Syllabus

Titel
2188 Advanced Methods in Qualitative Research
LV-Leiter/innen
ao.Univ.Prof. Dr. Elfriede Penz
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    2
  • Unterrichtssprache
    Englisch
Anmeldung
14.09.2020 bis 24.09.2020
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Doktorat/PhD
Termine
Wochentag Datum Uhrzeit Raum
Montag 19.10.2020 10:00 - 12:30 Online-Einheit
Montag 02.11.2020 10:00 - 12:30 Online-Einheit
Montag 16.11.2020 10:00 - 12:30 Online-Einheit
Montag 30.11.2020 10:00 - 12:30 Online-Einheit
Donnerstag 03.12.2020 09:30 - 15:30 Online-Einheit
Freitag 04.12.2020 09:30 - 15:30 Online-Einheit

Ablauf der LV bei eingeschränktem Campusbetrieb

This is an online course, which uses Microsoft Teams.

Inhalte der LV

The course focuses on two sets of material available to researchers, i.e. literature and qualitative data. It discusses both types of material and suggests a CAQDAS approach for the analysis of them.

Reviewing the literature is integral to thinking about the research that researchers are undertaking. It relates to the formulating of research questions, the framing and design of the work, the methodology and methods; the data analysis; and the final conclusions and recommendations. Undertaking a review of the literature allows researchers to define what the field of study is, establish what research has been done which relates to the research question or field of study, consider what theories, concepts and models have been used and applied in the field of study, identify and discuss methods and approaches that have been used by other researchers; and identify the ‘gaps’ or further contribution that the present piece of research will make.

Research issues are becoming increasingly complex and are getting harder to address, e.g. in new topic areas. Consequently, qualitative research in general and qualitative computing in particular has become widely accepted. This course covers parts of the broad field of qualitative methods and methodology: overview, sampling, analysis and quality assessment (leaving out how to collect qualitative data).

Lernergebnisse (Learning Outcomes)

The purpose of this course is to provide PhD students with special aspects within qualitative research methodology and to familiarize them with specific techniques for qualitative data analysis, including hands-on application of techniques using the NVIVO software.

At the end of the seminar students are expected to have an understanding of:

•    Goals and techniques of literature reviews

•    Qualitative research approaches

•    Coding techniques

•    Basics in analysis of literature, interview and observation material (transcription, field notes, photos and videos)

•    Quality assessment of literature review and qualitative research.

After completing the course, students will be familiar and able to work with a particular software package (NVivo), which integrates a wide range of tools and enables researchers to analyze and visualize qualitative data, and link it to quantitative data.

Regelung zur Anwesenheit

Overall there is a mandatory attendance rate of 80%.

Lehr-/Lerndesign

The course covers special topics in qualitative research. A mixture of presentation, discussion, software training and exercises will be used. Students are encouraged to bring their own data and/or use them in the training part.

Leistung(en) für eine Beurteilung

1. Participation (50%):

  • being physically present (20%) and
  • participate in class and individual discussions (30%).

2. Participants are required to work on their own projects (50%):

Each participant should

    • search for literature (at least 10 sources) and organize the literature in Endnote or a similar reference software program
    • collect qualitative data: conduct interviews (at least 3), run a focus group discussion, collect social media data (from twitter, facebook, etc.,) collect observation material (photos, videos, audio, website content, field notes, brochures, etc.);
    • apply a coding technique according to the chosen methodology (NODE SYSTEM);
    • prepare transcripts (FILES), manage material (SETS, CLASSIFICATION) and write a protocol (MEMO) for each interview, focusgroup, observation, etc.

      The data will be analyzed (including above mentioned steps, plus QUERY) using NVivo. The project will be handed in as NVivo project (*.nvp), which includes all above mentioned elements (homework).

      Weighting criteria for the homework are:

      • 10% - data collection (literature review, qualitative data)
      • 20% - coding (NODE SYSTEM)
      • 10% - prepare transcripts (FILES), manage material (SETS, CLASSIFICATION) and write a protocol (MEMO)
      • 10% - analytical steps (QUERY)

      Literatur

      1 Autor/in: Bazeley, Pat & Jackson, Kristi
      Titel:

      Qualitative Data Analysis with NVivo


      Verlag: Sage
      Auflage: 2nd
      Jahr: 2013
      Prüfungsstoff: Nein
      Diplomprüfungsstoff: Nein
      Empfehlung: Referenzliteratur
      Art: Buch

      Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

      Only for PhD Students.

      Erreichbarkeit des/der Vortragenden

      Elfriede Penz can be contacted via e-mail: elfriede.penz@wu.ac.at.

      Sonstiges

      n/a

      Detailinformationen zu einzelnen Lehrveranstaltungseinheiten

      Einheit Datum Inhalte
      1 Unit 1

      Introduction to the Course:

      • Organisation of course
      • Overview of qualitative methods
      2 Unit 2

      Analysis of Qualitative Data:

      • Coding strategies
      3 Unit 3

      Analysis of Qualitative Data:

      • Quality assessment
      4 Unit 4

      Doing a Systematic Literature Review

      • Nature and strategies
      • Quality assessment
      5 Unit 5

      Practical Part:

      • Handling literature and qualitative data with NVivo (Basic)
      6 Unit 6

      Practical Part:

      • Handling literature and qualitative data with NVivo (Advanced)
      Zuletzt bearbeitet: 29.09.2020



      Zurück