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This short and focussed course enables early-career researchers to use qualitative research methods to explore key questions on the Urban. Delivered by an expert in the subject, this course will include case studies, discussions and activities, that will enable participants to understand the various stages in the qualitative research process, exploring the following high-level questions:
Who this is for
This course will enable participants to:
Divya’s research interests include informal work, social protection, gender and urban health. Drawing from her experience of using a wide range of qualitative methods in research, Divya has been teaching qualitative methods both as a foundation-level course and as an advanced course in the IIHS Urban Fellows Programme. She has also taught qualitative methods as visiting faculty to Master’s and doctoral students at CEPT, and was part of the IIHS faculty team that conducted a methods training workshop for participants at the Atal Bihari Vajpayee Institute of Good Governance and Policy (AIGGPA), Bhopal. Divya is a PhD in Social Work from Washington University, St. Louis, and has a Master’s in Social Work from Tata Institute of Social Sciences.
Programme Structure
Key Differentiators
Programme Details:
For more information, get in touch at upp@iihs.ac.in or on 9611911169
Week 1
Friday, 12 July 2024 | |
2:00 pm – 3:30 pm | Introduction to Qualitative Research |
4:00 pm – 5:30 pm | Ethics, Reflexivity and Positionality in Research |
Saturday, 13 July 2024 | |
9:30 am – 11:00 am | Observation and Writing Field Notes (Part 1) |
11:30 am – 1:00 pm | Observation and Writing Field Notes (Part 2) |
2:00 pm – 3:30 pm | Interviews (Part 1) |
4:00 pm – 5:30 pm | Interviews (Part 2) |
Week 2
Friday, 19 July 2024 | |
2:00 pm – 3:30 pm | Focus Group Discussions and Activities (Part 1) |
4:00 pm – 5:30 pm | Focus Group Discussions and Activities (Part 2) |
Saturday, 20 July 2024 | |
9:30 am – 11:00 am | Data Transcription and Coding (Part 1) |
11:30 am – 1:00 pm | Data Transcription and Coding (Part 2) |
2:00 pm – 3:30 pm | Data Analysis (Part 1) |
4:00 pm – 5:30 pm | Data Analysis (Part 2) |
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