Collaborative Learning Support Knowledge Management for Asynchronous Learning Networks Toshio OKAMOTO, Mizue KAYAMA and Alexandra CRISTEA University of Electro- Communications Graduate School of Information Systems {okamoto, kayama, alex}@ai.is.uec.ac.jp Abstract The large amount of information available on the distributed network environment is an excellent source basis for remote learning environments. However, to support the decision making process of both learners and learning mediators in such a huge information space, some prior arrangement and integration of the learning information is necessary. If managed accordingly, various information can be referred and reused in educational context. At the Laboratory of AI & Knowledge Computing, University of Electro- Communications, Japan, we are constructing a digital portfolio database, which is rapidly increasing, as well as building a learning infrastructure. The remote learning support environment called RAPSODY-EX (Remote and Adaptive Educational Environment: A Dynamic Communicative System for Collaborative Learning) can effectively carry out the collaborative learning support in asynchronous/synchronous learning mode, based on the following two functions: 1) learning control function for individual learner and group. 2) learning information managing function for mediation. 1. Management of learning information The managing mechanism consists of two modules: the learning environment and the collaborative memory, which controls information and data produced in the learning environment. The learning environment is characterized by two functions: learning progress monitoring and collaborative learning tools and applications. The first function controls the learning record of individual learners and the progress of the collaborative group learning. The learning information created in such a learning environment is used by the collaborative memory. The collaborative memory is based on two functions: the knowledge processing (input learning information is re-shaped into a standard form) and the knowledge storage (attributes related to content are added). 2. Knowledge management in RAPSODY-EX Knowledge management can be expressed as a conversion cycle between tacit knowledge and expressive knowledge [8]. Tacit knowledge has a non-linguistic representation form, while expressive knowledge results when transforming tacit knowledge into a linguistic form, which enables sharing. In the SECI model [8], socialization (S), externalization (E), combination (C) and internalization (I) of knowledge are expressed. Figure 1: The mechanism schema of the RAPSODY-EX Knowledge management in educational context is "the systematic process of finding, selecting, organizing, distilling and presenting information in a way that improves a learner's comprehension and/or ability to fulfill his/her current learning objectives." (from [14]) RAPSODY-EX, supports item C, as well as the knowledge conversions: C -> I and E -> C. The learning information is expressed learners' knowledge, as a result of transformation of tacit knowledge via a language. The questions to consider are: • What are the knowledge resources in the learning group? • What is the expected gain for the learning group? • How can the knowledge resources be controlled, to guarantee a maximum gain for the learning group? Proceedings of the IEEE International Conference on Advanced Learning Techniques (ICALT’01) 0-7695-1013-2/01 $10.00 © 2001 IEEE