2021 Faculty Courses School of Environment and Society Department of Social and Human Sciences Graduate major in Social and Human Sciences

Analyses and Modeling Techniques of Educational Data

Academic unit or major: Graduate major in Social and Human Sciences
Instructor(s): Kimihiko Yamagishi / Naoko Kuriyama
Class Format: Exercise
Media-enhanced courses: -
Day of week/Period (Classrooms): 1-2 Tue / 1-2 Thu
Class: -
Course Code: SHS.D463
Number of credits: 020
Course offered: 2021
Offered quarter: 2Q
Syllabus updated: Jul 10, 2025
Language: Japanese

Syllabus

Course overview and goals

This course covers standard statistical analysis technology dealing with educational data. We concentrate on the conduct of experimental and survey data collection, and statistical analysis and modeling afterwards. Prerequisites include Practices for Psychological and Educational Measurement A & B. This course makes use of the "active learning" teaching technique, and hence sets a "minimum passenger count" of nine on the very first day of instruction. Registration deadline is at 0:00 am, on June 7th, 2021. The 2021 class meets online via Zoom.

Course description and aims

Keywords

Statistical Modeling, Survey data analysis, collaborative group learning, active learning

Competencies

Specialist skills
Intercultural skills
Communication skills
Critical thinking skills
Practical and/or problem-solving skills

Class flow

This class goes online via Zoom in 2021. Basically we adopt　both conventional lecture-style teaching as well as the "active learning", accompanied by occasional in-class demonstrations using statistical programs.

Course schedule/Objectives

	Course schedule	Objectives
Class 1	Orientation	Mastery of Preparation for PC environment
Class 2	Planning of surveys and experimentation	Can plan research objectives. Each group establishes their goal of research through the active learning.
Class 3	Ethical considerations in empirical research	Grasp and understand necessary ethical considerations. The group discusses applicable ethical issues through the active learning.
Class 4	Survey methods	Each group can explain survey methods and research objectives
Class 5	Observation studies	Master observational data collection
Class 6	Experimental design	Master factorial experimental design. Each group prepare for data collection through the active learning.
Class 7	Student presentations	Carry out data collection
Class 8	Description of data	Can characterize the obtained data through active learning.
Class 9	Analyses of educational data	Select the most applicable method of analysis through the active learning.
Class 10	Basics of the causal modeling	Can explain the basics of the causal model construction　through the active learning.
Class 11	Constriction of causal models (1)	Can explain causal model selection and construction
Class 12	Constriction of causal models (2)	Can explain data analyses generated by causal models　through the active learning.
Class 13	Students' presentation of model construction	Prepare for the in-class presentation　through the active learning.
Class 14	Wrap-up and Q & A	Each active learning group prepares the term paper.

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

In-class handouts

Reference books, course materials, etc.

Will be introduced in class as necessary. The class makes use of publicly available data for analysis practices.

Evaluation methods and criteria

Contributions to the group and the active learning.: 10% Exhibition report: 90%

Related courses

LAT.A403 ： Practices for Psychological and Educational Measurement A
LAT.A404 ： Practices for Psychological and Educational Measurement B

Prerequisites

Desiderata: Concurrent registration to the following:
LAT.A403 ： Practices for Psychological and Educational Measurement A
LAT.A404 ： Practices for Psychological and Educational Measurement B

Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).

yamagishi.k.aa[at]m.titech.ac.jp
kuriyama[at]ila.titech.ac.jp