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.

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

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.