Measuring cooperative score on online activity
Sang-Gook Han, Dukshin Oh, SahmYook University, Korea (South)
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, NV, USA ISBN 978-1-939797-05-6 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
The advent of the Internet offers new ways of collaboration no matter how far colleagues or students are physically separated. Text-based digital communication is widely adopted because its cost is cheap and many people can join a group easily. In spite of those advanced technologies, it is hard to measure cooperativeness numerically. To overcome this problem, the cooperative score from online messages can be estimated from entropy in information theory and an amount of online activity with inhibiting biased activity. Moreover, cooperative score from tagged messages is able to reveal more hidden information in detail. Using the proposed method in this paper, we find that the cooperative scoring system detects best workers and best group no matter how biased activity disturbs group activity. Consequently, benevolent and malevolent invisible hands in online group activity would be revealed from the numerical analyzing method.
Han, S.G. & Oh, D. (2013). Measuring cooperative score on online activity. In T. Bastiaens & G. Marks (Eds.), Proceedings of E-Learn 2013--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 339-345). Las Vegas, NV, USA: Association for the Advancement of Computing in Education (AACE).
© 2013 Association for the Advancement of Computing in Education (AACE)