Making Meaning from Your Data
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Engaging in Qualitative Research Methods: Opportunities for Prevention and Health Promotion
Engaging in Qualitative Research Methods: Opportunities for Prevention and Health Promotion LeConté J. Dill, DrPH, MPH Assistant Professor Department of Community Health Sciences SUNY Downstate School of Public Health Learning Objectives O Describe personal values, life experiences, and professional activities that inform one’s research standpoint O Describe the value of engaging in qualitative research methods O Describe ethical concerns in qualitative research O Discuss the data collection and analytical procedures inherent in each approach of qualitative inquiry Qualitative Research O Shaped by both the subjects’ and researcher’s O Personal experience O Age O Gender O Race/ethnicity O Social class O Sexuality O Biases Peshkin, 1988; Merriam, 2002; Charmaz, 2004 What is Qualitative Research? O Long tradition in: anthropology, sociology, and clinical psychology O Emerging in: public health, medicine, nursing, education, and management O Concentrates on words and observations to express reality O Describes people in natural situations and settings O Asks: O What? O Why? O How? Peshkin, 1988; Merriam, 2002; Charmaz, 2004 The Role of Theory & Qualitative Research O Theory as a starting point for scrutiny rather than for application O The best qualitative studies are theoretically informed O Generate new theoretical insights through qualitative methods Charmaz, 2004; Denzin & Lincoln,2011 “While quantitative research can tell us much about the incidence and outcomes of disease, it cannot answer how to get patients to use medication when -
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 Coding Manual for Qualitative Researchers for Manual Coding The
2E Second Edition The Coding Manual for Qualitative Researchers ‘This book fills a major gap in qualitative research methods courses. Saldaña has accomplished what has not been done before - creating a text that clearly identifies the many choices one has in coding their data. I wish I had this book when I started conducting qualitative research. It should be required reading for all.’ Mark Winton, Criminal Justice Instructor, University of Central Florida ‘An excellent handbook that helps demystify the coding process with a comprehensive assessment of different coding types, examples and exercises. As such it is a valuable teaching resource and it will also be of use to anyone undertaking qualitative analysis.’ Kevin Meethan, Associate Professor in Sociology, Plymouth University The ‘The Coding Manual describes the qualitative coding process with clarity and expertise. Its wide array of strategies, from the more straightforward to the more complex, are skillfully explained and exemplified. This extremely usable manual is a must-have resource for qualitative researchers at all levels.’ Coding Manual for Tara M. Brown, Assistant Professor of Education, Brandeis University The second edition of Johnny Saldaña’s international bestseller provides an in-depth guide to the Qualitative Researchers multiple approaches available for coding qualitative data. Fully up-to-date, it includes new chapters, more coding techniques and an additional glossary. Clear, practical and authoritative, the book: • Describes how coding initiates qualitative data analysis • Demonstrates the writing of analytic memos • Discusses available analytic software • Suggests how best to use The Coding Manual for Qualitative Researchers for particular studies In total, 32 coding methods are profiled that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. -
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 ...................................................................................... -
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. -
A Meta Synthesis of Content Analysis Approaches
American Journal of Educational Research, 2018, Vol. 6, No. 6, 632-637 Available online at http://pubs.sciepub.com/education/6/6/8 ©Science and Education Publishing DOI:10.12691/education-6-6-8 A Meta Synthesis of Content Analysis Approaches G. Manimozhi, P. Srinivasan* Department of Education, Central University of Tamil Nadu, Thiruvarur, India *Corresponding author: [email protected] Abstract The present analyzing is an attempt to Meta synthesis of content analysis method. The content analysis method was collected by the journals like as “The qualitative Report, Google Scholar and JSTOR”. The sample consists of literature reviews based on content analysis method. Every reviews detail was noted. The reviews responses were in a synthesis. The synthesis refers information about content analysis method. Therefore the investigators categorized the content analysis method