Course: Qualitative Data Analysis

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Syllabus

Course Description

This course emphasizes the analysis of ethnographic and other forms of qualitative data in public health research. We introduce various interpretive analytic approaches, explore their use, and guide students in applying them to data. We also introduce the use of computer software for coding textual data (Atlas.ti). Students analyze data they have collected as part of fieldwork projects initiated in 410.690 and write up the results in a final paper. Classroom sessions include lectures, discussions, intensive group work related to the fieldwork projects, and instruction in the computer lab.

Course Objectives

By the end of the course, students will be able to:

  1. describe various styles of interpretation of qualitative data
  2. articulate the relative appropriateness of different analysis approaches for a particular qualitative study
  3. apply one or more analytic approaches to data they have collected and write an analysis paper
  4. describe special issues in ethics for qualitative research
  5. manage qualitative data files effectively to ensure ease of use and participant confidentiality
  6. use the basic and intermediate functions of a computer software program for coding of textual data

Readings

There are two books for this class.

  1. Qualitative Inquiry & Research Design: Choosing Among Five Approaches, Second Edition, by John Creswell, Sage Publications 2007
  2. Narrative methods for the Human Sciences, by Catherine Kohler Riessman, Sage Publications 2008

Additional assigned readings are listed on the Readings page.

Course Requirements

Grades for this course are based on the following:

  1. Active participation (10%). Students receive full credit for participation if they attend at least 14 of the 16 class sessions and participate constructively in class activities. Constructive participation is defined as coming to class prepared, listening attentively to our fellow classmates and instructors, contributing to discussions, and not multitasking during class.
  2. Completion of four interim class assignments (20%). Interim class assignments include a data inventory, one transcription, a draft codebook, and a draft paper (see details below). Students will receive full credit for these assignments as long as they turn them in on time.
  3. Presentation of student projects to the class in the form of a 15-minute Power Point presentation (20%). Presentation will be given a letter grade. Specific guidelines for preparing presentations are provided.
  4. Final write-up of data analysis (50%). Grading of the paper will be according to the following criteria:
    • A paper : Well-organized and clearly written analysis that is multifaceted and offers some fresh intellectual insight. Follows all the guidelines.
    • B paper : Organized and mostly clearly written. Will have some gaps in reasoning or writing that is at times not clear. Analysis may be somewhat simplistic or single-stranded. Follows all the guidelines.
    • C paper : Poorly organized with unclear exposition of ideas or concepts. Very simplistic analysis or analysis that is not well developed. Does not follow all of the guidelines.
    • D paper : Last-minute job. Disorganized, sloppy. Does not follow most of the guidelines.

Guidelines for Final Paper

  1. The paper will be an analysis of individual or group data collected during the Ethnographic Fieldwork course. If students have access to other data they would like to use for your analysis, they must get approval from the instructors at the beginning of the course.
  2. The paper should be written individually even if data were gathered as part of a group.
  3. The format of the paper may vary depending on the chosen analysis approach. In many cases, students benefit from following the standard public health publication structure of Introduction-Methods-Results-Discussion. However, if a student's data analysis lends itself to another format, they are encouraged to try. It can be very helpful for student to find a published paper whose structure they admire and then model their paper after that.
  4. Students should attach appendices to their papers. These should include instrument(s) used to collect the data (e.g. in-depth interview guide) and the Atlas.ti code book.