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Research Methods I - Research Design and Experimental Data Analysis

Informacje ogólne

Kod przedmiotu: BSTS-ResMeth-RDesign Kod Erasmus / ISCED: (brak danych) / (brak danych)
Nazwa przedmiotu: Research Methods I - Research Design and Experimental Data Analysis
Jednostka: Biuro do spraw obsługi projektu "Interdyscyplinarne studia doktoranckie STŚ"
Grupy:
Punkty ECTS i inne: (brak)
Język prowadzenia: angielski
Pełny opis: (tylko po angielsku)

1.1. Elements of the methodology of natural science

- 1.1.1. Research program and research project

- 1.1.2. The scientific hypothesis and falsification,

- 1.1.3. Evaluation of research project,

1.2. Causality in the life sciences

- 1.2.1. Causality in non-experimental projects

- 1.2.2. Experimental and quasi-experimental designs in natural and social sciences, experimental error and factor interactions

1.3. The theoretical basis of regression analysis

1.4.. Multiple regression and least squares methods

1.5. Introduction to General Linear Models

Literatura: (tylko po angielsku)

1. Shadish, W., R., Cook, T., D., Campbell, D. T., (2002) Experimental and Quasiexperimental Designs for Generalized Causal Inference, Wadsworth,

2. G. Quinn and M. Keough (2002): Experimental design and data analysis for biologists. Cambridge Univ.. Press

Efekty kształcenia: (tylko po angielsku)

Knowledge:

After the course the student is able to understand:

1. Inter- and multidisciplinary approaches in scientific projects, the role of analogies and metaphors in scientific progress with avoiding cross-scientific superficial analogies and metaphors in development of research design. Aspects of specificity and commonness of research design in natural and social sciences

2. The concept of causality in natural and social sciences in non-experimental, quasi-experimental and experimental context and its differences in natural and social sciences.

3. Statistical methods and tools in diagnosis of cause-effect relationship in natural and social systems

4. Contextual and hierarchical nature of data (and social and natural systems) as well as interactions among hierarchical levels of the analysis. Specificity of research designs and analytical methods in hierarchical, multilevel context and proper use of statistical models that explain the nested and hierarchical levels of physical, biological and social data.

5. The nature of multidimensionality of the data in life and social sciences (complex, large scale, sequential, relational, data). Problems of reduction, classification, ordination and scaling of life and social data and content - method analogies across the life and social phenomena

6. Concept of dimension and a latent unobserservable variable in life and social sciences. Philosophical and empirical context of latent variable modeling. Measurement models with latent variables in natural and social sciences. Causality in non-experimental design and causal models with latent variables in multigroup comparisons.

7. Qualitative nature of scientific research in the context of cultural reproduction and social change. Importance of perspectives and methods triangulation in scientific (qualitative) research. Ethical issues linked to research projects and setting research projects in an ethical framework.

Abilities:

After the course the student should posses the ability to:

1. Search for inter- and multidisciplinary research problems

1. Combine approaches and research methods from different fields of knowledge and scientific disciplines

2 Find applications of research methods and data analysis tools from one field of science into another one

3. Join knowledge and proper use the analogies and metaphors in interdisciplinary studies

4. Work in cross-disciplinary research teams, use of research language and conceptual networks rooted in various research traditions and types of sciences

5. Communicate the research problems, assumptions, analytical concepts and outcomes in interdisciplinary context

6. Enhance the social and group learning and the knowledge diffusion from different fields of science

7. Use of analytical methods and tools from social and natural sciences

Attitudes:

After the course the student should posses the social competencies in:

1. Developing of social skills in building and participating in the interdisciplinary research teams,

2. Improving the group communication, sharing knowledge and capabilities, mixing various contents and research methods in integrated research team.

3. Overcoming communicational barriers, misunderstandings and conflicts concerning different research traditions, scientific languages, or uneven levels of statistical and numerical proficiencies

4. Mutual interpersonal inspiration with research problems coming from own scientific fields and areas

5. Sharing content and methods' experiences from various context (social and natural) in projecting of observational, experimental and quasiexperimental research designs.

6. Learning the unified view of hierarchical nature of phenomena in various natural, life and social systems.

7. Developing the ethical framework in research project and holistic view of scientific problem in interdisciplinary studies.

Metody i kryteria oceniania: (tylko po angielsku)

Method of evaluation: written exam

Condition of credits: Active participation in lectures/seminars

Przedmiot nie jest oferowany w żadnym z aktualnych cykli dydaktycznych.
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Jagielloński w Krakowie.