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
Link To Document :
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