Session 3 Research Methods - Data Analysis - Case Study Example
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Transcript of Session 3 Research Methods - Data Analysis - Case Study Example
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New Media Research Methods
Part 1 – How research methods relate to the research questionPart 2- Qualitative and Quantitative Part 3 – Data collection and analysis – Case Study ExamplePart 4 – Presentation and analysis
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Recap from last week
• Qualitative and Quantitative Research Methods
• Interviews and surveys• Types of questions• Designing questionnaires and interviews • Good practice
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Project team: Nick Weldin, Karen Bunning and
Gosia Kwiatkowska
Case Study – Symbol Surfing Project
Funded by Esmee Fairbairn Trust
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Symbol Surfing Project - Background
• Ubiquity of computer technology and the WWW – access and participation problems
• Accessibility issues – keyboard/mouse
• Match between the interface and the individual capacity of the user
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Symbol Surfing Project - Background
• The role of the user/the role of the supporter
• Interactions: student/supporter; student/computer + supporter/interface/computer
• Teacher initiating role to align the student – operational engagement
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Symbol Surfing Project - Background
• Communication – symbols, signs, pictures e.g. Makaton, Widgits etc
• Use user experience (using symbols) but for different purpose – control the computer
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Symbol Surfing Project - Background
• Benefits – low cost, using existing skills, control, etc
• Exploring the use of freely available symbol recognition software for PMLD community
• Accessing and controlling computers by PMLD
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Research questions
• What are the ways in which individuals are able to use and engage with a simple symbol recognition system to access media on a computer?
• What role is played by the supporter during user activity with this system?
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Symbol Surfing Project - Method
• Design – an action research, ethics, consent• Settings – specialised collage (2), secondary
part of special school (2), residential setting (1). Supporters all knew the participants and understood their communication e.g. gestures, facial expressions etc
• Sample – five people with PMLD, age range 15 – 28, difficult to engage, English – first language,
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Symbol Surfing Project – Data Collection
• Four visits, monthly intervals, • Symbol surfing software was installed
• Two video cameras were used – one to capture the screen and the other to capture the engagement
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Symbol Surfing Project – Data Collection
• Environment – familiar• Researchers role –
marginal participants – guiding the supporter if required
• Field notes were recorded • Length of the sessions –
varied
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Symbol Surfing Project – Data Collection
• The formats : model, withdraw support, observe• Number of cards used – varied• Video footage – combined and displayed side by
side• Sampling of video – 60 sec at 2 min intervals• Data transcribed through repeated viewings
1 3 5 7 9 11 13 1517
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Symbol Surfing Project – Data Collection
• Transcriptions template – actions participant/ supporter/ researcher
• Actions: – vocal, – non vocal communication behaviours, – computer related actions, – contextual information
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Symbol Surfing Project –Data Analysis
• Coding framework – structural linguistics – to capture user attempts at manipulating the symbol tools, but also recording user responses to the activity and the facilitation role performed by the supporter
• Initiating moves, response moves, pre-initiating moves and self expression
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Symbol Surfing Project –Data Analysis
• Refining the coding framework – viewing video and observing behaviours
• Definition for each category with examples
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Coding Framework Used
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• Transcriptions reviewed with the video footage
• Code annotations applied to transcripts
Symbol Surfing Project –Data Analysis
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Symbol Surfing Project –Data Analysis
• Frequency of occurrence for each code per trial was summarised in a prepared excel spreadsheet
• An overall mean scores were calculated – to explore user engagement across trials
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Symbol Surfing Project - Reliability
• Two researchers reviewing each transcripts and assigning the code via a process of consensus, which informed the definition of each code.
• Also independent coding on 10% of data – Cohen’s Kappa Coefficient
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Symbol Surfing Project - Findings
• Individual use of and engagement with symbol recognition system
• Levels of ‘self expression’ • ‘Basic’ and ‘Functional actions’ with symbols
varied – factors: alertness and physical demands of manipulating the symbol, attention
• Role of supporter during user activity- move types: ‘instruction’, ‘query’, ‘technical’, feedback’ – facilitating engagement
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The following slides are for you to look at independently as they cover material covered by Tony and myself
in previous lectures.
For next week please be ready to discuss your research question and
your proposal.
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Emotional Tools - Recap
• Emotional Text Analysis – locating emotion in what users have to say
• Facial Recognition – observing emotional responses to experiences
• EEG – observing brainwaves (relaxed and attentive states)
• GSR – skin conductance
• Blending of the above with eye tracking
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Emotional Analysis of The School Plan
Nice
Pleasant
Fun
Active
Nasty
Unpleasant
Sad
Passive
High Imagery
Low Imagery
Sample 1Total words 27201Sentence Length 18.72Sentences 1453Periods 614Question Marks 466% Nice 2.06% Pleasant 4.38% Fun 7.80% Active 4.43% Nasty 1.74% Unpleasant 1.52% Sad 4.42% Passive 13.87% High Imagery 2.57% Low Imagery 39.27
Emotional text recognition using Whissell’s Dictionary of Affective Language
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Blair’s Speech on War in Iraq
0
5
10
15
20
25
Series1
Nice 2.04
Pleasant 3.53
Fun 3.79
Active 4.02
Nasty 4.3
Unpleasant 4.53
Sad 4.53
Passive 19.62
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Analyzing User Feedback• What is your goal?
– “I’m not sure. I am a little confused at this point as to what I am supposed to be doing, It’s not obvious.”
• What did you expect when you did that?– “I was hoping that if I clicked this icon I would be able to move to the
help page, but I am surprised that didn’t work.” • Can you tell me what you were thinking?
– “I’m not sure. I think I’m supposed to be moving through this section of the maze, but there is no help and I’m getting lost.”
• How did you feel about that process?– “In a word confused. It looked good to begin with, but I am lost and
feel like giving up.”
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Analyzing User Feedback
0
2
4
6
8
10
12
14
Series1
Nice 4.3
Pleasant 2.69
Fun 2.15
Active 3.76
Nasty 1.08
Unpleasant 5.91
Sad 1.61
Passive 11.83
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http://compling.org/emotion_in_text_cgi/DAL_app/index.php
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match tools to your questions• For questions on factual clarification• Use polls and surveys
• For questions on opinion• Use surveys, interviews, focus groups
• For questions on experience• Interviews, focus groups,
observations, user testing, and ethnographies
• For questions on concepts• surveys, interviews,
ethnographies, and user testing
• For questions on emotions• Surveys, interviews, focus groups,
and observations
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CorrelationsInterview, Questionnaire & Focus Group
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References• Bunning, K., Kwiatkowska, G., Weldin, N. (2012) Journal
of Assistive Technology, V24 n4 p259-270• May T (1997) Social research: issues, methods, progress
Buckingham: OUP• Rugg, D. (1941) Experiments in wording question. II
Public Opinion Quarterly, 5:91-92. • Silverman D (1997) Qualitative research: theory, method,
practice London: Sage • Silverman D (2004) Doing Qualitative Research: A
Practical Handbook London: Sage