Cel One of the most important trends in CSCL/W is the proliferation of tools to support e-discussion due to their value in learning, negotiating, and other social applications. Discussions, however, do not necessarily lead to desirable results but often turn out to be ineffective or chaotic when no moderator/tutor is present.The characteristics and demands of the role of the moderator/tutor have not been fully studied, especially in synchronous discussions using environments displaying graphical argumentation maps. Moreover, appropriate tools to assist moderators in these duties have not been developed to any satisfactory level. ARGUNAUT aims at unifying awareness and feedback mechanisms for working in e-discussion environments. The mechanisms will work on two existing (and potentially more) platforms: Digalo and Cool Modes. The feedback is primarily directed to a human moderator facilitating the interaction but may also help students.At the heart of the AI components proposed, an off-line analysis mechanism based on machine learning techniques - the "deep loop" - takes selected human-annotated examples and generalizes them to indicators that can in turn be used for awareness feedback. Some semantic indicators will also be included. The evaluation scenarios will rely on the analysis of discourse arising from this setting. The impact: A big change in education and training programs at all levels, which will build to a larger extent on argumentative practices capitalizing on the proposed tools.Using our tools, we expect to increase the learners per moderator by a factor of 2-3, although it is not our intention to focus on such a quantitative measure but to improve the quality of discussions and enhance their value for learning. Experimentation will be done in secondary, higher, professional and vocational education environments. The project, planned for 33 months, will be carried out by 7 partners: 3 univ., 2 R&D institutes and 2 industrial companies in 5 countries. Dziedzina nauki natural sciencescomputer and information sciencesartificial intelligencemachine learning Program(-y) FP6-IST - Information Society Technologies: thematic priority under the specific programme "Integrating and strengthening the European research area" (2002-2006). Temat(-y) IST-2004-2.4.10 - Technology-enhanced Learning Zaproszenie do składania wniosków Data not available System finansowania STREP - Specific Targeted Research Project Koordynator THE HEBREW UNIVERSITY OF JERUSALEM Wkład UE Brak danych Adres MT. SCOPUS 91905 JERUSALEM Izrael Zobacz na mapie Koszt całkowity Brak danych Uczestnicy (6) Sortuj alfabetycznie Sortuj według wkładu UE Rozwiń wszystko Zwiń wszystko DEUTSCHES FORSCHUNGSZENTRUM FUER KUENSTLICHE INTELLIGENZ GMBH Niemcy Wkład UE Brak danych Adres ERWIN-SCHROEDINGER-STRASSE 57 67663 KAISERSLAUTERN Zobacz na mapie Koszt całkowity Brak danych FRAUNHOFER IAF Niemcy Wkład UE Brak danych Adres Tullastr. 72 79108 MÜNCHEN Zobacz na mapie Linki Strona internetowa Opens in new window Koszt całkowity Brak danych POULIADIS ASSOCIATES CORP Grecja Wkład UE Brak danych Adres SIGROU AVENUE 142 17671 ATHENS Zobacz na mapie Koszt całkowity Brak danych SILOGIC S.A. Francja Wkład UE Brak danych Adres 6 RUE ROGER CAMBOULIVES 31100 TOULOUSE Zobacz na mapie Koszt całkowity Brak danych UNIVERSITAET DUISBURG-ESSEN - STANDORT DUISBURG Niemcy Wkład UE Brak danych Adres UNIVERSITATSSTRASSE 2 47117 ESSEN Zobacz na mapie Koszt całkowity Brak danych UNIVERSITY OF EXETER Zjednoczone Królestwo Wkład UE Brak danych Adres NORTHCOTE HOUSE, THE QUEENS DRIVE EX4 4QJ EXETER Zobacz na mapie Koszt całkowity Brak danych
