DOCSLIB.ORG

Laadullisen Aineiston Analyysiohjelmistot: Atlas.Ti

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

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). 2 Fears and high hopes 3 Software shape our research practices, our relationship to research, and ourselves as researchers, both extending and restricting human possibilities (Goble et al. 2012, 17). ”The greater the methodological expertise and confidence in using a certain methodology in the context of software, the lesser is the influence of software.” (Friese 2011, 1.) Herkama & Laajalahti 2019 THE ROLE OF THE SOFTWARE IN ANALYSIS 1 Software do not conduct the analysis, they only assist it. 2 Software are not good or bad per se. The question is always about how we use them. 3 CAQDAS does not make the analysis any better nor it is a guarantee of a high-quality research. 4 If the research problem is vague or the analytic approach unclear, CAQDAS do not fix the problem! (Jolanki & Karhunen 2010; Laajalahti & Herkama 2018.) Herkama & Laajalahti 2019 WHAT ARE THE OPTIONS AVAILABLE? 1 Commercial ones: ATLAS.ti …and many other options, e.g., CAQDAS are often ANSWR, Datagrav, Dedoose, Ethnograph, f4analyse, Focuss On, based on the same HyperRESEARCH, MAXQDA (aiemmin WinMAX), NVivo (aiemmin idea but some NUD*IST), QDA Miner, Qiqqa, Qualrus, Quirkos, Raven’s Eye, Saturate differences do exist! App, Transana, webQDA, and Xsight 2 Free, open source software: e.g., AQUAD, Cassandre, CLAN, Coding Analysis Toolkit (CAT), Compendium, Computer Assisted Textual Markup and Analysis (CATMA), ELAN, KH Coder, RQDA, and TAMS Analyzer Herkama & Laajalahti 2019 WHAT CAN YOU DO WITH ATLAS.TI? 1 Explore various types of research material, even simultaneously (e.g., textual, graphical, audio, and video documents; both empirical material and literature reviews) 2 Organise and save research material 3 Mark and analyse data segments (that is coding) 4 Explore only some parts of the data (e.g., groups of respondents or codes, parts of the research material), make comparisons if needed 5 Save ideas and thinking process (e.g., create memos, comment items) 6 Use search functions 7 Create reports 8 Visualise abstract and theoretical ideas (e.g., create networks) 9 Create relationships (e.g., create links and relations) 10 Utilise also other software while working with ATLAS.ti 11 Work in teams and collaborate with other researchers (Laajalahti & Herkama 2018.) Herkama & Laajalahti 2019 INTERFACE Herkama & Laajalahti 2019 WHAT CAN’T YOU DO WITH ATLAS.TI? Researcher is always the key to 1 Researcher makes the analysis and interpretation, the software do not successful analysis, make any analysis! (Laajalahti & Herkama 2018.) not the software! 2 ATLAS.ti offers support to the researcher – without taking control of the intellectual process. (ATLAS.ti 8 Windows – User Manual.) 3 Researcher is searching for meanings, a computer for character strings. Cheers to that small (?) of a difference! (Eskola & Suoranta 2008.) Herkama & Laajalahti 2019 www.atlasti.com ATLAS.ti 7 ATLAS.TI – HOW still in use, e.g., at TO GET IT? many universities ATLAS.ti 8 Used to be only for Windows; now also version for Mac OS and Mobile for the iPad and Android. out on 6.12.2016, In addition, beta version ATLAS.ti Cloud: https://atlasti.com/cloud progressing all the Free trial version available (for Windows and Mac, ATLAS.ti 8): time http://atlasti.com/free-trial-version Student licenses: https://atlasti.com/students Herkama & Laajalahti 2019 UTILISING ATLAS.TI – & Laajalahti 2019 GOOD TO REMEMBER Herkama • ATLAS.ti interface allows easily intuitive inductive approach. • Also negative evidence exists. • World is not built on classifications. • You might not need all the tools and options available. • Quantifying research material is easy – but is it needed? (Laajalahti & Herkama 2018.) UTILISING ATLAS.TI – PITFALLS & Laajalahti 2019 Herkama • The software are not doing the analysis but instead they assist you doing the analysis! • ATLAS.ti may not save your time, nor does it guarantee the quality of analysis. • Do not let yourself get lost! (”Mess of codes”, ”Code jungle”, ”Drowning in