Analysis of ubiquitous-learning logs using spatio-temporal data mining

Kousuke Mouri, Hiroaki Ogata, Noriko Uosaki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

5 被引用数 (Scopus)

抄録

This paper proposes an approach of the spatio-temporal data mining in order to predict next learning steps (next ubiquitous learning logs to be learned) in accordance with their situations or context from past learners' experiences in their daily lives accumulated in the ubiquitous learning system called SCROLL (System for Capturing and Reminding of Learning Log). Ubiquitous learning log (ULL) is defined as a digital record of what learners have learned in their daily life using ubiquitous technologies. It allows learners to log their learning experiences with photos, audios, videos, location, RFID tag and sensor data, and to share and reuse ULL with others. This paper describes some data mining methods using the association analysis in order to detect effective and efficient learning logs for learner from relationships among ubiquitous learning logs collected by a number of the research studies for a long period of the SCROLL project (2011~2014).

本文言語英語
ホスト出版物のタイトルProceedings - IEEE 15th International Conference on Advanced Learning Technologies
ホスト出版物のサブタイトルAdvanced Technologies for Supporting Open Access to Formal and Informal Learning, ICALT 2015
編集者Nian-Shing Chen, Tzu-Chien Liu, Kinshuk, Ronghuai Huang, Gwo-Jen Hwang, Demetrios G. Sampson, Chin-Chung Tsai
出版社Institute of Electrical and Electronics Engineers Inc.
ページ96-98
ページ数3
ISBN(電子版)9781467373333
DOI
出版ステータス出版済み - 9 14 2015
イベント15th IEEE International Conference on Advanced Learning Technologies, ICALT 2015 - Hualien, 台湾省、中華民国
継続期間: 7 6 20157 9 2015

出版物シリーズ

名前Proceedings - IEEE 15th International Conference on Advanced Learning Technologies: Advanced Technologies for Supporting Open Access to Formal and Informal Learning, ICALT 2015

その他

その他15th IEEE International Conference on Advanced Learning Technologies, ICALT 2015
Country台湾省、中華民国
CityHualien
Period7/6/157/9/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Experimental and Cognitive Psychology
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Education

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