2024 Faculty Courses Liberal arts and basic science courses Teacher education courses
Practices for Psychological and Educational Measurement
- Academic unit or major
- Teacher education courses
- Instructor(s)
- Toshiki Matsuda / Naoko Kuriyama
- Class Format
- Exercise (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Thu
- Class
- -
- Course Code
- LAT.A403
- Number of credits
- 010
- Course offered
- 2024
- Offered quarter
- 2Q
- Syllabus updated
- Mar 14, 2025
- Language
- Japanese
Syllabus
Course overview and goals
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."
Course description and aims
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
- 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/Objectives
Course schedule | Objectives | |
---|---|---|
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 |
Study advice (preparation and review)
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.
Evaluation methods and criteria
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
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.