codes”…) • Do I see the forest for the trees? • The codes created do not equal to insightful qualitative analysis! • Do not stop too early. You may still need to think over again! Interpret! (Laajalahti & Herkama 2018.) UTILISING ATLAS.TI – BENEFITS & Laajalahti 2019 Herkama • The administration and organisation of qualitative research material becomes easier. • Various types of data sets can be viewed simultaneously. • Remarks, thoughts, and comments can be saved and archived. • Quotations can be easily searched and copy-pasted to a final research report. • The amount of potential mistakes decreases. • When utilised properly, the accuracy, consistency, and transparency of the analysis increases potentially resulting to the higher level of quality in general. • At best, CAQDAS can free up researcher’s thinking capacity possibly allowing serendipity, i.e. ”unplanned or fortunate discoveries”. (Laajalahti & Herkama 2018.) SOMETHING FOR ME? WHAT TO & Laajalahti 2019 CONSIDER AS A NEW BEGINNER? Herkama • Size and structure of the research material • Aims of the current study • Research questions, designs, and analysis methods characteristic to your own field of study • Your own attitudes towards software in general and readiness to learn new things • Support and software available in your research community (Laajalahti & Herkama 2018.) GOOD LUCK! & Laajalahti 2019 • There is no ”right” or ”wrong” way to Herkama utilise ATLAS.ti. • Find your own way! • Do not give up! • Do not hesitate to try out! Be creative! Many inspiring moments with your qualitative data analysis! KIITOS! SANNA JA ANNE Herkama & Laajalahti 2019 LITERATURE • Adams, C. 2006. PowerPoint, habits of mind, and classroom culture. Journal of Curriculum Studies 38 (4), 389−411. • ATLAS.ti 8 Windows – User Manual. https://atlasti.com/manuals-docs/ • Eskola, J. & Suoranta, J. 2008. Johdatus laadulliseen tutkimukseen. 8th ed. Tampere: Vastapaino. • Friese, S. 2011. Using ATLAS.ti for analyzing the financial crisis data. Forum: Qualitative Social Research 12 (1), Art. 39. • Goble, E., Austin, W., Larsen, D., Kreitzer, L. & Brintnell, S. 2012. Habits of mind and the split- mind effect: when computer-assisted qualitative data analysis software is used in phenomenological research. Forum: Qualitative Social Research 13 (2), Art. 2. • Jolanki, O. & Karhunen, S. 2010. Renki vai isäntä? Analyysiohjelmat laadullisessa tutkimuksessa. & Laajalahti 2019 In J. Ruusuvuori, P. Nikander & M. Hyvärinen (Eds.), Haastattelun analyysi. Tampere: Vastapaino, 395–410. • Järpvall, C. 2016. Pappersarbete: formandet av och föreställningar om kontorspapper som Herkama medium. Lund: Mediehistoriskt arkiv, 1654-6601, 34. • Laajalahti, A. & Herkama, S. 2018. Laadullinen analyysi ATLAS.ti-ohjelmistolla. In R. Valli (Ed.), Ikkunoita tutkimusmetodeihin 2. 5th ed. Jyväskylä: PS-kustannus, 106–133. • McLuhan, M. 1964. Understanding media: the extensions of man. Toronto: McGraw Hill. ADDITIONAL READINGS • Friese, S. 2014. Qualitative data analysis with ATLAS.ti. 2nd ed. London: Sage. (Version 7.) • Friese, S. 2019. Qualitative data analysis with ATLAS.ti. 3rd ed. London: Sage. (Version 8.) • 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. • MacMillan, K. 2005. More than just coding? Evaluating CAQDAS in a discourse analysis of news texts. Forum: Qualitative Social Research 6 (3), Art. 25. • Paulus, T. M. & Lester, J. N. 2015. ATLAS.ti for conversation and discourse analysis studies. International Journal of Social Research Methodology. doi:10.1080/13645579.2015.1021949 • White, M. J., Judd, M. D. & Poliandri, S. 2012. Illumination with a Dim Bulb? What do social & Laajalahti 2019 scientists learn by employing qualitative data analysis software (QDAS) in the service of multimethod designs? Sociological Methodology 42 (1), 43–76. Herkama • Woods, M., Macklin, R. & Lewis, G. K. 2016. Researcher reflexivity: exploring the impacts of CAQDAS use. International Journal of Social Research Methodology 19 (4), 385–403. • Woolf, N. H. & Silver, C. 2017. Qualitative analysis using ATLAS.ti: the five-level QDA method. New York: Routledge..
Recommended publications
  • QPN-Vol1.Pdf

