Adaptive Problem Solving using Off-the-Shelf Adaptive Design
Construction of an Environment to Foster Adaptive Problem-Solving Skills based on the Cognitive Behavioral Science Theory of Action Selection and Memory
Our lab is developing a wearable device capable of measuring everyday behaviours. Our goal is to find the connection between these unconscious behaviors and our decision process, to enhance our life-styles and create a safer society.
This project consists of 3 stages:
- Find which information is relevant for our daily decision process and create a wearable device capable of recording this information.
- Analyze these data and create a decision model that can predict and support our adaptive problem solving skills.
- Design a support system that can be used in daily-life, that help us look back into past actions and support the decision of future events.
By understanding which elements from our daily behaviour influence our decision process, we can create a support system that enhances our Adaptive Problem Solving Skills, helping us make faster and better decision.
Based on the cognitive-behavioral science theory of action selection and memory, this study constructs an environment that smoothly integrates “memory enhancement by behavioral measurement, problem-solving behavior extraction, and cognitive process visualization” into individual activity lines by visualizing cognitive processes during task execution by the 4-PROCESS.
This project is supported by the Grants-in-Aid for Scientific Research (KAKENHI) Program from the Japan Society for the Promotion of Science (JSPS).
北島 宗雄
Professor at Nagaoka UT
Muneo Kitajima currently works at the Department of Management and Information Systems Engineering, Nagaoka University of Technology.
李 昇姫
Associate Professor of Kansei Design
Designing happiness for everyone, borderless use concerning Global Kansei.
恩智 英治
Graduated Student
My research interest is in human-robot interaction design, in particular on how people understand emotions in robots.
張 寒
Graduated Student
As a user-centered researcher with industrial design and Kansei design experiences, I would like to assist Human-Vehicle interaction in innovating through framing insights and exploring solutions.
