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.
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.
Topic 1 introduction to quantitative researchAudrey Antee
This document provides an introduction to quantitative research. It defines quantitative research as collecting and analyzing numerical data to explore, describe, explain, or predict trends. Quantitative research aims for objectivity and controls outside factors. It states hypotheses and uses statistics to analyze results. The document outlines reasons for quantitative research such as exploration, description, explanation, prediction, and evaluation. It also describes common types of quantitative research designs and the key components of measurement, sampling, research design, and statistical procedures.
Workshop 2 using nvivo 12 for qualitative data analysisDr. Yaar Muhammad
This document provides an overview of using NVivo 12 for qualitative data analysis. It discusses the seven key stages of qualitative analysis: 1) importing data, 2) coding data, 3) creating framework matrices, 4) reporting findings. It describes how to import various file types into NVivo and code data using both first and second cycle coding methods. Framework matrices allow for analyzing patterns across cases. Well supported assertions should be used to report the findings of the qualitative analysis.
This document provides an overview of structural equation modeling (SEM) using AMOS. It defines key SEM concepts like latent variables, observed variables, path analysis, and model identification. It also explains how to specify and estimate a SEM model in AMOS, including how to draw path diagrams, name variables, set regression weights, and view output. Model fit is discussed along with potential issues like sample size. Confirmatory factor analysis and other SEM models like path analysis and latent growth models are also introduced.
Research methodology is the systematic process of investigating a subject or problem to discover relevant information. It involves establishing a conceptual understanding or assessing facets of a problem through objective and systematic investigation. There are two main types of research: fundamental research which seeks to expand knowledge, and applied research which uses existing knowledge to solve problems. Research requires defining objectives, designing a study, collecting and analyzing data, and reporting findings. It provides information to make evidence-based decisions.
The document provides an introduction and overview of the Python programming language. It discusses that Python is an interpreted, object-oriented, high-level programming language that is easy to learn and read. It also covers Python features such as portability, extensive standard libraries, and support for functional, structured, and object-oriented programming. The document then discusses Python data types including numbers, strings, and various Python syntax elements before concluding with the history and evolution of the Python language through various versions.
Project Report Writing : Dr. Gopal Thapa Nepal Commerce CampusTribhuvan University
This document provides guidelines for writing a project report for a 4th year BBS degree at Tribhuvan University in Nepal. It outlines the steps, including selecting an organization and business units to study, collecting and analyzing data, and preparing the report in a prescribed format. The report should have 3 parts - preliminary matter, body, and back matter. It provides details on the content and formatting of each section, such as using Times New Roman font, 1.5 line spacing, and including components like the title page, declaration, and bibliography. The guidelines recommend the report be 8,000-10,000 words excluding preliminary materials and appendices.
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.
This document provides an overview of how to analyze content using NVivo software. It discusses uploading documents to NVivo, coding the content into categories or nodes, and using tools like word frequency queries, text searches, and visualization to analyze relationships within and across texts. The goal of content analysis is to make inferences about messages, authors, audiences, and cultural contexts by systematically coding and examining texts.
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.
A PRESENTATION ON RESEARCH METHODS: SELECTION OF A RESEARCH TOPIC, FORMULATING A HYPOTHESIS, PHILOSOPHICAL ISSUES IN RESEARCH, QUANTITATIVE VS QUALITATIVE DEBATE & SELECTION OF A RESEARCH METHOD
Qualitative research - type of data, analysis of qualitative data, software f...Dr.Preeti Tiwari
This document provides an overview of qualitative research methods, including:
- Qualitative research seeks to understand people's experiences and interpretations of the world through methods like interviews and observation.
- There are several types of qualitative research designs including case studies, grounded theory, phenomenology, and ethnography.
- Data collection methods include interviews, focus groups, participant observation, and analysis involves coding data into themes and concepts.
- Qualitative research aims to gather rich descriptive data rather than numerical data, and the researcher plays a role in data collection and interpretation.
Here are the key points about informed consent:
- It is a process, not just a form. Researchers must ensure participants understand what participation involves through clear verbal and written explanations.
- Consent forms should be written in plain, easy-to-understand language appropriate for the population.
- Participants must be able to refuse or withdraw from the study without penalty.
- Risks and limitations of confidentiality should be clearly explained.
- Participants should have the opportunity to ask questions to fully comprehend what they are consenting to.
- Informed consent is an ongoing process, not a single event, with the option for participants to withdraw later.
