Here is my coding of the passage about Amanda:
1. Getting pregnant
2. Uncertainty
3. Settling down
4. Lifestyle
5. Uncertainty
6. Lifestyle
7. Uncertainty
8. Uncertainty
The document discusses qualitative coding and memo writing. It provides an overview of coding approaches like descriptive, in vivo, and pattern coding. Codes are short phrases that symbolically represent portions of data. Memos are written reflections on codes, their relationships, and emerging ideas. The document emphasizes that coding and memo writing are iterative, cyclical processes to develop categories and analyze their connections for qualitative research.
Focus groups are qualitative research methods characterized by a moderated discussion among a sample of participants with specific traits to gather in-depth insights on a topic. They are used for exploring issues, guiding survey development, testing products, and interpreting results, but have limitations such as potential bias and lack of statistical generalizability. Successful implementation requires careful planning of objectives, participant recruitment, question scripting, and effective moderation.
The document outlines qualitative research methods in library settings, focusing on coding results to analyze data effectively. It covers various research goals such as assessment, description, and concept-building, along with coding techniques including hand-coding and the use of qualitative analysis software like Atlas.ti. The document emphasizes the importance of ethical data collection and the systematic organization of information to derive meaningful insights.
This document discusses questionnaires as a research method. It defines a questionnaire as a structured set of questions used to collect data from subjects about their knowledge, attitudes and beliefs. The document outlines different types of questions that can be included in a questionnaire like open-ended, closed-format, dichotomous and Likert questions. It also provides guidelines for designing a good questionnaire and discusses methods for questionnaire administration and their advantages/disadvantages.
This document provides an overview of qualitative data analysis (QDA). It discusses that QDA involves breaking down qualitative data collected into codes, categories and themes to develop an understanding. The key steps involve coding segments of text, organizing codes into categories/themes, identifying major and minor themes, and summarizing the data and themes. It also discusses collecting qualitative data through methods like interviews, observations and documents. The goal of QDA is to move from the raw data to an interpretation or explanation.
Thematic analysis is a common form of qualitative analysis that involves identifying and examining patterns (themes) within data related to a research question. The analysis is performed through a six phase coding process: 1) familiarizing with the data, 2) generating initial codes, 3) searching for themes among codes, 4) reviewing themes, 5) defining and naming themes, and 6) producing a final report. Themes differ from codes in that they describe what the data means rather than just labeling it. The coding process is cyclical, with researchers refining codes and themes by going back and forth between the phases until reaching satisfactory final themes.
The document discusses eliminating irrelevant barriers and unintended clues in objective test items that can undermine the validity of an assessment. Factors like complex sentences, difficult vocabulary, and unclear instructions are construct-irrelevant barriers that limit students' responses. Test items should measure the intended learning outcomes and not other irrelevant abilities. Care should be taken to avoid ambiguity, wordiness, biases and other barriers that prevent students from demonstrating their actual achievement levels. Clues within items could allow students without sufficient learning to still answer correctly, preventing the items from functioning as intended.
Questionnaire construction is presented by Prakash Aryal. Questionnaires can be used for primary research and involve asking respondents questions either in person or through mail/online surveys. Key steps in constructing a questionnaire include determining the type of survey, developing questions, organizing the question sequence and layout, and pilot testing. Questions should avoid ambiguity, bias, and double meanings. Both open-ended and closed-ended questions can be used, with closed-ended questions being easier to analyze but potentially limiting responses. The order and format of questions is also important to make the questionnaire smooth, logical and easy for respondents to follow.
Focus Group interview - qualitative research Alvis Loo
The document outlines the purpose and procedure of conducting focus groups to gain insights from a specific target market. It highlights the characteristics of participants, roles and qualifications of a moderator, and the steps for conducting and analyzing focus group discussions. Additionally, it discusses the advantages and disadvantages of focus groups, emphasizing their exploratory nature and potential biases in interpretation.
The document discusses data analysis techniques for quantitative, qualitative, and mixed research. It covers methods for collecting and analyzing both numerical and non-numerical data, emphasizing the use of computer software for analysis and highlighting the importance of validity in qualitative research. Furthermore, it outlines processes such as coding, identifying relationships among categories, and strategies for corroborating results.
This document outlines the process of action research for teachers. Action research involves teachers identifying questions about their classroom experiences, planning interventions to address the questions, observing the results of interventions, analyzing the data collected, and reflecting on the findings to improve teaching practices. It describes defining a research question, planning the research methodology, collecting and analyzing data, and reflecting on results to determine next steps in an iterative cycle for continuous learning and improvement. The goal of action research is to help teachers better understand and enhance student learning.
This chapter discusses selecting and defining a research topic. It covers identifying a topic through various sources like theory, personal experience, and reviewing literature. Topics should be narrowed to a manageable size. Both quantitative and qualitative studies are addressed. Developing hypotheses is also covered, including the difference between quantitative hypotheses aimed at testing theories and qualitative hypotheses generated through inductive research. Key aspects of reviewing literature and properly developing and stating hypotheses are emphasized.
This document discusses operationalizing variables and concepts for research. It begins by defining an operational definition as specifying how a concept can be measured through specific dimensions and elements.
As an example, it operationalizes the concept of achievement motivation through 5 dimensions: driven by work, inability to relax, impatience with ineffectiveness, seeking moderate challenges, and seeking feedback. Each dimension is then further defined by potential elements that could be measured, such as number of working hours, hobbies, and frequency of obtaining feedback.
It notes that an operational definition should specify quantifiable measures and not simply describe correlates of a concept. The document also provides examples of potential dimensions for operationalizing the concept of race discrimination, such as performance
This document discusses questionnaires as a research instrument in survey research. It defines questionnaires and describes their key characteristics, functions, types, and how they are used to measure variables. It also outlines the steps to construct a good questionnaire, including deciding what information is needed, defining the target respondents, choosing an administration method, writing question content and wording, determining length, and pre-testing the questionnaire. Questionnaires are used to collect factual information through a set of predetermined questions and can be fixed-response or open-ended.
The document discusses different types of interviews that can be used for research data collection. It describes personal interviews, telephone interviews, focus group interviews, depth interviews, and projective techniques. Personal interviews involve face-to-face communication between an interviewer and respondent. They are generally structured with questions planned in advance. Telephone interviews collect information by asking respondents questions over the phone. Focus group interviews involve a moderator leading a discussion among a small group of respondents. Depth interviews are nondirective and give respondents freedom to answer openly. Projective techniques indirectly reveal responses through interpretation of ambiguous objects or activities.
