Qualitative Research and Analysis Principles

Qualitative Research

Focuses on understanding phenomena, not testing hypotheses.

Grounded Theory

Develops theories based on data from specific situations.

Ethnography

Studies cultures through direct observation and participation.

Phenomenology

Explores lived experiences to understand perceptions.

Field Research

Collects data in natural settings to understand context.

Structured Interview

Predefined questions with fixed response options.

Semi-Structured Interview

Combination of predefined and open-ended questions.

Unstructured Interview

Flexible conversation without predefined questions.

Informal Conversational Interview

Casual dialogue to gather insights on topics.

Interview Protocol

Guide outlining questions and structure for interviews.

Standardized Open-Ended Interview

Predefined questions allowing for varied responses.

Closed Interview

Fixed responses limiting participant answers.

Thick Description

Detailed account capturing context and meaning.

Field Notes

Records of observations and reflections during research.

Self Reflective Comments

Insights from both respondents and researchers.

Obtrusive Observation

Researcher actively engages with participants during study.

Unobtrusive Observation

Researcher observes without influencing participant behavior.

Gatekeeper

Individual facilitating access to a research site.

Research Question

Guiding question directing the focus of the study.

Access to Site

Process of gaining permission to conduct research.

Descriptive Notes

Factual details about events and interactions observed.

Reflective Notes

Researcher's thoughts and interpretations during observations.

Mixed Methodology

Combines qualitative and quantitative research approaches.

Strengths of Qualitative Research

Depth of understanding and flexibility in approach.

Weaknesses of Qualitative Research

Subjectivity and limited generalizability of findings.

Data Collection Methods

Techniques used to gather qualitative data.

Field Notes

Records physical descriptions and social interactions observed.

Reflective Notes

Personal reactions and interpretations of observations.

Thick Description

Detailed account balancing context with participant anonymity.

Ethnographer

Researcher studying cultural groups through observation.

Participant Observer

Researcher actively engages while observing a group.

Unobtrusive Observer

Researcher observes without participating in activities.

Observer Role Spectrum

Range from participant to unobtrusive observation.

Data Preparation

Organizing transcripts and field notes for analysis.

Thematic Coding

Identifying and classifying data into themes.

Qualitative Analysis

Iterative process of analyzing non-numerical data.

Data Reduction

Condensing data into manageable themes or codes.

Biography Research

Coding personal stories and life transitions.

Ethnographic Research

Coding cultural norms and group interactions.

Data Cleaning

Initial step to prepare raw data for analysis.

Data Interpretation

Analyzing coded data to extract meaningful insights.

Iterative Process

Repeatedly refining themes through continuous data review.

Observer Introduction

Clarifying researcher's role to participants in study.

Social Norms

Shared expectations guiding behavior within a group.

Coding

Assigning labels to data for thematic analysis.

Chunking

Breaking data into smaller, manageable segments.

Field Note Challenges

Issues faced while recording observations accurately.

Researcher Bias

Influence of researcher's perspective on data interpretation.

Data Representation

Presenting findings using figures, tables, or narratives.

Initial Interpretations

First impressions and thoughts about observed data.

Information Overload

Feeling overwhelmed by excessive data during observation.

Observer Variability

Shifts between participant and unobtrusive observation roles.

Raw Data Management

Preparing and organizing raw data into meaningful units.

Meaningful Units of Analysis

Segments of data that provide insightful information.

Transcript

Written record of spoken audio data.

Data Reduction

Process of simplifying and condensing data.

Immersion

Deep engagement with data through repeated reading.

Memoing

Writing notes in margins for insights and thoughts.

Preliminary Classification Schemes

Initial categories emerging from data analysis.

Chunking

Grouping raw data into smaller, manageable sections.

Winnowing

Identifying usable data from a larger dataset.

Initial Code List

A master list of codes for data categorization.

Clusters

Groupings of data sharing similar meanings or qualities.

Coding Scheme

Systematic method for categorizing data segments.

Usable Data

Data deemed relevant and applicable to research.

Irrelevant Data

Data that does not contribute to research goals.

Qualitative Data

Non-numerical data providing descriptive insights.

Holistic Data Review

Comprehensive examination of data for overall understanding.

Data Analysis

Systematic approach to interpreting and understanding data.

Research Credentials

Qualifications necessary for advancement in academia.

Identity Shift

Change in self-perception due to new roles.

Special Knowledge

Expertise gained through advanced education.

Data Clustering

Grouping similar data points for analysis.

Interview Data

Information gathered through conversations with subjects.

Audio Data

Sound recordings used for analysis and transcription.

Visual Data

Images or graphics analyzed for information.

Data Transcription

Converting spoken words into written format.

Personal Struggles

Challenges faced by individuals in their experiences.

Data Reduction

Process of simplifying data into clusters.

Chunks

Segments of similar data leading to clusters.

Clusters

Groups of similarly labeled data for analysis.

Codes

Labels developed through multiple coding cycles.

Initial Coding

First stage with up to 30 categories.

Mutually Exclusive Codes

Codes that do not overlap in meaning.

A Priori Codes

Codes derived from existing literature or theories.

In Vivo Codes

Codes created from participant quotes or data.

Descriptive Coding

Summarizes data without deeper interpretation.

Interpretative Coding

Moves towards understanding the meaning of data.

Pattern Coding

Explains relationships and patterns in data.

Open Coding

Initial coding without predefined categories.

Axial Coding

Develops relationships between initial codes.

Selective Coding

Focuses on core categories for theory development.

First Cycle Coding

Initial description of data units.

Second Cycle Coding

Infers meaning from described data.

Code Book

A reference guide for coding definitions.

Career Goals (CG)

Code for aspirations related to career advancement.

Career Advancement (CA)

Code for progress in professional roles.

Self-Doubt (SD)

Code representing personal uncertainty in abilities.

Time Management (TM)

Code for challenges in balancing responsibilities.

Student Role (SR)

Code reflecting identity as a learner.