The goal is to respect participants' autonomy by
This presentation discuss various methods of qualitative data analysis. it further digs various methods used in qualitative data analysis in some Ph.D. thesis i.e. practical part
This presentation summarizes how the presenter would analyze and present findings from 5 chat interviews conducted with a student regarding a university module's support in developing research skills. The presenter would collate the data by checking reliability, removing personal details, and transferring the data to a usable format. They would analyze the data by categorizing comments, carefully coding them, and potentially mapping relationships. Findings would be presented by establishing the research's validity and reliability, directly answering the research question, and extracting quotes to support conclusions. Both strengths like providing depth and weaknesses like potential bias are acknowledged.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
The document discusses the importance of data extraction in systematic reviews and provides guidance on developing effective data extraction forms and processes. Specifically, it outlines that data extraction 1) involves accurately summarizing studies in a common format to facilitate analysis and presentation, 2) identifies numerical data for meta-analyses, and 3) obtains information to assess risk of bias and applicability; and recommends 4) developing structured yet adaptable forms, 5) providing clear instructions, and 6) considering single versus double extraction.
This document discusses various quantitative data analysis techniques for research. It covers describing and summarizing data, identifying relationships between variables, comparing variables, and forecasting outcomes. The five most important methods are identified as mean, standard deviation, regression, sample size determination, and hypothesis testing. Parametric and non-parametric techniques are also discussed. Four levels of data measurement are defined: nominal, ordinal, interval, and ratio data. Examples are provided for coding nominal/ordinal data and visualizing data through graphs and charts. Statistical tests like the t-test, ANOVA, and chi-square are also summarized.
4 Literature Search Techniques 2 Strategic Searchingrichard kemp
The document discusses strategies for conducting an effective literature search. It covers searching academic literature to find relevant sources, avoiding duplicating previous work, and learning from other scholars' methods and approaches. Search techniques include keyword searches in digital libraries and databases, browsing relevant books and articles, and tracking citations between sources. The optimal search strategy depends on the topic's scope and available sources. Literature searches should become more focused and specialized over time to increase knowledge of the subject.
This document provides an overview of EpiData, a free and open-source software for designing questionnaires, entering data, and exporting data for analysis. It discusses the key features and functions of EpiData including creating questionnaires, setting up data entry checks, entering data, and exporting data files. The document is presented by Getachew Hailu, an assistant professor of epidemiology in Ethiopia, and covers the contents of his presentation on using EpiData.
This document discusses qualitative data collection tools of document analysis and interviews. It provides an overview of document analysis, describing it as a systematic review of both printed and electronic materials to gain understanding. It also discusses different types of interviews including structured, semi-structured, and unstructured/in-depth interviews. For each type of interview, it outlines the advantages and disadvantages. Finally, it provides steps to conduct interviews such as defining objectives, selecting respondents, preparing questions, recording the interview, and organizing responses.
How to do a Literature search for your research and scientific publication BhaskarBorgohain4
Dr. Bhaskar Borgohain discusses strategies for conducting an effective literature search. He emphasizes defining a clear research question, brainstorming keywords, using appropriate search techniques like Boolean operators and filters, and keeping detailed records of the search process. Maintaining a search diary and using a citation manager are important for reproducing and organizing search results.
S. Venkataraman (DCC) talks about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). He discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
link to : dcc.ac.uk/resources
This document discusses bibliometrics, scientometrics, citation analysis, and content analysis. It defines bibliometrics as the quantitative study of recorded information and describes common tools used in bibliometrics like the Science Citation Index. Key variables that are studied include authors, origin, sources, contents, and citations. Important laws and methods in bibliometrics are also summarized, such as Lotka's Law, Bradford's Law, and Zipf's Law. Scientometrics is defined as the quantitative study of science output using bibliometric methods. Citation analysis examines citation patterns and links between scholarly works.
1) Mendeley is free academic software that allows users to organize documents and references, discover statistics and recommendations, and collaborate through groups.
2) It allows users to add documents to their library through dragging and dropping files, importing folders, or manually adding references, and fill in missing document details through lookups.
3) References can be searched, filtered, and cited in Word documents through a citation plugin, which automatically generates in-text citations and bibliographies in the chosen style.
Este documento describe los diferentes tipos de elementos que pueden contener un proyecto en NVivo. Estos incluyen recursos internos como notas de campo, entrevistas y videos; recursos externos como libros y artículos; memos para registrar observaciones e ideas; nodos para la codificación; atributos para casos; consultas; y modelos. También describe cómo se pueden organizar estos elementos en carpetas.
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.
This document provides an overview of how to analyze content using NVivo software. It discusses uploading documents to NVivo, coding the content into categories or nodes, and using tools like word frequency queries, text searches, and visualization to analyze relationships within and across texts. The goal of content analysis is to make inferences about messages, authors, audiences, and cultural contexts by systematically coding and examining texts.
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.
A PRESENTATION ON RESEARCH METHODS: SELECTION OF A RESEARCH TOPIC, FORMULATING A HYPOTHESIS, PHILOSOPHICAL ISSUES IN RESEARCH, QUANTITATIVE VS QUALITATIVE DEBATE & SELECTION OF A RESEARCH METHOD
Qualitative research - type of data, analysis of qualitative data, software f...Dr.Preeti Tiwari
This document provides an overview of qualitative research methods, including:
- Qualitative research seeks to understand people's experiences and interpretations of the world through methods like interviews and observation.
