Semester:WS 19/20
Type:Module
Language:English
ECTS-Credits:6.0
Scheduled in semester:1
Semester Hours per Week / Contact Hours:36.0 L / 28.5 h
Self-directed study time:151.5 h
Type:Module
Language:English
ECTS-Credits:6.0
Scheduled in semester:1
Semester Hours per Week / Contact Hours:36.0 L / 28.5 h
Self-directed study time:151.5 h
Module coordination/Lecturers
- Prof. Dr. Stefan Seidel
(Modulleitung)
- Angelika Schwarz
(Modulleitungsassistenz)
Curricula
Master's degree programme in Information Systems (01.09.2015)Description
Short description
The module provides an introduction to research methods.
Topics
- Introduction to scientific research
- Literature reviews
- Qualitative research
- Quantitative research
- Design science research
- Theories used in IS research
Learning Outcomes
- Students will know and understand the historical development of scientific research.
- Students will know and understand the concept of scientific research.
- Students will identify appropriate theories to explain empirical phenomena.
- Students will identify suitable research methods in order to seek answers to specific research questions.
- Students will use appropriate qualitative, quantitative, and design-oriented approaches to scientific research.
Qualifications
Lectures Method
- The module integrates theoretical knowledge and practical skills in an interactive lecture.The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.
Literature
Compulsory reading
- Bryman, A. & Bell, E. (2015) Business research methods (4th ed.). Oxford, UK: Oxford University Press.
- Creswell, J.W. (2013) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (3rd ed.). Sage Publications
- Oates, B. J. (2006). Researching information systems and computing. London, UK: Sage Publications.
- Recker, J. (2012). Scientific Research in Information Systems: A Beginner’s Guide. Springer, Heidelberg, Germany.
Further reading
- Miles, M. B. & Huberman, A. M. (1994). Qualitative data analysis. An expanded sourcebook. London, UK: Sage Publications.
- Provost, F. & Fawcett, T. (2013). Data Science for Business. Sebastopol: O'Reilly Media
Exam Modalities
Written Exam (90 min)
Comments
This module is prerequisite for taking the Master’s thesis Module and writing the Master’s thesis