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Qualitative Inquiry - Challenge
To make sense of massive amounts of data, reduce the volume of information, identify significant patterns and construct a framework for communicating the essence of what the data reveal
2. The Procedures
1 Coding/indexing2 Categorisation3 Abstraction4 Comparison5 Dimensionalisation6 Integration7 Iteration8 Refutation (subjecting inferences to scrutiny)9 Interpretation (grasp of meaning - difficult to
describe procedurally)
Constant Comparison
Each time you code data, compare it with other data to which you applied that code
Can also compare with cases/examples from outside your data set (other research…)
Similar to clustering algorithms… Similar to affinity diagrams
(discussed later)
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The Science and Art of Qualitative Inquiry (Patton, 1988) The Science
The scientific part is systematic, analytical, rigorous, disciplined, and
critical in perspective The Art
The artistic part is exploring, playful, metaphorical, insightful, and creative
Critical Thinking ‘Critical Thinking calls for a persistent effort to
examine any belief or supposed form of knowledge in the light of the evidence that supports it and the further conclusions to
which it tends’ (Glaser, 1941) or more simply!
Critical Thinking means weighting up the arguments and evidence for and against.
Critical Thinking• Key points (Glaser, 1941):
– Persistence: Considering an issue carefully and more than once
– Evidence: Evaluating the evidence put forward in support of the belief or viewpoint
– Implications: Considering where the belief or viewpoint leads; what conclusions would follow; are these suitable and rational; and if not, should the belief or viewpoint be reconsidered
Guidance for Creative Thinking
1 Be open2 Generate options3 Divergence before convergence4 Use multiple stimuli - triangulate5 Side track, zig-zag, and circumnavigate6 Change patterns7 Make linkages8 Trust yourself9 Work and play at it
The Credibility of Qualitative Analysis
1 Rigorous techniques and methods for gathering high-quality data that is carefully analysed, with attention to issues of validity, reliability, and triangulation
2 The credibility of the researcher, which is dependent on training, experience, track record, status, and presentation of self
3 Philosophical belief in the phenomenological paradigm, that is, a fundamental appreciation of naturalistic inquiry, qualitative methods, inductive analysis and holistic thinking
A Credible Qualitative StudyThe write-up for a credible qualitative study needs to address the following issues:
1 What techniques and methods were used to ensure the integrity, validity, and accuracy of the findings
2 What does the researcher bring to study in terms of qualifications, experience, and perspective
3 What paradigm orientation and assumptions ground the study
Principles of Analysing Qualitative Data1 Proceed systematically and rigorously
(minimise human error)2 Record process, memos, journals, etc.3 Focus on responding to research questions4 Appropriate level of interpretation
appropriate for situation5 Time (process of inquiry and analysis are
often simultaneous)6 Seek to explain or enlighten7 Evolutionary/emerging
Qualitative Research: Common Features of Analytic Methods (Miles & Huberman,1994)1 Affixing codes to a set of field notes
drawn from data collection2 Noting reflections or other remarks
in margin3 Sorting or shifting through the
materials to identify similar phrases, relationships between themes, distinct differences between subgroups and common sequences
Qualitative Research: Common Features of Analytic Methods (Miles & Huberman,1994)4 Isolating patterns and processes,
commonalties and differences, and taking them out to the field in the next wave of data collection
5 Gradually elaborating a small set of generalisations that cover the consistencies discerned in the data base
6 Confronting those generalisations with a formalised body of knowledge in the from of constructs or theories
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Articulate:•who users are•their key tasks
User and task descriptions
Goals:
Methods:
Products:
Brainstorm designs
Task centered system design
Participatory design
User-centered design
Evaluate
Psychology of everyday things
User involvement
Representation & metaphors
low fidelity prototyping methods
Throw-away paper prototypes
Participatory interaction
Task / Cognitive scenario walk-through
Refined designs
Graphical screen design
Interface guidelines
Style guides
high fidelity prototyping methods
Testable prototypes
Usability testing
Heuristic evaluation
Completed designs
Alpha/beta systems or complete specification
Field testing
Interface Design and Usability Engineering
brainstorming
the point is: to generate MANY, WIDE-RANGING ideasnutty and absurd are GOOD. go for the
extremes (to get out of the rut)
riff off other’s ideas.
the point is NOT: to generate excellent, complete, feasible
ideas … pressure stifles
to develop or critique ideas … go wide. deep is for later.
process
1. prepare a list of topics / questionsahead of time; or in a preliminary brainstorm
2. facilitator takes team through list of topics switch topic when energy ramps down
3. notetaker takes notes (very important)
4. switch roles so everyone can play
5. ground rules
6. followup
ground rules Postpone and withhold your judgment of
ideas: never criticize
Encourage wild and exaggerated ideas
Quantity counts at this stage, not quality
Switch topics when the popcorn slows down
Build on the ideas put forward by others
Every person and every idea has equal worth
Elect a facilitator (calls switches) and a note-taker
Form groups of 8-10assign a facilitator, note taker
Problem: User interface for a car proximity
detection system
Brainstorm 3 aspects of the problem: (e.g., current problems,
physical form factor, activity metaphor, input techniques, etc.)
go: 5 minutes
follow up collect the notes
go through carefully, with judgment turned on
look for interesting, surprising ideas that might work ideas that will combine well promising directions on which you should
brainstorm more
keep your notes. at a later design stage, come back to them and see if anything else has become useful in the meantime.
work consolidation:abstracting specific insights
one tool: the affinity diagram can use to “consolidate” insights from collected or
generated data. for example: brainstorming about design problems
categories of problems
brainstorming about design ideas categories of ideas
comments from users categories of desirable / successful features
Qualitative analysis
Another way to inductively determine appropriate codes
• Field studies• Interviews• Questionnaires• Prototyping• Cognitive walkthroughs• Surveying other literature
• Field studies• Interviews• Questionnaires• Prototyping• Cognitive walkthroughs• Surveying other literature
Methodology (Phase I)
• Field study:• Interviews • Participatory observation
• Field study:• Interviews • Participatory observation
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how do you make an affinity diagram?
1. team writes down all data & insights on post-it notes; be sure you can link the post-it detail back to its source!
2. stick one post-it on the wall a whiteboard or big sheet of butcher paper is best
3. arrange the other post-its around it, grouping by affinity to each other. iteration will be required.
4. look at each group and see what it has in common; name and describe each group.
5. “snapshot” the result for documentation• digital photo your design website or notebook• transfer post-its onto xerox paper, 1 sheet / notes-
cluster scan website
why does an affinity diagram work?
• use physical arrangement/proximity to understand connections
• openness to serendipity
• low cost to rearrange ideas
• many variants:
arrange along axes rather than by affinity
tie causes to effects
group evidence under assertions
affinity diagram exercise
Now take your notes from the earlier brainstorming and create an affinity
diagram
go: 8 minutes