A Meta Synthesis of Content Analysis Approaches
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Getting Started Guide Version 2.4 (November 2020) 1
Quirkos Getting started guide Version 2.4 (November 2020) 1 Contents Introduction p2 Installation p3 Your first project p4 Button by button guide p6 Step-by-step guide p7 Exports and reports p12 Tips and Tricks p13 Next Steps p14 2 Introduction Quirkos is a simple and visual tool to help with the qualitative analysis of text data. It is identical on Windows, Mac and Linux, so this guide applies to all platforms. Here are a few things to bear in mind as you learn Quirkos for the first time: Quirkos can store your projects in our secure cloud server, or in one project file on your computer. Everything is in one file for easy backup and sharing. Quirkos saves your work as you go, so there is no manual save button, but no risk of losing your work. Add your data to the project from txt, rtf, csv, Word (docx) or PDF files, or copy and paste from any other source. Describe your sources in any way with the source properties, such as age or gender, or type of source and comments. Your themes or topics are shown as bubbles on the left side of the screen. As you drag and drop sections of text to them they will grow. Drag and drop text onto the Memos column to add a note and record your thoughts and observations At any stage of your coding, you can create many different types of exports: detailed reports, coded transcripts for Word, or spreadsheets for statistical analysis. 3 Installation You can download the full version of Quirkos from our website, or from one of our USB sticks. -
Qualitative Data Analysis Software: a Call for Understanding, Detail, Intentionality, and Thoughtfulness
MSVU e-Commons ec.msvu.ca/xmlui Qualitative data analysis software: A call for understanding, detail, intentionality, and thoughtfulness Áine M. Humble Version Post-print/Accepted manuscript Citation Humble, A. M. (2012). Qualitative data analysis software: A call for (published version) understanding, detail, intentionality, and thoughtfulness. Journal of Family Theory & Review, 4(2), 122-137. doi:10. 1111/j.1756- 2589.2012.00125.x Publisher’s Statement This article may be downloaded for non-commercial and no derivative uses. This article appears in the Journal of Family Theory and Review, a journal of the National Council on Family Relations; copyright National Council on Family Relations. How to cite e-Commons items Always cite the published version, so the author(s) will receive recognition through services that track citation counts. If you need to cite the page number of the author manuscript from the e-Commons because you cannot access the published version, then cite the e-Commons version in addition to the published version using the permanent URI (handle) found on the record page. This article was made openly accessible by Mount Saint Vincent University Faculty. Qualitative Data Analysis Software 1 Humble, A. M. (2012). Qualitative data analysis software: A call for understanding, detail, intentionality, and thoughtfulness. Journal of Family Theory & Review, 4(2), 122-137. doi:10. 1111/j.1756-2589.2012.00125.x This is an author-generated post-print of the article- please refer to published version for page numbers Abstract Qualitative data analysis software (QDAS) programs have gained in popularity but family researchers may have little training in using them and a limited understanding of important issues related to such use. -
Qualitative Research 1
Qualitative research 1 Dr Raqibat Idris, MBBS, DO, MPH Geneva Foundation for Medical Education and Research 28 November 2017 From Research to Practice: Training Course in Sexual and Reproductive Health Research Geneva Workshop 2017 Overview of presentation This presentation will: • Introduce qualitative research, its advantages, disadvantages and uses • Discuss the various approaches to qualitative design Introduction • Qualitative research is a study done to explain and understand the meaning or experience of a phenomenon or social process and the viewpoints of the affected individuals. • Investigates opinions, feelings and experiences. • Understands and describes social phenomena in their natural occurrence- holistic approach. • Does not test theories but can develop theories. Mason, 2002 Features of qualitative research • Exploratory • Fluid and flexible • Data-driven • Context sensitive • Direct interaction with affected individuals Mason, 2002 Advantages and disadvantages Advantages: • Richer information • Deeper understanding of the phenomenon under study Disadvantages: • Time consuming • Expensive • Less objective • Findings cannot be generalized Mason, 2002 Uses of qualitative studies Exploratory or pilot study: • Precedes a quantitative study to help refine hypothesis • Pilot study to examine the feasibility of a program/ project implementation • Designing survey questionnaires • To improve the reliability, validity and sensibility of new or existing survey instruments in a new population Green, 2013 Uses of qualitative studies To explain quantitative data findings: • Can follow a quantitative research to help provide a deeper understanding of the results. For example, the use of ethnography to explain the social context in which mortality and birth rate data are produced. • Parallel studies in a mixed qualitative and quantitative design to provide greater understanding of a phenomenon under study. -
Current Issues in Qualitative Data Analysis Software (QDAS): a User and Developer Perspective