- There are several types of qualitative research designs including case studies, grounded theory, phenomenology, and ethnography.
- Data collection methods include interviews, focus groups, participant observation, and analysis involves coding data into themes and concepts.
- Qualitative research aims to gather rich descriptive data rather than numerical data, and the researcher plays a role in data collection and interpretation.
Here are the key points about informed consent:
- It is a process, not just a form. Researchers must ensure participants understand what participation involves through clear verbal and written explanations.
- Consent forms should be written in plain, easy-to-understand language appropriate for the population.
- Participants must be able to refuse or withdraw from the study without penalty.
- Risks and limitations of confidentiality should be clearly explained.
- Participants should have the opportunity to ask questions to fully comprehend what they are consenting to.
- Informed consent is an ongoing process, not a single event, with the option for participants to withdraw later.
The goal is to respect participants' autonomy by
This presentation discuss various methods of qualitative data analysis. it further digs various methods used in qualitative data analysis in some Ph.D. thesis i.e. practical part
This presentation summarizes how the presenter would analyze and present findings from 5 chat interviews conducted with a student regarding a university module's support in developing research skills. The presenter would collate the data by checking reliability, removing personal details, and transferring the data to a usable format. They would analyze the data by categorizing comments, carefully coding them, and potentially mapping relationships. Findings would be presented by establishing the research's validity and reliability, directly answering the research question, and extracting quotes to support conclusions. Both strengths like providing depth and weaknesses like potential bias are acknowledged.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
The document discusses the importance of data extraction in systematic reviews and provides guidance on developing effective data extraction forms and processes. Specifically, it outlines that data extraction 1) involves accurately summarizing studies in a common format to facilitate analysis and presentation, 2) identifies numerical data for meta-analyses, and 3) obtains information to assess risk of bias and applicability; and recommends 4) developing structured yet adaptable forms, 5) providing clear instructions, and 6) considering single versus double extraction.
This document discusses various quantitative data analysis techniques for research. It covers describing and summarizing data, identifying relationships between variables, comparing variables, and forecasting outcomes. The five most important methods are identified as mean, standard deviation, regression, sample size determination, and hypothesis testing. Parametric and non-parametric techniques are also discussed. Four levels of data measurement are defined: nominal, ordinal, interval, and ratio data. Examples are provided for coding nominal/ordinal data and visualizing data through graphs and charts. Statistical tests like the t-test, ANOVA, and chi-square are also summarized.
4 Literature Search Techniques 2 Strategic Searchingrichard kemp
The document discusses strategies for conducting an effective literature search. It covers searching academic literature to find relevant sources, avoiding duplicating previous work, and learning from other scholars' methods and approaches. Search techniques include keyword searches in digital libraries and databases, browsing relevant books and articles, and tracking citations between sources. The optimal search strategy depends on the topic's scope and available sources. Literature searches should become more focused and specialized over time to increase knowledge of the subject.
This document provides an overview of EpiData, a free and open-source software for designing questionnaires, entering data, and exporting data for analysis. It discusses the key features and functions of EpiData including creating questionnaires, setting up data entry checks, entering data, and exporting data files. The document is presented by Getachew Hailu, an assistant professor of epidemiology in Ethiopia, and covers the contents of his presentation on using EpiData.
This document discusses qualitative data collection tools of document analysis and interviews. It provides an overview of document analysis, describing it as a systematic review of both printed and electronic materials to gain understanding. It also discusses different types of interviews including structured, semi-structured, and unstructured/in-depth interviews. For each type of interview, it outlines the advantages and disadvantages. Finally, it provides steps to conduct interviews such as defining objectives, selecting respondents, preparing questions, recording the interview, and organizing responses.
How to do a Literature search for your research and scientific publication BhaskarBorgohain4
Dr. Bhaskar Borgohain discusses strategies for conducting an effective literature search. He emphasizes defining a clear research question, brainstorming keywords, using appropriate search techniques like Boolean operators and filters, and keeping detailed records of the search process. Maintaining a search diary and using a citation manager are important for reproducing and organizing search results.
S. Venkataraman (DCC) talks about the basics of Research Data Management and how to apply this when creating or reviewing a Data Management Plan (DMP). He discusses data formats and metadata standards, persistent identifiers, licensing, controlled vocabularies and data repositories.
link to : dcc.ac.uk/resources
This document discusses bibliometrics, scientometrics, citation analysis, and content analysis. It defines bibliometrics as the quantitative study of recorded information and describes common tools used in bibliometrics like the Science Citation Index. Key variables that are studied include authors, origin, sources, contents, and citations. Important laws and methods in bibliometrics are also summarized, such as Lotka's Law, Bradford's Law, and Zipf's Law. Scientometrics is defined as the quantitative study of science output using bibliometric methods. Citation analysis examines citation patterns and links between scholarly works.
