Qualitative Data Analysis Overview

Qualitative Data Analysis and Quality Criteria

• Qualitative Data: Relates to concepts, opinions, and behaviors; includes interviews, field notes, and visual materials.

• Qualitative Data Analysis (QDA): Involves interpreting and classifying linguistic materials, combining summaries with detailed analysis.

• Goals of Qualitative Research: Discovery and exploration of new ideas; developing empirically grounded theories.

• Coding: A Key process in QDA; requires both fine analysis and classification:

  • Deductive Coding: Starts with existing categories.

  • Inductive Coding: Codes emerge during data collection.

• First Cycle Coding Techniques:

  • Descriptive Coding: Summarizes data with labels.

  • In Vivo Coding: Uses participants' language as codes.

  • Process Coding: Includes action-oriented words.

• Second Cycle Coding: Involves summarizing first cycle codes into categories or themes (Pattern Coding).

• Quality Criteria for Qualitative Research: Trustworthiness includes credibility, transferability, dependability, and confirmability.

  • Triangulation: Using diverse methods to investigate phenomena.

• Group Assignment Report: Should be structured with sections like introduction, literature review, methodology, results, discussion, and conclusion, ensuring proper citation and avoidance of plagiarism.

  • Assessment Criteria: Includes clarity, relevance, and a systematic approach to analysis and findings.