The educational environment is changing from traditional classroom teaching from individual/collaborative learning ecology by development of Internet, mobile and wireless technology. Therefore, we need to develop the new pedagogy in consideration of such new technologies. Especially, our knowledge and wisdom  are cultivated by interactive learning/problem solving/building-something through collaborative activities. In this panel discussion, we would like to examine the meanings/ecology  of  "Collaborative Learning" again and explore the new technologies of comminications which evokes and enhances it.

Recently, “collaborative learning” using internet has become popular in educational technology societies. One of unique advantages of the collaborative learning using internet is that much amount of learning process data concerned with their discussions can be stored. However, there are few studies about how to analyze the data and how to efficiently utilize it. It is an urgent task to consider how to utilize efficiently this much data concerned with collaborative learning. This paper introduces some new Data mining technologies and text mining technologies for collaborative learning.

Internet technologies that support the asynchronous interchange of messages are used in a wide variety of collaborative learning contexts, and are described using a broad range of terms and theoretical frameworks. Despite this remarkable theoretical and terminological diversity, the software and interfaces that constitute this technology manifest specifiable uniformities in their underlying structural and behavioral characteristics. These uniformities, and the structured data that is created through their use can be processed, analyzed and reorganized using pattern and network analyses, concept mapping, syndication and a variety of semantic Web technologies. This structured data can also be extracted and be made portable, thus supporting system independence, data preservation, evaluation, and research. But before these and other potential benefits can be realized, it is necessary to develop a common, generalized and abstract model that can describe the structures and actions arising in these asynchronous communication systems. It is precisely such an abstract data model that this paper outlines; and it seeks to validate this model through reference to research, practice and existing software systems.

Competence structures of the content and competence modelling of the learners provide well-suitable means for finding appropriate peer tutors in CSCL based on asynchonous messaging and annotations. Various criteria for the appropiateness of potential peer tutors can be discussed. An internet-based system used as a large scale Web experiment can then also deliver data for evaluating such criteria.