Academic Year |
2025Year |
School/Graduate School |
Graduate School of Humanities and Social Sciences (Master's Course) Division of Humanities and Social Sciences Social Data Science Program |
Lecture Code |
WMK01400 |
Subject Classification |
Specialized Education |
Subject Name |
多分野データ解析実践演習 I |
Subject Name (Katakana) |
タブンヤデータカイセキジッセンエンシュウ1 |
Subject Name in English |
Practice of Data Analysis for Education and Social Data Science Programs I |
Instructor |
SUZUKI YOSHIHISA,KAJIKAWA HIROAKI,HARADA YUSUKE |
Instructor (Katakana) |
スズキ ヨシヒサ,カジカワ ヒロアキ,ハラダ ユウスケ |
Campus |
Higashi-Senda |
Semester/Term |
1st-Year, Second Semester, 3Term |
Days, Periods, and Classrooms |
(3T) Weds13-14 |
Lesson Style |
Seminar |
Lesson Style (More Details) |
Face-to-face, Online (simultaneous interactive) |
Exercise-centered, discussion, student presentations |
Credits |
1.0 |
Class Hours/Week |
2 |
Language of Instruction |
J
:
Japanese |
Course Level |
7
:
Graduate Special Studies
|
Course Area(Area) |
24
:
Social Sciences |
Course Area(Discipline) |
05
:
Sociology |
Eligible Students |
Students of Social Data Science program |
Keywords |
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Special Subject for Teacher Education |
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Special Subject |
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Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students) | |
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Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students) | |
Class Objectives /Class Outline |
The objective of this course is to foster the ability of students from different specialized fields to collaboratively solve problems by analyzing specific data together with experts from other fields. Students from the Social Data Science Program and the Educational Data Science Program will analyze real data and work together to solve problems through presentations and discussions. |
Class Schedule |
lesson1 Guidance lesson2 Task Setting ①: Sharing Tasks lesson3 Task Setting ②: Collecting Materials lesson4 Task Setting ③: Group Discussion lesson5 Task Setting ④: Determining Tasks lesson6 Data Analysis ①: Considering Methods of Analysis lesson7 Data Analysis ②: Conducting Analysis lesson8 Data Analysis ③: Summarizing Analysis lesson9 Data Analysis ④: Preparation for Interim Presentation lesson10 Interim Presentation (Collaborating with the Social Data Science Program) lesson11 Reporting Analysis Results ①: Considering Re-analysis Based on Interim Presentation lesson12 Reporting Analysis Results ②: Conducting Analysis lesson13 Reporting Analysis Results ③: Summarizing Analysis lesson14 Reporting Analysis Results ④: Final Presentation (Collaborating with the Social Data Science Program) lesson15 Summary
Reports will be assigned based on interim and final presentations. |
Text/Reference Books,etc. |
Introduce useful materials for exercises as appropriate. |
PC or AV used in Class,etc. |
Handouts, Microsoft Teams, moodle |
(More Details) |
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Learning techniques to be incorporated |
Discussions, PBL (Problem-based Learning)/ TBL (Team-based Learning), Post-class Report |
Suggestions on Preparation and Review |
Lessons 1-5: Organize your own awareness of issues in society. Lessons 6-10: Consider appropriate methods from the data analysis methods you have learned so far. Lessons 11-15: Based on the discussions from the interim presentation, consider more appropriate directions for analysis. |
Requirements |
"Practice of Data Analysis for Education and Social Data Science Programs I" is a common subject for the Social Data Science Program and the Education Data Science Program. This course (Lecture Code: WMK01400) is aimed at students in Social Data Science Program. Students in Education Data Science Program should take "Practice of Data Analysis for Education and Social Data Science Programs I" for Education Data Science Program (Lecture Code: WNF10050). |
Grading Method |
Evaluation will be based on overall performance in class participation, interim presentation, final presentation, and reports. |
Practical Experience |
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Summary of Practical Experience and Class Contents based on it |
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Message |
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Other |
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Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching. |