This system development enables ubiquitous peer review and reuse of reviewer comments to assess teaching/learning in higher education. The purpose of this project is two-fold: (1) to develop applications for recording and storing reviewer annotations on streaming class lectures as time sequence data of pen-tip coordinates, and (2) to identify key principles and criteria from annotated video data to assess and evaluate the quality of teaching and learning (e-teaching portfolio). The evaluation studies were conducted to gain a broad understanding of how reviewers identify and record educational events effectively and appropriately during ldquolesson study (Jyugyo kenkyu)rdquo when using this system. The collection and analysis of reviewers' annotations indicated that this system is capable of reusing collected comments in order to suggest weak and strong points in class lectures from different reviewers' perspectives.

In this study, we proposed and implemented "MultiPod", an online educational system for learning foreign words. This system is based on iPods and it uses word learning materials of very short movies. Each learning material consists of a 5-second moving image that corresponds to the word to be learned, its spelling, and its pronunciation. We conducted an evaluation experiment with ten subjects in which we compared the learning method based on our system against the traditional paper-and-pen method. By the t-test for the results, we proved that there is a significant difference between the long-term effectiveness of MultiPod and that of the paper-and- pen method.

To compensate the lack of awareness in CSCL environment, a CSCL chat tool capable of displaying all the participants' key typing process was developed. The system displays key by key typed in letters to other learners. Smooth turn-taking and topic negotiation are expected by the realization of real time display. From our preliminary evaluation, learners evaluated the conversation using this system easier, even though number of sentences between the proposed system and the usual chat system showed no difference. Learners' comments after the usage reveals that there are both merit and demerit such as natural awareness or neglecting of writing complete sentences.

An efficient e-learning system should provide learners with learning environment that has high degree of freedom. In order to realize this, e-learning systems must be equipped with such functions as letting learners themselves choose appropriate learning contents and understand correctly their level of progress and achievement for each learning contents. We have been developing an integrated e-learning environment which integrates learning history and learning content information to control each learner's learning. It is designed based on learning ecological model (LEM) and is now going to be integrated with the database run by educational affairs section. It will enable teachers to analyze e-learning log data with learners' academic achievements. This paper describes functions of the LMS and then reports a preliminary practice in a graduate school course.

In human-to-human interaction, people sometimes are able to pick up and respond sensitively to the other's internal state as it shifts moment by moment over the course of an exchange. To find out whether such an ability is worthwhile for computer human interfaces, we built a semi-automated tutoring-type spoken dialog system. The system inferred information about the user's \scare{ephemeral emotions}, such as confidence, confusion, pleasure, and dependency, from the prosody of his utterances and the context. It used this information to select the most appropriate acknowledgement form at each moment. In doing so the system was following some of the basic social conventions for real-time interaction. Users rated the system with this ability more highly than a version without.

Ratings of user satisfaction, although fairly easy to elicit for today's spoken language systems, can be more elusive for systems which operate at near-human levels of performance. This problem can be alleviated by adding a `relistening ' phase before eliciting judgements: in this phase the user listens to a recording of himself interacting with the system while consulting a transcript of that interaction. This technique allows more sensitive judgements of system quality by avoiding problems arising from attention limits. 1 EVALUATING PERSONABLE SYSTEMS Speech technology has advanced to the point where there exist systems which allow motivated users to accomplish useful tasks. However there are also potential applications where users are not so motivated and where there is no clear criterion of task-completion, including applications in education, commerce, and entertainment. In these situations it will be important for interaction with the system to itself be pleasant, otherwise the...