qualitiative data analysis: data triangulation
DESCRIPTION
As the second part of the lecture on qualitative data analysis we discussed the need to cross-validate the collected insights. In this presentation I show what are the different approaches to data triangulation and how I applied them in my research work.TRANSCRIPT
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qualitative data analysis: data triangulation
aga szóstek(at)gmail.com
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Any bias inherent in particular data sources, investigator and method would be neutralised when used in conjunction with other data sources, investigators and methods.
(Creswell, 1994: 174)
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Any bias inherent in particular data sources, investigator, and method would be neutralised when used in conjunction with other data sources, investigators and methods.
(Creswell, 1994: 174) It assumes that data from different methods will corroborate one another, where the choice of methods is intended to investigate a single social phenomenon from different vantage points.
(Denzin,1970; Brannen, 2005)
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Data collected from different methods cannot be simply added together to produce a unitary or rounded reality.
(Brannen 2005: 176)
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- corroboration: the same results are derived from both qualitative and quantitative methods
- elaboration: qualitative data analysis explains how the quantitative results can be applied
- complementarity: qualitative and quantitative results differ but when put together they generate coherent insights
- contradiction: qualitative data and quantitative findings conflict
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an example
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supporting communication at work Szostek, Agnieszka Matysiak, et al. "Understanding the implications of social translucence for systems supporting communication at work." Proceedings of the 2008 ACM conference on Computer supported cooperative work. ACM, 2008.
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context
social ways to initiate communication in face-to-face settings
technical ways to initiate communication in mediated settings
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study objective
- what is a successful way to achieve
visibility of one’s communicative state?
- what else is required to make a system
become socially translucent?
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designs
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AvBOX
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StatusME
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Status Viewer
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study setup
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triangulated data collection
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data logging
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Co-Discovery interviews with Repertory Grid Technique
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questionnaire
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results
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participants equally often indicated status using 4,3,2 or 1 slider availability slider alone used only 1% of times all sliders used equally often
availability messages: to indicate availability contextualized availability messages: to indicate unavailability contextual messages: to remain ambiguous
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co-discovery interviews with RGT
- manual setting of availability as a way to control ‘professional image
- AvBOX well depicting unavailability sufficiently ambiguous
- StatusME uninformative or privacy threatening - need for awareness to know by whom and how
often their status was checked - need for accountability to notify that
communication was poorly timed
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2.18* 4.03* Overall
2.81** 5.58** Week 3
1.48 2.75 Week 2
2.26 3.76 Week 1
StatusME (Mean)
AvBox (Mean)
731 logged interactions 485 with AvBox 246 with StatusME
* significant at p < .01 ** significant at p < .005
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questionnaire
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conclusions
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- visibility best achieved through abstract and graphical status indications
- need for mechanisms supporting
awareness and accountability
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different types of triangulation
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- Theoretical Triangulation: looking at the research situation from different theoretical perspectives
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- Theoretical Triangulation: looking at the research situation from different theoretical perspectives
- Methods Triangulation: - one researcher using two or more research techniques
(within and between quantitative-qualitative techniques); - two or more researchers using the same research
technique; - two or more researchers using two or more research
techniques.
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- Theoretical Triangulation: looking at the research situation from different theoretical perspectives
- Methods Triangulation: - one researcher using two or more research techniques
(within and between quantitative-qualitative techniques); - two or more researchers using the same research
technique; - two or more researchers using two or more research
techniques. - Data Triangulation: combining qualitative and quantitative data
within the same method
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how to triangulate?
