Social science research methodology WF-FI-KGN-MBNS
1.
Introduction to research methodology – why methodology matters, differences between science and everyday cognition, basic concepts.
2.
Research methods in cognitive science and psychology – observation, experiment, correlational studies, case studies.
3.
Formulating a research problem and hypotheses – how a research question differs from a hypothesis, how to construct hypotheses.
4.
Operationalization of variables – how to translate abstract concepts into measurable indicators.
5.
Reliability and validity of measurement – what they are, how to assess them, and why they are crucial in science.
6.
Definitions in science – analytical, ostensive, partial, and probabilistic definitions.
7.
Types and designs of experiments – control group, experimental group, one-group and multi-group designs, mixed designs.
8.
Spontaneous changes vs. changes caused by the experiment – how to distinguish experimental effects from the natural course of events.
9.
Scientific theory – characteristics of a good theory, the relationship between theory and hypothesis.
10.
Measurement and indicators – the indicator–indicatum relationship, examples of operationalization in practice.
11.
Mediation and moderation effects – what they are, how to identify them, examples of research result interpretation.
12.
Interaction effects – how they differ from main effects, how to interpret them in result analysis.
13.
Errors and pitfalls in research – sampling error, experimenter expectancy effect, replication problem.
14.
Qualitative and quantitative analysis with AI support – how modern algorithms assist research, from qualitative to quantitative data analysis.
15.
Presentation and interpretation of research results – principles of creating tables, graphs, and writing discussions and conclusions.
(in Polish) E-Learning
(in Polish) Grupa przedmiotów ogólnouczenianych
(in Polish) Opis nakładu pracy studenta w ECTS
Subject level
Learning outcome code/codes
Type of subject
Course coordinators
Learning outcomes
**KOG1_W13**
at an advanced level, the subject-matter and methodological specificity of cognitive science, as well as the basic research methods and heuristic strategies appropriate for the main branches of cognitive science
recognizes, compares, classifies, and analyzes the subject-matter and methodological specificity of cognitive science, and applies basic research methods and heuristic strategies appropriate for the main branches of cognitive science (classes 1–7)
**KOG1_W17**
knowledge in the field of research methodology in the social sciences
defines, explains, interprets, and evaluates selected issues in the field of research methodology in the social sciences (classes 8–15)
**KOG1_W19**
ethical consequences of the development of artificial intelligence and modern methods of studying cognition
identifies, analyzes, evaluates, and discusses the ethical consequences of the development of artificial intelligence and modern methods of studying cognition (class 14)
Assessment criteria
For a satisfactory grade (3.0), the student knows and understands the basic concepts of research methodology. They can indicate the difference between a research question and a hypothesis, distinguish between types of definitions (analytical, ostensive, partial, probabilistic), and provide examples of basic research methods (observation, experiment, correlational studies). They are able to identify the difference between a reliable and a valid measurement.
For a satisfactory plus grade (3.5), in addition to the above, the student can characterize different types of experiments (laboratory, field, natural, mixed) and describe patterns of spontaneous and controlled changes. They demonstrate the ability to identify simple relationships between variables and to present sample indicators for selected concepts.
For a good grade (4.0), the student independently interprets more complex relationships between variables, recognizes and defines mediation, moderation, and interaction effects. They can critically discuss classical psychological experiments (e.g., Asch, Milgram), indicating their significance and limitations. They are able to correctly operationalize selected concepts in research and propose appropriate indicators.
For a good plus grade (4.5), the student not only applies the acquired concepts but also compares different research strategies and evaluates their usefulness depending on the research problem. They can identify methodological errors in sample studies, analyze the validity of conclusions, and interpret results using methodological terminology. They are able to identify the boundaries and complementarity between qualitative and quantitative analysis.
For a very good grade (5.0), the student uses methodological knowledge comprehensively and critically. They can independently design a research framework, including hypotheses, indicators, and a data analysis plan. They integrate knowledge of qualitative and quantitative methods, demonstrating their combined application, including in contemporary contexts (e.g., using artificial intelligence tools). They are able to clearly present and interpret research results, pointing out both strengths and weaknesses of the conducted analyses.
The student is allowed two unexcused absences from lectures. The basis for passing the course is a test — achieving at least 60% guarantees a satisfactory grade. The instructor reserves the right to award additional points on the exam for active participation and engagement in class discussions.
Bibliography
Nowak, S. (2007). Metodologia badań społecznych. Warszawa: Wydawnictwo Naukowe PWN.
Babbie, E. (2007). Badania społeczne w praktyce. Warszawa: Wydawnictwo Naukowe PWN.
Szymańska, A. (2025). Mathematical Modeling in Psychology Using Artificial Intelligence. Warsaw: UKSW Press.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: