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Theory and Practice in Qualitative Data Analysis and Interpretation for the Social and Behavioral Sciences

East Baltimore
3rd term
Health Behavior and Society
3 credits
Academic Year:
2022 - 2023
Instruction Method:
Class Times:
  • Tu Th,  1:30 - 2:50pm
Auditors Allowed:
Undergrads Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor:
Jill Owczarzak

410.710 Concepts in Qualitative Research for Social and Behavioral Sciences


Prepares students to articulate and address core theoretical and methodological issues of qualitative inquiry. Develops students’ capacity to engage in critical qualitative research, including understanding the role of power and social position (race, gender, health status) in data collection, analysis, and interpretation. Introduces narrative, content, discourse, and life history analysis, and institutional ethnography. Considers analysis of both textual (e.g., interview transcripts) and visual (e.g., observations, images) data. Prepares students to select an analytic approach that is appropriate for particular research questions. Explores multiple ways in which health-related phenomena can be analyzed and interpreted. Uses a publicly available data set on women and substance use to provide students with hands-on data analysis and interpretation experience. Introduces students to MAXQDA, a qualitative data management and analysis software.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Explain the relationship between qualitative research questions, data collection, analytic method, and interpretative approach
  2. Distinguish different qualitative analytic traditions
  3. Conceptualize the role of the researcher in data analysis and interpretation
  4. Justify a decision regarding use (or not) of a qualitative analysis software package
  5. Develop and apply a coding framework to qualitative data
  6. Evaluate the quality and rigor of published qualitative research
  7. Explain how data collection, transformation, and management processes affect data analysis and interpretation
Methods of Assessment:

This course is evaluated as follows:

  • 21% Participation
  • 15% Written Assignment(s)
  • 44% Assignments
  • 20% Final Paper

Instructor Consent:

Consent required for some students

Consent Note:

Students who did not complete the prerequisite course but can demonstrate qualitative methods training may be permitted to take the course

For consent, contact: