Chapters authored
Toward Clarifying Human Information Processing by Analyzing Big Data: Making Criteria for Individual Traits in Digital Society
The purpose of this research is to solve those problems in education by indicating criteria for individual differences of cognitive mechanism when students interact using digital devices so that teachers would be able to instruct students with appropriate teaching strategies in collaborative learning. From the results of experiments for clarifying information processing by analyzing students’ various data (Big Data processing), there was a tendency of an interaction comparing students’ performance with the first and the second semesters between visual type and auditory type.
Part of the book: Strategy and Behaviors in the Digital Economy
A Case Study of Using Big Data Processing in Education: Method of Matching Members by Optimizing Collaborative Learning Environment
The purpose of this paper is to optimize the combination of members for collaborative learning that utilized learning management system (LMS), a kind of social media. It is considered that there is a problem of this combinatorial optimization because of various discrete elements in education and it is difficult to find exact solution. Then, we have solved this problem by the method of approximate solution in nursing science class with big data processing, for instance, individual traits, learning outcome, and so on. The result shows continuously learning effects. We will report in this fundamental research how to gather learners’ various data and optimize matching members of team by local searching. It might be explained how to solve problems of combinatorial optimization by AI.
Part of the book: Social Media and Machine Learning
Dual Loop Theory: Eidetic Feedback Control and Predictive Feedback Control
We have been studying on human information processing and finding out two types of feedback loop, positive and negative which are used when people understand a sentence. Former one is eidetic feedback control by visual sensory organs with encoding short-term memory (STM). Latter one is predictive feedback control by phonological imagery and schema, which help recall and reconstruction or reformation of concepts concerning with long term memory (LTM). Moreover, those strategies might be related to their behavior or attitudes. We have hypotheses that there are individual differences depending on strategies how two loops are used. Those findings must lead coordinating transformation and learning control for AI doctor or care assistive robots, which are required to interact with various types of people so that they can predict their behavior and attitudes through feedforward control.
Part of the book: Assistive and Rehabilitation Engineering
Development of Support System Modeled on Robot Suit HAL for Personalized Education and Learning
The purpose of this paper is to maintain quality education for each student who has her/his own differentiation and needs. To achieve it, we have developed our support system for education and learning. We have examined this support system, whether it improved or did not improve the performance of 98 students in 2015, compared with that in 2014. The results have shown to be more significant than those of the previous year. Moreover, we have observed that students’ behavior toward projects have been becoming greater autonomy and positive attitude in practical class. From those results, we might be able to say that this support system works effectively in personalized education and learning (PEL) by using big data processing.
Part of the book: e-Services