This document outlines the key steps in the data preparation process:
1. Check questionnaires for completeness and logical responses
2. Edit data to ensure consistency, correct errors, and fill in missing values
3. Code data by assigning numerical values to question responses
4. Clean data by identifying outliers and inconsistencies to improve data quality
This document provides an overview of qualitative data analysis. It discusses that qualitative data analysis involves coding texts, identifying patterns, and reducing qualitative data into quantitative codes. It also outlines several stages of qualitative analysis including familiarization with data, transcription, organization, coding, identifying themes, recoding, developing categories, exploring relationships between categories, and developing theories. Finally, it discusses challenges of qualitative analysis including placing raw data into logical categories and communicating interpretations to others.
The document discusses the characteristics, functions, types, and construction of questionnaires. It provides details on:
- Questionnaires should be short, simple, objective and avoid embarrassing questions.
- Functions include description and measurement of variables like attitudes and opinions.
- Types include fixed-response and open-ended questionnaires, and mail-administered vs face-to-face.
- Constructing a questionnaire involves deciding what to measure, the type, writing drafts, pretesting, and specifying procedures.
The document discusses various learning styles including visual, auditory, read/write, and kinesthetic, detailing how individuals process information and the teaching methods that work best for each style. It also references Kolb's experiential learning theory and Honey and Mumford's adaptation, highlighting the strengths and weaknesses of different learner types. Criticism of learning styles theories points to their limitations in addressing cultural differences and the complexities of the learning process.
Grounded theory is a qualitative research method that aims to develop theories inductively from data. It begins with data collection and analysis to allow concepts and theories to emerge from the data rather than testing a predetermined hypothesis. Grounded theory was developed in the 1960s by sociologists Glaser and Strauss and has since split into different paradigms including Straussian, Glaserian, and Constructivist approaches. The key aspects of grounded theory include coding data through open, axial, and selective coding to develop categories and concepts into a theoretical framework or model.
The document discusses various methods of data collection used in research, including interviews, observations, questionnaires, and focus group discussions. Each method has its own advantages and disadvantages, affecting factors such as accuracy, cost, and depth of information gathered. The choice of method is influenced by the research question, available resources, and desired outcomes.
Action research is a type of research conducted by teachers and administrators to improve the quality of their decisions and address immediate problems in education. It focuses on applying solutions in a local setting rather than developing theory. Key characteristics include addressing classroom-level practice problems through a scientific process aimed at immediate application and improvement of school practices through individual and group involvement. The objectives of action research are to create democratic values, study and improve the working system of schools, develop teacher skills, raise student performance, and eliminate traditional rigidity. Common areas that action research addresses include teaching methods, audio-visual aids, homework systems, discipline, absenteeism, and administrative problems. The main steps of action research are to identify a problem area, select a specific
The document provides guidance on developing a strong research question. It discusses that a research question should be clear, focused, complex and arguable. It emphasizes starting with a broad topic and conducting preliminary research to identify gaps in existing literature and better define the research question. The document also presents different types of research questions for quantitative, qualitative and mixed-methods studies. Additionally, it provides criteria called "FINER" to evaluate if a research question is feasible, interesting, novel, ethical and relevant. Developing a strong research question is presented as an important first step for guiding effective research.
This document discusses key aspects of research methodology. It begins by defining research as a systematic process of examining a topic closely through various methods such as observation and experimentation. The document then outlines several types of research including pure research, applied research, descriptive research, and correlational research. It also discusses different research methods like library research, field research, and laboratory research. The rest of the document delves into various steps of research methodology such as formulating hypotheses, preparing a research design, identifying variable types, and qualifying a rigorous research. Overall, the document provides a comprehensive overview of conceptualizing and planning a scientific research study.
This document provides an overview of quantitative research and report writing. It discusses the researcher's responsibility to report findings to stakeholders and communicate practical significance. It also describes the main differences between style manuals, particularly the American Psychological Association (APA) style. The main parts of a research report are outlined as the title, abstract, introduction, literature review, methodology, results, conclusion, references, and appendix.
This document outlines the processes of data processing, editing, and coding essential for research methodology. It details the steps involved in data processing, including collection, preparation, input, and interpretation, along with methods like manual, mechanical, and electronic data processing. The document emphasizes the importance of thorough editing and precise coding to ensure data accuracy and facilitate effective analysis.
The Delphi method is a structured communication technique that relies on a panel of experts to answer questionnaires to build consensus around solutions to a problem. It involves collecting responses anonymously from experts in multiple rounds to refine the answers into a group consensus without direct debate. Experts are selected to provide relevant information and respond to questionnaires about a problem, with responses collated and redistributed anonymously between rounds for scoring until a consensus or solutions emerge.
The document discusses in-depth interviews as a method for qualitative data collection in research. It provides definitions of in-depth interviews and notes that they involve one-on-one, unstructured or semi-structured conversations to allow participants to freely discuss their experiences and perspectives on a topic. The summary describes how in-depth interviews can be useful for obtaining detailed first-person accounts and exploring topics in depth, but require skill from interviewers in actively listening, asking probing questions and guiding the discussion.
10 fun projects to improve your coding skillsjan_mindmatters
The document outlines 10 fun projects to improve hacking skills, presented at Railswaycon 2010 in Berlin. The projects cover a range of technical skills like NoSQL databases, Twitter API, HTML5 canvas, JavaScript, websockets, sound processing, desktop applications, electronics, and multi-touch interfaces. Completing the projects would result in earning digital badges. More details on the projects and suggested technologies are provided on the speaker's website.
The document provides a history of computer programming from the 19th century to modern times. It discusses early programming languages and machines like the Analytical Engine, ENIAC, and EDVAC. It then outlines the evolution of programming languages through each decade from the 1950s to the 2000s. The document emphasizes that programming skills require constant learning and adapting to new technologies. Successful programmers of the future will need to integrate different technologies and understand business needs.
Focus Group interview - qualitative research Alvis Loo
The document outlines the purpose and procedure of conducting focus groups to gain insights from a specific target market. It highlights the characteristics of participants, roles and qualifications of a moderator, and the steps for conducting and analyzing focus group discussions. Additionally, it discusses the advantages and disadvantages of focus groups, emphasizing their exploratory nature and potential biases in interpretation.
The document discusses data analysis techniques for quantitative, qualitative, and mixed research. It covers methods for collecting and analyzing both numerical and non-numerical data, emphasizing the use of computer software for analysis and highlighting the importance of validity in qualitative research. Furthermore, it outlines processes such as coding, identifying relationships among categories, and strategies for corroborating results.
