▶Japanese
Post to SNS
- Home
- > Liberal arts and basic science courses
- > Teacher education courses
- > Practices for Psychological and Educational Measurement
- School of Science
-
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
- Teacher education courses
- Instructor(s)
- Matsuda Toshiki Kuriyama Naoko
- Class Format
- Exercise (Face-to-face)
- Media-enhanced courses
- Day/Period(Room No.)
- Thr5-6(W9-319)
- Group
- -
- Course number
- LAT.A403
- Credits
- 1
- Academic year
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- 2024/3/14
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
The course will focus on teaching statistical methods and the Warp and Woof model to do the statistical analysis of either psychological or educational data by utilizing the learning outcomes of "Introduction to Psychological and Educational Measurement."
Student learning outcomes
Students will be able to perform data analysis, such as calculation of basic statistics, statistical tests, ANOVA, multiple comparison, multiple regression analysis, principle component analysis, factor analysis, and cluster analysis, by using Excel or R Commander.
Keywords
Statistical data analysis, Excel, R Commander, Problem-solving, Statistical Ways of Viewing and Thinking
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
This course will be held only if "SHS.D463：Analyses and Modeling Techniques of Educational Data" is not held. Please check "Prerequisites" of this course.
Every lesson will be conducted as “Presentation of pre-exercise → discussion → post-exercise.”
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Introduction | Install R Commander pre-exercise for the next lesson |
| Class 2 | Presentation and discussion about exercise 1 | pre- and post-exercise |
| Class 3 | Presentation and discussion about exercise 2 | pre- and post-exercise |
| Class 4 | Presentation and discussion about exercise 3 | pre- and post-exercise |
| Class 5 | Presentation and discussion about problem analysis of comprehensive exercise | pre- and post-exercise |
| Class 6 | Mid-term presentation and discussion about comprehensive analysis exercise | pre- and post-exercise |
| Class 7 | Final presentation and discussion about comprehensive analysis exercise | Final report |
Textbook(s)
Matsuda, T. and Hagiuda, N. (Eds.) (2021) Introduction to data science for problem-solving, Jikkyo Syuppan.
Reference books, course materials, etc.
E-learning materials will be provided if necessary.
Assessment criteria and methods
Achievement levels of pre-and-post exercises for each lesson
Related courses
- LAT.A401 ： Introduction to Psychological and Educational Measurement
- SHS.D463 ： Analyses and Modeling Techniques of Educational Data
Prerequisites (i.e., required knowledge, skills, courses, etc.)
This course will be held only if "SHS.D463 ： Analyses and Modeling Techniques of Educational Data" is not held. Therefore, students who have not registered to "SHS.D463" take "Introduction to Psychological and Educational Measurement" until end of registration period cannot take this course.
In addition, students who has not taken "LAT.A401：Introduction to Psychological and Educational Measurement" cannot take this course.
Contact information (e-mail and phone) Notice : Please replace from "[at]" to "@"(half-width character).
stat-ask[at]et.hum.titech.ac.jp
Office hours
By appointment.
