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Qualitative Data: Oxymoron, right? Christine Maidl Pribbenow Wisconsin Center for Education Research [email protected]
Qualitative Data:Oxymoron, right?
Christine Maidl PribbenowWisconsin Center for Education
General discussion about educational research, assumptions, and contrasting educational research with research in the sciences
Define common qualitative analysis terms Code text and discuss
Session Outline
Free Association…
DATA
QUALITATIVE
Qualitative data is information which does not present itself in numerical form and is descriptive, appearing mostly in conversational or narrative form.
Words, phrases, text…
Definition
Hard vs. soft (mushy) Rigor Validity and reliability Objective vs. subjective Numbers vs. text What is The Truth?
Qualitative Data: Oxymoron or inherent tensions?
What are some of the assumptions that you have about educational
research?
How are they helping or hindering the development of your study?
“Soft” knowledge Findings based in specific
contexts Difficult to replicate Cannot make causal
claims due to willful human action
Short-term effort of intellectual accumulation– “village huts”
Oriented toward practical application in specific contexts
“Hard” knowledge Produce findings that
are replicable Validated and
accepted as definitive (i.e., what we know)
Knowledge builds upon itself– “skyscrapers of knowledge”
Oriented toward the construction and refinement of theory
Research in the sciences vs. research in education
Lab notebooks Open-ended exam questions Papers Journal entries On-line discussions, blogs Email Twitter/ ‘tweets’ Notes from observations Responses from interviews and focus groups
What are some sources of qualitative data?
Qualitative analysis is the “interplay between researchers and
data.”
Researcher and analysis are “inextricably linked.”
Qualitative Data Analysis
Inductive process◦ Grounded Theory
Unsure of what you’re looking for, what you’ll find No assumptions No literature review at the beginning Constant comparative method
Deductive process◦ Theory driven
Know the categories or themes using rubric, taxonomy Looking for confirming and disconfirming evidence Question and analysis informed by the literature,
“theory”
Qualitative Data Analysis
Why do faculty leave UW-Madison?
Do UW-Madison faculty leave due to climate issues?
Example Research Questions
Coding process: ◦ Conceptualizing, reducing, elaborating and
relating text– i.e., words, phrases, sentences, paragraphs.
Building themes:◦ Codes are categorized thematically to describe or
explain phenomenon.
Definitions: Coding and Themes
Read through the reflection paper written by a student from an Ecology class and highlight words, parts of sentences, and/or whole sentences with some “code” attached and identified to those sections.
Let’s Code #1
What did you highlight?Why?
Read through this reflection paper and code based on this question:
What were the student’s assumptions or misconceptions before taking this course?
Let’s Code #2
What did you highlight?Why?
Read through this reflection paper and code based on this question:
What did the student learn in the course?
Let’s Code #3
What did you highlight?Why?
Can we say that the students learned something in the course using reflection
papers?
Why or why not?
Use mixed methods, multiple sources. Triangulate your data whenever possible. Ask others to review your design
methodology, observations, data, analysis, and interpretations (e.g., inter-rater reliability).
Rely on your study participants to “member check” your findings.
Note limitations of your study whenever possible.
Ensuring “validity” and “reliability” in your research
Questions?
• Designing and Conducting Mixed Methods Research, Creswell, J.W., and Plano Clark, V.L., 2006, Sage Publications.
• Discipline-Based Education Research: A Scientist’s Guide, Slater, S.J., Slater, T.F., and Bailey, J.M., 2010, WH Freeman.
• “Educational Researchers: Living with a Lesser Form of Knowledge,” Labaree, D.L., 1998, Educational Researcher, 27(8), 4-12.
Software• Atlas.ti and Nvivo
References
