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1
Who’s Afraid of Qualitative Analysis?
Brigitte Scott, Ph.D.Evaluation and Research
SpecialistMilitary Families Learning
Network
7Photo by d_pham - Creative Commons Attribution License https://www.flickr.com/photos/69004005@N02 Created with Haiku Deck
13Photo by Matt. Create. - Creative Commons Attribution-NonCommercial-ShareAlike License https://www.flickr.com/photos/76583692@N00 Created with Haiku Deck
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Basic Text Analysis: Inductive
Use data to discover concepts, themes, or models
Doing Qualitative
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Basic Text Analysis: Inductive
Use data to discover concepts, themes, or models Evaluator as interpreter; highly involved
Doing Qualitative
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Basic Text Analysis: Inductive
Use data to discover concepts, themes, or models Evaluator as interpreter; highly involvedEmergent, “bottom up”
Doing Qualitative
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Basic Text Analysis: Inductive
Use data to discover concepts, themes, or models Evaluator as interpreter; highly involvedEmergent, “bottom up”Qualitative outcome: key themes or categories relevant to evaluation/research questions
Doing Qualitative
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Application: Inductive Analysis
• Focus groups• Text-entry survey questions• Interviews• Documents• Social media
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Step. 1. Collect and organize your raw data
Doing Qualitative
Considerations:• Number of collection points
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Step. 1. Collect and organize your raw data
Doing Qualitative
Considerations:• Number of collection points• Transcription
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Step. 1. Collect and organize your raw data
Doing Qualitative
Considerations:• Number of collection points• Transcription• Audit trail
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Step. 1. Collect and organize your raw data
Doing Qualitative
Considerations:• Number of collection points• Transcription• Audit trail• Research journal
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Step. 1. Collect and organize your raw data
Doing Qualitative
Considerations:• Number of collection points• Transcription• Audit trail• Research journal• Participant key/aliases/anonymity
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Step. 1. Collect and organize your raw data
Doing Qualitative
End results:• Clean, anonymized data files
• Transcription files• Audit trail• Participant key• Research journal (including protocols
for all of the above)
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Basic Text Analysis: Deductive
Data is analyzed according to prior assumptionsEvaluator is “independent” from data
Doing Qualitative
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Basic Text Analysis: Deductive
Data is analyzed according to prior assumptionsEvaluator is “independent” from data A-priori; “top down”
Doing Qualitative
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Basic Text Analysis: Deductive
Data is analyzed according to prior assumptionsEvaluator is “independent” from data A-priori; “top down”Quantitative outcome: metrics relevant to evaluation/research objectives
Doing Qualitative
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Application: Deductive Analysis• Category comparison, comparison over time
• Answers to survey questions across participants
• Answers to interview questions across participants
• Analyzing webinar chat pods• Social media: hashtag use in Twitter,
Facebook/LinkedIn audience engagement
Doing Qualitative
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Basic Deductive Analysis: 5 Steps
1.Develop data categories.2.Clearly define those categories.3.Read through all raw data and apply
categories.4.Count. 5.Narrative and visual analysis.
Doing Qualitative
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Chat Pod Engagement Metrics
Unique chat pod participants
Resources shared by participants
Resources shared by MFLN
Participant questions
Unique participant to participant exchanges
0 5 10 15 20 25
21
0
17
10
5
Doing Qualitative
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The fine print….Only DCO viewers can participate in the chat pod; percentage of chat pod participants based on total number of DCO viewers and total number of unique participants.
Resources shared by participants include shared links, authors, studies, books, etc.; demonstrates high-level engagement because participants are contributing to the co-construction of knowledge during webinar.
Resources shared by MFLN include links, peer-reviewed studies and books, etc., from both MFLN and non-MFLN authors; demonstrates direct CA engagement with participants by further supporting and contextualizing knowledge construction by situating webinar presentation within the larger disciplinary area.
Participant questions are those listed in the chat pod; demonstrates intent to pursue two-way engagement in webinar and therefore high-level engagement.
Unique participant to participant exchanges are those in which chat pod participants respond directly to one another’s comments; demonstrates high-level engagement through realized reactive (two-way) and interactive (dependent) discourse patterns.
Chat pod text related to webinar content is not captured as an engagement measure due to its discursive category as declarative (one-way) communication. (It is noted, however, that declarative text is still understood to indicate webinar engagement, and MFLN encourages and values such participant engagement.)
Chat pod text related to technical issues and/or CEUs is not included in MFLN evaluation.
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ReferencesDavies, C. A. (2008). Reflexive ethnography: A guide to researching selves and others (2nd Ed.). New York and London: Routledge.
Denzin, N. K., and Lincoln, Y. S. (2011). The Sage Handbook of Qualitative Research (4th Ed.). Thousand Oaks, Calif: Sage.
Patton, M. Q. (2014). Qualitative research & evaluation methods (4th Ed.). Thousand Oaks, Calif.: Sage.
Richardson, L., and St. Pierre, E. A. (2005). Writing: A method of inquiry. In Norman K. Denzin and Yvonna S. Lincoln (Eds.), The Sage Handbook of Qualitative Research (3rd ed.) (pp. 959–97). Thousand Oaks, Calif.: Sage.
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Photographs by Haiku Deck: http://www.haikudeck.com. Haiku Deck is licensed by Creative Commons 3.0.