This document provides an overview of NVivo and how it can be used for literature reviews. It discusses NVivo as a qualitative data analysis software that allows users to organize and analyze unstructured data. The document then outlines an 8 step process for using NVivo for literature reviews: 1) Create an NVivo project, 2) Import references, 3) Name and classify references, 4) Identify important bits to code, 5) Code them, 6) Combine similar codes, 7) Develop themes, 8) Write up findings while writing memos and using queries. Key functions of NVivo explained include importing data, coding, memo writing, and running queries to facilitate analysis.
A presentation to the UC Berkeley D-Lab on the basics of using CAQDAS software for qualitative analysis, plus an introductory walkthrough of the features of Atlas.ti.
This document provides an introduction to NVivo, a qualitative data analysis software. It describes how NVivo can be used to organize, analyze, and find insights in unstructured qualitative data like documents, interviews, and social media posts. The document outlines the basic NVivo workspace and functions for importing data sources, coding data, running queries, and visualizing results. It also provides guidance on setting up an NVivo project and includes some example tasks for getting started with the software.
This document provides information on referencing and plagiarism. It begins by stating the learning outcomes, which are to understand plagiarism and how to reference work using the Harvard system. It then defines plagiarism and discusses different types of plagiarism. The document also covers how to reference sources in-text and provide full references, highlighting important information to include. Various tools and guides for referencing are also mentioned.
Research Data Management for Qualitative ResearchersCelia Emmelhainz
This presentation reviews concerns with research data management (RDM) specific to qualitative researchers such as sociologists and anthropologists. Presented to the qualitative methods working group in the D-Lab at UC Berkeley.
The document discusses using computer software to analyze qualitative data, describing different types of analysis software and their functions. It also provides examples of research studies that used various computer-assisted qualitative data analysis software packages like MS Word, NVivo, and NUD*IST to code and analyze interview transcripts, field notes, and other qualitative data sources. The document emphasizes that the choice of software depends on the researcher's methodology, data types and amount, and analysis approach.
Using NVivo QSR Theory and Practice for Qualitative Data Analysis in a PhDKEDGE Business School
Session from Salford Business School http://www.salford.ac.uk/business-school doctoral school at the Digital Business Centre. This explain the rationale and some of the basic concepts when it comes to using NVivo QSR for data analysis.
NVivo is a tool for helping to you analyse qualitative data but it does not replace the thinking process - there is a need for you to consider the bigger picture of how NVivo will fit into your research project and this presentation offers some themes you should explore before you commit to the use of NVivo.
This document provides an overview of methodology and tools for reading scientific papers. It discusses the objectives of actively reading papers, including understanding their content and writing reading notes, literature reviews, and reviews. It describes different types of papers and their typical structure. The document outlines a three-pass approach for actively reading papers: an initial skim, a deeper reading to understand the content, and a final careful reading. It also discusses justifying and evaluating the results and contributions of papers through formal proofs, experimentation, argumentation, and benchmarks. The key message is that actively reading papers involves writing annotations and notes to fully comprehend and synthesize their information.
This document provides an introduction and overview of a course on methodology and tools for research. The course is designed and taught by Yannick Prié of Polytech Nantes, University of Nantes. The course has four main objectives: to understand the world of research, know how to search and evaluate scientific materials, know how to write scientific documents, and know how research is practiced. It covers topics such as knowledge production, scientific publishing, paper writing and evaluation, and the research landscape. The course includes both lectures and tutoring units, and will be evaluated based on students' participation on a program committee, writing a scientific publication, and a final exam.
A presentation to the UC Berkeley D-Lab on the basics of using CAQDAS software for qualitative analysis, plus an introductory walkthrough of the features of Atlas.ti.
This document provides an introduction to NVivo, a qualitative data analysis software. It describes how NVivo can be used to organize, analyze, and find insights in unstructured qualitative data like documents, interviews, and social media posts. The document outlines the basic NVivo workspace and functions for importing data sources, coding data, running queries, and visualizing results. It also provides guidance on setting up an NVivo project and includes some example tasks for getting started with the software.
This document provides information on referencing and plagiarism. It begins by stating the learning outcomes, which are to understand plagiarism and how to reference work using the Harvard system. It then defines plagiarism and discusses different types of plagiarism. The document also covers how to reference sources in-text and provide full references, highlighting important information to include. Various tools and guides for referencing are also mentioned.
Research Data Management for Qualitative ResearchersCelia Emmelhainz
This presentation reviews concerns with research data management (RDM) specific to qualitative researchers such as sociologists and anthropologists. Presented to the qualitative methods working group in the D-Lab at UC Berkeley.
