As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Interaction analysis plays an important role in computer-supported collaborative learning. This paper proposes an interaction analysis model CSCAC composed of three dimensions: group building level, member contribution, member support, which lays the foundation for interaction content analysis. Based on the model and domain ontology, this paper explores the text mining and semantic analysis technologies to automatically analyze the interaction content for collaborative knowledge building. An experiment is conducted to compare the auto-analysis result with that of manual analysis, which shows the the proposed approach is feasible and effective mostly to automatically analyze the interaction content in CSCL.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.