Qualitative Data:Oxymoron, right?

Christine Maidl PribbenowWisconsin Center for Education

Researchcmpribbenow@wisc.edu

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

cmpribbenow@wisc.edu

(608) 263-4256