Information Technology and Information Society

Course title

11760330

Course description

Based on our university's founding principle of "nurturing engineers who learn from society and contribute to society," this course explores how information science contributes to society and integrates with social sciences. Students will be expected to understand how computational social science, at the forefront of integrating humanities and sciences, contributes to SDGs, allowing them to visualize the connection between information science and social sciences.
The course introduces the latest research papers in computational social science, explaining their content and encouraging students to consider the social impact of information technology. Students will also explore how generative AI technologies can support their everyday learning.
While the course covers specific data analysis methods and mathematical models, explanations will be based on high school-level science knowledge, making it accessible even for students who are not confident in data or mathematical analysis.
*Note: Some materials (such as slides) may be in English to accurately convey the content of research papers, but the course will be conducted in Japanese.

Purpose of class

1. Understand the focus of computational social science and why social science knowledge is necessary alongside information science to solve social issues through specific research examples.

2. Explore how generative AI can support learning and understand precautions for its use.

3. Understand the methodology and complexity of solving social issues through data analysis via hands-on projects.

4. Understand the necessity of international and interdisciplinary perspectives in achieving SDG goals.

5. Recognize the ethical issues inherent in computational social science research processes.

Goals and objectives

Understand the focus of computational social science.
Explore how generative AI can support learning and understand precautions for its use.
Understand the methodology and complexity of solving social issues through data analysis via hands-on projects.
Understand the necessity of international and interdisciplinary perspectives in achieving SDG goals.
Recognize the ethical issues inherent in computational social science research processes.

Relationship between 'Goals and Objectives' and 'Course Outcomes'

	Peer evaluation from group members	Evaluation from other groups	Instructor evaluation	Attendance	Total.
1.	4%	6%	6%	4%	20%
2.	4%	6%	6%	4%	20%
3.	4%	6%	6%	4%	20%
4.	4%	6%	6%	4%	20%
5.	4%	6%	6%	4%	20%
Total.	20%	30%	30%	20%	-

Evaluation method and criteria

The hands-on group project, which analyzes real data to address social issues, is considered the core of this course.
Final grades will be calculated based on the hands-on project (80 points) + attendance (20 points). The specific evaluation items are as follows. Detailed evaluation criteria will be explained in the first class.

A comprehensive evaluation will be made based on the above, converted to a 100-point scale, with 60 points or more required to pass the course.
Evaluation Item 　　　　　　　Points
------------------------------------------------------------------------------------
Peer evaluation from group members: Contribution 20 points
Evaluation from other groups: Clarity of presentation 　 15 points
Evaluation from other groups: Interesting content 15 points
Instructor evaluation: Clarity of presentation 　 10 points
Instructor evaluation: Appropriateness of methods 10 points
Instructor evaluation: Validity of conclusions 　 10 points
Attendance 　 20 points
-------------------------------------------------------------------------------------
A comprehensive evaluation will be made based on the above, converted to a 100-point scale, with 60 points or more required to pass the course.

Language

Japanese(English accepted)

Class schedule

	Class schedule	HW assignments (Including preparation and review of the class.)	Amount of Time Required
1.	Introduction: "What is Computational Social Science?"	Watch the film "The Oxford Murders."	120minutes
2.	Political Science Focus: From Organization Formation to Polarization	Watch the film "The Great Hack."	150minutes
3.	Sociology Focus: Crime Prediction and Cultural Measurement	Watch the film "Minority Report."	140minutes
4.	Economics Focus: Stock Markets and Job Hunting	Watch the film "The Social Network."	120minutes
5.	Complex Systems Focus: Measuring the Complexity of Human Behavior	Watch the film "The Butterfly Effect."	120minutes
6.	Large Language Models Focus: Intelligence vs. Imitation	Watch the film "Her."	120minutes
7.	Media Studies Focus: Biased Algorithms	Watch the film "Searching."	120minutes
8.	Information Ethics Focus 1: Computational Privacy and the Veil of Ignorance	Play the game "Trolley Problem of Armageddon."	60minutes
9.	Information Ethics Focus 2: AI Values vs. Human Values	Watch the film "Avengers: Age of Ultron."	120minutes
10.	Methodology Focus: Social Geometry and Causal Learning	Read Chapter 1 of "How to Lie with Statistics."	120minutes
11.	Hands-on Project Practice: Select Your Research Topic	Group work	120minutes
12.	Hands-on Project Practice: Data Collection	Group work	120minutes
13.	Hands-on Project Practice: Data Analysis	Group work	120minutes
14.	Hands-on Project Practice: Presentation of Results and Q&A	Group work	120minutes
Total.	-	-	1670minutes