Syllabus data

Teacher name ： Saddam Khalid
Course Title
Seminar I (A)
Course Title in English
Seminar I (A)
Course Type
-
※
Eligible Students
Graduate School of Social Sciences
Target Grade
All
Course Numbering Code
KCWMS5MCA3
Credits
4.00Credits
The course numbering code represents the faculty managing the subject, the department of the target students, and the education category (liberal arts / specialized course). For detailed information, please download the separate manual from the upper right 'question mark'.
Type of Class
演習 (Seminar)
Eligible Year/Semester
Spring semester 2026,Fall semester 2026
(Spring semester)
Instructor
Saddam Khalid
Affiliation
Graduate School of Social Science 
Language of Instruction
English
Related SDGs
8／9／12
Office Hours and Location
9am to 6pm Monday to Friday research building one room 323 
Contact
Contact using Cross Profile

Corresponding Diploma Policy
A double circle indicates the most relevant DP number and a circle indicates the associated DP.
Corresponding Undergraduate School DP
ー
Corresponding Graduate School DP
1◎／3◎／4◎
Corresponding University-Wide DP
N/a
Academic Goals of Teacher Training Course
Ability to keep polishing／Ability to teach and lean on／Ability to collaborate

Course Objectives and Learning Outcome
【Lecture Objectives】
To be able to think of your own research theme, examine existing research, set your own analytical framework, conduct research, and write a paper.

【Achievement Objectives】
To be able to set a research theme.
To be able to examine existing research critically.
To be able to set your own analytical framework.
To be able to conduct research in the research area you have set.
To be able to describe research results in academic paper format.

Subtitle and Keywords of the Class
Course Overview and Schedule
This course introduces undergraduate students to the fundamentals of academic research in preparation for their graduation thesis. Over fourteen weeks, students will learn how to identify research topics, formulate research questions, review existing literature, understand basic research methodologies, and practice academic writing. The course also provides introductory training in data handling and basic quantitative and qualitative data analysis. Through lectures, exercises, and student presentations, students will develop a research proposal and build the foundational skills required for Research Seminar II and final thesis writing.
In-person/Remote Classification
In-person
Implementation Method and Remote Credit Limit Application
his course introduces undergraduate students to the fundamentals of academic research in preparation for their graduation thesis. Over fourteen weeks, students will learn how to identify research topics, formulate research questions, review existing literature, understand basic research methodologies, and practice academic writing. The course also provides introductory training in data handling and basic quantitative and qualitative data analysis. Through lectures, exercises, and student presentations, students will develop a research proposal and build the foundational skills required for Research Seminar II and final thesis writing.
Uses of Generative AI
Fully permitted
Precautions for using Generative AI
Textbook
Handouts from class
References
Handouts from class
Contents and Estimated Time for Pre- and Post- Learning (Preparation and Review)
Preparation
Research activities 25h
Preparation of materials 5h

Review
Review of manuscript 30h

Contents of Active Learning

  • Week 1: Orientation and introduction to academic research and graduation thesis

  • Week 2: Identifying research interests and selecting research themes

  • Week 3: Formulating research questions and research objectives

  • Week 4: How to search, read, and understand academic literature

  • Week 5: Introduction to literature review and academic writing basics

  • Week 6: Overview of research methodologies (qualitative, quantitative, experimental)

  • Week 7: Research ethics, data types, and research planning

  • Week 8: Introduction to variables, measurement, and data structure

  • Week 9: Basic quantitative data analysis and descriptive statistics

  • Week 10: Basic qualitative data analysis and thematic analysis

  • Week 11: Introduction to data analysis tools and software

  • Week 12: Writing a research proposal and research design

  • Week 13: Student presentations on research proposals and feedback

  • Week 14: Summary, reflection, and preparation

Grading Criteria and Methods
3 interim manuscript submissions 30%
Final presentation 35%
manuscript 35%
How to Disclose Assignments and Exam Results
Assignments will be collected through unipa and weekly feedback will be given 
Precautions and Requirements for Course Registration
Students are required to conduct research independently


Practical Education
Not applicable
Remarks
In cases where any differences arise between the English version and the original Japanese version, the Japanese version shall prevail as the official authoritative version.