| Program / Major | mDP | Goals |
|---|---|---|
| Department of Architecture | 3. | 3．自然科学や人文社会科学に関する知識を援用して、建築にかかわるさまざまな事象を論理的に説明することができる |
| Department of Architecture | 5. | 5．豊富な教養と専門知識を統合、駆使して、種々の制約条件や解決するべき課題を整理・分析し、合理的な方法によって建築をデザインすることができる |
1. Understand the research focus of computational social science and why knowledge from social sciences, not just information
science, is necessary for solving social issues, through concrete research examples.
2. Experience how to use generative AI in learning and understand the precautions for its use.
3. Understand the necessity of international and interdisciplinary perspectives in achieving SDGs goals.
4. Recognize the ethical issues inherent in the research process of computational social science.
2. Experience how to use generative AI in learning and understand the precautions for its use.
3. Understand the necessity of international and interdisciplinary perspectives in achieving SDGs goals.
4. Recognize the ethical issues inherent in the research process of computational social science.
***This course is offered in a ”fully on-demand” format, allowing you to study anytime and anywhere. Therefore, the main content
differs from traditional lecture-style classes. The primary activity involves completing assignments using generative AI tools
prepared by the instructor. If you wish to enroll, please be sure to check the first session guidance posted on ScombZ.***
Based on our university’s founding philosophy of ”nurturing engineers who learn from society and contribute to society,” this course teaches how information science contributes to society and how it integrates with social sciences. In particular, you will understand how computational social science, a cutting-edge field that bridges humanities and sciences, contributes to the SDGs, and experience the connection between information science and social sciences.
The course will cover the latest research papers in the field of computational social science, explaining their content while encouraging students to think about the impact of information technology on society. Additionally, opportunities will be provided to experience how generative AI, which has recently attracted attention, can be useful in daily learning.
Specific data analysis methods and mathematical models will also be introduced during the course, but explanations are based on high school-level science fundamentals, so students who are not confident in data analysis or mathematical analysis can participate with confidence.
Note: Some materials will be provided in English to accurately convey the content of research papers, but assignments and communication with the instructor will be conducted in Japanese.
Based on our university’s founding philosophy of ”nurturing engineers who learn from society and contribute to society,” this course teaches how information science contributes to society and how it integrates with social sciences. In particular, you will understand how computational social science, a cutting-edge field that bridges humanities and sciences, contributes to the SDGs, and experience the connection between information science and social sciences.
The course will cover the latest research papers in the field of computational social science, explaining their content while encouraging students to think about the impact of information technology on society. Additionally, opportunities will be provided to experience how generative AI, which has recently attracted attention, can be useful in daily learning.
Specific data analysis methods and mathematical models will also be introduced during the course, but explanations are based on high school-level science fundamentals, so students who are not confident in data analysis or mathematical analysis can participate with confidence.
Note: Some materials will be provided in English to accurately convey the content of research papers, but assignments and communication with the instructor will be conducted in Japanese.
- Understand the research focus of computational social science.
- Understand how to use generative AI and its precautions.
- Understand the international and interdisciplinary perspectives necessary for achieving SDGs goals.
- Be aware of the ethical issues inherent in conducting computational social science research.
| Instructor evaluation | Feedback Questionnaire (Attendance) | Total. | |
|---|---|---|---|
| 1. | 20% | 5% | 25% |
| 2. | 20% | 5% | 25% |
| 3. | 20% | 5% | 25% |
| 4. | 20% | 5% | 25% |
| Total. | 80% | 20% | - |
This course emphasizes the use of generative AI.
The final grade is calculated based on 12 reading assignments using generative AI (total 80 points) + attendance (20 points). Detailed evaluation criteria will be explained in the first session guidance materials.
Based on the above, a comprehensive evaluation will be conducted, and a score of 60 or above out of 100 points is required to pass.
The final grade is calculated based on 12 reading assignments using generative AI (total 80 points) + attendance (20 points). Detailed evaluation criteria will be explained in the first session guidance materials.
Based on the above, a comprehensive evaluation will be conducted, and a score of 60 or above out of 100 points is required to pass.
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1. | Introduction: Course Guidance | Review distributed materials | 250minutes |
| 2. | Political Science Focus 1 | Reading Assignment | 200minutes |
| 3. | Political Science Focus 2 | Reading Assignment | 200minutes |
| 4. | Sociology Focus 1 | Reading Assignment | 200minutes |
| 5. | Sociology Focus 2 | Reading Assignment | 200minutes |
| 6. | Economics Focus 1 | Reading Assignment | 200minutes |
| 7. | Economics Focus 2 | Reading Assignment | 200minutes |
| 8. | Large Language Models Focus 1 | Reading Assignment | 200minutes |
| 9. | Large Language Models Focus 2 | Reading Assignment | 200minutes |
| 10. | Information Ethics Focus 1 | Reading Assignment | 200minutes |
| 11. | Information Ethics Focus 2 | Reading Assignment | 200minutes |
| 12. | Data Analysis Practice 1 | Data Analysis Assignment | 200minutes |
| 13. | Data Analysis Practice 2 | Data Analysis Assignment | 200minutes |
| 14. | Q＆A Session | NA | 0minutes |
| Total. | - | - | 2650minutes |
| ways of feedback | specific contents about "Other" |
|---|---|
| Feedback outside of the class (ScombZ, mail, etc.) |
Textbook: None, as the course content is based on the latest research papers.
Materials required for assignments will be distributed via ScombZ.
Materials required for assignments will be distributed via ScombZ.
The first session will provide detailed explanations about the course format, content, and grading criteria, so please be
sure to watch it.
- Contact via email to the address specified during class.
- Course that cultivates an ability for utilizing knowledge
- Course that cultivates a basic problem-solving skills
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| N/A | N/A |
- 1.NO POVERTY
- 5.GENDER EQUALITY
- 10.REDUCED INEQUALITIES
- 13.CLIMATE ACTION
Last modified : Mon Mar 16 04:01:56 JST 2026