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