The Qualitative Report Volume 23 Number 13 Article 5 3-6-2018 Current Issues in Qualitative Data Analysis Software (QDAS): A User and Developer Perspective Jeanine C. Evers Erasmus University of Rotterdam, [email protected] Follow this and additional works at: https://nsuworks.nova.edu/tqr Part of the Law Commons, Quantitative, Qualitative, Comparative, and Historical Methodologies Commons, and the Social Statistics Commons Recommended APA Citation Evers, J. C. (2018). Current Issues in Qualitative Data Analysis Software (QDAS): A User and Developer Perspective. The Qualitative Report, 23(13), 61-73. https://doi.org/10.46743/2160-3715/2018.3205 This Article is brought to you for free and open access by the The Qualitative Report at NSUWorks. It has been accepted for inclusion in The Qualitative Report by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Current Issues in Qualitative Data Analysis Software (QDAS): A User and Developer Perspective Abstract This paper describes recent issues and developments in Qualitative Data Analysis Software (QDAS) as presented in the opening plenary at the KWALON 2016 conference. From a user perspective, it reflects current features and functionality, including the use of artificial intelligence and machine learning; implications of the cloud; user friendliness; the role of digital archives; and the development of a common exchange format. This user perspective is complemented with the views of software developers who took part in the “Rotterdam Exchange Format Initiative,” an outcome of the conference. Keywords Qualitative Data Analysis Software, QDAS, Artificial Intelligence, Machine Learning, TLA AS.ti, Cassandre, Dedoose, f4analyse, MAXQDA, NVivo, QDA Miner, Quirkos, Transana, Exchange format, Interoperability, Qualitative Data Analysis, Learning Curve QDAS, Textual Data Mining, Cloud services. -
The Value of CAQDAS for Systematising Literature Reviews
BY DR. CHRISTINA SILVER, [email protected] RESEARCH FELLOW, UNIVERSITY OF SURREY The value of CAQDAS for systematising literature reviews Software designed to facilitate qualitative and mixed methods research is collectively known as CAQDAS Undertaking a literature review is similar to con- (Computer Assisted Qualitative Data AnalysiS). ducting a qualitative data analysis (QDA) in terms Available since the 1980s it provides tools designed of the analytic activities involved (Table 2.). Specific to support a range of analytic activities across disci- analytic requirements should drive the way tools are plines and sectors. Using references from bibliographic used rather than the availability of product features software (e.g. Endnote, Zotero, Mendeley) enables systematic literature reviewing, integrated with data Table 2. analysis. This article outlines some possibilities, high- Analytic activities supported by CAQDAS lighting considerations in planning a literature review for librarians and others. Integration revy revy • Bring together all relevant material into one “workspace” • Quantify qualitative data / qualify quantitative data 01 2016 01 What CAQDAS packages “do”? Organisation The acronym “CAQDAS” is misleading because • Manage facts about data (metadata, socio-demo- these programs do not “do” analysis; users remain in graphics etc.) control of and responsible for everything. It’s there- • Represent ideas that form the basis of analysis fore better to think of them as project management tools. Harnessing CAQDAS powerfully involves their Exploration use from start to finish, whether for an academic • Familiarise with data study, service evaluation, public consultation, liter- • Access and mark inherent structure ature review, or anything else. Each program has a suite of features, too many to list here. -
Qualitative Data Sharing and Re-Use for Socio-Environmental Systems Research: a Synthesis of Opportunities, Challenges, Resources and Approaches
Qualitative data sharing and re-use for socio-environmental systems research: A synthesis of opportunities, challenges, resources and approaches SESYNC WHITE PAPER Lead authors: Kristal Jones and Steven M. Alexander National Socio-Environmental Synthesis Center Lead authors: Kristal Jones (SESYNC) and Steven M. Alexander (Science Advisor, Canadian Department of Fisheries and Oceans) Contributing authors (in alphabetical order): Nathan Bennett (University of British Columbia and Stanford University), Libby Bishop (UK Data Service and UK Data Archive - University of Essex), Amber Budden (DataONE), Michael Cox (Dartmouth University), Mercè Crosas (Harvard University), Eddie Game (The Nature Conservancy), Janis Geary (University of Alberta), Charlie Hahn (University of Washington), Dean Hardy (SESYNC), Jay Johnson (University of Kansas), Sebastian Karcher (Qualitative Data Repository), Matt LaFevor (University of Alabama), Nicole Motzer (SESYNC), Patricia Pinto da Silva (NOAA), Jeremy Pittman (University of Waterloo), Heather Randell (SESYNC), Julie Silva (University of Maryland), Joseph Smith (University of Maryland), Mike Smorul (Nava Public Benefit Corporation, formerly at SESYNC), Carly Strasser (Collaborative Knowledge Foundation), Colleen Strawhacker (National Snow & Ice Data Center), Andrew Stuhl (Bucknell University), Nicholas Weber (University of Washington), Deborah Winslow (National Science Foundation) This white paper present a summary and extension of discussions that occurred during a workshop supported by the National Socio-Environmental Synthesis Center (SESYNC) and held at the SESYNC offices in Annapolis, MD on February 28-March 2, 2017. All contributing authors listed below were workshop participants, and so contributed to the discussion that informed and/or writing of the white paper. The National Socio-Environmental Synthesis Center (SESYNC) is supported under funding received from the National Science Foundation DBI-1052875. -