This document outlines the process of action research for teachers. Action research involves teachers identifying questions about their classroom experiences, planning interventions to address the questions, observing the results of interventions, analyzing the data collected, and reflecting on the findings to improve teaching practices. It describes defining a research question, planning the research methodology, collecting and analyzing data, and reflecting on results to determine next steps in an iterative cycle for continuous learning and improvement. The goal of action research is to help teachers better understand and enhance student learning.
This chapter discusses selecting and defining a research topic. It covers identifying a topic through various sources like theory, personal experience, and reviewing literature. Topics should be narrowed to a manageable size. Both quantitative and qualitative studies are addressed. Developing hypotheses is also covered, including the difference between quantitative hypotheses aimed at testing theories and qualitative hypotheses generated through inductive research. Key aspects of reviewing literature and properly developing and stating hypotheses are emphasized.
This document discusses operationalizing variables and concepts for research. It begins by defining an operational definition as specifying how a concept can be measured through specific dimensions and elements.
As an example, it operationalizes the concept of achievement motivation through 5 dimensions: driven by work, inability to relax, impatience with ineffectiveness, seeking moderate challenges, and seeking feedback. Each dimension is then further defined by potential elements that could be measured, such as number of working hours, hobbies, and frequency of obtaining feedback.
It notes that an operational definition should specify quantifiable measures and not simply describe correlates of a concept. The document also provides examples of potential dimensions for operationalizing the concept of race discrimination, such as performance
This document discusses questionnaires as a research instrument in survey research. It defines questionnaires and describes their key characteristics, functions, types, and how they are used to measure variables. It also outlines the steps to construct a good questionnaire, including deciding what information is needed, defining the target respondents, choosing an administration method, writing question content and wording, determining length, and pre-testing the questionnaire. Questionnaires are used to collect factual information through a set of predetermined questions and can be fixed-response or open-ended.
The document discusses different types of interviews that can be used for research data collection. It describes personal interviews, telephone interviews, focus group interviews, depth interviews, and projective techniques. Personal interviews involve face-to-face communication between an interviewer and respondent. They are generally structured with questions planned in advance. Telephone interviews collect information by asking respondents questions over the phone. Focus group interviews involve a moderator leading a discussion among a small group of respondents. Depth interviews are nondirective and give respondents freedom to answer openly. Projective techniques indirectly reveal responses through interpretation of ambiguous objects or activities.
This document outlines the key steps in the data preparation process:
1. Check questionnaires for completeness and logical responses
2. Edit data to ensure consistency, correct errors, and fill in missing values
3. Code data by assigning numerical values to question responses
4. Clean data by identifying outliers and inconsistencies to improve data quality
This document provides an overview of qualitative data analysis. It discusses that qualitative data analysis involves coding texts, identifying patterns, and reducing qualitative data into quantitative codes. It also outlines several stages of qualitative analysis including familiarization with data, transcription, organization, coding, identifying themes, recoding, developing categories, exploring relationships between categories, and developing theories. Finally, it discusses challenges of qualitative analysis including placing raw data into logical categories and communicating interpretations to others.
The document discusses the characteristics, functions, types, and construction of questionnaires. It provides details on:
- Questionnaires should be short, simple, objective and avoid embarrassing questions.
- Functions include description and measurement of variables like attitudes and opinions.
- Types include fixed-response and open-ended questionnaires, and mail-administered vs face-to-face.
- Constructing a questionnaire involves deciding what to measure, the type, writing drafts, pretesting, and specifying procedures.
The document discusses various learning styles including visual, auditory, read/write, and kinesthetic, detailing how individuals process information and the teaching methods that work best for each style. It also references Kolb's experiential learning theory and Honey and Mumford's adaptation, highlighting the strengths and weaknesses of different learner types. Criticism of learning styles theories points to their limitations in addressing cultural differences and the complexities of the learning process.
Grounded theory is a qualitative research method that aims to develop theories inductively from data. It begins with data collection and analysis to allow concepts and theories to emerge from the data rather than testing a predetermined hypothesis. Grounded theory was developed in the 1960s by sociologists Glaser and Strauss and has since split into different paradigms including Straussian, Glaserian, and Constructivist approaches. The key aspects of grounded theory include coding data through open, axial, and selective coding to develop categories and concepts into a theoretical framework or model.
The document discusses various methods of data collection used in research, including interviews, observations, questionnaires, and focus group discussions. Each method has its own advantages and disadvantages, affecting factors such as accuracy, cost, and depth of information gathered. The choice of method is influenced by the research question, available resources, and desired outcomes.
Action research is a type of research conducted by teachers and administrators to improve the quality of their decisions and address immediate problems in education. It focuses on applying solutions in a local setting rather than developing theory. Key characteristics include addressing classroom-level practice problems through a scientific process aimed at immediate application and improvement of school practices through individual and group involvement. The objectives of action research are to create democratic values, study and improve the working system of schools, develop teacher skills, raise student performance, and eliminate traditional rigidity. Common areas that action research addresses include teaching methods, audio-visual aids, homework systems, discipline, absenteeism, and administrative problems. The main steps of action research are to identify a problem area, select a specific
The document provides guidance on developing a strong research question. It discusses that a research question should be clear, focused, complex and arguable. It emphasizes starting with a broad topic and conducting preliminary research to identify gaps in existing literature and better define the research question. The document also presents different types of research questions for quantitative, qualitative and mixed-methods studies. Additionally, it provides criteria called "FINER" to evaluate if a research question is feasible, interesting, novel, ethical and relevant. Developing a strong research question is presented as an important first step for guiding effective research.
This document discusses key aspects of research methodology. It begins by defining research as a systematic process of examining a topic closely through various methods such as observation and experimentation. The document then outlines several types of research including pure research, applied research, descriptive research, and correlational research. It also discusses different research methods like library research, field research, and laboratory research. The rest of the document delves into various steps of research methodology such as formulating hypotheses, preparing a research design, identifying variable types, and qualifying a rigorous research. Overall, the document provides a comprehensive overview of conceptualizing and planning a scientific research study.
This document provides an overview of quantitative research and report writing. It discusses the researcher's responsibility to report findings to stakeholders and communicate practical significance. It also describes the main differences between style manuals, particularly the American Psychological Association (APA) style. The main parts of a research report are outlined as the title, abstract, introduction, literature review, methodology, results, conclusion, references, and appendix.
This document outlines the processes of data processing, editing, and coding essential for research methodology. It details the steps involved in data processing, including collection, preparation, input, and interpretation, along with methods like manual, mechanical, and electronic data processing. The document emphasizes the importance of thorough editing and precise coding to ensure data accuracy and facilitate effective analysis.