1) Mendeley is free academic software that allows users to organize documents and references, discover statistics and recommendations, and collaborate through groups.
2) It allows users to add documents to their library through dragging and dropping files, importing folders, or manually adding references, and fill in missing document details through lookups.
3) References can be searched, filtered, and cited in Word documents through a citation plugin, which automatically generates in-text citations and bibliographies in the chosen style.
Este documento describe los diferentes tipos de elementos que pueden contener un proyecto en NVivo. Estos incluyen recursos internos como notas de campo, entrevistas y videos; recursos externos como libros y artículos; memos para registrar observaciones e ideas; nodos para la codificación; atributos para casos; consultas; y modelos. También describe cómo se pueden organizar estos elementos en carpetas.
Improving Your Literature Reviews with NVivo 10 for WindowsQSR International
Find out how NVivo supports you in writing robust literature reviews. Share the procedures and technology tools that a research team from three different universities used to complete four comprehensive scoping reviews of the literature.
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.
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.
Holistic Monitoring and Evaluation Data Driven and Gender Sensitive Mixed Met...QSR International
Holis&c M&E uses a gender sensi&ve, data driven approach with mixed methodologies to improve accountability, partnerships, and program learning. Key outcomes include increased transparency, sustainable results, and capacity building. NVivo so`ware helps code and analyze qualita&ve data, while STATA can import codes and run complementary quan&ta&ve analysis. The document provides &ps on using these tools at different stages of the M&E process.
Setting Up a Qualitative or Mixed Methods Research Project in NVivo 10 to Cod...Shalin Hai-Jew
This document summarizes a presentation on using NVivo 10 software to code and analyze qualitative and mixed methods research data. It introduces NVivo 10 as a data management and analysis tool, demonstrates how to import and code data from various sources, and shows how to visualize and analyze coded data through matrices, models, and queries. The goals are to introduce NVivo 10's capabilities and to demonstrate the process of setting up a project for qualitative or mixed methods research.
El documento presenta la experiencia de Jesús Manuel Gómez Pérez en convertir un proyecto secundario en una startup exitosa de agregación de entradas de conciertos llamada nvivo.es. Ofrece consejos para emprendedores como validar la idea, buscar financiación temprana, enfocarse en la escalabilidad, prepararse para una salida y centrarse en un único foco para el negocio.
Choosing the right software for your research study : an overview of leading ...Merlien Institute
Choosing the right software for your research study : an overview of leading CAQDAS packages by Christina Silver. This presentation is part of the proceedings of the International workshop on Computer-Aided Qualitative Research organised by Merlien Institute. This workshop was held on the 4-5 June in Utrecht, The Netherlands
Este documento presenta información sobre diversos programas de análisis cualitativo de datos. Describe brevemente las características y precios de programas como NVivo, Atlas.ti, MAXQDA, Dedoose y otros. También menciona algunas opciones de software libre como ELAN, EZ-Text y AnsSWR. El documento proporciona enlaces a los sitios web de los diferentes programas.
A workshop for academic librarians on using qualitative methods for user assessment and research in the library. Part 3 focuses on coding qualitative text in light of your research questions or goals, as well as highlights one option for qualitative research software.
Matrix Queries and Matrix Data Representations in NVivo 11 PlusShalin Hai-Jew
This slideshow, "Matrix Queries and Matrix Data Representations in NVivo 11 Plus," covers the following points:
Matrices and their basic structures
Types of elements (variables) for matrix comparisons
Setting up matrix queries in NVivo 11
Specific matrix “use cases” in qualitative and mixed methods research
Wrap-up
Researchers have long known that the words of a text have always contained more information than on the surface. As such, texts have been studied for subtexts and other latent or hidden information. One approach has involved the machine-enabled analysis of human sentiment, usually mapped out on a positive-negative polarity. NVivo 11 Plus (a qualitative research tool released in late 2015) enables the automated sentiment analysis of texts (coded research, formal articles, text corpora, Tweetstream datasets, Facebook wall posts, websites, and other sources) based on four categories: very positive, moderately positive, moderately negative, and very negative. The tool feature compares the target text set against a sentiment dictionary and enables coding at different units of analysis: sentence, paragraph, or cell. Further, the sentiment capability extracts the coded text into respective text sets which may be further analyzed using text frequency counts, text searches, automated theme and sub-theme extractions (topic modeling), and data visualizations.
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 discusses strategies for becoming a perfect candidate for programming interviews. It recommends developing strong coding and problem solving skills through online courses, side projects, hackathons and open source contributions. The document outlines preparing for different types of interview questions, including practicing data structures and algorithms, and how to approach problem solving questions in a structured way. It emphasizes the importance of communication skills and staying relaxed during the interview process.
The document provides an overview of grounded theory methods, noting the diversity of approaches that have developed since its introduction and highlighting key components of the methodology such as simultaneous data collection and analysis, coding practices, and grounding emerging theories in qualitative data to develop conceptual categories.
