Spring, 2026

Comparative Research

Professor: JeongHun Han

Schedule: Tuesday 10:00 – 13:00

Class Room: 103 ho, 140 dong

Contact Info: gurus72@snu.ac.kr

<Aims of Course>

This course aims to introduce graduate students of international studies to the foundational methodologies for academic thesis writing. To this end, through Week 4 the course focuses on developing students’ ability to employ thesis writing techniques as well as case studies, comparative studies, statistical research, and experimental research methods. From Week 5 onward, the course shifts its focus to quantitative research methodology. Students will learn what concepts are in social science research, how such concepts can be empirically measured, how to formulate hypotheses using variables, and the various methodologies used to test those hypotheses. Students enrolled in this course are expected to complete the assigned reading materials prior to each class session. Presenters are required to deliver concise summaries of the assigned readings and to lead class discussions centered on those materials. In addition, all students should be able to respond to questions posed by the instructor during class. Whether students have completed the assigned readings, the quality of presentations, and the ability to respond to the instructor’s questions will all be reflected in the final grade. Fifty percent of the final grade for this course consists of an in-class midterm examination and a take-home final paper.

<Evaluation Method>

Participation (10%) + Presentation (20%) + Q&A (20%) + Mid-term Exam (25%) + Final Report (25%)

<Rule of Class Attendance>

Students who are absent for over 1/3 of the class will receive a grade of 'F' or 'U' for the course. (Exceptions can be made when the cause of absence is deemed unavoidable by the course instructor)

<Regulation on AI Use>

Generative AI may be used as a supplementary learning tool in this course. Students may use generative AI to explore ideas or topics needed to complete assignments and to analyze data. However, if generative AI is used to complete an assignment, the name of the tool used, the process of its use, and the generated content must be clearly stated in the assignment.

<Course Schedule>

Week 1 (03 March): Course Introduction & Selection of Presenters

Syllabus

Week 2 (10 March): Writing Thesis, Description & Explanation

– How to Write your MA thesis (Chaarani & Elabiad 2021)

A Case for Description (Holmes et al. 2023)

Mere Description (Gerring 2012)

Taking Explanation Seriously in Political Science (Beland 2015)

Week 3 (17 March): Varieties of Research Methods

Case Selection Techniques in Case Study Research (Seawright & Gerring 2008)

Case Study Method: A Step-by-Step Guide for Business Researchers (Rashid et al. 2019)

Four Varieties of Comparative Analysis (Pickvance 2001)

Varieties of Social Explanation (D. Little 2012, Chapter 8)

The Growth and Development of Experimental Research in Political Science (Druckman et al. 2006)

Week 4 (24 March): Review of Research Examples

Political Recruitment and party structure: A Case study (Selignman 1961)

Entrenchment or Retrenchment (Reisenbichler 2022)

How Large and long-lasting .....? (Gerber et al. 2011)

Week 5 (31 March): Definition and Measurement of Concept

P.H. Pollock (2015) pp.1-24

Week 6 (7 April): Measuring and Describing Variables

P.H. Pollock (2015) pp.25-46

Week 7 (14 April): Proposing Explanations, Framing Hypotheis and Making Comparison

P.H. Pollock (2015) pp. 48-77

Week 8 (21 April): Mid-term Exam (In-Class)

Week 9 (28 April): Reserach Design and Logic of Control

P.H. Pollock (2015) pp. 78-101

Week 10 (5 May): National Holiday – Home Assignment (Data Description)

Week 11 (12 May): Making Controlled Comparison

P.H. Pollock (2015) pp.102-122

Week 12 (19 May): Foundation of Statistical Inference

P.H. Pollock (2015) pp.123-155

Week 13 (26 May): Tests of Significance and Measures of Association

P.H. Pollock (2015) pp.156-182

Week 14 (31 May): Correlation and Linear Regression

P.H. Pollock (2015) pp.183-214

Week 15 (2 June): Take-Home Exam