The Delphi method is a structured communication technique that relies on a panel of experts to answer questionnaires to build consensus around solutions to a problem. It involves collecting responses anonymously from experts in multiple rounds to refine the answers into a group consensus without direct debate. Experts are selected to provide relevant information and respond to questionnaires about a problem, with responses collated and redistributed anonymously between rounds for scoring until a consensus or solutions emerge.
The document discusses in-depth interviews as a method for qualitative data collection in research. It provides definitions of in-depth interviews and notes that they involve one-on-one, unstructured or semi-structured conversations to allow participants to freely discuss their experiences and perspectives on a topic. The summary describes how in-depth interviews can be useful for obtaining detailed first-person accounts and exploring topics in depth, but require skill from interviewers in actively listening, asking probing questions and guiding the discussion.
10 fun projects to improve your coding skillsjan_mindmatters
The document outlines 10 fun projects to improve hacking skills, presented at Railswaycon 2010 in Berlin. The projects cover a range of technical skills like NoSQL databases, Twitter API, HTML5 canvas, JavaScript, websockets, sound processing, desktop applications, electronics, and multi-touch interfaces. Completing the projects would result in earning digital badges. More details on the projects and suggested technologies are provided on the speaker's website.
The document provides a history of computer programming from the 19th century to modern times. It discusses early programming languages and machines like the Analytical Engine, ENIAC, and EDVAC. It then outlines the evolution of programming languages through each decade from the 1950s to the 2000s. The document emphasizes that programming skills require constant learning and adapting to new technologies. Successful programmers of the future will need to integrate different technologies and understand business needs.
The document provides an overview of object-oriented programming (OOP), emphasizing its principles such as encapsulation, inheritance, and polymorphism. It explains the importance of modularizing code and designing systems to mimic real-life structures, enhancing readability and maintainability. The conclusion highlights the flexibility of OOP across various programming languages and the need to adhere to principles for effective system design.
Qualitative Comparative Analysis (QCA) is a methodological approach that integrates qualitative and quantitative research to explore causal relationships in social sciences, accommodating the study of complex causation through set-theoretic methods. It is particularly useful for small to intermediate sample sizes and focuses on identifying different combinations of causal conditions linked to specific outcomes. The process involves constructing truth tables, resolving contradictions among cases, and analyzing causal combinations, ultimately providing solutions that reflect the complexity of real-world social phenomena.
The document discusses programming skills needed for test automation. It outlines skills in areas like programming languages, scripting, test frameworks, databases, performance testing and more. Automated testing requires both testing expertise and strong programming abilities to build test suites that can validate software accurately and repeatedly. Successful test automation depends on having the right tools, process and blending of testing and coding skills on the test automation team.
From first cycle to second cycle qualitative coding: "Seeing a whole"Heather Ford
This document discusses strategies for qualitative coding from first cycle to second cycle coding. It provides an overview of readings on focusing strategies and theory development. The readings discuss tactics for drawing conclusions from data and moving from codes to categories, themes, and concepts. Specific strategies mentioned include clustering, making metaphors, coding and category handling, modeling, writing, typologies, and matrices. The document emphasizes that qualitative analysis is an iterative process that occurs over time through working with the data, rather than a single moment of discovery.
The document provides a comprehensive overview of data analysis methods and best practices for conducting research, emphasizing the importance of planning and framing one's approach to analysis. It highlights the distinction between quantitative and qualitative research, offers tips for managing data, and stresses the critical role of the researcher's assumptions and methodologies. Specific guidance on interview analysis and techniques like thematic analysis is also presented, along with advice on maintaining ethical considerations throughout the research process.
This document discusses empirical studies in planning theory and the differences between quantitative and qualitative research methods. It explains that empirical studies rely on experience and sensory data to generate knowledge. Quantitative methods use statistical analysis and structured data collection to investigate relationships, while qualitative methods use unstructured data and communication to understand human behavior and develop theories. Both methods aim to evaluate and refine planning theories based on evidence from practice.
This document outlines an Object-Oriented Programming course in C++ for second-year software engineering students at Salahaddin University. It highlights prerequisites, course structure, important topics to be covered, and emphasizes the importance of attending lectures and practicing in labs. The course will include theoretical and practical assessments, with a final exam contributing 60% to the overall grade.
Globalisation and its links to the five dimensions of povertyNoel J Harrison
The document discusses the concept of globalization, outlining its evolution through three stages and its impact on developed and developing nations. It emphasizes the multidimensional nature of poverty and the interconnected dimensions of trade, finance, migration, aid, and intellectual property. The potential positive and negative effects of globalization on economies are highlighted, particularly the challenges faced by developing nations and the ongoing disparity in wealth.
20. Object-Oriented Programming Fundamental PrinciplesIntro C# Book
The document outlines the fundamental concepts of object-oriented programming (OOP), including inheritance, encapsulation, abstraction, and polymorphism. It discusses how inheritance allows classes to derive characteristics from parent classes, while encapsulation keeps data hidden and accessible through interfaces. The document emphasizes the importance of strong cohesion and loose coupling to avoid complexities and promote maintainable code.
The document provides an overview of grounded theory, a qualitative research methodology developed by Glaser and Strauss, which focuses on generating theory inductively from data rather than verifying existing theories. It outlines the phases involved in grounded theory research, including data collection, coding, and memoing, and emphasizes the importance of comparative analysis in theory development. Additionally, it discusses various applications of grounded theory, its key concepts, and suggests strategies for researchers to effectively utilize this methodology.
This document provides an overview of grounded theory designs in qualitative analysis. It defines grounded theory as a systematic qualitative method for generating theory from data. Grounded theory was developed in the 1960s by sociologists Glaser and Strauss and involves collecting and analyzing data to build theories through identifying patterns and relationships. The document discusses the key aspects of grounded theory including when to use it, types of designs, conducting research using the approach, and evaluating grounded theory studies. It provides examples and references key sources on grounded theory.
The document outlines 8 steps for qualitative data analysis: 1) transcribe all data, 2) organize the data, 3) code the first set of field notes, 4) note personal reflections, 5) sort and sift through materials to identify patterns, themes, and relationships, 6) identify patterns and processes and test them in further data collection, 7) elaborate a small set of generalizations covering consistencies, 8) examine generalizations in relation to formal theories and constructs.
The document discusses key concepts in object-oriented programming including objects, classes, messages, and requirements for object-oriented languages. An object is a bundle of related variables and methods that can model real-world things. A class defines common variables and methods for objects of a certain kind. Objects communicate by sending messages to each other specifying a method name and parameters. For a language to be object-oriented, it must support encapsulation, inheritance, and dynamic binding.
This document provides a comprehensive overview of qualitative data analysis, discussing its definitions, purposes, methodologies, and comparison with quantitative research. It elaborates on data collection techniques, sampling methods, and various frameworks for analysis, including content, narrative, and grounded theory. Additionally, it emphasizes the importance of contextual understanding and the iterative nature of qualitative research, as well as introduces software tools that facilitate qualitative analysis.
