• DocumentCode
    2899519
  • Title

    An Evaluation Framework for Extreme Learning Process (XLP)

  • Author

    Wei-Tek Tsai ; Alimbekov, Kubatbek ; Koo, Benjamin Hsueh-Yung

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
  • fYear
    2015
  • fDate
    March 30 2015-April 3 2015
  • Firstpage
    357
  • Lastpage
    366
  • Abstract
    This paper presents an evaluation framework for Extreme Learning Process (XLP), a crowd-learning process that utilizes version control tools, blog entries, and virtual currencies to digitally track and motivate participant learning. This evaluation framework assesses motivation, knowledge, creativity, and collaboration of XLP participants based on process data generated during a typical XLP-based learning activity. This paper applied this framework to assess an XLP session done at Tsinghua University. The results showed that participants who are more involved in digital publishing are more reputable and productive among fellow participants.
  • Keywords
    data acquisition; electronic publishing; learning (artificial intelligence); social networking (online); Tsinghua University; XLP-based learning activity; blog entry; crowd-learning process; digital publishing; extreme learning process; version control tool; virtual currencies; Collaboration; Constitution; Context; Education; Electronic publishing; Knowledge engineering; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Service-Oriented System Engineering (SOSE), 2015 IEEE Symposium on
  • Conference_Location
    San Francisco Bay, CA
  • Type

    conf

  • DOI
    10.1109/SOSE.2015.49
  • Filename
    7133553