Formation au logiciel NVivo d'analyse de données qualitativesvaléry ridde
Le 20 mars dernier, la Chaire REALISME organisait à l'IRSPUM une formation donnée par Pierre Lefèvre, sociologue du Département de Santé Publique de l'Institut de Médecine Tropicale d'Annvers, pour les étudiants sur l'utilisation du logiciel d'analyse de données qualitatives NVivo.
Non-numerical – converse of quantitative data
Typically word based – but may include imagery, video, etc.
Can record attitudes, behaviours, experiences, motivations, etc.
Descriptive – describing events/opinions etc.
Explanatory – explaining events/opinions etc.
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.
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.
The document provides an overview of a one day workshop on qualitative data analysis using Atlas.ti 7. It discusses why qualitative research is useful, what Atlas.ti is and how it can help with analyzing qualitative data. The workshop covers topics such as setting up a project in Atlas.ti, importing different types of primary documents, organizing codes and families, creating codes and quotations, memo writing, network views and creating outputs. Attendees will learn practical skills for working with Atlas.ti to systematically analyze qualitative data.
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.
This document discusses using qualitative research software like WebCT and N6 to collect and analyze online discussion data. It outlines a three stage data collection strategy including open, axial, and selective coding. Advantages of computer assisted qualitative data analysis include organization, systematic approaches, and time savings. Disadvantages include complex software, loss of context, and potential data loss. The document demonstrates exporting discussion data, open coding to develop categories and properties, transforming free nodes to a tree structure, and using text searching to support research variables in analysis.
Using Computer as a Research Assistant in Qualitative ResearchJoshuaApolonio1
This document discusses using qualitative research software to collect and analyze online discussion data. It demonstrates exporting discussion data from WebCT into N6 for coding. A three-stage data collection strategy is outlined, beginning with open coding to generate categories and properties, then axial coding to interconnect categories, and ending with selective coding to build a theoretical model. Advantages of this approach include organization of large data sets and time savings, while disadvantages include complexity of software and potential to lose sight of data contexts.
The document summarizes Lynn Cherny's work setting up a data science program at emlyon business school. It discusses the courses taught in the first year of the program and plans for the next year. It also describes a student project analyzing job postings using skills extracted from text with word embeddings to identify gaps between teaching and job requirements. Ideas are proposed for improving the curriculum and student job searches.
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.
The document provides guidance on planning dissertation research by outlining a 5-step process: 1) describing the research topic, 2) identifying keywords, 3) identifying relevant databases and sources, 4) searching additional sources, and 5) searching databases using Boolean logic, limiters, truncation and alternative spellings. It emphasizes building search strategies iteratively and searching across journal databases to access up-to-date peer-reviewed research. Key databases recommended include Compendex, Web of Science, Business Source Premier and Emerald.
This workshop was presented in Riyadh, SA in 21-22 Jan 2019, with the collaboration with Riyadh Data Geeks group.
To learn more about the workshop please see this website:
http://bit.ly/2Ucjmm5
This document provides an overview of NVivo, a qualitative data analysis software package. It discusses what NVivo is and its main functions, including coding, memos, annotations, queries, and data visualization tools. The presentation also covers the pros and cons of using NVivo, how to get started with a project in NVivo by importing sources and creating nodes, and tips for planning a NVivo project by determining cases, attributes, thematic nodes, and important queries. Visualization tools demonstrated include charts, word clouds, word trees, and cluster 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 overview of using the qualitative data analysis software Nvivo. It discusses key aspects such as creating a new project, organizing sources, importing and coding text sources with nodes, visualizing nodes and sources, performing word queries, and exporting simple reports. The workshop aims to help researchers learn the basic functions and analysis techniques available in Nvivo to organize and analyze qualitative data.
This document provides an overview of using NVivo software for qualitative data analysis. It discusses key aspects such as creating a new project, organizing sources, importing and coding text sources with nodes, visualizing nodes and sources, performing word queries, and exporting simple reports. The workshop aims to help researchers learn the basic functions and analysis techniques using NVivo to effectively organize and analyze qualitative data.
Presentation for a seminar part of the AI in focus series at the University of Malmö in Sweden. It is about artificial intelligence and bias, and the implications for learning and teaching.
Presentación sobre conocimiento abierto y Wikipedia realizada en el marco de la Semana de la Educación Abierta 2025 (Open Education Week): +mujeres, +wikipedia, +ciencIA. Este evento se llevó a cabo en la Facultad de Psicología de la Universidad Autónoma de Nuevo León
Presentación impartida en el contexto de WikiEducación 2024, un evento en el que docentes nos reunimos para hablar sobre conocimiento abierto, organizado por el equipo de Wikimedia México.
Presentation for a session with Master's students at the University of Portsmouth. March 19, 2024
Based on a book chapter titled "Normativas de Educación a Distancia en México" by García Quezada, Espinosa de la Rosa & Padilla Rodríguez (in press)
Preliminary results of a twelve-year follow-up study on the acceptance of online degrees by undergraduate Mexican students.
