This course provides an introduction to qualitative and quantitative research methods and will provide information on 1) methodological underpinnings of research methods and research designs 2) different methods 3) use of statistical software 4) applications to test data, and finally 5) the combination of quantitative and qualitative approaches in a fruitful manner.

Topic-wise, this course has an emphasis on empirical applications in mobility and transport. As discrete choices (for instance between transport modes; between different policies) play an important role here, the quantitative part of the course will emphasize the estimation of models with discrete dependent variables. The qualitative part will emphasize the user perspective on transport and mobility and provide research strategies to address this perspective.

Besides becoming acquainted with qualitative and quantitative research methods, students will learn to critically reflect on applications of these methods, thereby building a foundation for the development of own research projects in the winter term.

After successful completion of this introduction, students will be able to:

General:

- understand different research methods and strategies

- know how to use various tools for empirical analysis

- understand the significance of quantitative as well as qualitative empirical research 

- critically reflect on quantitative and qualitative methods (as for instance used in published empirical studies)

- gain familiarity with methods frequently used in the area of mobility and transportation

Qualitative part:

- understand the principles of good qualitative research

- use qualitative sampling strategies

- apply qualitative methods of data collection (e.g. interviews, focus groups, participant observation)

- apply qualitative methods of data analysis (e.g.Grounded Theory, hermeneutics, content analysis)

- reflect on research ethics

Quantitative part: 

- gain a good understanding of quantitative research design

- introduction to standard modeling techniques with continuous and discrete dependent variables (relevance, potential data sources, interpretation of results, etc.)

- proficiency in the use of R

Students are required to attend at least 80% of the course sessions. If you miss a class, please inform us in advance!

Lectures, discussions, student presentations, computer tutorials, use of statistical software packages

Students are expected to:

1. participate in all courses (80% attendance of the class is required! If you miss a class, please inform us in advance)
2. complete the qualitative and quantitative individual assignments
3. complete the qualitative and quantitative open book tests

Grading is based on your contributions in the quantitative and qualitative part:

• Qualitative part: in class contributions: 10 pts
• Qualitative part: assignments: 20 points
• Qualitative part: exam: 20 points
• Quantitative part: in class contributions: 10 pts 
• Quantitative part: assignments: 20 points
• Quantitative part: exam: 20 points

Overview:

• In class contributions, oral presentations:  20%
• Assignments 40%
• Exams: 40%

Overall, 100 points can be reached. Minimum points for each grade are as follows:
5    -
4    61
3    71
2    81
1    91

SEEP courses do not allow creation of assignments, exam answers or other assessed work using generative AI (e.g. ChatGPT).  All such work is expected to be the original work by the student concerned and is assessed as such.  Work copied from a generative AI source is equivalent to plagiarism and will be treated as such.

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Prior experience with the estimation of basic statistical models is recommended, but not mandatory.

stefanie.peer@wu.ac.at

cornelia.reiter@wu.ac.at

Assignments and exams

Qualitative Assignments 

• Assignment 1: Presentation: (10 points) a (team) presentation of about 10 minutes in sum!
  • Students present the main aspects of a methodological text or a journal article discussing a qualitative research project. You focus on the research question, research objectives, sampling, methodology and method, the role of the researcher and level and type of findings. 
  • You are prepared to illustrate the respective topic of the seminar unit with your example
• Assignment 2: Methods application (10 points)
  • Students apply a method of data collection in a team
  • Students present their experiences of applying methods in the qualitative workshops and bring transcripts/field notes for the analysis in class
• Exam: Open Book Test (online) for 1 hour (20 points)

Quantitative Assignments 

• Assignment 1: Home assignment (10 points) – individual tasks
  • Descriptive statistics and estimation of a linear regression model: due 4 June
• Assignment 2: Home assignment (10 points) – individual task
  • Model estimations due 11 June
• Exam: Open Book Test (online) for 1 hour (20 points)