2019 Exercise in Human-Centric Information Processing

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Academic unit or major
Graduate major in Information and Communications Engineering
Instructor(s)
Kaneko Hirohiko 
Course component(s)
Exercise
Mode of instruction
 
Day/Period(Room No.)
Mon5-8(G224)  
Group
-
Course number
ICT.H505
Credits
2
Academic year
2019
Offered quarter
1Q
Syllabus updated
2019/3/18
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).

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