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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Information and Communications Engineering
- Instructor(s)
- Kaneko Hirohiko
- Class Format
- Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Mon5-8(G224)
- Group
- -
- Course number
- ICT.H505
- Credits
- 2
- Academic year
- 2018
- Offered quarter
- 1Q
- Syllabus updated
- 2018/4/9
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course is Project-based learning （PBL） to acquire knowledge and skills for human centered informatics. Students make a group to carry out a project related to human centered informatics using the equipment such as human motion capturing systems, biosensors, virtual reality systems and the popular methods in the field.
Student learning outcomes
The aim of this lecture is to understand the methodology and techniques for investigating human information processing with experiments and exercises. In addition, it is intended to develop the ability to find subjects worth for study.
Keywords
PBL（Project-Based Learning), psychophysics, biometrics, biological measurements, presentation training, discussion training, data collection, data analysis
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | ✔ Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
In guidance, students choose one of the topics (laboratory) for exercise．Exercises are held at each laboratory. At the middle and end of the course, students give presentations on their achievements. The schedule of excercise in each laboratory might be changed depending on the schedules of perticipants and the lab.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Guidance | Understand the subject of exercise. |
| Class 2 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 3 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 4 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 5 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 6 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 7 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 8 | Midterm presentation | Prepare slides and give a presentation on the achievements. |
| Class 9 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 10 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 11 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 12 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 13 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 14 | Exercise in each laboratory. | Prepare for experiment, collect data and analyze and interpret the results. |
| Class 15 | Final presentation | Prepare slides and give a presentation on the achievements. |
Textbook(s)
Textbook specified by each supervisor.
Reference books, course materials, etc.
Materials provided by each supervisor.
Assessment criteria and methods
Midterm and final presentations and the activities in exercise. Midterm presentation: 25%, final presentation: 25% and the activities in exercise:50%.
Related courses
- No related courses.
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Students must have successfully completed either Basic Sensation Informatics（ICT.H411) or Computational Brain（ICT.H422）.