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- sequential implementation: the researcher collects both quantitative and qualitative data in phases
- concurrent implementation: the researcher collects both quantitative and qualitative data at the same time
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- equal priority: the same weight is given to quantitative and qualitative data
- dominant priority: priority is give to either quantitative and qualitative data
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- integration of quantitative and qualitative data occurs at different stages of the research process: - during data collection - during data analysis - during interpretation - or in combination of places
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- sequential explanatory strategy: using qualitative results to explain and interpret the findings of a primarily quantitative study
- sequential exploratory strategy: using quantitative data to support qualitative findings
- concurrent triangulation strategy: running both abovementioned strategies in parallel to cross-validate or corroborate the obtained results
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- within qualitative methods triangulation: combining different qualitative methods, eg. observations, interviews and creative workshops to validate the results
- quantification of qualitative data: running quantitative analysis of the qualitative data
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dealing with email overload Szóstek, Agnieszka Matysiak. "‘Dealing with My Emails’: Latent user needs in email management." Computers in Human Behavior 27.2 (2011): 723-729.
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- immediate - asynchronous - textual - shared - traceable - efficient
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- no way to distinguish between important and unimportant message
- email indications come either with every message or none
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filers, pilers and spring cleaners
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what creates the feeing of email overload?
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- too many emails in the inbox - too many folders - too many emails that do not require response - using email as task manager - checking email at different times of the day
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what people really need?
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an effective ToDo list
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the study
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Repertory Grid Technique
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- evaluate which quality differentiates two chosen inbox concepts from the third one, e.g.: ‘Managing this (traditional) inbox is effortless as it doesn’t allow but also doesn’t require any action from me.”
- after determining a particular quality define its other polar, e.g.: ‘Managing inboxes allowing for restructuring emails like the two I designed might require quite some effort, so I can end up spending more time arranging my emails rather than answering them.’
- finally assess which of these qualities is a positive quality in the context of inbox design, e.g.: positive - effortless and negative – effortful
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quantification of qualitative data
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qualitative analysis
- qualitative content analysis of the narratives - all paired comparisons open-coded while preserving their
positive or negative affiliation by two independent coders - formulation of two main categories defining two distinct
phases in email management: email organization and email retrieval
- identifying three types of user needs for each category - mapping each statement to a relevant category from the
classification scheme - creation of two mappings for statements pointing at a causal
dependency between two needs
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quantitative analysis
- choosing two indices to compare the relative salience of the identified needs: importance and dominance
- importance measured by the order in which one need was mentioned in relation to all other needs
- dominance computed based on a normalized index ranging from 0 to 1, where a value of 0 identified a need reported first and averaged it for all references related to the same group of needs
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results
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reliable inbox structure
‘It has a structure that remains consistent over time, so I don’t need to learn it over and over again.’
‘The structure should not be complicated and have too many rules, because if I forget them I can have difficulties finding an email that I am looking for.’
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no obligation to classify
‘It doesn’t force me to annotate my messages right away. I wouldn’t know how to classify many emails right after their arrival.’
‘It forces me to classify messages. It might be very difficult to categorize many emails right away as it is difficult to imagine what an email may imply in the future.’
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contextual email information
‘These inboxes allow to visualize thematic priority rather than priority of each individual email, give context to a project or an activity and help me to see if I follow everything per theme.’
‘There is no relationship with my activities visualized. It is difficult to see what was the last information in a discussion or where this information is located. It loses the continuity between emails, so it requires extra effort to find the email I am looking for.’
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sorting flexibility
‘Sorting only according to the arrival date lacks the overview regarding the problems and cases; it takes into account only one attribute of emails (time).’
‘Sorting according to tasks allows to quickly get an overview of different cases, shows more than one view on a specific case; uses two or more attributes of emails at the same time - like subject and time.’
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possibility to annotate information
‘An automatic structure of the inbox implies no effort to organize my emails.’
‘Emails can be arranged, I can change their order and have them grouped in a customized rather than predefined way. The structure is more flexible, I can change it if I want to but I don’t have to do so if I don’t want to.’
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efficient search engine
‘It is easy to remember when an email arrived, which gives a good starting point for email search.’
‘Annotating emails results in higher awareness of their content and therefore it gives better means to memorize and to search old emails.’
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