Data Analysis Process

Overview of Sampling in Qualitative Research

  • The importance of sampling in the research process
    • First section of research centers on guidelines for sampling
    • Emphasis on the necessity of justification for the sample size selected
    • Discussion of how to approach quantitative sampling as a framework for qualitative research

Guidelines for Sample Selection

  • Criteria for selecting a sample in qualitative research

    • Identification of key participants who have intentional motivations or professional development goals resulting in their engagement in research
    • Importance of collecting feedback from participants to improve understanding of their motivations and perspectives

  • Sampling Process in Qualitative Research

    • Step 1: Outline the sample selection process in the design of qualitative research
    • Description of the simplest approaches to conducting a study
    • Use of previous studies from the same field as a guide for sample selection

Data Saturation in Qualitative Research

  • Definition of data saturation
    • The point at which no new information is being discovered from the sample
    • Guidelines for determining when to conclude sampling based on data saturation
    • Essential for ensuring the sample is adequate to represent varied perspectives within the qualitative data

Research Question Development

  • The significance of research questions in qualitative studies
    • Research questions guide the direction of the study and ensure relevance of collected data
    • Clarification that questions should elicit comprehensive responses from participants

Data Collection Techniques

  • Overview of data collection strategies
    • Collection of data from a completion sample that corresponds with research goals
    • Explore participant experiences and perspectives through guided interactions

Ethical Considerations in Sampling

  • Consent is required from participants
    • Each participant must sign consent to be involved in the study
    • Reaffirmation of consent for sharing their responses and involvement in the study

Data Analysis Process

  • Steps involved in data analysis

    • Description of a five-step process for thematic analysis
    • Utilization of contextualized data—50 to 100 words per respondent for analysis

  • Identifying Codes from Responses

    • Codes should be categorized based on common themes as part of the analysis
    • Discussion of product, process, and outcome in the development of themes

Presentation of Findings

  • Raw data incorporation in research presentations
    • Clarification that raw data or transcripts are not to be presented verbatim at the end of a project
    • Emphasis on the responsibility of students to develop a storage plan for data

Data Organization Framework

  • Explanation of the mass data structure

    • Flow of interview responses organized into themes
    • Use of drivers of financial disclosures as a case study reference

  • Two Broad Categories Influencing Reporting

    • Organizational Level Drivers: Factors within organizations impacting their reporting decisions
    • External Drivers: Influences from outside the organization affecting financial disclosure

  • Narrative Discussion Accompanying Findings

    • Summary of findings should complement narrative discussions that interpret themes and data outcomes
    • Importance of connecting structured data analysis with thoughtful narrative insights in presenting your research