2011 study: https://www.learntechlib.org/primary/p/37872/
Presentation for the Ed-Media 2023 conference
Presentación para la sexta sesión del taller "Inteligencia artificial y sus usos en educación superior".
Se inicia con una revisión de la actividad de una sesión anterior.
Tema: Plan para la implementación
Duración aproximada: 2 horas
Se concluye con una actividad asincrónica de 1 hora
Audiencia meta: Docentes y equipo de apoyo pedagógico de una universidad
Presentación para la quinta sesión del taller "Inteligencia artificial y sus usos en educación superior".
Se inicia con una revisión de la actividad de una sesión anterior.
Tema: Guías y lineamientos
Duración aproximada: 2 horas
Se concluye con una actividad asincrónica de 1 hora
Audiencia meta: Docentes y equipo de apoyo pedagógico de una universidad
Presentación para la cuarta sesión del taller "Inteligencia artificial y sus usos en educación superior".
Se inicia con una revisión de la actividad de una sesión anterior.
Tema: Retos y preocupaciones
Duración aproximada: 2 horas
Se concluye con una actividad asincrónica de 1 hora
Audiencia meta: Docentes y equipo de apoyo pedagógico de una universidad
Presentación para la primera sesión del taller "Inteligencia artificial y sus usos en educación superior".
Tema: Aplicaciones en aprendizaje y enseñanza
Duración aproximada: 2 horas
Se concluye con una actividad asincrónica de 1 hora
Audiencia meta: Docentes y equipo de apoyo pedagógico de una universidad
Presentación para la primera sesión del taller "Inteligencia artificial y sus usos en educación superior".
Tema: Panorama general
Duración aproximada: 2 horas
Se concluye con una actividad asincrónica de 1 hora
Audiencia meta: Docentes y equipo de apoyo pedagógico de una universidad
Presentación para estudiantes universitarios sobre la importancia de la investigación cuantitativa, con un enfoque en el uso de escalas Likert y su análisis.
This document discusses quantitative research methods, including learning analytics data sources like grades, forum posts, resource clicks and video watch times. It covers questionnaires, Likert scales, developing accurate scales, advantages like ease of analysis, disadvantages like oversimplification. It recommends identifying and removing mistakes from survey responses like incomplete answers. Data analysis is discussed, like interpreting average results on a scale. Other tests mentioned are correlations, regressions, t-tests and ANOVA. Ensuring valid educational research is challenging given potential confounding variables from human diversity. Lab studies also have limitations.
Presentation on how to code qualitative data. We examine two approaches: inductive (emergent themes) and deductive coding (theory-based). There are some activities you can use. Feel free to use and share.
Este documento trata sobre la identidad virtual y sus aspectos personales, académicos y laborales. La identidad virtual puede reflejar la realidad o no a través de nombres de usuario y avatares. Tiene beneficios como evitar prejuicios e inclusión social, pero también riesgos como fraudes, robo de identidad e inconsistencia con la vida real. Se recomienda ser consistente en los nombres y fotos usados, cuidar la privacidad y no compartir información que podría afectar la reputación personal o laboral.
Este documento presenta la metodología de un curso sobre investigación de proyectos. Incluye una introducción al curso, cronograma de temas como introducción a la investigación aplicada, búsqueda de artículos, formato APA y diseños de investigación. También describe herramientas como Google Drive, Twitter y un blog para compartir conocimientos. Finalmente, explica el proceso general de investigación que incluye planteamiento del problema, marco teórico y metodología.
Este documento presenta una agenda para una clase sobre cognición y tecnologías educativas. La agenda incluye una presentación, características de la clase, alfabetismo digital, entornos personales de aprendizaje, y evidencias de aprendizaje. El documento también discute el uso de tecnologías en México, elementos del alfabetismo digital, saberes digitales, entornos personales de aprendizaje, y cursos masivos en línea abiertos.
Presentación para el 3er Encuentro de WikiEducación organizado por Wikimedia México. Describo las experiencias organizando editatones en varias universidades mexicanas.
Módulo 2 del Taller "Estrategias para cursos en línea efectivos", impartido para una empresa. Revisamos un poco del diseño de cursos y cómo mejorar el uso de Storyline de Articulate
Presentación para un taller para maestros. Durante la sesión, identificamos los cambios en la educación a partir de la pandemia del Covid-19, revisamos algunas tendencias y reflexionamos sobre el futuro. Ahondamos un poco en el modelo hyflex.
Computer crime and Legal issues Computer crime and Legal issuesAbhijit Bodhe
• Computer crime and Legal issues: Intellectual property.
• privacy issues.
• Criminal Justice system for forensic.
• audit/investigative.
• situations and digital crime procedure/standards for extraction,
preservation, and deposition of legal evidence in a court of law.
Happy May and Happy Weekend, My Guest Students.
