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• Qualitative research


  • Seldom has numerical data arising from data collection; instead, qualities of a phenomenon are often generated from this research
• Transferability


  The extent that the findings of a particular qualitative study can be applied to other situations
• Transferability


  • Should be reflected in the large and variant sample size, depending on the research question
• Packing up data gathered from respondents


  Using related literature and studies to ensure that it supports your study claims/findings
• Quantitative data interpretation

  • Includes studying the results from various questions in a survey; Results are usually displayed numerically and by percentage in the data tables
• Quantitative data interpretation


  The process of analyzing results from surveys, where information is often compiled into data tables for easy reference
• Causal-comparative research


  A methodology used to identify cause-effect relationships between independent and dependent variables; Researchers can study cause and effect in retrospect
• Causal-comparative research


  • Can help determine the consequences or causes of differences already existing among or between different groups of people
• Inferential statistics for causal-comparative research


  • Chi-square test, paired-samples and independent t tests, and analysis of variance (ANOVA) or ANCOVA
• Correlational research


  A research design that investigates relationships between variables without the researcher controlling or manipulating any of them
• Correlation


  • Reflects the strength and/or direction of the relationship between two (or more) variables; The direction of a correlation can be either positive or negative
• Inferential statistics for correlational research

  • Pearson's, Spearman's (rho) and Kendall's (tau) correlation coefficients
• Descriptive research


  Aims to accurately and systematically describe a population, situation or phenomenon; Can answer what, where, when and how questions, but not why questions
• Descriptive research


  • Can use a wide variety of research methods to investigate one or more variables
• Descriptive statistics


  • Numerical (e.g. central tendency measures such as mean, mode, median or measures of variability) and graphical tools (e.g. histogram, box plot, scatter plot)
• The final analysis involves selection of vivid, compelling extract examples, the final analysis of selected extracts, relating the analysis to their research question and literature, producing a scholarly report of the analysis
• Writing up the report


  The qualitative researcher presents the findings and interpretation of the data
• Several vital statements/features representing the data were extracted to showcase the resulting outcomes both as statements in the form of ideas and feelings, and visual representations are drawn using interconnections between codes
• Naming themes


  Involves utilizing the labels created for the theme and providing a comprehensive name that describes the relationship or meaning conveyed in the theme
• Defining themes


  The qualitative researcher defines the theme according to the content and meaning of the codes; This definition summarizes the content of what is discussed within the theme
• Reviewing themes


  Checking if the themes work in relation to the coded extracts at the first level and then the entire data set at the second level, generating a thematic map of the analysis
• Initial review of themes

  The qualitative researcher takes the themes and begins to review them against the data to make sure the themes capture the meaningful aspects of the data without missing any important details
• Using MAXQDA Analytics


  The complete interview data were re-read to validate the codes; In-built tools in MAXQDA were used to see patterns within the data, and these were used to draw thematic maps
• From codes to themes


  Collating codes into potential themes, gathering all data relevant to each potential theme
• Listing possible themes


  Clustering codes together that have similar meanings or have a relationship to one another, and labeling the clusters based on the meaning or relationships shared among the codes
• Examining the formed themes


  Examining the clusters to see if there are any additional relationships between clusters themselves, and clustering the two or more clusters together and providing another preliminary label with the relationship
• There are two ways to code data: manually or using MAXQDA software
• Initial coding of data

  Acquiring and sorting ideas, labeling the isolated ideas
• Familiarization with data


  Transcribing the data, reading and re-reading the data, noting down the initial ideas
• Typical steps of all qualitative research methods: data collection (interview), transcription (field text), coding, clustering/categorizing, formation of themes
• Braun & Clarke's Thematic Analysis (2006)


  A method of analyzing qualitative data, usually applied to a set of texts such as interview or transcripts
• Purpose of this step

  To get the qualitative researcher engaged with the data and begin thinking about prevalent topics discussed by participants
• Qualitative researchers can


  1. Note prevalent topics on a sheet of paper as they read or transcribe the data

  2. These notes can help when moving into the second phase of Thematic Analysis
• Braun & Clarke's Thematic Analysis (2006) is a method of analyzing qualitative data
• Braun & Clarke Thematic Analysis (2006)


  • It is usually applied to a set of texts, such as an interview or transcripts
  • The researcher closely examines the data to identify common themes - topics, ideas and patterns of meaning that come up repeatedly
• Steps of Braun & Clarke Thematic Analysis (2006)


  1. Familiarization

  2. Coding of Data

  3. Generate Initial Themes

  4. Reviewing Themes

  5. Naming and Defining Themes

  6. Writing up Report
• Van Kaam's Method (1966) allows qualitative researchers to deeply explore the participants' lived experiences in order to understand the essence of the phenomenon through the voices of those who lived it
• Steps of Van Kaam's Method (1966)

  1. Horizonalization: Listing and grouping each expression related to the experience

  2. Reducing and Eliminating: Reduce the data and eliminate any expressions that are not essential elements

  3. Clustering of Horizons in to Themes: Organizing the invariant constituents into themes

  4. Constructing Textural Descriptions

  5. Develop a Structural Description: Textural descriptions and imaginative variation used to create Structural Description

  6. Synthesis of Meanings and Essences: Composite Structural Description
• Giorgi's method of analysis aims to uncover the meaning of a phenomenon as experienced by a human through the identification of essential themes
• Steps of Giorgi's Method (1986)

  1. Collecting and describing phenomenological data

  2. Reading whole descriptions

  3. Breaking descriptions into meaning units

  4. Transforming meaning units

  5. Identifying the essential structure of the phenomenon

  6. Integrating features into essential structure of the phenomenon