• DocumentCode
    169607
  • Title

    A Framework of Educational App Repositories with Recommendation Powered by Social Tag Mining

  • Author

    Wen-Chung Shih

  • Author_Institution
    Dept. of Appl. Inf. & Multimedia, Asia Univ., Taichung, Taiwan
  • fYear
    2014
  • fDate
    6-9 May 2014
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Existing remedial instruction focuses on teacher-oriented or self-learning approaches. However, we think that the tutor-based approach with the support of educational repositories can provide students with an opportunity to correct their misconceptions. In this paper, the architecture is proposed to help users find suitable educational apps in repositories for the purpose of Math tutoring. The proposed recommender subsystem is combined with a social tagging mining approach. Evaluation results indicate that despite the need for further improvement, the tutoring method with the educational repositories is promising for remedial instruction.
  • Keywords
    data mining; intelligent tutoring systems; recommender systems; EAR; educational app resources; educational application repositories; educational repositories; educational resource recommendation; math tutoring; recommender subsystem; remedial instruction; self-learning approach; social tag mining; tutor-based approach; Data mining; Educational institutions; Learning systems; Mathematics; Recommender systems; Tagging; Taxonomy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2014 International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4799-4443-9
  • Type

    conf

  • DOI
    10.1109/ICISA.2014.6847328
  • Filename
    6847328