, Recommendation method in the context of real-world language learning. in Doctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015. Asia-Pacific Society for Computers in Education, pp. 704-712, 23rd International Conference on Computers in Education, ICCE 2015, Hangzhou, China, 11/30/15.
Mouri K, Ogata H, Uosaki N. Recommendation method in the context of real-world language learning. In Doctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015. Asia-Pacific Society for Computers in Education. 2015. p. 704-712
Mouri, Kousuke ; Ogata, Hiroaki ; Uosaki, Noriko. / Recommendation method in the context of real-world language learning. Doctoral Student Consortium (DSC) - Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015. Asia-Pacific Society for Computers in Education, 2015. pp. 704-712
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