Collective contribution of content can be problematic in case assumptions are made regarding the data provided by the users.
The second case study described in this article uses social bookmarking services for easy authoring of learning objects.
There, bookmarks are stored on a Web 2.0 service2 annotated with tags that provide additional information
about the bookmarked resources. In the case study, the tags were predefined and carried specific semantics that
were exploited by a learning management system to suggest new learning resources. However, such a fixed semantic can be enforced only in closed communities.
Otherwise, problems might arise if by chance other users employ the same tags but with a different semantic. While most Web 2.0 services offer a possibility to define closed communities, this of course undermines the benefits of an open community.
Some research was performed on harnessing the collective intelligence for e-learning applications. For instance,investigate the usage of tags for ontology generation and authoring support.