Ethnography As an Inquiry Process in Social Science
ETHNOGRAPHY AS AN INQUIRY PROCESS IN SOCIAL SCIENCE RESEARCH Ganga Ram Gautam ABSTRACT This article is an attempt to present the concept of ethnography as a qualitative inquiry process in social science research. The paper begins with the introduction to ethnography followed by the discussion of ethnography both as an approach and a research method. It then illustrates how ethnographic research is carried out using various ethnographic methods that include participant observation, interviewing and collection of the documents and artifacts. Highlighting the different ways of organizing, analyzing and writing ethnographic data, the article suggests ways of writing the ethnographic research. THE INQUIRY PROCESS Inquiry process begins consciously and/or subconsciously along with the beginning of human life. The complex nature of our life, problems and challenges that we encounter both in personal and professional lives and the several unanswered questions around us make us think and engage in the inquiry process. Depending upon the nature of the work that one does and the circumstances around them, people choose the inquiry process that fits into their inquiry framework that is built upon the context they are engaged in. This inquiry process in education is termed as research and research in education has several dimensions. The inquiry process in education is also context dependent and it is driven by the nature of the inquiry questions that one wants to answer. UNDERSTANDING ETHNOGRAPHY Ethnography, as a form of qualitative research, has now emerged as one of the powerful means to study human life and social behavior across the globe. Over the past fifteen years there has been an upsurge of ethnographic work in British educational research, making ethnography the most commonly practiced qualitative research method. -
Research Techniques in Network and Information Technologies, February
Tools to support research M. Antonia Huertas Sánchez PID_00185350 CC-BY-SA • PID_00185350 Tools to support research The texts and images contained in this publication are subject -except where indicated to the contrary- to an Attribution- ShareAlike license (BY-SA) v.3.0 Spain by Creative Commons. This work can be modified, reproduced, distributed and publicly disseminated as long as the author and the source are quoted (FUOC. Fundació per a la Universitat Oberta de Catalunya), and as long as the derived work is subject to the same license as the original material. The full terms of the license can be viewed at http:// creativecommons.org/licenses/by-sa/3.0/es/legalcode.ca CC-BY-SA • PID_00185350 Tools to support research Index Introduction............................................................................................... 5 Objectives..................................................................................................... 6 1. Management........................................................................................ 7 1.1. Databases search engine ............................................................. 7 1.2. Reference and bibliography management tools ......................... 18 1.3. Tools for the management of research projects .......................... 26 2. Data Analysis....................................................................................... 31 2.1. Tools for quantitative analysis and statistics software packages ...................................................................................... -
The Quest for Collaborative Ministry in the Church in Wales
The quest for collaborative ministry: an investigation into an elusive practice in the Church in Wales Item Type Thesis or dissertation Authors Adams, Stephen, A. Citation Adams, S, P. (2019). The quest for collaborative ministry: an investigation into an elusive practice in the Church in Wales (Doctoral dissertation). University of Chester, UK. Publisher University of Chester Rights Attribution-NonCommercial-NoDerivatives 4.0 International Download date 30/09/2021 15:35:27 Item License http://creativecommons.org/licenses/by-nc-nd/4.0/ Link to Item http://hdl.handle.net/10034/623501 The quest for collaborative ministry: an investigation into an elusive practice in the Church in Wales Thesis submitted in accordance with the requirements of the University of Chester for the degree of Doctor of Professional Studies in Practical Theology by Stephen Paul Adams July 2019 2 “The material being presented for examination is my own work and has not been submitted for an award of this or another HEI except in minor particulars which are explicitly noted in the body of the thesis. Where research pertaining to the thesis was undertaken collaboratively, the nature and extent of my individual contribution has been made explicit.” 30th July 2019 3 Contents Table of Figures ........................................................................................................ 7 Acknowledgements .................................................................................................. 8 Abstract .................................................................................................................. -