Coding of languages an introduction to seriesmsaifee
Coding in qualitative analysis involves categorizing and labeling data for systematic retrieval and comparison, allowing for the identification of patterns. Codes can be based on various elements such as themes, ideas, and keywords and may evolve as new content is analyzed. Researchers should maintain a list of codes and continually ask questions about the data to interpret and generate narratives from the codes.
Coding in qualitative analysis involves categorizing data by marking similar text strings with code labels, enabling systematic retrieval for future comparison and analysis. Codes can be based on various elements such as actions, themes, and keywords and can evolve over time as new data emerges. The process includes generating and maintaining a list of codes and continually questioning the data to derive meaningful themes and narratives.
Introduction to Coding: Its Application in Qualitative ResearchJericCManalili
The document outlines the coding process in qualitative research, detailing what gets coded, the mechanics of coding, and the importance of maintaining a balance between depth and breadth in analysis. It highlights both manual and computer-assisted qualitative data analysis (CAQDA) methods, emphasizing the need for organization, perseverance, and ethical considerations in coding. Additionally, it discusses solo vs. team coding dynamics and offers practical tips for developing effective codes and categories.
The Science and Art of Qualitative Writing and Analysis UWI 2023ssuserfefc95
This document provides an overview of qualitative coding and analysis. It discusses what coding is, provides examples of how to code interview transcripts, and explains how codes can be clustered into categories and themes. The key steps in coding are breaking down data into small units of meaning and assigning labels or codes to those units. Coding involves both decoding, or determining appropriate codes, and encoding, or labeling the data. Initial coding involves assigning descriptive phrases to chunks of data, which can then be grouped into categories and analyzed at a higher conceptual level to identify themes. The inductive process of moving from codes to categories to themes is discussed.
This document provides an overview of coding qualitative data. It discusses that coding is the process of organizing and sorting data by assigning labels or codes. There are two types of codes - pre-set codes developed before analysis based on the research questions, and emergent codes that arise from the data. The document emphasizes that developing a storyline of the overall purpose and themes is important to guide the coding process and analysis. It also provides an example of how coded data can be organized by cutting and pasting quotes under each code to identify themes within the data.
PR1 Lesson 7 - ANALYZING THE MEANING OF DATA AND DRAWING CONCLUSION.pptxLEONILAMIRANDA2
Module 7 focuses on data analysis in qualitative research, covering methods such as content analysis, coding, and thematic analysis. It emphasizes the importance of categorizing data, developing theories from patterns, and the distinction between everyday conclusions and research conclusions. The module also outlines steps in analyzing data, including open-coding, identifying themes, and organizing findings for presentation.
This document provides an overview of qualitative data analysis techniques including inductive and deductive approaches, coding methods like open coding and axial coding, developing code hierarchies, comparative analysis using tables and models, and ensuring analytic quality through reflexivity. It discusses writing as a tool for analysis, such as keeping a research diary, and the importance of anonymity and validity in qualitative research ethics.
Summary of different approaches collection of coding and data analysis for q...Upwork, LinkedIn
This document discusses various approaches to coding and data analysis in qualitative research. It describes six coding techniques proposed by Saldana, including in vivo coding, process coding, initial coding, focused coding, axial coding, and theoretical coding. It also summarizes five approaches to qualitative data analysis: the constant comparative method of Lincoln and Guma, Huberman and Miles' approach, Morse and Field's approach, Marshall and Rossman's approach, and Tesch's approach. Finally, it briefly discusses Creswell's six-step data analysis process. The document provides examples and explanations of how each of these coding techniques and analytical approaches works in organizing and deriving meaning from qualitative data.
This document provides an overview of key concepts and processes in text analysis, including identifying themes, building codebooks, coding data, describing codes, making comparisons, and building and testing models. Some of the main points covered include defining what a theme is, different approaches to identifying themes (inductive vs. deductive), tips for building codebooks, the open and axial coding process, using code descriptions to help coders, comparing findings to prior literature, and testing conceptual models that are developed.
Coding, Segmenting & Categorizing in Qualitative Data AnalysisDr. Sarita Anand
The document discusses qualitative data analysis, emphasizing the importance of coding and categorizing non-numerical data to identify themes and insights. It outlines various methods of analysis, such as content analysis, narrative analysis, and grounded theory, along with coding processes including open, axial, and selective coding. Best practices for coding and categorizing data are shared, highlighting the significance of establishing coding procedures for accuracy.
This document discusses analyzing both qualitative and quantitative data. It begins by defining data analysis as a complex process involving moving between concrete data and abstract concepts, inductive and deductive reasoning, and description and interpretation. Both qualitative and quantitative analysis are examined. For qualitative data, the document discusses coding, developing descriptions and themes, and analyzing interviews and texts. For quantitative data, it discusses measurement scales, descriptive statistics like measures of central tendency and dispersion, and generating statistics using software. The overall goal of data analysis is to make meaning from the data and answer research questions.
Data analysis – qualitative data presentation 2Azura Zaki
The document discusses qualitative data analysis techniques such as coding, developing themes from qualitative data, and conducting content analysis. It provides examples of coding processes like developing initial codes and focused coding, as well as summarizing data and identifying themes and relationships across data sources. Qualitative data collection techniques mentioned include observation, interviews, and analyzing documents.
How to do qualitative analysis: In theory and practice Heather Ford
This document outlines the process of qualitative analysis, focusing on coding techniques, memo writing, and strategies for moving from data to insights. It highlights various coding types, the importance of organization and flexibility, and emphasizes that analysis is gradual rather than a single revelation. The document also underscores the role of metaphors and the construction of theories in qualitative research.
Discussion Coding Qualitative DataCOLLAPSETop of FormIkhuorLyndonPelletier761
The document discusses the process of coding in qualitative research, highlighting its significance in analyzing and summarizing complex data from various sources such as interviews and observations. It outlines the benefits of coding, including the identification of themes and patterns, and provides methods and strategies for effective coding, while also warning about potential biases and dangers in the coding process. Additionally, it emphasizes the importance of staying true to the data through different coding strategies like inductive and deductive coding.
Coding as a necessary part of the qualitative research method.pptxlrbinala
This document provides an overview of qualitative data coding methods. It discusses what coding is, the purposes of coding, and different approaches to coding including deductive, inductive, and hybrid methods. It describes various types of codes such as in vivo codes that use direct participant quotes, process codes that indicate actions, descriptive codes that summarize data, and structural codes that label structural attributes. The document also outlines the steps for initial coding and line-by-line coding of qualitative data.
