In this study, we seek to design a developmental education class in a department of education based on a collaborative learning environment using information technology. We focus on a basic seminar program that aims to write a report including argumentation in the area of declining academic ability. Students tend to encounter ambiguity in this area while they struggle to adopt a new learning style at the university. Thus, we implemented a framework of collaborative learning to facilitate interaction among the students using the jigsaw method to address knowledge building and problem finding in this area and to exploit blogging to promote reflection of students' ideas through writing on the blogs. Students' outputs on the blogs demonstrated the results of idea generation and problem identification in preparing the final report. We also recognized the effectiveness of collaborative learning and blogging in developmental education at the university.

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Because academic fields are becoming increasingly segmented, various faculties here and elsewhere at a university often offer similar courses. Faculties publish syllabus information about their courses, but there are no means to search for this information across faculties. Consequently, it is not possible for students to conduct university-wide searches when they want to attend the most suitable courses outside their faculties, and difficult for faculty members to conduct systematic searches when they want to refer to other courses related to theirs. This problem motivated us to develop a campus-wide syllabus database, "Course Database." To make it possible to identify relationships between independently registered courses, we associated courses with the descriptions of prerequisite and acquired knowledge using a common ontology. Then, we introduced a similarity measure used for searching the ontology to alleviate differences in terminology used in the various knowledge descriptions. In this paper, we explain the format of the knowledge description, the structure of the ontology, and the similarity measure, introduce our prototype system, and show some experimental results.

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When we learn the motor skill, we cannot acquire the motor skill by knowing only the form and the action timing as the external information of a body. We acquire the motor skill by accumulating knowledge that we repeat learning the motion image and the proprioceptive sense as the motor sense. It is not able to transfer the motor sense directly, because the motor sense is the internal information in his/her mind and different from each other. However, a learner individually recognizes the motor sense. Then we propose the image training assist system that promotes accumulating the motor sense and acquiring the motor skill. The learner can records and retrieve the motor sense by using the image training assist system. We implement the image training assist system and apply to Kyudo (Japanese traditional archery) as one of the motor skill learning for an evaluation. We show the system is effective for the motor skill learning by the experimental results.

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The National Institution for Academic Degrees and University Evaluation is engaged in the awarding of academic degrees based on the accumulation of credits. These credits must be classified according to pre-determined criteria for the chosen disciplinary field. This work is carried out by the sub-committees within the Committee of Validation and Examination for Degrees, whose members are well-versed in the syllabus of each course. The number of applicants is increasing yearly so that a course classification system supported by information technology is strongly desired. We know the Course Classification Suport system (CCS), which is a prototype system to support the course classification for the awarding of degrees in NIAD-UE. CCS recommends several courses to the Committee of Validation and Examination for Degrees at the same time. It cannot give any priority how each course belongs to the class. In this paper, we propose the Active Course Classification Support system (ACCS) that can give the Committee of Validation and Examination for Degrees the priority which course fits more than the others. According to the priority given by ACCS, the committee can actively control the number of courses that are to be judged their suitability for each class. We show its effectiveness in the classification of courses that were actually submitted in the fiscal year 2003 and 2004.

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Comprehending the features of curricula provided by various higher education institutions is significant in designing and evaluating a curriculum. To facilitate comprehension of the curricula's features, Curriculum Analyzing System has been developed by Nozawa et al. utilizing document-clustering of syllabus data. However, speeding up and improvement of interactivity in the clustering procedure remained to be accomplished. In this article, a co-clustering method based on graph partitioning is introduced in order to improve the curriculum analyzing system. We show that recursive application of co-clustering to syllabus-term data makes the system more efficient and enables the users to understand the curricula's features more interactively.

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Recently, there are some approaches of shooting a situation of a lecturer and converting the teaching materials used by a lecturer into the electronic media, then they are put on Web and offered to learners. In a conventional lecture archiving, only videos of a lecturer and teaching materials are put on Web, and learners are able to utilize the media anytime and anywhere. However, the information generated in a lecture is derived not only from a lecture but also from students because there is a bilateral communication between a lecturer and students attending the lecture or between students themselves. This information is important not only for lecturers who has interest in Faculty Development(FD) but also for learners in order to understand the contents of a lecture. In this paper, we discussed conventional lecture archives and availability of recording of a bilateral communication between a lecture and students attending the lecutre or between students in order to understand the situation of a lecture. Based on the discussion, we sum up our research about an automatic lecture archiving system for recording bilateral communication by shooting students attending the lecture from the perspective of recording information of students in a lecture room.

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As an application of a computer to education, we made a computerized questionnaire system used for educational evaluation, the layout of which we here discuss. The proposed system, which facilitates in a Web environment, is ought to be used in higher education. The questionnaire in this system is made for consciousness survey. It asks, of subjects, agreement for each item in an ordinal scale. In making the questionnaire, the maker can select one of three answer modes : A mode-agreement of each item statement; B mode-the agreement and importance of the item; C mode-the agreement/importance, and those properties of subordinate items if an item(original item) has them. If a questionnaire maker thinks an original item equivalent to a set of several subordinate items in their contents, C mode can be used. This research discusses the layout of the system concept and the consideration.

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[in Japanese]

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[in Japanese]

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Messiaen and Scriabin are well-known as the synesthesea hold person with regard to sound and color. We are able to imagine the relation of the cooperation between music and color from the report of the color-heard-person. We propose the method of a new characteristic recognition for music, by paying attention to the relation of the cooperation between sound and color. It is shown that the characteristic of music is extracted from the adjective image scale that is used with the color image scale. We verified the utility of this method from the questionnaire survey to the university student of the music major. It is shown that the extraction of the feature concerning feeling of music is possible as a result of the verification. Moreover, one proof was able to be given to various discussions concerning synesthesea and common recognition by extracting such cooperated feature.

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Neural networks (NNs) can solve only a simple problem if the network size is too small. On the other hand, if the network size increases, it costs a lot in terms of memory space andcalculation time. Therefore, we have studied how to construct the network structure with high performances and low costs in space and time. A solution is a multi-branch structure. Conventional NNs use the single-branch for the connections, while the multi-branch structurehas multibranches between nodes. In this paper, a new method which enables the multi-branch NNs to have functional localization is proposed. Neural networks with Branch Control adjust signals propagating through branches between the intermediate layer and output layer depending on the inputs of the network. Therefore, a branch could be cut depending on input values. Simulation results of function approximations and a classification problem illustrated the effectiveness of multi-branch NNs with functional localization.

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A portfolio is a useful method to calculate the rate of expected earnings and risks based on changes in stock prices. However, past methods such as the fundamental analysis, the technical analysis and etc. are not proposed as a decision support system available for real investments. On the other hand, speaking about the asset allocation, those methods determine asset allocation ratio using general indices such as TOPIX independently of the portfolio selections. This paper describes a novel decision support system for assisting in actual investment decisions. First, the system makes a stock investment brand selection using SOM (Self-Organizing Maps). Secondly, the system calculates asset allocation ratio of risk/nonrisk assets using both fuzzy reasoning and the management indices of the brands selected by SOM. We apply this method to actual stock price data and show better results than those by TOPIX. Finally, we discuss an effectiveness of the proposed support system against a steep fall in stock prices, such as IT Bubble collapse that began in 2000.

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