Although it is important to understand learners’ emotional situations in teaching and learning processes, learners sometimes do not express negative emotions intentionally. This study has termed this intentional non-expression of negative emotions “emotional concealment,” and examined its estimation from learners’ biometric information. In particular, we focused on learners’ facial features, and attempted to clarify their relationship with emotional concealment. Using these results, we attempted to quantify emotional concealment from the time-series data of biometric information and detect it as an outlier. Additionally, we attempted to develop a feedback generation system to inform teachers about emotional concealment.

Cognitive architecture plays essential role in Intelligent Tutoring System (ITS). For effective learning support, dynamic model subserving the function of the prediction of learners’ states should be incorporated. In this paper, we proposed a neural network-based architecture in progress that can incorporate the dynamic model to generate the prediction of leaners’ perceptual states when categorical ambiguous stimulus and the instruction of category were given.

The emotion regulation mechanism of mindfulness plays an important role in the stress reduction effect. Many researchers in the fields of cognitive psychology and cognitive neuroscience have attempted to elucidate this mechanism by documenting the cognitive processes that occur and the neural activities that characterize each process. However, previous findings have not revealed the mechanism of information propagation in the brain that achieves emotion regulation during mindfulness. In this study, we constructed a functional brain model based on its anatomical network structure and a computational model representing the propagation of information between brain regions. We then examined the effects of mindfulness meditation on information propagation in the brain using simulations of changes in the activity of each region. These simulations of changes represent the degree of processing resource allocation to the neural activity via changes in the weights of each region's output. As a result of the simulations, we reveal how the neural activity characteristic of emotion regulation in mindfulness, which has been reported in previous studies, is realized in the brain. Mindfulness meditation increases the weight of the output from each region of the thalamus and sensory cortex, which processes sensory stimuli from the external world. This sensory information activates the insula and anterior cingulate cortex (ACC). The orbitofrontal cortex and dorsolateral prefrontal cortex inhibit amygdala activity (i.e., top-down emotion regulation). However, when mindfulness meditation dominates bottom-up processing via sensory stimuli from the external world, amygdala activity increases through the insula and ACC activation.

Every human processes a set of mental schemas for problem solving. We develop and improve these schemas by reflecting on our experiences with errors, which is a type of metacognition (Kayashima, 2008). In this study, we proposed a cognitive model of this "self-reflection" process based on Kayashima's two-layer working memory model, and developed a food recommender system using our cognitive model. In the test simulation, the users were satisfied with the foods that the system recommended, although the recommendation results were unexpected to the users. This implied the system practically worked to satisfy the user's expectation. On the other hand, the candidate recommendations which the system selected as its final output were different from those provided by the users. This suggests that the cognitive model needs improvement in terms of psychological reality.

Facial expression of humanlike pedagogical agent plays important role to affect the learners’ motivation to interact with it. Uncanny Valley (UV) effect is notorious in the agent design in that extraordinary humanlike agents affect observers negatively to feel eerie. In this study, to uniformly describe the conceptual brain function model which provides the explanation for the mechanism of UV effect, we propose the qualitative description with “basic function” and “representation primitives.” Basic functions are hypothesized to be intrinsic functions of brain functions with a consequence of which can represent arbitrary brain functions. Representation primitive is a semantic description that is defined in correspondence with a basic function.

Many studies have been conducted during the last two decades examining learner reactions within e-learning environments. In an effort to assist learners in their scholastic activities, these studies have attempted to understand learner mental states by analyzing participants’ facial images, eye movements, and other physiological indices and data. To add to this growing body of research, we have been developing IMS (Intelligent Mentoring System) which performs automatic mentoring by using an ITS (Intelligent Tutoring System) to scaffold learning activities and an ontology to provide a specification of learner’s models. To identify learner mental states, the ontology operates based on theoretical and data-driven knowledge of emotions. In this study, we use statistical models to examine constructs of emotions evaluated in previous psychological studies, and then produce a construct of academic boredom.

Recently, the research in intelligent educational systems has much interest in exploring data from academic settings to understand learners behavior and mental states. We have been developing IMS (Intelligent Mentoring System) which performs automatic mentoring by using an ITS (Intelligent Tutoring System) to scaffold learning activities and an ontology to provide a specification of learner ’s models. To provide learner ’s models in mentoring, the ontology describes qualities and quality values on awareness which are conceptualization of subjective evaluation. To specify relationships among qualities on awareness in academic settings, this study organized academic emotions in the psychological research and proposed their ontological descriptions.

