we describe how we used micro-blogging, i. e., SMS-like news exchange between users, for learning English as a
second language. The large community of pre-existing users
of this service allowed the learners to observe communica-tion of native speakers and to practice by communicating
with other users who were no member of the class.
Even in domains other than language learning, the value
of communicating is important. For instance, in mathemat-ics learning being able to verbally explain results and prob-lem solving steps is increasingly emphasized. Competency-based learning as, among others, put forward by Niss [27]
regards communication of results as similar important as
formal proving skills.
On the other hand, having the learners engaged in an un-restricted community can be distracting. During our micro-blogging usage, learners suddenly started to post German
and Japanese messages, which in itself is no bad thing but
distracted from the goal of practicing English. Additionally,
unmoderated contributions can be problematic if oending
content is posted. However most Web 2.0 services have built-in quality control mechanisms.
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 arti-cle uses social bookmarking services for easy authoring of
learning objects. There, bookmarks are stored on a Web 2.0
service
2
annotated with tags that provide additional infor-mation about the bookmarked resources. In the case study,
the tags were predened and carried specic semantics that
were exploited by a learning management system to suggest
new learning resources. However, such a xed semantic can
be enforced only in closed communities. Otherwise, prob-lems might arise if by chance other users employ the same
tags but with a dierent semantic. While most Web 2.0 ser-vices oer a possibility to dene closed communities,
3
this
of course undermines the benets of an open community.
Some research was performed on harnessing the collective
intelligence for e-learning applications. For instance, [1, 8,
42] investigate the usage of tags for ontology generation and
authoring support