The document discusses using computer software to analyze qualitative data, describing different types of analysis software and their functions. It also provides examples of research studies that used various computer-assisted qualitative data analysis software packages like MS Word, NVivo, and NUD*IST to code and analyze interview transcripts, field notes, and other qualitative data sources. The document emphasizes that the choice of software depends on the researcher's methodology, data types and amount, and analysis approach.
Using NVivo QSR Theory and Practice for Qualitative Data Analysis in a PhDKEDGE Business School
Session from Salford Business School http://www.salford.ac.uk/business-school doctoral school at the Digital Business Centre. This explain the rationale and some of the basic concepts when it comes to using NVivo QSR for data analysis.
NVivo is a tool for helping to you analyse qualitative data but it does not replace the thinking process - there is a need for you to consider the bigger picture of how NVivo will fit into your research project and this presentation offers some themes you should explore before you commit to the use of NVivo.
This document provides an overview of methodology and tools for reading scientific papers. It discusses the objectives of actively reading papers, including understanding their content and writing reading notes, literature reviews, and reviews. It describes different types of papers and their typical structure. The document outlines a three-pass approach for actively reading papers: an initial skim, a deeper reading to understand the content, and a final careful reading. It also discusses justifying and evaluating the results and contributions of papers through formal proofs, experimentation, argumentation, and benchmarks. The key message is that actively reading papers involves writing annotations and notes to fully comprehend and synthesize their information.
This document provides an introduction and overview of a course on methodology and tools for research. The course is designed and taught by Yannick Prié of Polytech Nantes, University of Nantes. The course has four main objectives: to understand the world of research, know how to search and evaluate scientific materials, know how to write scientific documents, and know how research is practiced. It covers topics such as knowledge production, scientific publishing, paper writing and evaluation, and the research landscape. The course includes both lectures and tutoring units, and will be evaluated based on students' participation on a program committee, writing a scientific publication, and a final exam.
This document provides an overview of methodology and tools for writing scientific material. It discusses key elements of research papers such as the introduction, body, conclusion and references. The introduction should present the problem, motivation and contributions. The body should substantiate the claims, provide definitions, theorems and related work. Experimental work requires clear methodology, results and discussion of implications. Figures and tables must be clearly presented and cited. The conclusion summarizes key ideas and can discuss future work. References are included within the text and at the end in the appropriate style. Acknowledgments recognize funding and contributions.
The document discusses using technology in qualitative research. It describes various technologies that can be used including word processing, spreadsheets, presentation software, and qualitative data analysis (QDA) software like Ethnograph. It emphasizes that QDA software like Ethnograph helps researchers organize, code, search, and analyze large amounts of qualitative data. The document provides an overview of the basic processes involved in using QDA software to compile data, organize it through coding, and manipulate the data through searching and comparing coded segments.
This document provides an overview of using NVivo software for qualitative data analysis. It discusses why NVivo is useful for organizing data, speeding up the analysis process, and making research traceable. The document then describes NVivo terminology, how to prepare documents for import, and the coding and analysis process which involves organizing codes into nodes and node trees to develop models. Training sessions and resources for learning NVivo are also mentioned.
Atlas.ti making sense of research data in policy analysisMerlien Institute
This document provides an overview of ATLAS.ti, a qualitative data analysis software. It discusses the central concept of the Hermeneutic Unit, which contains all project data and analysis. The document outlines the main project elements including primary documents, quotations, codes, memos, families, and networks. It also addresses how ATLAS.ti can be used for team collaboration and exporting data.
This document provides an overview of methodology and tools for scientific publishing. It discusses the objectives of the course, which are to understand facets of publishing such as journals, conferences, books, and publication workflows. It also covers obtaining an idea of publication-based evaluation metrics like impact factor and h-index. The document outlines different types of scientific documents, principles of publication, economics of publishing, and bibliometrics.
NVivo is qualitative data analysis software produced by QSR International. It allows users to organize and classify various forms of unstructured data like documents, audio, video and images. NVivo provides tools to help users capture online data, visualize connections in their data, link ideas and themes, and perform mixed methods research. The software aims to replicate the paper-based qualitative analysis process digitally for improved organization and faster work with large datasets.
ATLAS.ti training presentation: Covering the basics Arun Verma
This is a short introduction to using ATLAS.ti on Mac. This presentation provides you with all the basics to get you started with your qualitative data analysis.
ATLAS.ti Training - Covering the Basics (Mac edition)Arun Verma
Covering the basics for ATLAS.ti users Mac edition (With some Windows version information as well). For information on introductory workshops, support or advice on ATLAS.ti, please get in touch.
