Syllabus
Course objectives:- knowledge of major theories, history and terminology (technical terms, definitions and standard words)- training in both quantitative and qualitative research methodologies- experience in research design, data collection, analysis and reporting of results- organizing data in a suitable format for analysis- experience with computer software facilitating analysis of both quantitative and qualitative data
Course structure (lecture+workshop):
Week 1 (5/10/2023): Epistemology and Philosophy of the Social Sciences: rationalism, positivism, skepticism; paradigms: subjectivity vs. objectivity; realism, relativism, social constructivism; Selection of appropriate research methods by identifying its strengths and limitations, the research problem identification (lecturer: V. Nečas)
Week 2 (12/10/2023): Language of research – type of research, research question, hypothesis, variables, relationship, causal explanation (V. Necas)
Week 3 (19/10/2023): Quantitative vs. qualitative research: an overview of use, differences, advantages, and limitations (L. Vochocova)
Week 4 (26/10/2023): Review of published literature associated with the problem area, formulation of research questions, hypotheses central to the problem selected (V. Necas)
Week 5 (2/11/2022): Qualitative approach I: Data gathering techniques (focus groups, interviews) (L. Vochocova)
Week 6 (9/11/2022): Qualitative approach II: Data analysis techniques - qualitative coding, grounded theory - introduction (L. Vochocova)
Week 7 (16/11/2022): Quantitative approach I: Content analysis: Data selection and gathering (variables, code-book, data input, sampling) (V. Necas)
Week 8 (23/11/2022): Quantitative approach II: Survey (questionnaire design): Data selection and gathering, sampling (V. Necas)
Week 9 (30/11/2023): Qualitative approach III: Grounded theory - categorization, axial coding, paradigmatic model (L. Vochocová)
Week 10 (7/12/2023): Qualitative approach IV: Semiotic analysis - an introduction (L. Vochocová)
Week 11 (14/12/2023): Research software and tools: online surveys, transcription, text mining, SPSS, STATA, Atlas.ti, NVivo (V. Necas)
Week 12 (21/12/2023): Data interpretation, contextualization, building theory, hermeneutics (L. Vochocova)
Week 13 (4/1/2024): Student presentations (optional), lecturers' feedback
Annotation
The course addresses main areas of research in social sciences - it focuses on all necessary aspects of research design, including theoretical preparation, literature review, formulation of research questions and hypotheses, operationalization and data gathering and analysis. It introduces the basic methods used for data gathering and analysis with a specific focus on analyses of the media and communication.
Lectures introducing the above specified topics will be accompanied with workshops in which students will have an opportunity do design and conduct their own research project.