Qualitative Research Methods

Numbering Code G-ECON31 5A420 LE82
G-ECON31 5A420 LE31
G-ECON31 5A420 LE43
Year/Term 2021 ・ Second semester
Number of Credits 2 Course Type Lecture
Target Year Target Student
Language English Day/Period Thu.2
Instructor name Hart Nadav FEUER (Graduate School of Agriculture Program-Specific Senior Lecturer)
Outline and Purpose of the Course Students joining this course will encounter a range of qualitative research methods and learn how young researchers with primary background in one social science (economics, sociology or other humanities) can potentially integrate other social science methods into their data gathering and/or analysis.

The First Module of this course is especially designed for the early graduate students and those who have yet to conduct their primary research, as it provides guidance about the design, proposal and implementation of qualitative data gathering methods. However, it is also useful reflection for more advanced students. The Second Module of the course focuses on efficient data management, transformation, and preparation for analysis. The Third Module is designed for students at all graduate levels, but can be especially timely for 2nd year (and later) students who are beginning their data analysis. It presents a range of Qualitative Content Analysis approaches and how to use mixed data (qualitative, quantitative, multi-media, etc.). All Modules include live examples and interactive elements to provide a basic introduction to key topics.
Course Goals To help students to choose from the range of qualitative data collection and analytical methods to find those best suited for the research they conducting, and how to implement them given time and financial constraints.
Schedule and Contents Module 1: Research Methods for Data Collection
1. Introduction: Your Progress/Experience & Asking the Tough Question
2. Meet-n-Greet with Life History & What is a Case Study, really?
3. Open-ended methods for gaining new perspective - Ethnography & Observation
4. Semi-structured tools to stay rigorous - Semi-structured Interviews
5. Semi-structured tools for making comparisons - Focus groups & Natural Experiments

Module 2: Date management, transformation and preparation
6. Using unconventional data sources
7. Field notes, data preparation
8. Converting data: field notes digitization, audio transcription, other conversion

Module 3: Analytical Methods
9. Matching research questions and methods
10. Analyzing in-depth data: Qual/Quant Transformations and Coding
11. Practical Day: Analyzing mixed data types
12. Mixed Data: Integrating pre-existing qualitative data
13. Analyzing in-depth data: Qualitative Content Analysis (January 7)
14. Practical Day: Content Analysis
Evaluation Methods and Policy Grading will be carried out on a basis of attendance (10%); participation in class/group activities [20%], one methods critique homework [35%], and reflection essay [35%].
Course Requirements English language ability sufficient to interact actively in class and work in groups efficiently.
Study outside of Class (preparation and review) Basic reading / skimming of critical articles prior to each class is required. In addition, some homework doing "lite" analysis for practice will also be expected.
Textbooks Textbooks/References Readings will be made available in PDF through PandA. All readings will be labeled depending on their importance: (a) Required, (b) Suggested, (c) Recommended, and (d) Optional.
References, etc. Other reference literature will be made available on PandA. They will be labeled "Reference", and are useful for students wishing to dig deeper into a specific method.
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