Response neighborhoods in online learning networks: A quantitative analysis

Reuven Aviv, Zippy Erlich, Gilad Ravid

פרסום מחקרי: פרסום בכתב עתמאמרביקורת עמיתים


Theoretical foundation of Response mechanisms in networks of online learners are revealed by Statistical Analysis of p* Markov Models for the Networks. Our comparative analysis of two networks shows that the minimal-effort hunt-for-social-capital mechanism controls a major behavior of both networks: negative tendency to respond. Differences in designs of the networks enhance certain mechanisms while suppressing others: cognition balance, predicted by the theories of cognitive balance, and peer pressure, predicted by the theories of collective action are enhanced in a team like network but suppressed in a Q&A like forum. On the other hand, exchange mechanism, predicted by the theory of exchange & resource dependency and tutor's responsibility mechanism are enhanced in the Q&A type forum but suppressed in the team like network. Contagion mechanism, predicted by the theory of collective action did not develop in both networks. The different mechanisms lead to the formation of different micro and macro structures in the topologies of the responses of the networks and hence in the buildup of collaborative knowledge. The techniques presented in this work can be extended to other types of mechanisms and networks.

שפה מקוריתאנגלית
עמודים (מ-עד)90-99
מספר עמודים10
כתב עתEducational Technology and Society
מספר גיליון4
סטטוס פרסוםפורסם - 2005

טביעת אצבע

להלן מוצגים תחומי המחקר של הפרסום 'Response neighborhoods in online learning networks: A quantitative analysis'. יחד הם יוצרים טביעת אצבע ייחודית.

פורמט ציטוט ביבליוגרפי