(User must get permission from author to re-use any part of this presentation. Any use of presentation must be referenced clearly to the author with relevant hyperlinks and contact information to author)
This document outlines various workflows and activities involved in the job of a researcher. It begins by describing common workflows such as writing a paper, supervising PhD students, writing grant proposals, participating in research projects, and attending conferences. It then discusses how researchers combine these various workflows with teaching and administrative responsibilities. The document characterizes research as a type of knowledge work and discusses how personal knowledge management is important. It argues that while research shares some similarities with other jobs, it also has unique aspects like freedom and peer evaluation. Qualities important for researchers like curiosity and tenacity are outlined. The document encourages maintaining an active research mindset and choosing topics that can sustain long-term research.
This document provides an overview of research methodology and tools. It discusses the French research landscape including various public and private research bodies such as universities, CNRS, and industrial labs. It also outlines funding sources like ANR grants and the process for evaluating research units. Career paths are explored for students, postdocs, professors, engineers, and administrative roles. Finally, the document defines what a PhD thesis entails in terms of dissertation and examination requirements.
Computer Software in Qualitative Research: An Introduction to NVivoAdam Perzynski, PhD
This document introduces the qualitative data analysis software NVivo. It discusses NVivo's vocabulary, capabilities for managing and analyzing textual data, and advanced tasks. The document also covers example data used in NVivo, demonstrations of its functions, frequently asked questions, debates around computer software for qualitative research, and conclusions about using NVivo and remaining reflexive in the research process.
This document summarizes tips for organizing lecture notes and electronic materials. It recommends organizing notes by subject in separate folders based on how the materials will be used later. Lecture notes should be dated and labeled clearly. Electronic files should also have descriptive names and be organized in a logical folder structure. The document discusses online tools for organizing notes and bookmarks, such as Evernote, EndNote, and social bookmarking sites. It emphasizes thinking about how materials will be used and customized organization methods for individual study styles.
This document provides an overview of a presentation on developing a successful dissertation. It includes an agenda with topics, activities, and times. The learning goals are to understand the dissertation timeline and process, develop a master plan based on research questions, and learn digital tools for each phase. Teaching methods include an audience response system and branching presentation. The document then discusses transforming the typically linear dissertation process into an iterative, multimedia, cloud-based process. It provides details on the major phases of developing a dissertation, including expected activities, decisions, deliverables, and tips.
This document outlines the Big Six skills approach to conducting dissertation research. It discusses the six steps: 1) task definition, 2) information seeking strategies, 3) location and access, 4) use of information, 5) synthesis, and 6) evaluation. For each step, it provides guidance on how to effectively implement that step for dissertation research, including defining the research topic, developing search strategies, evaluating and organizing sources, avoiding plagiarism, and assessing the overall process. Key resources and techniques are described, such as developing search terms, using databases and catalogs, taking notes, and creating a concept map.
This document provides an overview of resources for university studies, including different types of information sources, keywords for effective searching, and how to evaluate sources. It discusses primary, secondary and tertiary sources and gives examples. It also covers using the library search tool, referencing styles, databases like VetMed and PubMed, and getting help from subject librarians. The goal is to help students effectively find and use high-quality sources for their academic work.
This document provides guidance on publishing research results in technical periodicals and conferences. It discusses conducting a thorough literature review to demonstrate how the research contributes new knowledge. Authors must follow ethical standards, including properly attributing sources to avoid plagiarism. The document reviews responsibilities of authors and outlines the process of writing and submitting manuscripts, including developing an outline, writing drafts, peer review, and final publication. Following these steps will help authors successfully share their work and advance their field.
This document provides an overview of methodology and tools for research. It discusses scientific knowledge production, validation of claims through peer assessment, and the role of scientific disciplines and ethics in research. The document is divided into sections on scientific knowledge, scientific disciplines, studying science, and the relationship between science and society. It provides context for understanding knowledge production and the socio-technical organization that supports the accumulation of scientific knowledge.
NVivo is software that helps organize and analyze qualitative data. It allows importing different file types into a single project. The core function is coding - tagging chunks of text from sources like interviews with descriptive nodes or labels. Coding can be done a priori based on theory or inductively as themes emerge. Nodes are also used to classify cases like people. Content analysis involves systematically tagging text to identify and describe themes. Coding is an iterative process to make sense of the data with no single correct way. NVivo provides tools to aid the analysis but understanding comes from the researcher's analysis.
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.
This document provides step-by-step instructions for conducting library research on emerging economies and world politics. It outlines choosing a topic and keywords, constructing a search strategy, selecting appropriate resource types like books, articles, datasets and primary sources, running searches in relevant databases and tools, obtaining full-text versions when possible, and evaluating sources. The focus is on using the UCSD library resources and databases to find in-depth information to develop arguments and draw conclusions.