Weekends seem more popular for Workshop Class Days lol.
These Presentations are timeless. Tune in anytime, any weekend.
<<I am Adult EDU Vocational, Ordained, Certified and Experienced. Course genres are personal development for holistic health, healing, and self care. I am also skilled in Health Sciences. However; I am not coaching at this time.>>
A 5th FREE WORKSHOP/ Daily Living.
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Hopefully Before Summer, We can add our courses to the teacher/creator section. It's all within project management and preps right now. So wish us luck.
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Currency is Euro. Courses can be free unlimited. Only pay for your diploma. See Website for xtra assistance.
Make sure to convert your cash. Online Wallets do vary. I keep my transactions safe as possible. I do prefer PayPal Biz. (See Site for more info.)
Understanding Vibrations
If not experienced, it may seem weird understanding vibes? We start small and by accident. Usually, we learn about vibrations within social. Examples are: That bad vibe you felt. Also, that good feeling you had. These are common situations we often have naturally. We chit chat about it then let it go. However; those are called vibes using your instincts. Then, your senses are called your intuition. We all can develop the gift of intuition and using energy awareness.
Energy Healing
First, Energy healing is universal. This is also true for Reiki as an art and rehab resource. Within the Health Sciences, Rehab has changed dramatically. The term is now very flexible.
Reiki alone, expanded tremendously during the past 3 years. Distant healing is almost more popular than one-on-one sessions? It’s not a replacement by all means. However, its now easier access online vs local sessions. This does break limit barriers providing instant comfort.
Practice Poses
You can stand within mountain pose Tadasana to get started.
Also, you can start within a lotus Sitting Position to begin a session.
There’s no wrong or right way. Maybe if you are rushing, that’s incorrect lol. The key is being comfortable, calm, at peace. This begins any session.
Also using props like candles, incenses, even going outdoors for fresh air.
(See Presentation for all sections, THX)
Clearing Karma, Letting go.
Now, that you understand more about energies, vibrations, the practice fusions, let’s go deeper. I wanted to make sure you all were comfortable. These sessions are for all levels from beginner to review.
Again See the presentation slides, Thx.
Ajanta Paintings: Study as a Source of HistoryVirag Sontakke
This Presentation is prepared for Graduate Students. A presentation that provides basic information about the topic. Students should seek further information from the recommended books and articles. This presentation is only for students and purely for academic purposes. I took/copied the pictures/maps included in the presentation are from the internet. The presenter is thankful to them and herewith courtesy is given to all. This presentation is only for academic purposes.
The insect cuticle is a tough, external exoskeleton composed of chitin and proteins, providing protection and support. However, as insects grow, they need to shed this cuticle periodically through a process called moulting. During moulting, a new cuticle is prepared underneath, and the old one is shed, allowing the insect to grow, repair damaged cuticle, and change form. This process is crucial for insect development and growth, enabling them to transition from one stage to another, such as from larva to pupa or adult.
What makes space feel generous, and how architecture address this generosity in terms of atmosphere, metrics, and the implications of its scale? This edition of #Untagged explores these and other questions in its presentation of the 2024 edition of the Master in Collective Housing. The Master of Architecture in Collective Housing, MCH, is a postgraduate full-time international professional program of advanced architecture design in collective housing presented by Universidad Politécnica of Madrid (UPM) and Swiss Federal Institute of Technology (ETH).
Yearbook MCH 2024. Master in Advanced Studies in Collective Housing UPM - ETH
How to Configure Public Holidays & Mandatory Days in Odoo 18Celine George
In this slide, we’ll explore the steps to set up and manage Public Holidays and Mandatory Days in Odoo 18 effectively. Managing Public Holidays and Mandatory Days is essential for maintaining an organized and compliant work schedule in any organization.
How to Add Customer Note in Odoo 18 POS - Odoo SlidesCeline George
In this slide, we’ll discuss on how to add customer note in Odoo 18 POS module. Customer Notes in Odoo 18 POS allow you to add specific instructions or information related to individual order lines or the entire order.
This slide is an exercise for the inquisitive students preparing for the competitive examinations of the undergraduate and postgraduate students. An attempt is being made to present the slide keeping in mind the New Education Policy (NEP). An attempt has been made to give the references of the facts at the end of the slide. If new facts are discovered in the near future, this slide will be revised.
This presentation is related to the brief History of Kashmir (Part-I) with special reference to Karkota Dynasty. In the seventh century a person named Durlabhvardhan founded the Karkot dynasty in Kashmir. He was a functionary of Baladitya, the last king of the Gonanda dynasty. This dynasty ruled Kashmir before the Karkot dynasty. He was a powerful king. Huansang tells us that in his time Taxila, Singhpur, Ursha, Punch and Rajputana were parts of the Kashmir state.
