Tatsunori Matsui

Experimental study of learning support through examples in mathematical problem posing

When using mathematics to solve problems in everyday life, problem solvers must recognize and formulate problems by themselves because structured problems are not provided. Therefore, in general education, fostering learner problem posing is an important task. Because novice learners have difficulty in composing mathematical structures (solutions) in problem posing, learning support to improve the composition of solutions is required. Although learning by solving examples is adopted in general education, it may not be sufficiently effective in fostering learner problem posing because cognitive skills differ between problem solving and problem posing. This study discusses and experimentally investigates the effects of learning from examples on composing solutions when problem posing. We studied three learning activities: learning by solving an example, learning by reproducing an example, and learning by evaluating an example. In our experiment, undergraduates were asked to pose their own new, unique problems from a base problem initially presented after the students learned an example by solving, reproducing, or evaluating it. The example allowed the undergraduates to gain ideas for composing a novel solution. The results indicated that learning by reproducing the example was the most effective in fostering the composition of solutions.

Development of know-how information sharing system in care planning processes – mapping new care plan into two-dimensional document space

The purpose of this study is to develop a computer support system for educating personnel who are involved in care management. We wish to develop 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 their plans and an expert plan. Sharing know-how information is possible by recording, accumulating, and giving titles to what has been noticed in comparing documents. This function can visualize the similarities among documents that interpreted the results of an assessment, and can flexibly change different viewpoints. In order to promote user awareness, we mapped a users new document into a two-dimensional document space, and confirmed that the results of this mapping were appropriate.

Development and evaluation of a mental model forming support ITS-the qualitative diagnosis simulator for the SCS operation activity

We built an educational Qualitative Diagnosis simulator (QUAD) to model SCS (Space Collaboration System) conferences. Our research aim is supporting SCS beginner users in forming correct SCS mental models and in understanding SCS essentials. Therefore, we use a logical circuit, to model the possible computations. The system diagnoses the students conceptual understanding mistakes about the SCS system and explains their cause.

Supporting Mathematical Problem Posing with a System for Learning Generation Processes through Examples

Problem posing, by which learners create new problems by themselves, is an important activity in mathematics education. However, novice learners have difficulty in posing problems, particularly when formulating appropriate solution structures of problems. Although they are provided with example problems that can serve as hints for composing novel problems, they do not necessarily understand the key ideas used to generate the examples. To improve problem posing for novices, this study discusses an approach that supports learning from examples as a production task. We propose a method of learning from examples through imitation, where a learner reproduces problems identical to given examples. We implement a system that presents examples of problem posing and supports learners in understanding the examples by having the learners reproduce them. We conducted an experimental evaluation in which learners learned from an example that embeds useful ideas to alter solution structures in the system. The results demonstrated that the learners successfully adapted the example when posing their own problems if they learned the example by the reproduction method. Thus, learning from examples through reproduction appears to be effective in the domain of problem posing as a production task.

A cooperative linkage between university and industry via an Internet distance education system

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 programs starting courses involve this discipline. The lectures were focused on high information technology, large-scale information system planning and application, and network technology.

Structural analysis for fuzzy rating scale data

In order to analyze the results of a questionnaire using the rating scale method, it is important to clarify the relational structure among questionnaire items. A fuzzy structural analysis (FSA) method is proposed for structural analysis of the fuzzy rating scale. The authors define the ordering coefficient between two items and show that FSA is the generalization of semantic structure analysis and ordering theory.<<ETX>>

A Method for Consensus Building Between Teachers and Learners in Higher Education Through Co-design Process

Improving added value and productivity of services entails improving both value-in-exchange and value-in-use. Value-in-use is realized by value co-creation, where providers and receivers create value together. In higher education services, value-in-use comes from learners achieving learning outcomes (e.g., knowledge and skills) that are consistent with their learning goals. To enhance the learning outcomes of a learner, it is necessary to enhance and utilize the abilities of the teacher along with the abilities of the learner. To do this, however, the learner and the teacher need to build a consensus about their respective roles. Teachers need to provide effective learning content; learners need to choose the appropriate learning strategies by using the learning content through consensus building. This makes consensus building an important factor in value co-creation. However, methods to build a consensus about their respective roles may not be clearly established, making such consensus difficult. In this paper, we propose some strategies for consensus building between a teacher and a learner in value co-creation. We focus on a teacher and learner co-design and propose an analysis method to clarify a collaborative design process to realize value co-creation. We then analyze some counseling data obtained from a university class. This counseling aimed to build a consensus for value-in-use, learning outcomes, and learning strategies between the teacher and the learner.

Framework to describe constructs of academic emotions using ontological descriptions of statistical models

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 a learner’s 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 the intelligent mentoring system (IMS), which performs automatic mentoring by using an intelligent tutoring system (ITS) to scaffold learning activities and an ontology to provide a specification of learner’s models. To identify learner’s mental states, the ontology operates on the basis of the 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. In concrete terms, we develop ontological descriptions of academic boredom that are represented with statistical models. To evaluate the validity and utility of the descriptions, we conduct an experiment to obtain subjective responses regarding learners’ academic emotions in their university course and describe them as instances on the basis of the ontological descriptions.

Development of Ontology Toward Common Understanding of Human Sensibilities and Emotions

With the ongoing development of information and communications technology, it is apparent that computers will be indispensable partners in future human life. In terms of computer information processing, techniques for coordinating human sensitivity and emotional levels are attracting attention and stand in contrast to conventional knowledge information processing. In this chapter, we present an overview of content-oriented research considering knowledge itself and describe an approach to handling knowledge of human sensitivity and emotions using computers. First, we provide an overview of existing content-oriented studies in the field of artificial intelligence (AI). Second, we discuss problems regarding the handling of knowledge of human sensibilities and emotions. Then, we introduce an ontology pertaining to the concept of color emotion as an approach to understanding human sensibilities and emotions. Finally, we describe the applicability of such an ontology to human–computer interactions and for the understanding of human nature through the concept of analysis-by-synthesis.

Qualitative Model for Neuro-Functional Mechanism Inducing Human Error Detection to Humanlike Agents Based on Cortico-Cerebellar Function

The uncanny valley is a major phenomenon that occurs during the implementation of facial expressions in a humanlike agent. Recent studies have explained that the negative impression of the agent’s expressions is a “prediction error.” We hypothesized that the prediction error stemmed from the differential output of dual processing, - that is, emotional and rational processing, - and it negatively affected a person’s impression of the facial expression of the agent, which was similar to that when perceiving an eerie sensation. A qualitative computational model was proposed to clarify this mechanism according to cortico-cerebellar function to compute the prediction of the humanlike agent’s facial movement. Thus, rapid emotional processing was indispensable with the thalamus playing an essential role in the processing.