Group X analyzed data using computer software. They discussed several types of software for analyzing qualitative data, including those for coding text, developing theories, and building conceptual networks. The functions to look for include coding, memoing, searching, and displaying data. There is no single best software; the researcher must consider their data, approach, and needs. The document provided examples of research articles that used different software like MS Word, NVivo, and Qualrus to analyze qualitative data.
This document provides an overview of methodology and tools for writing scientific material. It discusses key elements of research papers such as the introduction, body, conclusion and references. The introduction should present the problem, motivation and contributions. The body should substantiate the claims, provide definitions, theorems and related work. Experimental work requires clear methodology, results and discussion of implications. Figures and tables must be clearly presented and cited. The conclusion summarizes key ideas and can discuss future work. References are included within the text and at the end in the appropriate style. Acknowledgments recognize funding and contributions.
The document discusses using technology in qualitative research. It describes various technologies that can be used including word processing, spreadsheets, presentation software, and qualitative data analysis (QDA) software like Ethnograph. It emphasizes that QDA software like Ethnograph helps researchers organize, code, search, and analyze large amounts of qualitative data. The document provides an overview of the basic processes involved in using QDA software to compile data, organize it through coding, and manipulate the data through searching and comparing coded segments.
This document provides an overview of using NVivo software for qualitative data analysis. It discusses why NVivo is useful for organizing data, speeding up the analysis process, and making research traceable. The document then describes NVivo terminology, how to prepare documents for import, and the coding and analysis process which involves organizing codes into nodes and node trees to develop models. Training sessions and resources for learning NVivo are also mentioned.
Atlas.ti making sense of research data in policy analysisMerlien Institute
This document provides an overview of ATLAS.ti, a qualitative data analysis software. It discusses the central concept of the Hermeneutic Unit, which contains all project data and analysis. The document outlines the main project elements including primary documents, quotations, codes, memos, families, and networks. It also addresses how ATLAS.ti can be used for team collaboration and exporting data.
This document provides an overview of methodology and tools for scientific publishing. It discusses the objectives of the course, which are to understand facets of publishing such as journals, conferences, books, and publication workflows. It also covers obtaining an idea of publication-based evaluation metrics like impact factor and h-index. The document outlines different types of scientific documents, principles of publication, economics of publishing, and bibliometrics.
NVivo is qualitative data analysis software produced by QSR International. It allows users to organize and classify various forms of unstructured data like documents, audio, video and images. NVivo provides tools to help users capture online data, visualize connections in their data, link ideas and themes, and perform mixed methods research. The software aims to replicate the paper-based qualitative analysis process digitally for improved organization and faster work with large datasets.
ATLAS.ti training presentation: Covering the basics Arun Verma
This is a short introduction to using ATLAS.ti on Mac. This presentation provides you with all the basics to get you started with your qualitative data analysis.
ATLAS.ti Training - Covering the Basics (Mac edition)Arun Verma
Covering the basics for ATLAS.ti users Mac edition (With some Windows version information as well). For information on introductory workshops, support or advice on ATLAS.ti, please get in touch.
(User must get permission from author to re-use any part of this presentation. Any use of presentation must be referenced clearly to the author with relevant hyperlinks and contact information to author)
This document outlines various workflows and activities involved in the job of a researcher. It begins by describing common workflows such as writing a paper, supervising PhD students, writing grant proposals, participating in research projects, and attending conferences. It then discusses how researchers combine these various workflows with teaching and administrative responsibilities. The document characterizes research as a type of knowledge work and discusses how personal knowledge management is important. It argues that while research shares some similarities with other jobs, it also has unique aspects like freedom and peer evaluation. Qualities important for researchers like curiosity and tenacity are outlined. The document encourages maintaining an active research mindset and choosing topics that can sustain long-term research.
This document provides an overview of research methodology and tools. It discusses the French research landscape including various public and private research bodies such as universities, CNRS, and industrial labs. It also outlines funding sources like ANR grants and the process for evaluating research units. Career paths are explored for students, postdocs, professors, engineers, and administrative roles. Finally, the document defines what a PhD thesis entails in terms of dissertation and examination requirements.
Computer Software in Qualitative Research: An Introduction to NVivoAdam Perzynski, PhD
This document introduces the qualitative data analysis software NVivo. It discusses NVivo's vocabulary, capabilities for managing and analyzing textual data, and advanced tasks. The document also covers example data used in NVivo, demonstrations of its functions, frequently asked questions, debates around computer software for qualitative research, and conclusions about using NVivo and remaining reflexive in the research process.
This document summarizes tips for organizing lecture notes and electronic materials. It recommends organizing notes by subject in separate folders based on how the materials will be used later. Lecture notes should be dated and labeled clearly. Electronic files should also have descriptive names and be organized in a logical folder structure. The document discusses online tools for organizing notes and bookmarks, such as Evernote, EndNote, and social bookmarking sites. It emphasizes thinking about how materials will be used and customized organization methods for individual study styles.
