Qualitative Analysis Flashcards
Grounded Theory
Grounded theory is an inductive research approach that uses qualitative data to develop theories rooted in empirical data, not preconceived notions. In HCI research, it delves into user interactions with technology, their perceptions of interfaces, and their responses to tech changes. It’s valuable for exploring user behaviours, preferences, and experiences in usability testing, interface design, or tech adoption studies. Grounded theory shines when researchers aim to create fresh theories or models that account for the intricacies of user-tech interactions beyond existing frameworks.
Thematic Analysis
Thematic analysis is a widely used qualitative research method for identifying, analysing, and reporting patterns (themes) within qualitative data. It provides a structured and systematic approach to making sense of textual or visual data and is valuable for understanding user experiences and behaviours.
Thematic Analysis Process
Thematic analysis involves the following key steps:
- Data Familiarization: Researchers become familiar with the data by reading and re-reading it to gain a deep understanding of its content.
- Initial Coding: Researchers generate initial codes by highlighting and labeling sections of the data that represent meaningful concepts, ideas, or themes.
- Theme Development: Codes are grouped into potential themes based on commonalities or patterns. Researchers refine and define these themes through further analysis.
- Review and Naming of Themes: Themes are reviewed, and clear and meaningful names or labels are assigned to each theme.
- Reporting: The analysis results in a detailed report that includes descriptions of the themes, illustrative quotes or examples, and an interpretation of their significance in relation to the research question.
Affinity Diagram
An affinity diagram is a qualitative research technique often used in design thinking, user experience (UX) design, and brainstorming sessions. It is a visual method for organising and categorising ideas, observations, or data generated during research or problem-solving sessions.
Affinity Diagram Process
- Data Collection: Researchers or participants gather data, such as ideas, insights, or observations, on sticky notes or cards. This data can come from user interviews, observations, brainstorming sessions, or any other source of qualitative information.
- Grouping and Categorisation: Participants then group these notes or cards into clusters based on common themes, similarities, or relationships. This process is often done collaboratively to capture different perspectives.
- Labeling: After grouping, each cluster is labelled with a descriptive heading or category that summarizes the main theme or idea represented by the cluster.
- Visualisation: The grouped and labelled clusters are arranged spatially on a board or wall, creating a visual representation of the data’s structure and relationships. This visual diagram helps participants and researchers gain insights and identify patterns or opportunities.
Standards for Rigour
Standards for Rigour are guidelines and principles that researchers follow to ensure the credibility, trustworthiness, and validity of their research findings. These standards are particularly important in qualitative research, including fields like Human-Computer Interaction (HCI), where the focus is on understanding complex phenomena, behaviors, and experiences.
Examples:
- Referenced Method
- Saturation
- Emerging: Positionality
Referenced Method
Referenced method refers to the practice of clearly stating and justifying the qualitative research method or approach used in a study. This involves providing a well-defined framework or methodology for collecting, analysing, and interpreting data.
Referencing the method is crucial for several reasons:
- Transparency: It ensures transparency in research, allowing readers to understand the theoretical and methodological foundations of the study.
- Reproducibility: It enables other researchers to replicate or build upon the study’s methods, enhancing the reproducibility of research.
- Validity: It demonstrates that the research approach aligns with the research question and goals, enhancing the validity of the study.
Saturation
Saturation is a concept in qualitative research that signifies the point at which no new information or themes are emerging from the data. It indicates that data collection has reached a point of sufficiency, and further data collection is unlikely to yield significant new insights.
Providing a clear and well-defined criterion for saturation is essential for several reasons:
- Methodological rigor: It contributes to the methodological rigor of the study by preventing excessive or redundant data collection.
- Data quality: It ensures that the data collected are relevant and meaningful to the research question
- Research efficiency: It helps researchers manage resources effectively by knowing when to stop data collection, reducing unnecessary efforts.
Positionality
Positionality refers to the recognition that researchers’ personal backgrounds, experiences, and perspectives can influence the research process and findings.
Acknowledging and addressing positionality is vital for several reasons:
- Bias reduction: It helps researchers recognize and minimize the potential influence of their own biases, beliefs, and subjectivities on data collection, analysis, and interpretation.
- Reflexivity: It promotes reflexivity, encouraging researchers to continuously reflect on how their positionality may impact the study.
- Enhanced objectivity: It enhances the objectivity of the research by making the researcher’s role and potential biases explicit and manageable.
Open Coding
During the initial stages of data analysis, researchers engage in open coding, where they systematically and iteratively categorize and label sections of the data. This process helps identify concepts and patterns emerging from the data without imposing pre-existing theories.
Axial Coding
After open coding, researchers engage in axial coding to explore the relationships between different categories or concepts. This stage involves connecting categories and subcategories to create a more organized and interconnected framework.
Selective Coding
In the final stages, selective coding is performed to refine and integrate the emerging theory. Researchers focus on the central categories or core concepts that explain the phenomena under investigation. This step involves developing a coherent and comprehensive theory that accounts for the data.
Comparative Analysis
Comparative analysis is a qualitative research technique that involves systematically comparing data, themes, or categories to identify similarities, differences, patterns, and relationships within the data.
Comparative analysis plays a critical role in identifying patterns and relationships in the data that may not have been apparent during earlier coding stages. It helps researchers refine and consolidate their codes and categories, contributing to the development of a more coherent and structured understanding of the data.
Comparative Analysis Process
During comparative analysis, researchers examine the codes or categories that have emerged from the open coding and axial coding phases. They look for connections, contrasts, and recurring themes among these codes. This process helps in understanding how different elements in the data relate to one another.
Theory Building
Theory building in qualitative research, including HCI research, involves the development of conceptual frameworks or explanations that account for the observed phenomena or patterns in the data.
The primary purpose of theory building is to generate new insights and explanations based on empirical data. In HCI research, this may involve developing theories or models that describe user behaviors, interactions, or experiences with technology. These theories aim to capture the complexity and richness of the phenomena under investigation and can serve as a foundation for future research, design, or interventions.
