Analyzing Collaborative Interactions with Data Mining Methods for the Benefit of LearningPeter Reimann, Kalina Yacef, Judy Kay
Zu finden in: Analyzing Interactions in CSCL (Seite 161 bis 185), 2010
|
|
Diese Seite wurde seit 4 Jahren inhaltlich nicht mehr aktualisiert.
Unter Umständen ist sie nicht mehr aktuell.
Zusammenfassungen
In this paper, we attempt to relate types of change processes that are prevalent in groups to types of models that might be employed to represent these processes. Following McGrath´s analysis of the nature of change processes in groups and teams, we distinguish between development, adaptation, group activity, and learning. We argue that for the case where groups act as activity systems (i.e., attempt to achieve common goals in a co-ordinated manner involving planning and division of labour), the notion of a group process needs to take into account multiple types of causality and requires a holistic formal representation. Minimally, a process needs to be conceived on the level of patterns of sequences, but in many cases discrete event model formalisms might be more appropriate. We then survey various methods for process analysis with the goal to find formalization types that are suitable to model change processes that occur in activity systems. Two types of event-based process analysis are discussed in more depth: the first one works with the view of a process as a sequence pattern, and the second one sees a process as an even more holistic and designed structure: a discrete event model. For both cases, we provide examples for event-based computational methods that proved useful in analyzing typical CSCL log files, such as those resulting from asynchronous interactions (we focus on wikis), the those resulting from synchronous interactions (we focus on chats).
Von Peter Reimann, Kalina Yacef, Judy Kay im Buch Analyzing Interactions in CSCL (2010) im Text Analyzing Collaborative Interactions with Data Mining Methods for the Benefit of Learning Dieses Kapitel erwähnt ...
Anderswo finden
Volltext dieses Dokuments
Analyzing Collaborative Interactions with Data Mining Methods for the Benefit of Learning: Artikel als Volltext bei Springerlink (: , 1837 kByte; : 2020-11-28) |
Anderswo suchen
Beat und dieses Kapitel
Beat hat Dieses Kapitel während seiner Zeit am Institut für Medien und Schule (IMS) ins Biblionetz aufgenommen. Beat besitzt kein physisches, aber ein digitales Exemplar. Eine digitale Version ist auf dem Internet verfügbar (s.o.). Aufgrund der wenigen Einträge im Biblionetz scheint er es nicht wirklich gelesen zu haben. Es gibt bisher auch nur wenige Objekte im Biblionetz, die dieses Werk zitieren.