This document provides guidance on qualitative data analysis methods, including:
- The process of immersion in qualitative data through repeated reading/listening to become familiar with the content.
- Coding qualitative data by applying abstract representations or labels to segments of data that are relevant to the research question.
- Developing codes that are data-derived (based on the explicit content) or researcher-derived (conceptual interpretations).
- Using analytical memos and diaries to document the analysis process, including emerging codes, themes, and interpretations.
- Identifying themes by examining codes for patterns and relationships that answer the research question. Themes capture broader meanings than codes.
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3. The open coding process typically involves an initial read-through of transcripts followed by multiple coders open coding a sample of transcripts to build an initial codebook, which is then tested and modified on additional transcripts through an iterative process.
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Chapter8.coding
1. Chapter 8: Coding of Qualitative Data
1
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CHAPTER OVERVIEW
Preamble
What is coding?
What to look for when you are
coding
Example #1: Coding
Example #2: Coding
Example #3: Coding
Example #4: Coding
Computer software
Key Terms
Summary
References
CONTENTS
Chapter 1: Introduction to Qualitative Research
Chapter 2: Qualitative Data Collection Method
Chapter 3: Ethnography
Chapter 4: Case Study
Chapter 5: Action Research
Chapter 6: Other Qualitative Methods
Chapter 7: Qualitative Data Analysis
Chapter 8: Coding of Qualitative Data
CHAPTER LEARNING OUTCOMES
When you have completed this chapter you will be able to:
Discuss the techniques of coding qualitative data
Apply data coding techniques when analysing qualitative data
2. Chapter 8: Coding of Qualitative Data
2
Since coding is an important and sometime most difficult phase of qualitative data
analysis, this chapter has been devoted to the coding phase. Several examples are
provided to illustrate how coding is done. However, the coding method shown is not the
only way to go about coding qualitative data as there are several other methods.
Let us repeat what was discussed in Chapter 7 about coding. Coding is the process
of examining the raw qualitative data which will in the form of words, phrases, sentences
or paragraphs) and assigning CODES or labels. Strauss and Corbin (1990) identified the
following types of coding: Axial coding and Open Coding (see Figure 8.1).
Data
[from a Transcript]
OPEN CODING
Code or Label words and phrases found in
the transcript or text
AXIAL CODING
Create Themes or Categories by grouping
codes or labels given to words and phrases
PREAMBLE
WHAT IS CODING?
3. Chapter 8: Coding of Qualitative Data
3
Open Coding – You “sweep” through the data and mark (by circling or
highlighting) sections of the text selected codes or labels. For example,
you circle words or phrases describing the behaviour of the head of
department.
Axial Coding – Eventually, you have a large number of codes and you
will find it necessary to sort them into some sort of order or into groups
and this is called axial coding. Two common types of axial coding are:
Non-hierarchical or Hierarchical
Non-Hierarchical: For example, in a study a the researcher asked a group of adults
how they take a break from their normal work. The responses are grouped are
grouped as follows in a non-hierarchical manner (also called flat coding).
CODES / LABELS
Hierarchical: Here you find that several codes group together as types or kinds of
something. You need to put some of the codes or labels into a group of their own or
make them sub-codes, i.e. a hierarchical arrangement of codes, like a tree, a
branching arrangement of sub-codes. Ideally, codes in a tree relate to their parents by
being 'examples of...', or 'contexts for...' or 'causes of...' or 'settings for...' and so on.
For example, a researcher was doing a study on friendship‟ and asked a group of
adults their views on the topic and the following is the classification.
take a holiday,
go out for a walk,
read a book,
watch TV,
take a nap,
wander round the garden,
work out at the gym,
go for a drink with friends,
go for a drive,
play a computer game,
follow a hobby,
do voluntary work
Adults taking a
break from
work
THEME / CATEGORY
4. Chapter 8: Coding of Qualitative Data
4
THEME / CATEGORY CODES / LABELS
Friendship types
Close friend
Sporting
Club
Non-club
Work
Changes in Friendship
Making new friends
New same sex
friends
New different sex
friends
Losing touch
Becoming sexual relationship
the data into meaningful analytical units (i.e.,
segmenting the data). When you locate meaningful
segments, you code them.
Coding is defined as marking the segments of data
with symbols, descriptive words, or category
names.
To recap, whenever you find a meaningful segment of text in a transcript, you assign a
code or label to signify that particular segment. You continue this process until you have
segmented all of your data and have completed the initial coding. Next, you find
relationships between the codes or labels and group them into themes or categories.
During coding, you must keep a master list (i.e., a list of all the codes that are developed
and used in the research study). Then, the codes are reapplied to new segments of data
each time an appropriate segment is encountered.
Most typically, when coding, you usually have some codes already in mind and
are also looking for other ideas that seem to arise out of the data. According to Charmaz
(2003), you should ask the following questions about the data you are coding:
Sub-codes
Sub-codes
WHAT TO LOOK FOR WHEN YOU ARE CODING
5. Chapter 8: Coding of Qualitative Data
5
What is going on?
What are people doing?
What is the person saying?
What do these actions and statements take for granted?
How do structure and context serve to support, maintain, impede or change these
actions and statements?
Lewins, Taylor. & Gibbs, (2005) provide a more detailed list of the kinds of
things that can be coded (see Table 8.1). The examples of each kind tend to be descriptive
because it makes it is easier to explain the phenomena. However, when you are coding it
is advisable to move from descriptive codes to more analytic ones as quickly as possible.
What can be coded Examples
1 Behaviours, specific acts Seeking reassurance, Bragging
2 Events – short once in a lifetime events or things
people have done that are often told as a story.
Wedding day, day moved out
of home for university, starting
first job
3 Activities – these are of a longer duration, involve
other people within a particular setting
Going clubbing, attending a
night course, conservation
work
4 Strategies, practice or tactics Being nasty to get dumped,
Staying late at work to get
promotion
5 States – general conditions experienced by people
or found in organisations
Hopelessness “I‟ll never meet
anyone better at my age”
settling for someone who is
not really suitable
6 Meanings – A wide range of phenomena at the
core of much qualitative analysis. Meanings and
interpretations are important pars of what directs
participants actions.
The term „chilling out‟ is used
by young people to mean
relaxing and not doing very
much
a. What concepts do participants use to
understand their world? What norms,
values, and rules guide their actions
b. What meaning or significance it has for
participants, how do they construe events,
what are the feelings
Jealousy “ I just felt why did
she get him”
c. What symbols do people use to
understand their situation? What names do
they use for objects, events, persons, roles,
setting and equipment?
