Advanced Research Methods

Advanced Research Methods (WIF)

1/2. Semester 5 ECTS | 4 SWS Continuous Assessment (CA)

CSM IM

Prepare for Your Master`s Thesis: Learn scientific methods, models, and ways of thinking, and apply them to systematically investigate IT-related problems, evaluate research studies, and plan and conduct your own research according to academic standards.

Fundamentals of Philosophy of Science: Instrumentalism, Scientific Realism, Fundamentals of Logic, Deductive and Inductive Reasoning, Deductive-Nomological Model, Falsifiability and Information Content, Hypothetical-Deductive Method and Duhem's Problem, Theory and Model, Theory-Charged Observation, Freedom from Value Judgment, Paradigm
Systematics: Differentiation of theoretical, methodological, constructive and empirical research, methodological approach in computer science practice with special consideration of multi-/inter-/transdisciplinarity
Empirical research: research process, research questions, controlled experiment, hypotheses and other basic concepts, selected methods of statistical hypothesis testing, reproduction of statistical tests, selected qualitative and quantitative methods
System properties and their operationalization
Normative decision theory (expected utility hypothesis)
Modelling and simulation, load tests, benchmarks
Good scientific practice and ethics (management of primary/secondary data in terms of good scientific practice)
Development of the technical/scientific questions and the derived methodology for the own master's thesis

Competencies

Students are able to

of identifying the systematics and methodology of different scientific approaches
of applying the systematics and methodology of different scientific approaches to problems in practical computer science
of assessing projects for the application of systematic and methodological approaches
of applying the principles of "good scientific practice" to their own Master's thesis

Literature

H. Balzert, M. Schröder, and C. Schäfer, Wissenschaftliches Arbeiten - Ethik, Inhalt & Form wiss. Arbeiten, Handwerkszeug, Quellen, Projektmanagement, Präsentation, [3rd ed.]. Dortmund: Prof. Balzert Stiftung, 2022, doi: 10.18420/LB-WISSARBEITEN.
N. Döring and J. Bortz, Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. doi: 10.1007/978-3-642-41089-5.
DFG, Deutsche Forschungsgemeinschaft (ed.), Sicherung Guter Wissenschaftlicher Praxis. Weinheim: Wiley-VCH Verlag, 2013.
HS Mannheim. "Satzung wissenschaftliches Fehlverhalten." Accessed: Aug. 27, 2026. [Online.] Available: https://www.th-mannheim.de/fileadmin/user_upload/hauptseite/forschung/Dokumente/Forschungsprofil/Satzung_WissenschaftlichesFehlverhalten_HS_Mannheim.pdf
K. Popper, Logik der Forschung. Vienna: Springer, 1935. doi: 10.1007/978-3-7091-4177-9.
L. Prechelt, Kontrollierte Experimente in der Softwaretechnik. Potenzial und Methodik. Berlin: Springer, 2001.
H. D. Rombach, J. Rech, and M. Ciolkowski, Forschungsmethoden im Software Engineering, 2001.
T. Wilde and T. Hess, “Forschungsmethoden der Wirtschaftsinformatik: Eine empirische Untersuchung,” Wirtsch. Inform., vol. 49, no. 4, pp. 280–287, Aug. 2007, doi: 10.1007/s11576-007-0064-z.
C. Wohlin, P. Runeson, M. Höst, M. C. Ohlsson, B. Regnell, and A. Wesslén, Experimentation in Software Engineering. Berlin, Heidelberg: Springer, 2012. doi: 10.1007/978-3-642-29044-2.

Lecturer

Prof. Dr.-Ing. Sandro Leuchter
Prof. Dr. Till Nagel
Prof. Dr. Lutz Strüngmann
Prof. Dr. Ivo Wolf

Recommended Previous Knowledge

Grundlagen des wissenschaftlichen Arbeitens: Literaturrecherche, -verwaltung, Zitieren, Plagiate, Aufbau von wissenschaftlichen Arbeiten, Textverarbeitung/Textsatz, Korrekturzeichen

Module Details

Semester	1/2
Lecture Language	German
Frequency	Every Term
Credit Points (ECTS)	5
Course Coordinator	Prof. Dr.-Ing. Sandro Leuchter
Duration	1 Semester
Study Focus	Medical Data Science (MDS) Software Engineering (SE) Creative Technology (CT)
Course Achievement	None
Prerequisite for exam	None
Exam	Continuous Assessment (CA)

Weekly Hours (SWS)

Lecture	2 SWS
Exercises	2 SWS
Sum	4 SWS

Work Load

Lecture	30 h
Lab	30 h
Self Study	45 h
Assignments	45 h
Sum	150 h