Syllabus

Title
1916 Advanced Methods in Qualitative Research
Instructors
ao.Univ.Prof. Dr. Elfriede Penz
Contact details
  • Type
    PI
  • Weekly hours
    2
  • Language of instruction
    Englisch
Registration
09/14/21 to 09/24/21
Registration via LPIS
Notes to the course
This class is only offered in winter semesters.
Subject(s) Doctoral/PhD Programs
Dates
Day Date Time Room
Monday 10/11/21 01:00 PM - 03:30 PM TC.5.16
Monday 11/08/21 01:00 PM - 03:30 PM TC.5.16
Monday 11/29/21 01:00 PM - 03:30 PM Online-Einheit
Monday 12/13/21 01:00 PM - 06:00 PM Online-Einheit
Tuesday 12/14/21 01:00 PM - 06:00 PM Online-Einheit
Monday 12/20/21 01:00 PM - 06:00 PM Online-Einheit
Monday 12/20/21 01:00 PM - 06:00 PM Online-Einheit

Contents

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).

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.

Attendance requirements

Overall there is a mandatory attendance rate of 80%.

Teaching/learning method(s)

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.

Assessment

1. Participation (25%)

  • being physically present and participate in class  discussions.

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;
    • prepare transcripts, manage material and write a protocol for each interview, focusgroup, observation, etc.

      The data will be analyzed (including above mentioned steps) 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
      • 10% - prepare transcripts, manage material and write a protocol
      • 10% - analytical steps

      3. Participants present their projects (25%)

      Prerequisites for participation and waiting lists

      Only for PhD Students.

      Readings

      1 Author: Bazeley, Pat & Jackson, Kristi
      Title:

      Qualitative Data Analysis with NVivo


      Publisher: Sage
      Edition: 2nd
      Year: 2013
      Content relevant for class examination: No
      Content relevant for diploma examination: No
      Recommendation: Reference literature
      Type: Book

      Availability of lecturer(s)

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

      Other

      n/a

      Unit details

      Unit Date Contents
      1 Unit 1

      Introduction to the Course:

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

      Analysis of Qualitative Data:

      • Coding strategies
      • Quality assessment
      3 Unit 3

      Doing a Systematic Literature Review:

      • Nature and strategies
      • Quality assessment
      4 Unit 4

      Practical Part:

      • Handling literature and qualitative data with NVivo (Basic)
      5 Unit 5

      Practical Part:

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

      Student presentations

      Last edited: 2021-07-13



      Back