This document provides an overview of a presentation on developing a successful dissertation. It includes an agenda with topics, activities, and times. The learning goals are to understand the dissertation timeline and process, develop a master plan based on research questions, and learn digital tools for each phase. Teaching methods include an audience response system and branching presentation. The document then discusses transforming the typically linear dissertation process into an iterative, multimedia, cloud-based process. It provides details on the major phases of developing a dissertation, including expected activities, decisions, deliverables, and tips.
This document outlines the Big Six skills approach to conducting dissertation research. It discusses the six steps: 1) task definition, 2) information seeking strategies, 3) location and access, 4) use of information, 5) synthesis, and 6) evaluation. For each step, it provides guidance on how to effectively implement that step for dissertation research, including defining the research topic, developing search strategies, evaluating and organizing sources, avoiding plagiarism, and assessing the overall process. Key resources and techniques are described, such as developing search terms, using databases and catalogs, taking notes, and creating a concept map.
This document provides an overview of resources for university studies, including different types of information sources, keywords for effective searching, and how to evaluate sources. It discusses primary, secondary and tertiary sources and gives examples. It also covers using the library search tool, referencing styles, databases like VetMed and PubMed, and getting help from subject librarians. The goal is to help students effectively find and use high-quality sources for their academic work.
This document provides guidance on publishing research results in technical periodicals and conferences. It discusses conducting a thorough literature review to demonstrate how the research contributes new knowledge. Authors must follow ethical standards, including properly attributing sources to avoid plagiarism. The document reviews responsibilities of authors and outlines the process of writing and submitting manuscripts, including developing an outline, writing drafts, peer review, and final publication. Following these steps will help authors successfully share their work and advance their field.
This document provides an overview of methodology and tools for research. It discusses scientific knowledge production, validation of claims through peer assessment, and the role of scientific disciplines and ethics in research. The document is divided into sections on scientific knowledge, scientific disciplines, studying science, and the relationship between science and society. It provides context for understanding knowledge production and the socio-technical organization that supports the accumulation of scientific knowledge.
NVivo is software that helps organize and analyze qualitative data. It allows importing different file types into a single project. The core function is coding - tagging chunks of text from sources like interviews with descriptive nodes or labels. Coding can be done a priori based on theory or inductively as themes emerge. Nodes are also used to classify cases like people. Content analysis involves systematically tagging text to identify and describe themes. Coding is an iterative process to make sense of the data with no single correct way. NVivo provides tools to aid the analysis but understanding comes from the researcher's analysis.
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.
This document provides step-by-step instructions for conducting library research on emerging economies and world politics. It outlines choosing a topic and keywords, constructing a search strategy, selecting appropriate resource types like books, articles, datasets and primary sources, running searches in relevant databases and tools, obtaining full-text versions when possible, and evaluating sources. The focus is on using the UCSD library resources and databases to find in-depth information to develop arguments and draw conclusions.
Group X analyzed data using computer software. They discussed several types of software for analyzing qualitative data, including those for coding text, developing theories, and building conceptual networks. The functions to look for include coding, memoing, searching, and displaying data. There is no single best software; the researcher must consider their data, approach, and needs. The document provided examples of research articles that used different software like MS Word, NVivo, and Qualrus to analyze qualitative data.
The document provides an overview of library resources for a COMM 1130 class. It discusses:
1) How to identify different types of sources and evaluate them using the CRAAP test.
2) Where to find tools to create IEEE citations and that a research guide is available on the library website with relevant resources.
3) The different types of resources like scholarly journals, popular magazines, and trade journals; and how to determine their credibility using the CRAAP test.
Data analysis – using computers for presentationNoonapau
The document discusses using computer software for data analysis. It provides examples of different types of software including word processors, code-and-retrieve programs, and conceptual network builders. It emphasizes that the researcher should choose software based on their methodology and the type and amount of data, rather than which software is considered "best." The document also summarizes several research articles that used different software programs like MS Word, NVivo, and Qualrus to analyze qualitative data.
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.
Are you manually coding all or part of your research data? Are you analyzing large volumes of text? See how NVivo can speed up the coding process giving you the ability to efficiently and effectively review and refine your research data.
Using NVivo to tell the story - the power of codingQSR International
Discover how NVivo was used in two projects in healthcare.
Presented by Kamden Hoffman, President and Senior Technical Advisor at Innovative Social Change in Global Health, LLC.
Analyzing observational data during qualitative researchWafa Iqbal
This document discusses qualitative data analysis methods. It explains that qualitative data analysis explores and interprets complex data from sources like interviews and observations to generate new understandings without quantification. The generic process of analysis involves organizing, reading, and coding the data by assigning labels to chunks of information to develop themes and descriptions. Coding is a primary element of analysis and allows the researcher to summarize and synthesize the data. Developing themes is also part of the analysis process and involves discovering core and peripheral elements of themes from the data.