Recently, the research area of intelligent educational systems has increasingly approached Educational Data Mining, which addressed a variety of learner aspects such as mental states. Although data of eye movements is promising in realizing mental states of learners, we have to empirically understand features of eye movements in advance due to difficulty in handling them. Toward the final goal of automatic estimation of learner mental states based on eyes, this study experimentally described changes of eye movements by confidence of correct answers. In our experiment, participants were asked to answer multiple-choice problems and respond to questionnaires about the problems, with the results indicating that transitions of eyes in initial processes where all choices were scanned differed depending on the levels of confidence.

Recently, the research in intelligent educational systems has much interest in exploring data from educational settings to understand learners behavior and mental states. To further understand learners based on such the data and sophisticate supportive interventions by educational systems, knowledge of relationships between learners' behavior and mental states must be shared. To propose a framework to share the knowledge, this study attempted ontological descriptions for learners’ eye-movement and mental states in solving computer-based multiple-choice problems. The current study forms a technical basis for development of an IMS (Intelligent Mentoring System) in which an automatic mentoring function is implemented with ITS (Intelligent Tutoring System).

Problem posing is identified as an important activity in mathematics education. Although it is difficult for novice learners to pose diverse problems, they must do so. Such novices particularly have difficulty in appropriately composing mathematical structures of solutions when posing new problems. This paper discussed and experimentally studied an approach to support learning of problem posing as a production task. We designed support for learning by imitation of examples, in which learners reproduce problems presented as examples. That is expected to facilitate learners’ understanding ideas used in generation of the examples, and to stimulate new idea generation in learners’ own problem posing. We then verified the effects of learning an example through imitation, with the results indicating that learning by imitation can facilitate adaptation of ideas used in an example into learners' problem posing, whereas it cannot necessarily facilitate appropriate problem posing when they try to diversify.

Sharing know-how information for appropriately grasping care needs is an important factor to improve the quality of care service. Our know-how information sharing method highlights the differences between beginners and more skillful persons and brings them to the attention of the former. When a skillful person is given assessment data, first she roughly observes them based on a certain pattern that reflects her experience and then gradually notices the details. In this paper, we promote awareness by showing beginners this process. We classified assessment data using cluster analysis. With our results, which were verified by skillful persons, we verified that they basically agreed with the skillful person's classification pattern. Therefore, a skillful person's data observation process can be presented to beginners.

We have developed the know-how information sharing system. As the method to extract the know-how information, we consider that visualizing and showing care plans drawn up by experts in various forms allows a beginner to see the differences between a novice plan and an expert plan. This system can visualize the similarities among documents that experts interpreted the results of an assessment and can flexibly change viewpoints. Additionally, it can map a userpsilas and several beginnerspsila new document into a two-dimensional document space. Through the result of the evaluation used by a nurse, care workers and care takers, we confirmed that this system was effective in educational supports.

The purpose of this study is the establishment of a method and the development of a support system for educating personnel involved in care management by computer. We propose a system in which know-how information can be shared. We consider that visualizing and showing care plans drawn up by experts in various forms allows a beginner to see the differences between a novice plan and an expert plan. Sharing know-how information is possible by recording, accumulating, and giving titles to what has been noticed by comparing documents. This system can visualize the similarities among documents that interpreted the results of an assessment and can flexibly change viewpoints. Additionally, it can map a user's and another beginner's new document into a two-dimensional document space. Through evaluations by experts in nursing and caring, we confirmed that this system could be educational.

We have developed a software that supports care management by the KOMI Chart System, aimed at improving the visibility of the KOMI Chart System with functions for drawing, revising and observing the time-series charts. The purpose of this study is to evaluate the effectiveness of computer support for care management. The experiment results showed: (1) the time required for care planning was reduced, and (2) grasping client's daily life was affected by the speed of drawing the KOMI Chart.

The Industry and University cooperation program is a project of the Japanese Ministry of Education (Mombusho). The target objective of this program is the harmonization of university level educational research, society practice and practical business. The University of Electro-Communications has been appointed by Mombusho to fulfill some specific parts of this program. The authors report on their experience with the introduction of this program, its framework, settings, actual implementation and preliminary findings. The problems encountered are discussed, together with a number of solutions to assist good practice in the building of such an applied educational program. Career development, via acquiring of experience and knowledge in the field of information communication technology, is an important subject for the future information communication society. The program's starting courses involve this discipline. The lectures were focused on high information technology, large-scale information system planning and application, and network technology.