The document outlines a data analysis course led by Nicolas Nova, focusing on user research processes, design implications, and methodologies for analyzing qualitative data collected from fieldwork. It emphasizes the importance of understanding user context, employing various data gathering techniques, and developing coding strategies to identify patterns and themes. Additionally, it provides recommendations for students' projects, including creating personas and summarizing findings in a detailed report.

1. Course #5: data analysis
nicolas nova | liftlab
Head, Geneva | March, 25th 2010

2. Recap - what we are looking for
meaning - interest in how people make sense of
what they are doing
process - interest in how they are doing it (rather
than outcome)
fieldwork - interest in people in their context
descriptive - explore and describe with words,
pictures or videos
inductive - from empirical data to hypotheses,
concepts, categories, exceptions

3. design issue
user research / data gathering
data analysis
implications for design
communication

4. observation / participant observation
design issue (photo, video, notes)
interview (open, in-depth...), contexual
user research / data gathering interview, lead-users/expert interview
survey / census / photo survey
data analysis
implications for design
communication

6. design issue
user research / data gathering
“Thick/rich” descriptions: context,
data analysis process/sequence of actions, ...
Problems or recurring events (to be
implications for design categorized): repetitions, cycles,
clusters, absence, growth...
Lists of ressources employed for the
activity (tools, people, ...)
...

7. How to analyze this big mess?
collected data preparation: interview transcriptions,
observational notes, visual material (photo, video),
diary, documents
aimed at reaching a “higher level” through data
“reduction” (patterns, categories, themes) and
“interpretation”, a “continuous dialogue with
empirical data”
“coding”: form categories by attaching codes to the
corresponding excerpts from the collected data
different coding strategies (one example in the next
slide)

8. How to “code” your data?
1. Data overview: get the sense of the data as a whole (read interview
transcriptions, look at pictures, video...), sort similar data (photo,
quotes), note your first reactions, ideas, questions as they come to mind.
Write separately feelings and intuition
2. Pick up one data item, understand and extract the main points and
topics you see (motivation to do something, opinion, peculiar stories, relevant behavior,
pertinent response to something, use of a tool/feature, surprising reaction, interesting problem
that reveal unmet needs, unexpected failure...)
3. Repeat this for several data items, make a list of all topics. Cluster the
similar topics, put them in a table with 3 columns (major topics, unique
topics, leftovers).
4. Use this list to get back to your data. Abbreviate topic names as codes
and write codes to the appropriate segments of the data (transcript,
photo).
5. Find the most descriptive wording for your topics and turn them into
categories. Draw inter-relationships between categories.

9. Recommendations when coding (H.Becker)
1. Find elements that do not fit, do not ignore inconvenient data items,
focus on data that “upset your thinking”.
2. There is always something happening: “what was happening when
nothing was happening”
3. Theories of “middle range”: “What is useful is the description of
something more general than the particular facts we discovered, but
less general than notions of identity or social interactions”. DO NOT
LOSE THE SPECIFICITY OF WHAT YOU FOUND
4. Do not mistake a specific instance of something for the entire class
of phenomena it belongs to (education, entertainment, ...)

10. How do things evolve over time?
1. Single occurence/repetition?
2. Growth/decrease over time?
3. Periodic cycle (irregular or not)?
4. Sequences: different steps

11. design issue
user research / data gathering
data analysis Persona/user profiles
Design guidelines/recommendations
implications for design Experiences models: storyboard,
intermediary objects scenario/vignettes
Problem lists
Unusual behavior = suggest
directions that can benefit to
others...
Prototypes
Use cases

13. Mood board:
gamer hands

14. Activity sequence
(Lego)

15. Persona examples
(Open Moko)

16. Storyboard (Kars
Alfrink)
http://cli.gs/U0djhg

17. Prototype: design patterns
by Christian Crumlish

18. Prototype:
wireframe

19. Design framework
(T. Jobert & E.
Guerry)

20. Project discussion

21. Menu for next courses
➡ Course’s blog: http://usages.wordpress.com/
➡ Next course will be about “probes”

22. Assignement
➡ Each student will have to read a research paper and present it to
the class:
• 10 minutes, no slides
• Outline: summary + why is it relevant for design + personal opinion
• Gaver, B., Dunne, T., and Pacenti, E. (1999). Design: Cultural probes.
Interactions 6, 1 (Jan. 1999), 21-29. http://portal.acm.org/citation.cfm?
id=291235
➡ Project:
• Analyze the data collected from the field (one page verbal description)
and turn them into an “intermediary object”: specification for a designed
product, 3 personas, a use case of your product (narrative or storyboard).

23. ➡ To be completed for May 27th, 2010
➡ A short report with:
• Executive summary of the project (one page / 20 lines)
• Summary of your design question (10 lines) + motivation to deal with this
problem (10 lines)
• Table (one page) that describes the research question in detail: What do I
need to know? Why do I need to know this? What kind of data will answer
the question? Where can I find the data? Whom do I contact to access these
data?
• Methodology description (one page): describe what you did (interview,
pictures, number of people observed, etc.)
• Result analysis (6-10 pages): describe the main results of your field study
(the most important situation you observed, patterns and problems you
noticed, exceptions you remarked) with excerpts of interviews, pictures
(photo you took) and element from your personal observation.
• Design implications (3-4 pages): specification for a designed product, 3
personas, a use case of your product (narrative or storyboard).
• Conclusion (one page): what you learned doing this, how you would
continue such as a project, ideas for design, etc.

24. thanks
nicolas@liftlab.com