A PhD is referred to as „a test
of endurance‟ (because
finishing a PhD is a challenge)
7 Participation – adaptation to a new setting or
involvement
About new neighbours “In my
new house I have to keep my
6. Chapter 8: Coding of Qualitative Data
6
music down at night as the
neighbours have young
children”.
8 Relationships or interaction Seeing family “ Now my sister
lives in the next road she visits
more and we‟ve become much
closer.
9 Conditions or constraints Lose of job (before financial
difficulties), moving away
(before lost contact with old
friends)
10 Consequences Confidence gets dates, positive
attitude attracts opportunities
11 Settings – the entire context of the events under
study
University, work place,
housing estate
12 Reflexive – researcher‟s role in the process, how
intervention generated the data
Probing question “How did
you feel when he said that?”
Table 8.1: Types of phenomena that can be coded
Refer to this EXAMPLE in which a researcher interviewed several staff in an office
and asked this question: “What specific problems that needed immediate action in your
organisation”?
The following are some of the responses to the question. Try to code the data and
compare your themes / categories with the themes / categories provided below:
LEARNING ACTIVITY
a) What is coding?
b) What is the difference between open and axial coding?
c) What do you look for when coding data?
d) Lewins, Taylor. & Gibbs (2005) provide a list of phenomena
that is often coded. What are they? Are there others?
EXAMPLE #1: CODING QUALITATIVE DATA
7. Chapter 8: Coding of Qualitative Data
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Table 8.2 Reponses of subjects in an office
The responses to the question: “What specific problems that needed immediate
action in your organisation”?
There is not enough space for everyone
Our office furniture is dated and needs replacing
We nee a better cleaning service for the office
We need more objective recruitment and hiring standards
We need objective performance appraisal and reward system
We need consistent application of policy
There are leadership problems
Unproductive staff should not be retained
Each department stereotypes of other departments
Decisions are often based on inaccurate information
We need more opportunities for advancement here
Our product is not consistent because there are too many styles
There is too much gossiping and criticising
Responsibilities at various levels are unclear
We need a suggestion box
There is a lot of “us and them” sentiment here.
There is a lack of attention to individual needs.
There is favouritism and preferential treatment of staff.
More training is needed at all levels.
There need to better assessment of employee ability and performance can be
more objectively based.
Training is needed for new employees.
Many employees are carrying the weight of other untrained employees.
This off ice is “turf” oriented.
There is a pecking order at every level and within every level.
Communication needs improving.
Certain departments are put on a pedestal.
There are too many review levels for our products.
Too many signatures are required.
There is a lot of overlap and redundancy.
The components of our office work against one another rather than a team.
We need more computer terminals
8. Chapter 8: Coding of Qualitative Data
8
THE DATA IS CODED INTO THE FOLLOWING CATEGORIES:
CATEGORIES DATA
Management Issues
There are leadership problems
We need a suggestion box
There is a lack of attention to individual needs.
There is favouritism and preferential treatment of staff.
Decisions are often based on inaccurate information
We need consistent application of policy
Physical Environment
We nee a better cleaning service for the office
Our office furniture is dated and needs replacing
We need more computer terminals
There is not enough space for everyone
We need more objective recruitment and hiring
standards
We need objective performance appraisal and reward
systems
Non-productive staff members should not be retained
There need to be better assessment of employee ability
and performance so that promotions can be more
objectively based
Employee Development
More training is needed at all levels
Training is needed for new employees
Many employees are carrying the weight of other
untrained employees
We need more opportunities for advancement here
Intergroup and Interpersonal Relations
The office is “turf” oriented
There is a lot of “us and them” sentiment here
9. Chapter 8: Coding of Qualitative Data
9
There is pecking order at every level and within every
level
Communication needs improving
There is too much gossiping and criticising
Certain departments are put on a pedestal
Each department has stereotypes of the other
departments
Work Structure
There are too many reviews for our product
Too many signatures are required
Responsibilities at various levels are unclear
The components of our office work against one another
rather than as a team
There is a lot of overlap and redundancy
Our product is not consistent because there are too
many styles
LEARNING ACTIVITY
Try coding this short passage about Terry in Example #2.
10. Chapter 8: Coding of Qualitative Data
10
The example below show the coding of a short passage of text about a Terry moving
out of his parents home and becoming independent.
Terry
“When you move into your own home, you're alone. There is no bustle of people
around the house. I miss having someone to chat to when I get home. I put the TV
or some music so there’s some background noise, the silence makes me feel so alone.
Sometimes I will be sat watching trash TV and thinking I should be out doing
something rather than watching this rubbish. I read a lot but sometimes I am too
tired and just want to veg out. But it's been good to move out of mum and dad’s as
it's not healthy to rely on them as they won't last forever. I become independent
and made my own decisions. It's good they still there when I need them. It's good to
have some distance as when I was at home I was arguing a lot with my dad and that
was what made me decide it was time to go.”
EXAMPLE #2: CODING QUALITATIVE DATA
11. Chapter 8: Coding of Qualitative Data
11
In Example #2, to help the analyst mark up the page, the text has been printed using
double spacing, so that it is possible to write code ideas and code labels between the
lines.
DESCRIPTIVE CODING AND NOTES.
12. Chapter 8: Coding of Qualitative Data
12
The analyst has read the text carefully and circled what seem to be key terms or key
events or actions. A short note of what these are has been written besides the circling.
These are the start of descriptive, or what grounded theorists refer to as open coding. An
initial coding list from this might be:
Own home
Lonely
Independence
Moving out of parents
Conflict
Dependence
Desire for company
These terms summarise the events and actions noted by the coding in Example #2, and
some are more analytical, i.e. not merely describing something that happened or was said.
They could form the start of a coding list that could be used to mark-up the rest of this
transcript and other similar cases.
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DESCRIPTIVE AND ANALYTIC CODING WITH NOTES.
Using the sample data, a wide margin is used, so that code labels and other
comments can be written there. Print out your transcriptions in whatever way supports
your preferred approach to coding the text.
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The codes used are still essentially descriptive but begin to move away from
simply summarising what the respondent has said. Using brackets to the right of the
transcribed text, they also code much larger chunks or passages of text. This form of
coding is most useful when you go on to make retrievals, i.e. gather together all the text
about one topic – that is to say, all the text that is coded the same way. With larger
chunks, the retrieved text is less likely to be decontextualised. The analyst has also used a
highlighter to identify words that refer to feelings and these words suggest that the
passage about living alone is actually about the emotions and feelings associated with
living alone.
Read the passage of text below about Amanda finding out she was pregnant. Look
at the list of codes below and decide which code sums up what is being talked about
in each line of the text (you may use a code more than once).
