The process of analyzing qualitative data has become a critical concern for every modern product design team. There is an abundance of data and user feedback coming from different sources such as user interviews, call-centers, social media posts, usability testing sessions, ethnographic observations, etc.
However, all these data are worthless unless there is a certain way to analyze them and convert them into insights that will make digital products and services better.
We offer a 3-part online course where we will present, discuss, and practice qualitative data analysis techniques. Emphasis will be put on the coding technique i.e. the art of sorting, labeling, analyzing, and even correlating non-numerical data. This is a hands-on online course, and we will work both as individuals and members of small groups by reflecting on real case studies and scenarios.
- The fundamentals of qualitative research methods
- The fundamentals of thematic analysis
- How to code transcripts and build themes in a deductive and inductive setting
- How to present and report qualitative data
- UX Researchers
- UX and Product Designers
- Product Managers
- Product Owners
- Chief Innovation Officers
- Startuppers
1. Inductive Coding - Introduction
- The tradition of qualitative analysis
- Types of qualitative analysis
- Qualitative data
- Qualitative VS Quantitative analysis
- Data collection methods (emphasis on interviews)
- Sampling
2. Inductive Coding (Bottom-up coding)
- What is a code, a category, a theme?
- Defining and describing the coding process
- Inductive Vs Deductive coding
- The pre-coding work
- Performing inductive coding live
3. Practice
- Individual assignment
- Presenting and discussing the coding output (findings) (40’)
+ Homework: Group work on inductive coding
Deductive Coding
1. Presenting homework
2. Deductive coding (top-down coding)
- The importance of prior research (Literature review)
- Performing deductive coding live
3. Practice
- Individual assignment
- Presenting and discussing the coding output (findings)
- Computer-assisted qualitative data analysis software (CAQDA) vs coding with highlighters on hard copies
- Discussion on the extent to which UX professionals code qualitative data and to what depth, challenges, constraints, etc.
- Q and A
Vasileios Kalyvis
Vasilis has been working in the private retail banking industry since 2007. In 2018 he gained a Ph.D. in the field of the sociology of telehealth. He has a strong research interest in computer-mediated communication (CMC) and human-computer interaction theories and patient-physician communication via ICTs. He is a social scientist specializing in qualitative research, aiming to transfer key knowledge and skills from the academic world to the real business world. Since 2019 and after receiving lots of UX research training, he is collaborating with theUXProdigy in several UX research projects.
Dr. Panagiotis Zaharias
Panagiotis started his career as an academic UX researcher pursuing a Ph.D. in the field of Human-Computer Interaction. He worked on several European research projects and after the successful completion of the Ph.D. degree, he started teaching at Universities in Greece and Cyprus. In parallel, he started to provide consulting services on UX Research & Design as a freelancer working with several companies and startups. He is a published author (70+ scientific papers and book chapters) and he has given talks and taught workshops on UX topics at academic & industry conferences around the world. He is also the organizer of the first UX community in Greece, the so-called Athens UX Community. Recently he co-founded "The Scaffolders", an e-learning content design company.
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Copies of slides, training material, and proposed resources
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Certification of attendance