    QPN-Vol1.Pdf

    Qualitative Psychology Nexus: Vol. 1 Mechthild Kiegelmann (Ed.) Qualitative Research in Psychology Verlag Ingeborg Huber All parts of this publication are protected by copyright. All rights reserved. No portion of this book may be reproduced by any process or technique, without the prior permission in writing from the publisher. Enquiries concerning reproduction should be sent to the publisher (see address below). Die Deutsche Bibliothek - CIP Cataloguing-in-Publication-Data Qualitative research in psychology / Mechthild Kiegelmann (ed.). - 1. ed.. - Schwangau : Huber, 2001 (Qualitative psychology nexus ; Vol. 1) ISBN 3-9806975-2-5 1. Edition 2001 © Verlag Ingeborg Huber Postfach 46 87643 Schwangau, Germany Tel./Fax +49 8362 987073 e-mail: [email protected] Web-Page: http://www.aquad.de ISBN 3-9806975-2-5 Content Preface by the editor 7 Introduction 8 Group I: Examples of Applications of Qualitative Methods, Part I 1. Discussion (summarized by Leo Gürtler) 17 2. Categorizing the Content of Everyday Family Communication Irmentraud Ertel 21 3. Emotions and Learning Strategies at School – Opportunities of Qualitative Content Analysis Michaela Gläser-Zikuda 32 4. The Role of Subjective Theories on Love Leo Gürtler 51 5. Deciding which Kinds of Data to Collect in an Evaluative Study and Selecting a Setting for Data Collection and Analysis Inge M. Lutz 66 6. Dynamics of a Qualitative Research Design. An Interactive Approach to Interactive Reception Thomas Irion 78 7. Cross-Cultural Youth Research as International and Inter- disciplinary Cooperation: The Project “International Learning.” Ilze Plaude and Josef Held 90 Group 2: Examples of Applications of Qualitative Methods, Part II 8.
  • Audiovisual Media Annotation Using Qualitative Data Analysis Software: a Comparative Analysis

    Audiovisual Media Annotation Using Qualitative Data Analysis Software: a Comparative Analysis

    The Qualitative Report Volume 23 Number 13 Article 4 3-6-2018 Audiovisual Media Annotation Using Qualitative Data Analysis Software: A Comparative Analysis Liliana Melgar Estrada University of Amsterdam, [email protected] Marijn Koolen Huygens ING, [email protected] Follow this and additional works at: https://nsuworks.nova.edu/tqr Part of the Library and Information Science Commons, and the Quantitative, Qualitative, Comparative, and Historical Methodologies Commons Recommended APA Citation Melgar Estrada, L., & Koolen, M. (2018). Audiovisual Media Annotation Using Qualitative Data Analysis Software: A Comparative Analysis. The Qualitative Report, 23(13), 40-60. https://doi.org/10.46743/ 2160-3715/2018.3035 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]. Audiovisual Media Annotation Using Qualitative Data Analysis Software: A Comparative Analysis Abstract The variety of specialized tools designed to facilitate analysis of audio-visual (AV) media are useful not only to media scholars and oral historians but to other researchers as well. Both Qualitative Data Analysis Software (QDAS) packages and dedicated systems created for specific disciplines, such as linguistics, can be used for this purpose. Software proliferation challenges researchers to make informed choices about which package will be most useful for their project. This paper aims to present an information science perspective of the scholarly use of tools in qualitative research of audio-visual sources. It provides a baseline of affordances based on functionalities with the goal of making the types of research tasks that they support more explicit (e.g., transcribing, segmenting, coding, linking, and commenting on data).
  • Developing an Argument Learning Environment Using Agent-Based ITS (ALES)

    Developing an Argument Learning Environment Using Agent-Based ITS (ALES)

