2 research outputs found
Combining Structural Process-Oriented and Textual Elements to Generate Awareness Indicators for Graphical E-Discussions
Moderation of e-discussions can be facilitated by online feedback promoting awareness and
understanding of the ongoing discussion. Such feedback may be based on indicators, which
combine structural and process-oriented elements (e.g., types of connectors, user actions) with
textual elements (discussion content). In the ARGUNAUT project (IST-2005027728, partially
funded by the EC, started 12/2005) we explore two main directions for generating such indicators,
in the context of a synchronous tool for graphical e-discussion. One direction is the training of
machine-learning classifiers to classify discussion units (shapes and paired-shapes) into predefined
theoretical categories, using structural and process-oriented attributes. The classifiers are
trained with examples categorized by humans, based on content and some contextual cues. A
second direction is the use of a pattern matching tool in conjunction with e-discussion XML log
files to generate "rules" that find "patterns" combining user actions (e.g., create shape, delete link)
and structural elements with content keywords
Computer Supported Moderation of E-Discussions: the ARGUNAUT Approach
Despite their potential value for learning purposes, e-discussions do not necessarily
lead to desirable results, even when moderated. The study of the moderator's role, especially
in synchronous, graphical e-discussions, and the development of appropriate tools to assist
moderators are the objectives of the ARGUNAUT project. This project aims at unifying
awareness and feedback mechanisms in e-discussion environments, presently implemented on
two existing platforms. This system is primarily directed to a human moderator and
facilitating moderation, but might also help the students monitor their own interactions. At the
heart of system are the inter-relations between an off-line AI analysis mechanism and an online
monitoring module. This is done through a collaboration of technological and pedagogical
teams, showing promising preliminary results