Making qualitative analysis more transparent by using NVivoQSR International
This document provides an overview of using NVivo software to conduct transparent qualitative data analysis. It discusses using a team or solo approach, documenting the analytic process through memos and a detailed codebook, coding interviews and other sources, running queries to identify relationships between codes and themes, and making the analysis iterative and supported by the source data. The goal is to facilitate a rigorous qualitative analysis process that meets standards for trustworthy qualitative research.
Writekraft Research & Publication LLP.
We are one of the leading PhD assistance company that deals in helping PhD scholars in their Thesis, Research paper writing and publication work. We are providing custom PhD Thesis written for you exactly the way you want along with a Turnitin plagiarism report.
For more Information Contact us@ admin@writekraft.com
Or Call us @ 7753818181, 9838033084
www.writekraft.com
The presentation deals with Basic Research Skills for conducting scientific research. Its an abridged version of the course/module offered at ITC, The Netherlands.
The document discusses the use of information technology in scientific article writing and publication strategies. It provides examples of digital tools that can help with tasks like finding relevant papers, summarizing research, editing manuscripts, and improving writing quality. AI tools are presented that can assist with activities involving scientific publications such as paper editing, paraphrasing sentences, and journal review. Guidelines are offered for selecting suitable journals for publication and navigating the submission process.
Trendspotting: Helping you make sense of large information sourcesMarieke Guy
This document provides an overview of a presentation on trendspotting and making sense of large information sources. The presentation introduces qualitative data analysis and thematic coding. It discusses collecting and organizing qualitative data, identifying themes and patterns through coding, and presenting findings through reports, visualizations and infographics. Practical exercises are included to have participants analyze text data by identifying codes and themes in small groups. Resources on qualitative analysis techniques are also provided.
Writekraft Research & Publication LLP.
We are one of the leading PhD assistance company that deals in helping PhD scholars in their Thesis, Research paper writing and publication work. We are providing custom PhD Thesis written for you exactly the way you want along with a Turnitin plagiarism report.
For more Information Contact us@ admin@writekraft.com
Or Call us @ 7753818181, 9838033084
www.writekraft.com
This document provides an overview of research methods for narrative analysis. It discusses key concepts in narrative analysis including scripts, stories, patterns, themes, coding, and temporal organization. It also covers approaches like contextual analysis, focus groups, retelling narratives, and assumptions related to subjectivity and usefulness. Narrative analysis is presented as an exploratory qualitative methodology to give respondents a venue to articulate their own viewpoints and standards.
The document provides guidance on conducting library research for political scientists. It outlines an 8-step research process: 1) develop a research question, 2) choose appropriate research tools, 3) develop search strategies, 4) apply limits to searches, 5) obtain full-text items, 6) get accurate citations, 7) evaluate sources, and 8) repeat the process as needed. Key tools discussed include books, scholarly articles, primary sources, statistics, and limiting searches by date, publication type, language, and peer-review status. The goal is to find relevant high-quality sources to answer the research question.
This lesson teaches students scanning strategies to help with reading skills for the TOEFL test. Students will practice scanning various books, magazines, news articles, and web pages to identify general information within texts. They will then present a one-page summary of what they learned from the materials. The lesson connects to PA Core standards of reading comprehension, using media sources, and applying digital tools to gather and evaluate information for tasks.
This document provides step-by-step instructions for conducting academic library research. It outlines choosing a topic and keywords, constructing a search strategy, choosing appropriate research tools like books, articles, primary sources, and datasets, running searches and evaluating results. Key tips include using synonyms, limiting or expanding search terms, combining terms with "and" or "or", trying different databases and subject headings, and getting full text or requesting items through interlibrary loan when not available locally.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Chapter wise All Notes of First year Basic Civil Engineering.pptx
N vivo tutorial 2020
1. NVivo Tour
& its use for literature reviews
By Saqar Alzaabi
PhD student
IRDR, UCL
2. What we will cover in this lecture?
• Introduction to NVivo – what
is it? And why use it?
• The basic functions of NVivo
– a step by step guide
• How it can be used for
literature reviews
• Advanced coding (optional)
• Extra materials and help.
3. What is NVivo?
• NVivo is a qualitative data analysis software.
• It enables the user to categorize unstructured nonnumeric
data.
• BUT it does provide some numeric data.
• For literature reviews: it can also be used as an organizing
and analysis tool
• It is straightforward but it is based on the analyst work (you
build it using your data).