    Educational Data Mining 2009 Developing an Argument Learning Environment Using Agent-Based ITS (ALES) Sa¯a Abbas1 and Hajime Sawamura2 1 Graduate School of Science and Technology, Niigata University 8050, 2-cho, Ikarashi, Niigata, 950-2181 JAPAN [email protected] 2 Institute of Natural Science and Technology, Academic Assembly,Niigata University 8050, 2-cho, Ikarashi, Niigata, 950-2181 JAPAN [email protected] Abstract. This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF) using "Walton Theory". ALES uses di®erent mining techniques to manage a highly structured arguments repertoire. This repertoire was designed, developed and implemented by us. Our aim is to extend our previous framework proposed in [3] in order to i) provide a learning environment that guides student during argument learning, ii) aid in improving the student's argument skills, iii) re¯ne students' ability to debate and negotiate using critical thinking. The paper focuses on the environment development specifying the status of each of the constituent modules. 1 Introduction Argumentation theory is considered as an interdisciplinary research area. Its techniques and results have found a wide range of applications in both theoretical and practical branches of arti¯cial in- telligence and computer science [13, 12, 16]. Recently, AI in education is interested in developing instructional systems that help students hone their argumentation skills [5]. Argumentation is classi- ¯ed by most researchers as demonstrating a point of view (logic argumentation), trying to persuade or convince (rhetoric and dialectic argumentation), and giving reasons (justi¯cation argumentation) [12].
  • Introduction for Conducting Social Science Research Michael C. Gizzi, Ph.D. Stage 1

    Introduction for Conducting Social Science Research Michael C. Gizzi, Ph.D. Stage 1

    Harnessing the power of MAXQDA for conducting social science research Michael C. Gizzi, Ph.D. Professor of Criminal Justice, Illinois State University Introduction Stage 3 & 4 – The Art of Data Analysis MAXQDA is a professional qualitative software designed for content analysis and mixed methods research. This poster provides an overview of MAXQDA describes itself with the tag line “The Art of Data Analysis.” These the “Four Stages of Research,” a conceptual model I’ve developed for words capture the heart of the Four Stages of Research. Stage 3 and 4 conducting a qualitative research project. This was designed as tool for involves reading, coding, writing memos (taking notes), looking for patterns effectively using MAXQDA to conduct qualitative legal research, but can be and themes, and then engaging in a thematic analysis of cases. applied to almost any social science qualitative project. MAXQDA has transformed how I conduct my research on the impact and implementation Once the initial content analysis completed, you can begin the creative and of judicial policies by lower courts. often emergent process of analysis: summarizing the data, looking for patterns, quantifying them, identifying core examples, and then further refining The Four Stages of Research provides a conceptual model for thinking the data and findings. MAXQDA also has a full set of statistical tools that you through a research project: can use for mixed methods analysis. As this process unfolds, you are ready to write your final product. • Identify the research questions and conceptual framework of the research design. • Collect the data and create a workspace and analytical process to evaluate it in MAXQDA.
  • Mendeley Mendeley Is a Reference and Citation Manager Available for Free up to 2 GB of Web Storage (More Storage Is Available for $55 Per Year)

    Mendeley Mendeley Is a Reference and Citation Manager Available for Free up to 2 GB of Web Storage (More Storage Is Available for $55 Per Year)

    Mendeley Mendeley is a reference and citation manager available for free up to 2 GB of web storage (more storage is available for $55 per year). Mendeley is available as a desktop app, mobile app, as well as online. An MS Word extension allows users to connect to and cite their references while writing. Mendeley allows users to add resources in three ways. First, one may upload a PDF to Mendeley. Mendeley stores the PDF and allows the user to comment on and write notes in the PDF. Users may also enter sources manually, in cases where no PDF is present. For this entry approach, a few templates are available for the most common resource types. Users may also use the web extension to download source information from the web. Once sources have been entered, users can then then organize their sources in a variety of ways. The most prevalent use is through folders, which allow users to categorize sources by topic or project. However, users can also create tags for their files and sources so that they can search for keywords or topics that are important to them. Points in favor: • In-app PDF reader with commentary ability Points against: • Surprising lack of resource templates and information fields (e.g. no template for a conference paper or a book with translator). • MS Word extension has bugs that cause it to crash. Screenshots: Microsoft Word Citation Generator Although we tested Microsoft Word primarily as a writing app, the program includes a citation generator which was tested for facility and accuracy alongside the other reference management apps.1 Like other apps, MS Word has templates for common and uncommon resource types, including book, journal, and sound recording.
  • Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria

    Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria

    Walden University ScholarWorks Walden Dissertations and Doctoral Studies Walden Dissertations and Doctoral Studies Collection 2021 Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria Benjamin Chukwuka Nnadozie Walden University Follow this and additional works at: https://scholarworks.waldenu.edu/dissertations Part of the Public Administration Commons This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been accepted for inclusion in Walden Dissertations and Doctoral Studies by an authorized administrator of ScholarWorks. For more information, please contact [email protected]. Walden University College of Social and Behavioral Sciences This is to certify that the doctoral dissertation by Benjamin Chukwuka Nnadozie has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Ernesto Escobedo, Committee Chairperson, Public Policy and Administration Faculty Dr. Raj Singh, Committee Member, Public Policy and Administration Faculty Dr. Meena Clowes, University Reviewer, Public Policy and Administration Faculty Chief Academic Officer and Provost Sue Subocz, Ph.D. Walden University 2021 Abstract Public Perceptions of Nigeria Police Monetary Bribery in Awka, Nigeria By Benjamin Chukwuka Nnadozie Dissertation Submitted in Partial Fulfullment of the Requirements for the Degree of Doctor of Philosophy Public Policy and Administration Walden University February 2021 Abstract The Nigerian police are often perceived by the Nigerian public as a very corrupt institution due to reports in the media and direct experiences of police brutality, extortion, injustice, and especially monetary bribery. The refusal to pay monetary bribes to the police has led to loss of lives and a lack of trust in the police.
  • Book of Abstracts Translata 2017 Scientific Committee

    Book of Abstracts Translata 2017 Scientific Committee

    Translata III Book of Abstracts Innsbruck, 7 – 9 December, 2017 TRANSLATA III Redefining and Refocusing Translation and Interpreting Studies Book of Abstracts of the 3rd International Conference on Translation and Interpreting Studies December 7th – 9th, 2017 University Innsbruck Department of Translation Studies Translata 2017 Book of Abstracts 3 Edited by: Peter Sandrini Department of Translation studies University of Innsbruck Revised by: Sandra Reiter Department of Translation studies University of Innsbruck ISBN: 978-3-903030-54-1 Publication date: December 2017 Published by: STUDIA Universitätsverlag, Herzog-Siegmund-Ufer 15, A-6020 Innsbruck Druck und Buchbinderei: STUDIA Universitätsbuchhandlung und –verlag License: The Bookof Abstracts of the 3rd Translata Conference is published under the Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses) Disclaimer: This publications has been reproduced directly from author- prepared submissions. The authors are responsible for the choice, presentations and wording of views contained in this publication and for opinions expressed therin, which are not necessarily those of the University of Innsbruck or, the organisers or the editor. Edited with: LibreOffice (libreoffice.org) and tuxtrans (tuxtrans.org) 4 Book of Abstracts Translata 2017 Scientific committee Local (in alphabetical order): Erica Autelli Mascha Dabić Maria Koliopoulou Martina Mayer Alena Petrova Peter Sandrini Astrid Schmidhofer Andy Stauder Pius ten Hacken Michael Ustaszewski
  • Qualitative Data Analysis Software: a Call for Understanding, Detail, Intentionality, and Thoughtfulness

    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.
  • Activity Report 2013

    Activity Report 2013

    Project-Team EXPRESSION Expressiveness in Human Centered Data/Media Vannes-Lannion-Lorient Activity Report Team EXPRESSION IRISA Activity Report 2013 2013 Contents 1 Team 3 2 Overall Objectives 4 2.1 Overview . 4 2.2 Key Issues . 4 3 Scientific Foundations 5 3.1 Gesture analysis, synthesis and recognition . 5 3.2 Speech processing and synthesis . 9 3.3 Text processing . 13 4 Application Domains 16 4.1 Expressive gesture . 16 4.2 Expressive speech . 16 4.3 Expression in textual data . 17 5 Software 17 5.1 SMR . 17 5.2 Roots ......................................... 18 5.3 Web based listening test system . 20 5.4 Automatic segmentation system . 21 5.5 Corpus-based Text-to-Speech System . 21 5.6 Recording Studio . 22 5.6.1 Hardware architecture . 23 5.6.2 Software architecture . 23 6 New Results 24 6.1 Data processing and management . 24 6.2 Expressive Gesture . 24 6.2.1 High-fidelity 3D recording, indexing and editing of French Sign Language content - Sign3D project . 24 6.2.2 Using spatial relationships for analysis and editing of motion . 26 6.2.3 Synthesis of human motion by machine learning methods: a review . 27 6.2.4 Character Animation, Perception and Simulation . 28 6.3 Expressive Speech . 29 6.3.1 Optimal corpus design . 30 6.3.2 Pronunciation modeling . 31 6.3.3 Optimal speech unit selection for text-to-speech systems . 32 6.3.4 Experimental evaluation of a statistical speech synthesis system . 32 6.4 Miscellaneous . 33 2 Team EXPRESSION IRISA Activity Report 2013 6.5 Expression in textual data .
  • Qualitative Research 1

    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

    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

    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.