LEARNING OUTCOMES
After completing the course, students will be able to …
- Recall and distinguish a broad range of common qualitative and quantitative data collection and analysis methods for scientific research.
- Execute a subset of the most used methods independently.
- Construct specific research questions and select appropriate research frameworks and methods to tackle them.
- Recall gold standard example applications of each taught method.
- Defend good research practices via quality assurance, research ethics, open science and canonical scientific research reporting.
Credits: 3
Schedule: 02.09.2024 - 21.10.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Christian Guckelsberger
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
The goal of the course is to equip students with a toolbox of scientific research methods to benefit their future work in industry and academia, and to successfully plan and execute empirical studies for their Doctoral or Master's theses. The methods will cover the dimensions of qualitative vs. quantitative; subjective vs. objective, obtrusive vs. unobtrusive. They will be complemented with a set of strategies for assuring quality in empirical studies.
The needs and interests of students from different majors and programmes (e.g. Information Networks, Software Engineering, Game Design and Development) will be met based on a diverse set of research examples and custom-tailored learning and exercise materials.
Further specialisation courses are available for students who successfully completed this foundation course:
- Research Methods: Case studies & Design Science (CS-E5011)
- Research Methods: AI-based Data Synthesis & Analysis (CS-E5012)
Assessment Methods and Criteria
valid for whole curriculum period:
Exercises, classroom activity, exam.
Workload
valid for whole curriculum period:
Lectures, labs, weekly learning tasks, exam.
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I
2025-2026 Autumn IRegistration:
Max. 100 students will be accepted to the course. Priority is given to 1. Master's students for whom this course is mandatory; 2. Other Master's and Doctoral students 3. Exchange students.