4. Why NVivo
• Systematic way to organize your research, manage its different
components and analyze your qualitative data
• Reduce the load on your memory by categorizing & classifying
literature (you can come back to them at anytime)
• A single workspace for analysis and writing
• Plenty of functions for data visualization
• Automating yourself for faster qualitative analysis
• Multiple analysts working on single project
• And of course, you can mention it in your CV
• FOR ME, it played a role in increasing my understanding of qualitative
research
5. NVivo for literature review – the why
• Systematic, effective and efficient way for
finding connections between the different
literature and categorizing them
• Helps you structure your literature review
by coding and categorizing themes or
commonalities
• To understand how your research problem
has been viewed and approached, schools
of thought, areas where scholars have
agreed or disagreed
• Then knowledge gaps are identified
6. • Use the UCL Remote
Desktop@Anywhere facility (see https://tinyurl.com/y
8m8whpg) as it allow users to work remotely from their
PC or Laptops. In addition, it grants the user access to
all Software in UCL's library, including NVivo.
• If UCL Remote Desktop@Anywhere becomes
problematic, you could instead download the NVivo 12
software from the UCL software database:
http://swdb.ucl.ac.uk/package/view/id/260
7. NVivo Key Terms
• Data or Files
The research materials you will be working on. They could be
interview transcripts, journal articles, social media feeds, any data.
The process is importing.
• Codes or Nodes
Containers for your coding*. You name them. There are the themes or
main ideas.
The process is coding.
• Cases
They are also containers or nodes but they are the units of analysis
e.g., people, events, places, authors, organizations
8. Key Terms in NVivo
• Notes or Memos
Your notes, your explanations and discussion. Can be
structured as chapters/sections of your work
• Search or Queries
Analysis tools to find specific phrases, to find frequent
words
• Mind Maps & Concept Maps
Visualizing the results
10. NVivo for literature review – the 8 steps
Create a new
Nvivo project
Import
references
(articles)
Name them
(Author, Year)
Classify them
Identify the
important bits
Code them
Combine similar
codes
Develop themes
‘nodes’
‘categories’
Write up
Write Memos
& link them to codes
Do word or phrase
Queries
‘Visualize results’
Write Annotations
& link them to codes
These tools are
used along the
process.
11. Import data
• They are the research
material.
• They could be interview
transcripts, datasets from
social media accounts.
• Here are the references
‘journal articles PDFs’ or your
bibliographic database.
• Once imported better to
organize them based on their
types.
12. Case Classification –
classifying the reference
• Case classification let you store
demographic information about the ‘units
of analysis’
• Usually in qualitative research, the case is
a person and the attributes are age,
gender, level of education and
occupation.
• In L.R., the case is the reference and the
attributes are type of research, year,
author, theoretical framework, location.
13. Coding – the core function
• Coding is assigning a word or phrase that accurately describes the text
segment or its meaning – a way for indexing the data
• Plenty of codes could be created. Therefore, aggregating the similar
codes into one node (container/theme) is done along the way.
• The Node refers to one concept or theme.
• Either drag the text excerpt to an existing code or click the code icon
to create a new code. Remember to describe it.
14. What is it that you code?
• This is the most important part.
• In general, they could actions, activities,
perceptions, concepts, differences, opinions,
processes, whatever you think is relevant.
• For L.R., they could be conceptualizing a
term, ontological and epistemological
position of the author, evolution of thought,
models, frameworks, similarities/differences
with others, whatever you think is relevant.
• Remember that, you are the interpreter and
you code what you code because you
consider them important.
15. Code – combining codes and creating themes
• Bringing the similar codes into one node (theme) e.g., vulnerability as
a social construct, vulnerability as a physical construct
16. Write Memos – record your thoughts
• Memos and links are the companion tools to coding; used in
conjunction with coding.
• You record your thoughts, comments and analysis while coding by
creating memos and linking them to the relevant code.
• They form your input e.g., literature review, results and discussion
chapters. They could also form a new piece of research.
• Linking nodes to memos is what makes NVivo a well-organized way of
analysis.
• Write critically: agree, reject, caveat, highlight similarities/differences
and reconcile between arguments
17. Run query – text search
• If you are interested in specific key terms e.g., learn, learning, learned
• You can
1. how many times ‘the term’ has been mentioned across the
different sources
18. Run query – text search
• If you are interested in specific key terms e.g., learn, learning, learned
• You can
2. Visualize the term using Word tree
19. Run query –
word frequency
• If you are interested to
find out the frequently
used terms across the
data set
• Could be the first step to
understand the different
topics/phenomena
addressed by participants
• You can then locate the
key terms
20. Run query – word
frequency
• You can visualize the common
terms using Word tree
• You can then click on any word
to find its references and
visualize its word tree
• You can save them as new
codes.
