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2020　Analyses and Modeling Techniques of Educational Data

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Academic unit or major
Graduate major in Social and Human Sciences
Instructor(s)
Yamagishi Kimihiko  Kuriyama Naoko 
Class Format
Exercise     
Media-enhanced courses
Day/Period(Room No.)
Tue1-2(W9-706)  Thr1-2(W9-706)  
Group
-
Course number
SHS.D463
Credits
2
Academic year
2020
Offered quarter
2Q
Syllabus updated
2020/9/18
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

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 six on the very first day of instruction.

Student learning outcomes

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. We emphasize active learning method in the classroom.

Keywords

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

Competencies that will be developed

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

Class flow

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/Required learning

  Course schedule Required learning
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 on 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 Construction of causal models (2) Can explain data analyses generated by causal models　through the active learning.
Class 13 (English) 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.
Class 15 (In 2020, the second Quarter consists of fourteen classes.) (In 2020, the second Quarter consists of fourteen classes.)

Out-of-Class Study Time (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.

Assessment criteria and methods

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 (i.e., required knowledge, skills, courses, etc.)

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

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