How to Configure Scheduled Actions in odoo 18Celine George
Scheduled actions in Odoo 18 automate tasks by running specific operations at set intervals. These background processes help streamline workflows, such as updating data, sending reminders, or performing routine tasks, ensuring smooth and efficient system operations.
pulse ppt.pptx Types of pulse , characteristics of pulse , Alteration of pulsesushreesangita003
what is pulse ?
Purpose
physiology and Regulation of pulse
Characteristics of pulse
factors affecting pulse
Sites of pulse
Alteration of pulse
for BSC Nursing 1st semester
for Gnm Nursing 1st year
Students .
vitalsign
Lecture 2 CLASSIFICATION OF PHYLUM ARTHROPODA UPTO CLASSES & POSITION OF_1.pptxArshad Shaikh
*Phylum Arthropoda* includes animals with jointed appendages, segmented bodies, and exoskeletons. It's divided into subphyla like Chelicerata (spiders), Crustacea (crabs), Hexapoda (insects), and Myriapoda (millipedes, centipedes). This phylum is one of the most diverse groups of animals.
Link your Lead Opportunities into Spreadsheet using odoo CRMCeline George
In Odoo 17 CRM, linking leads and opportunities to a spreadsheet can be done by exporting data or using Odoo’s built-in spreadsheet integration. To export, navigate to the CRM app, filter and select the relevant records, and then export the data in formats like CSV or XLSX, which can be opened in external spreadsheet tools such as Excel or Google Sheets.
How to Manage Purchase Alternatives in Odoo 18Celine George
Managing purchase alternatives is crucial for ensuring a smooth and cost-effective procurement process. Odoo 18 provides robust tools to handle alternative vendors and products, enabling businesses to maintain flexibility and mitigate supply chain disruptions.
Form View Attributes in Odoo 18 - Odoo SlidesCeline George
Odoo is a versatile and powerful open-source business management software, allows users to customize their interfaces for an enhanced user experience. A key element of this customization is the utilization of Form View attributes.
Rock Art As a Source of Ancient Indian HistoryVirag Sontakke
This Presentation is prepared for Graduate Students. A presentation that provides basic information about the topic. Students should seek further information from the recommended books and articles. This presentation is only for students and purely for academic purposes. I took/copied the pictures/maps included in the presentation are from the internet. The presenter is thankful to them and herewith courtesy is given to all. This presentation is only for academic purposes.
2. Aims of this workshop
Explore the basic functions of Nvivo:
Adding data sources.
Creating a node tree.
Coding.
Create a project.
Practice deductive and inductive qualitative data
coding using NVivo.
2
3. Establishing a common language
Qualitative analysis
Identification, examination and interpretation of themes in the data to
answer research questions.
Themes
Patterns in the data
Nodes (also called codes!)
Usually a word or short phrase that captures the essence or salient
attributes of a portion of data.
Coding
Process of assigning nodes to data
3
4. What is NVivo?
It is a qualitative data analysis software.
It is useful for coding…
o Interviews
o Messages in a discussion forum
o Focus group sessions
o Documents
o And more!
4
5. Let’s start!
Objective
To evaluate participants’ course expectations before delivery.
Data sources
http://tinyurl.com/nvivo-sd
Idea of how to code
Inductive (emergent themes)
Deductive (based on theory)
5
6. Basics
Create a node tree for online experience (low, medium,
high).
Select parent node and the click on Create > Node.
Code online learning experience.
Analyze > Code selection at > Existing node
6
DONE?
Create a journal to keep track of your research progress. Include
the objective of this exercise (to evaluate participants’ expectations
before the course).
Create > Memos
7. Induction (emergent themes)
Code participants’ course expectations.
Read data sources, identify themes, create nodes and then code:
Analyze > Code selection at > Existing node
Code as you go: Analyze > Code In Vivo
Compare your nodes with a colleague.
Find examples of your codes by double-clicking a node.
7
DONE?
Record extra notes. Example: North-S4 is excited about online
learning. Is this an opportunity that should be taken advantage of?
Add an annotation about it!
Analyze > New Annotation
8. Deduction (theory based)
Check coding scheme: http://tinyurl.com/nvivo-cs
Match your node tree to the coding scheme.
Rename: Right click - Node properties
Delete nodes you don’t need or use an “other” node.
Compare your coding with a colleague.
What were the main course expectations of participants?
8
DONE?
Read about inter-rater reliability in Nvivo:
http://tinyurl.com/nvivo-ir
(Warning: Advanced stuff!)
9. Extra!
Add data sources 6-7 (image and audio).
External data > Pictures
External data > Audio
Code by selecting parts of the image or the audio
(you can have a transcript there).
Check how the code examples are provided
(coordinates in images and time in audios).
9
#3: Thanks to the people who answered the survey. Most were from health, psychology, social work.
Two people mentioned “Mind Meld” as special request for the workshop.
#5: Nvivo helps store, classify and categorise data
Surveys: Texts, audio and images
Feel free to use your own data for coding
#6: Data sources: can include text, video, audio or pictures