Syllabus

Title
2378 Empirical Research Methods I
Instructors
Dr. Maria Belen Abdala, Dr. Dennis Kolcava, M.A.
Contact details
Type
VUE
Weekly hours
5
Language of instruction
Englisch
Registration
09/11/26 to 09/24/26
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
Day Date Time Room
Thursday 10/01/26 03:00 PM - 06:00 PM TC.2.01
Thursday 10/08/26 03:30 PM - 06:30 PM TC.0.01
Monday 10/12/26 10:00 AM - 01:00 PM TC.3.10
Thursday 10/15/26 02:00 PM - 05:00 PM D4.0.250 OeNB Auditorium
Monday 10/19/26 10:00 AM - 01:00 PM TC.3.10
Thursday 10/22/26 02:00 PM - 05:00 PM D4.0.250 OeNB Auditorium
Thursday 10/29/26 03:00 PM - 06:00 PM TC.1.02
Monday 11/02/26 10:00 AM - 01:00 PM TC.3.10
Thursday 11/05/26 03:30 PM - 06:30 PM TC.0.04
Monday 11/09/26 10:00 AM - 01:00 PM D2.0.342 Teacher Training Raum
Thursday 11/12/26 04:30 PM - 07:30 PM TC.2.01
Monday 11/16/26 10:00 AM - 01:00 PM TC.3.10
Thursday 11/19/26 05:00 PM - 08:00 PM TC.2.02
Monday 11/23/26 10:00 AM - 01:00 PM TC.3.10
Thursday 11/26/26 06:00 PM - 09:00 PM TC.2.02
Monday 11/30/26 10:00 AM - 01:00 PM TC.3.10
Thursday 12/03/26 04:30 PM - 07:30 PM TC.2.02
Monday 12/07/26 10:00 AM - 01:00 PM TC.3.10
Monday 12/14/26 10:00 AM - 01:00 PM TC.3.10
Contents

This course introduces the logic of social science inquiry, theory building, and the fundamentals of social science research design. The course focuses on the various steps of empirical social science research, such as

- the formulation of theory and the derivation of predictions

- designing the research process

- developing operational definitions

- data collection

- data analysis.

Learning outcomes

After successfully participating at this course, students will have an overview of different empirical research methods in social sciences and understand the strengths and weaknesses of each approach. Students will have gained the necessary skills to act both as informed “consumers” of empirical articles and as “producers” of small-scale research projects.

Students will acquire the skills needed to

  • Formulate theoretical frameworks and derive testable predictions from them.
  • Design an appropriate research process to investigate a given question.
  • Develop reliable operational definitions for latent concepts and variables.
  • Apply systematic methods for data collection.
  • Analyse data using basic quantitative techniques.
Attendance requirements

Attendance in the exercises is compulsory.
Attendance in the lecture is not compulsory but strongly recommended. It is encouraged through graded activities that can only be completed in the classroom. There are no make-up opportunities for missed activities. If a lecture is missed, no explanation or excuse is required.

More detailed information will be explained in the first unit. Students are required to attend the first constitutive session. 

Teaching/learning method(s)

The course relies on a mix of learning techniques including lectures, classroom discussions, practical exercises, and student presentations.

Assessment

Overall course performance will be evaluated based on three components:

- exercises in research methods and inferential statistics (50%), 

- a written essay at the end of the semester (30%), and

- in-class tasks in the lecture meetings (20%).

 

Grading / Notenschlüssel:

0-50%: Insufficient; 50.1-62.5% Sufficient; 62.6-75% Satisfactory; 75.1-87.5% Good; 87.6-100% Excellent

 

Academic Conduct

Plagiarism is a serious academic offense with serious consequences. Plagiarism is the act of presenting someone else's ideas as your own, either verbatim or in your own words. Please familiarize yourself with the concept of plagiarism.

The use of AI is not permitted unless otherwise indicated.

Readings

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Last edited: 2026-06-10



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