23. Extra Learning Materials
• Bazeley, P. and Jackson, K. eds., 2013. Qualitative data analysis with
NVivo. Sage Publications Limited.
• http://www.qsrinternational.com/nvivo/nvivo-community/the-nvivo-
blog/tackling-the-literature-review
• https://www.youtube.com/watch?v=VtEWglfB2Hw&feature=youtu.b
e
• Braun, V. and Clarke, V., 2006. Using thematic analysis in psychology.
Qualitative research in psychology, 3(2), pp.77-101.
• https://www.linkedin.com/learning/nvivo-2018-essential-
training/welcome?u=69919578
I will explain how NVivo is used for qualitative research in general and how it been used for literature reviews. I will try my best to explain each step simultaneously. This is how it is used in general and this is how it is used for literature reviews.
It is not possible to explain the technical aspect of NVivo without also addressing some aspects of qualitative research.
It could be a powerful research tool, particularly if you’ve got large amount data.
It is a tool for organizing and analyzing qualitative data. They could be for example interview transcripts, qualitative surveys, articles, social media and web content.
Sources could be for example interview participants. They are not homogeneous. So you could differentiate between based on their ages, experience, role
So you gathered lots of text. From One source for example newspapers or plenty sources such as websites, interviews, magazines, newspapers or even scientific literature. And now you want to analyze them. You could do it manually or you do it by using a software to help you out. Nvivo is one of them. It is
Nvivo is used for any non-numerical data collected as part of evaluation such observations, interviews, written documents, focus groups transcripts and diaries.
In many cases, a researcher finds an extensive literature written about a topic and wonders how to categorize and classify them so he/she is able to find out the knowledge gaps and justify his/her focus area.
Yes, plenty of research is published but most share common views.
There is the Windows and Mac version. I will be working on the Mac version but they are very similar. There are also two other versions of NVivo, NVivo Pro and NVIvo Plus.
costs $1199.00 USD
So first lets familiarize ourselves with the key terms used in NVivo 12.
Files or data and some call them sources: they could also be audio, video, pictures, surveys,
Nodes or codes or coding the process of gathering the pieces of texts under one topic, idea or theme, a pattern or a relationship bwt two things two factors
Cases allow us to record demographic data about people or organizations
Memos allow you to record your thoughts.
Queries allow you to search your files or your codes or your cases
The main areas of the NVivo interface are the navigation view, the list view, the detail view and the ribbon or the command view.
It may look familiar to most of you because it was designed based on Microsoft Outlook appearance.
Ribbon - locate all NVivo commands
Navigation View – organize your materials into folders.
List View —When a folder is selected in Navigation View the contents are displayed in list view.
Detail View —When an item from list view is opened, it is displayed in Detail View. This is where you actually see the contents of the files.
NOTE—the workspace can be rearranged to suite your needs.
There are many ways in using NVivo for literature review. `But I am developing this method which I found very helpful and system.
They are not necessarily linear. Some functions overlap and it is as the case with qualitative research an iterative process. You go back and forth.
Most steps are similar if using NVivo for qualitative data such as interview transcripts.
Once the appropriate literature is identified like important journal articles, books, reports, etc.
Then you need to create a new project
So the first step is to import the data you will be working on into the software Nvivo. You bring the document into NVivo.
Sources could be for example interview participants. They are not homogeneous. So you could differentiate between based on their ages, experience, role.
So you would classify the references by assigning attributes to them.
Three types of literature are usually reviewed in a research: topic-based, theoretical and methodological.
Why do we need to code data? Three main reasons, to reduce data, to organize data and to generate ideas.
Coding sometimes is referred to as ‘indexing’ or ‘labeling’.
They are of a particular importance to the phenomenon under study.
So you would highlight the text and give it a name (code).
Coding is about demarcating data into segments and assigning a code to each one. Analysis could begin with relative frequency of codes and relationships of between them.
So in my study for example, I found participants tend to make comparisons between the different networks or sectors. Some are perceived better and they would give reasons and factors so I though it is important to address this topic.
So NVivo lets you to visualize the connections between codes. This may be important to discuss with others.
They are of a particular importance to the phenomenon under study.
Themes must be connected and you should describe the theme as well as the connection with other themes.
They are of a particular importance to the phenomenon under study. You want to understand what officials mean by learning for example.
The word learning or learn or learned mentioned by participants who have disaster experience while the ones who are new rarely mention it.
They are of a particular importance to the phenomenon under study. You want to understand what officials mean by learning for example.
They need … resources, support from others, etc. The organizations that are not well developed mention it more than the ones that are well-developed. It also indicative of the organizations that are more reliant on others. So it would show the hierarchy of dependency.
Visualize how a case (participant) is connected to its files and codes.