List of codes
1. Breaking up
2. Getting pregnant
3. Insecurity
4. Lifestyle
5. Moving in together
6. Not wanting to move
7. Proposal
8. Settling down
9. Uncertainty
LEARNING ACTIVITY
Try coding this short passage about Amanda.
EXAMPLE #3: CODING QUALITATIVE DATA
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1 2 3 4 5 6 7 8 9
When I found out I was pregnant, I wasn‟t sure if I wanted to
get married and he …
wasn‟t the settling down kind. He was old enough to bring
up a child but I knew he …
wasn‟t ready to. He was in the Navy he liked the life and
preferred going off with …
his friends and that bothered me. At first I hoped something
would happen so I …
didn‟t have the baby and I wanted him to marry me ‟cause he
wanted to not …
because I was pregnant. Anyway when the baby was born we
broke up and I have …
seen him a couple of times but he has phoned lots and says
he will marry me. He …
wanted me to marry him and go and live with him, but I
didn‟t want to leave home.
He leaves the Navy in 6 months so I‟m getting the flat ready
for him to move in. But …
I still worry he‟ll go off with his friends and won‟t be able to
give up the life.
COMPARE your answer with the possible answer below. You may have chosen to
use different codes from the ones we used, this does not mean you are wrong as you may
have a very good reason for selecting that code. Often the same text can be coded in two
or more different ways.
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ANSWER:
CODES
When I found out I was pregnant, I wasn‟t sure if I wanted to get
married and he …
Getting pregnant
wasn‟t the settling down kind. He was old enough to bring up a child
but I knew he …
Settling down
wasn‟t ready to. He was in the Navy he liked the life and preferred
going off with …
Lifestyle
his friends and that bothered me. At first I hoped something would
happen so I …
Uncertainty
didn‟t have the baby and I wanted him to marry me ‟cause he wanted to
not …
Insecurity
because I was pregnant. Anyway when the baby was born we broke up
and I have …
Breaking up
seen him a couple of times but he has phoned lots and says he will
marry me. He …
Proposal
wanted me to marry him and go and live with him, but I didn‟t want to
leave home.
Not wanting to move
He leaves the Navy in 6 months so I‟m getting the flat ready for him to
move in. But …
Moving in together
I still worry he‟ll go off with his friends and won‟t be able to give up
the life.
Insecurity
You may have chosen to use different codes from the ones we used, this does not mean
you are wrong as you may have a very good reason for selecting that code. Often the
same text can be coded in two or more different ways.
LEARNING ACTIVITY
Try coding this short passage about Karen.
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Read the passage of text below about Karen leaving home. Provide a code that
summaries what is happening for each line of text in the boxes.
CODES
It was challenging, after living in Italy for 6 months and then I moved home
before …
I started university. I was used to doing things my own way when it suited me
…
and not having to tell people where I was going. I was living with friends and
they …
didn‟t care what I did or where I went. It was really hard to go back to sort of
…
thinking of others … ‟cause Mum and Dad wanted to know where I was
going and …
who with, which was a nightmare. My parents were strict but I had a lot of …
freedom growing up, as long as I didn‟t overstep the boundaries. After I came
…
back from Italy they realised I was more independent and things changed and
…
they didn‟t try and stop me doing things anymore but they would still let
know if …
they didn‟t approve.
COMPARE your answer with the possible answer below. You may have chosen to
use different codes from the ones we used, this does not mean you are wrong as you may
have a very good reason for selecting that code. Often the same text can be coded in two
or more different ways.
EXAMPLE #4: CODING QUALITATIVE DATA
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ANSWER:
CODES
It was challenging, after living in Italy for 6 months and then I moved home
before …
Moving away
I started university. I was used to doing things my own way when it suited me
…
Independence
and not having to tell people where I was going. I was living with friends and
they …
Freedom
didn‟t care what I did or where I went. It was really hard to go back to sort of
…
Moving back
home
thinking of others … ‟cause Mum and Dad wanted to know where I was
going and …
Control
who with, which was a nightmare. My parents were strict but I had a lot of … Control
freedom growing up, as long as I didn‟t overstep the boundaries. After I came
…
Boundaries
back from Italy they realised I was more independent and things changed and
…
Growing up
they didn‟t try and stop me doing things anymore but they would still let
know if …
Letting go
they didn‟t approve. Disapproval
The important point is that line-by-line coding helps you to focus on the content of the
text in the line and helps you to focus on what it is about. When doing line-by-line coding
there is a tendency to produce descriptive codes. However, some of those you have
suggested may be more analytic or more theoretical. That's good. The next step is to try
and develop such analytic codes and/or recode some of the descriptive codes you have
used.
Today, various types of software are available to assist in qualitative data
analysis. Thus many researchers have replaced physical files and cabinets with computer
based directories and files along with the use of word processors to write and annotate
texts. Many analysts now also use dedicated computer assisted qualitative data analysis
(CAQDAS) packages that not only make the coding and retrieval of text easy to do, but
can add other functions like searching that computers do quickly but which takes humans
ages to do or in some cases, which humans have never done.
At first the focus of CAQDAS was on text since that was easy to handle on PCs,
but now that much audio and video is in digital form too, software has been developed to
COMPUTER-BASED QUALITATIVE DATA ANALYSIS
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support the analysis of audio and video data. Among the popular software used in
analysing qualitative data is NVivo, Nudist and an open source software called Weft
QDA [We will not be discussing the use of these software in this course]. You can
download Weft QDA and try it out. http://www.pressure.to/qda/
Coding is the process of examining the raw qualitative data which will in the form
of words, phrases, sentences or paragraphs) and assigning CODES or labels.
Open Coding – You “sweep” through the data and mark (by circling or
highlighting) sections of the text selected codes or labels.
Eventually, you have a large number of codes and you will find it necessary to
sort them into some sort of order or into groups and this is called axial coding.
The way codes are developed and the timing of this process will depend on
whether your research project and your approach is inductive or deductive.
Most typically, when coding, researchers have some codes already in mind and
are also looking for other ideas that seem to arise out of the data.
SUMMARY
KEY WORDS
Coding
Open coding
Axial coding
Hierarchical
Non-Hierarchical
Meanings
Reflexive
Categories
Descriptive codes
Analytic codes
Conditions
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In coding, the researcher is looking for what is going on, what are people doing,
what is the person saying, what do these actions and statements take for granted,
how do structure and context serve to support, maintain, impede or change these
actions and statements.
In coding, the researcher is looking for behaviours, events, activities, states,
strategies, meanings, participation, relationships, conditions, consequences,
settings and reflexive.
Computer software is used by researchers to facilitate qualitative data analysis.
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