reviews. A synthesis of content analysis method review is formed in conclusion and finalizing the common approach of content analysis. Keywords: content analysis, approach of content analysis, meta-synthesis Cite This Article: G. Manimozhi, and P. Srinivasan, “A Meta Synthesis of Content Analysis Approaches.” American Journal of Educational Research, vol. 6, no. 6 (2018): 632-637. doi: 10.12691/education-6-6-8. occurrence of identified terms (word counts), by the mid- 1950's researchers were already starting to consider the 1. Introduction need for more sophisticated methods of analysis, focusing on concepts rather than simply words, and on semantic Systematic reviewing and meta-analysis of the quantitative relationships rather than just presence [18]. research indication has extended from the health disciplines At the same time as both conduct still continue into other disciplines. -
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. -
Laadullisen Aineiston Analyysiohjelmistot: Atlas.Ti
LAADULLISEN AINEISTON ANALYYSIOHJELMISTOT: ATLAS.TI Sanna Herkama & Anne Laajalahti Metodifestivaalit, Tampere 27.8.2019 SANNA HERKAMA ANNE LAAJALAHTI Erikoistutkija, FT Koulutus- ja kehittämisjohtaja, FT INVEST-tutkimushanke, www.invest.utu.fi Infor, www.infor.fi Psykologian ja logopedian laitos Prologos ry, puheenjohtaja Turun yliopisto Mevi ry, varapuheenjohtaja ProCom ry, Tiede- ja teoriajaos, puheenjohtaja TOPICS & Laajalahti 2019 Herkama • Technologies in qualitative analysis • What can you and can’t do with ATLAS.ti? • ATLAS.ti in practice Laajalahti, A. & Herkama, S. (2018). Laadullinen analyysi ATLAS.ti-ohjelmistolla. • Utilising ATLAS.ti – pitfalls and benefits In R. Valli (Ed.), Ikkunoita • Closing remarks tutkimusmetodeihin 2. 5th edition. Jyväskylä: PS-kustannus, 106–133. TECHNOLOGIES SHAPE OUR THINKING Medium is the 1 Conducting research has always been intertwined with the usage of message! various aids, tools, and technologies. Also, various software have assisted ~ Marshall McLuhan researchers for long. 2 Even such choices as the utilisation of A4 paper size (Järpvall 2016) and PowerPoint slides (Adams 2006) guide the way we process information, i.e. how we produce, reproduce, use, and share information! Herkama & Laajalahti 2019 TRADITIONAL OR COMPUTER ASSISTED Computer ANALYSIS? Assisted/Aided Qualitative 1 Traditional analysis: Should I go for a traditional way of analysing Data research material? Paper prints and coloring, copy-paste procedures, Analysis hanging papers on the wall, post-it tags etc.? Software 2 Computer assisted analysis: Should I use Computer Assisted/Aided Qualitative Data Analysis Software (CAQDAS)? Storing data in one place, checking up things quickly, handling text and audiovisual material parallel, creating summaries in seconds… Herkama & Laajalahti 2019 CAQDAS – RESTRICTING OR EXPANDING THINKING? 1 Technologies shape our thinking – whether we want it or not (Laajalahti & Herkama 2018). -
Europeana Cloud Deliverable 1.3 User Requirements Analysis and Case Studies Report
DELIVERABLE Project Acronym: Europeana Cloud Grant Agreement number: Europeana Cloud Deliverable 1.3 User Requirements Analysis and Case Studies Report. Content Strategy Report. Project Title: Europeana Cloud: Unlocking Europe’s Research via The Cloud Europeana Cloud Deliverable 1.3 User Requirements Analysis and Case Studies Report. Content Strategy Report. [Joint Deliverables 1.3 and 1.6: User Requirements Analysis and Case Studies Report (1.3) and Content Strategy Report (1.6)] Revision: Authors: Stavros Angelis (Athena RC) Agiatis Benardou (Athena RC) – Work Package Leader Nephelie Chatzidiakou (Athena RC) Panos Constantopoulos (Athena RC) Costis Dallas (Athena RC) Alastair Dunning (Europeana Foundation) Jennifer Edmond (TCD) Stefan Ekman (UGOT/SND) Vicky Garnett (TCD) Dimitris Gavrilis (Athena RC) Caspar Jordan (UGOT/SND) Kika Kalogeropoulou (Athena RC) Konstantinos Karozos (Athena RC) Ilze Lace (UGOT/SND) Rufus Latham (UGOT/SND) Marian Lefferts (CERL) Dimitra-Nefeli Makri (Athena RC) Athanassios Mantes (Athena RC) Eliza Papaki (Athena RC) Dimitar Popovski (UGOT/SND) Owain Roberts (NLW) Norman Roger (University of Edinburgh) Martin Schaller (ONB) Björn Sjögren (UGOT/SND) Ingeborg Versprille (CERL) Kees Waterman (KNAW) Project co-funded by the European Commission within the ICT Policy Support Programme Dissemination Level P Public P C Confidential, only for members of the consortium and the Commission Services Revision History Revision Date Author Organisation Description 1. September Agiatis Athena RC Table of Contents, initial content of the 2015 Benardou report. 2. October WP1 Revision of ToC and structure 08, 2015 members 3. November WP1 Amendments to the text, revisions and 2015 members changes. 4. November RCAB Review and approval of the text. 2015 5.