Predictive Analytics
BUTLER A N A L Y T I C S BUSINESS ANALYTICS YEARBOOK 2015 Version 2 – December 2014 Business Analytics Yearbook 2015 BUTLER A N A L Y T I C S Contents Introduction Overview Business Intelligence Enterprise BI Platforms Compared Enterprise Reporting Platforms Open Source BI Platforms Free Dashboard Platforms Free MySQL Dashboard Platforms Free Dashboards for Excel Data Open Source and Free OLAP Tools 12 Cloud Business Intelligence Platforms Compared Data Integration Platforms Predictive Analytics Predictive Analytics Economics Predictive Analytics – The Idiot's Way Why Your Predictive Models Might be Wrong Enterprise Predictive Analytics Platforms Compared Open Source and Free Time Series Analytics Tools Customer Analytics Platforms Open Source and Free Data Mining Platforms Open Source and Free Social Network Analysis Tools Text Analytics What is Text Analytics? Text Analytics Methods Unstructured Meets Structured Data Copyright Butler Analytics 2014 2 Business Analytics Yearbook 2015 BUTLER A N A L Y T I C S Business Applications Text Analytics Strategy Text Analytics Platforms Qualitative Data Analysis Tools Free Qualitative Data Analysis Tools Open Source and Free Enterprise Search Platforms Prescriptive Analytics The Business Value of Prescriptive Analytics What is Prescriptive Analytics? Prescriptive Analytics Methods Integration Business Application Strategy Optimization Technologies Business Process Management * Open Source BPMS * About Butler Analytics * Version 2 additions are Business Process Management and Open Source BPMS This Year Book is updated every month, and is freely available until November 2015. Production of the sections dealing with Text Analytics and Prescriptive Analytics was supportedFICO by . Copyright Butler Analytics 2014 3 Business Analytics Yearbook 2015 BUTLER A N A L Y T I C S Introduction This yearbook is a summary of the research published on the Butler Analytics web site during 2014. -
Quirkos 2.1: Distinguishing Features and Functions
Software Reviews: Quirkos 2.1 Quirkos 2.1: Distinguishing features and functions This document is intended to be read in conjunction with the ‘Choosing a CAQDAS Package Working Paper’ which provides a more general commentary of common CAQDAS functionality. This document does not provide an exhaustive account of all the features and functions provided by Quirkos but is designed to highlight some of its distinguishing elements. The Comment section at the end details our opinions on certain aspects of functionality and usability. See also Silver & Lewins (2014) Using Software in Qualitative Research: A Step-by-Step Guide, Sage Publications and software developer website. This document reviews Quirkos version 2.1. Many thanks to Daniel Turner for reviewing this document for accuracy. Background http://www.quirkos.com/ Quirkos was developed by Daniel Turner and colleagues in response to what they saw as frustrations with existing CAQDAS packages ■ The company Quirkos was founded in 2013 and the public release of the first version of the software was in October 2014 ■ Developmental impetus was framed by a desire to design tools that open up qualitative analysis to everyone. The aim of Quirkos therefore is to provide software that is accessible to those without extensive research experience, as well as those working within professional research contexts, that is easy to use and that works across platforms ■ The pricing structure for Quirkos is considerably lower than most other CAQDAS packages ■ Quirkos works on Windows, Mac and Linux platforms ■ Quirkos runs on a local installation of the software ■ Future development will include a collaborative cloud version enabling team-members to work concurrently on the same Quirkos project. -
The New Face of Qualitative Research Software QSR Has Released Version Two of Xsight the Very Latest in Software from QSR Is Version Two of Xsight
The QSR Newsletter, Issue 30, November 2006 The New Face of Qualitative Research Software QSR has released version two of XSight The very latest in software from QSR is version two of XSight. Released in October 2006, XSight now has a new look and new enhancements designed to help you get from information to insight faster. While we originally designed XSight Designed to set the standard In This Issue as a sophisticated and portable We’ve redesigned the software interface The new face of qualitative 1 workspace for market researchers, in XSight 2 using Windows XP guidelines. today the program is used in a range This gives it a familiar look that makes research software of other industries that deal with it easy to learn and easy to use, even Message from the CEO 2 unstructured information, including if you’re new to research software. HR, law and tourism. Its streamlined interface is now more XSight – Getting you from 3 flexible too, letting you rearrange information to insight faster the layout to suit your working style. Getting started in XSight 4 University of Southampton 5 gives marketing students the edge in Europe NVivo 7: Coding 6 Policy Studies Institute adopts 7 NVivo 7 Conferences and events 8 In Their Own Words Qualitative research in the financial 9 & 10 services industry with XSight Using NVivo 7 to analyze 11 educational dialogue We’ve also included a range of powerful new tools that allow you to structure your data, organize your thoughts and build on your ideas like never before. Turn to pages 3 and 4 to read more.