Kanji Laboratory is a kanji learning ICAI system. In this paper, we describe the development of Kanji Laboratory, which is designed for foreigners who are learning Japanese kanji. We have developed Kanji Laboratory under the guidelines of environmental ICAI systems, based on a kanji learning method focusing on kanji radicals. Kanji Laboratory consists of a knowledge base, a learning environment and an advisor module. The knowledge base can well-handle the knowledge of Joyo Kanji (1,945 characters). Each one is related with its radicals via their inherited attributes. In addition, this knowledge base system can search kanji knowledge quickly. The learning environment has the following features: (1) Students can construct a kanji by combining radicals and disassemble the kanji into radicals and strokes. (2) Students can use electronic tools, such as a kanji dictionary, which support kanji learning. In this way, students can learn kanji and the relations with its radicals effectively. With regard to the advisor, although it occurs that students fall in plateaus of learning in environmental CAI, the advisor module is designed to give well-timed advice to students, avoiding those plateaus, based on the observation of their learning actions.

We develop a new class of stochastic Petri net: non-regenerative stochastic Petri net (NRSPN), which allows the firing time of its transitions with arbitrary distributions, and can automatically generate a bounded reachability graph that is equivalent to a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. Thus, it can model and analyze behavior of a system whose states include some non-regeneration points. We show how to model a system by the NRSPN, and how to obtain numerical solutions for the NRSPN model. The probabilistic behavior of the modeled system can be clarified with the reliability measures such as the steady-state probability, the expected numbers of visits to each state per unit time, availability, unavailability and mean time between system failure. Finally, to demonstrate the modeling ability and analysis power of the NRSPN model, we present an example for a fault-tolerant system using the NRSPN and give numerical results for specific distributions.

This paper describes a model of kanji (Chinese characters) learning, called KASTAM (Knowledge Acquisition and STAbility Model), in order to develop a CAI system which supports a student to stabilize her/his kanji knowledge. KASTAM can handle kanji learning as complementary acquisition and stability processes of kanji knowledge.

This paper describes the development of an environmental ICAI system for English conversation learning, which is equipped with a simulation-based learning environment and an advisor function. Recently there have been various educational applications or tools for adult second language education, where the learning target is the acquisition of formal knowledge of a language. When considering the implementation of a practical CAI system, methods for developing communicative competence in learners are required. Although there are a number of ICAI systems for conversation learning, often the methodologies which they apply are not completely suitable for the acquisition of the required fundamental knowledge. Our system, based on the architecture of environmental CAI, enhances communication skill acquisition. The system has a learning environment with the following features: (1) A simulation of language activities, implemented in the role-playing game style, which helps to promote a learner's motivation. (2) Educational behavior of the system is varied through the modification of the learning environment and changes in the simulation progress and control commands. (3) An induction strategy, which can cause learners to fail to achieve a learning target, is executed by an advisor mechanism. The system is a prototype architecture for application in environmental ICAI systems for simulation based learning. We believe that the architecture of this system is an efficient framework for linguistic education.

Object-Oriented database systems (OODBMS) are well known for modeling complex and dynamic application domains. Typically OODBMS have to handle large and complex structured objects whose values and structures can change frequently. Consequently there is a high demand for systems which support temporal and versioning features in both objects (or database population) and schema. This paper presents a mechanism for accessing the temporal versioned objects stored in the database which supports schema versioning. The results shown here can be considered as a value-added extension of our model called TVOO described in detail in [1] and [2]. In contrast to conventional database models, in TVOO objects and classes are not physically discarded from the database after they are modified or deleted. They are time dependent and the history of the changes which occur on them are kept as Version hierarchies. Therefore our model enriches the database environment with temporal and versioning features. Also, an access mechanism which makes it possible to access any object under any schema version is defined in such a way that not only objects created under old versions of schema classes can be accessed from new versions, but also objects created by new schema class versions can be accessed from old versions of the respective class.

Effective collaboration in ComputerSupported Collaborative Learning (CSCL) environments is nowadays an important research topic. It deals with two main problems: the configuration of an appropriate learning group and the intelligent task distribution in the practice of domain knowledge. In order to have effective collaboration in a CSCL environment, we have proposed a set of software agents that assist the learners to select their learning tasks, according to their capabilities and the possibilities of collaboration between them. In this paper the cooperation among software agents is presented as the key point for effective collaboration in CSCL environments. In this kind of environments the learner must have enough collaboration and learning possibilities, being motivated with the experience of social knowledge construction. We have been working on the problem of effective collaboration in CSCL environments, based on the cooperation between software agents developed for GRACILE, our Japanese Grammar CSCL environment. Before, we have proposed intelligent agents that assist the learners. Our next step has been the design of the cooperation between agents in order to create possibilities of effective collaboration in a virtual community of practice. In order to evaluate the performance of our agents we made several simulations. The results obtained from these simulations of diverse types of learning groups provided us with guidelines for the configuration of groups in CSCL environments, where effective collaboration is possible.