Syllabus
Topics:
1. Logic, benefits and limitations of quantitative research (compared with qualitative research), quantitative research designs, formulation of research questions and hypotheses, reviewing literature.
2. Representativeness (concepts of sample, population, etc.), types of probabilistic and non-probabilistic sampling techniques, selection error and response rates – concrete examples and demonstrations of sampling techniques typical for educational settings.
3. Designing the questionnaire (the role of theory, retrieval of research information, use of standardized scales and questionnaires), construction and structure of questionnaires, formulation of questions, order of questions.
4. Thinking beyond the horizon of individual questions – using summative rating scales, reliability and validity of summary indices.
5. Possibilities of the pilot study and its evaluation, questionnaire adjustment and choice of data collection methods, data file preparation, data cleansing, data analysis and interpretation.
Annotation
This course will introduce the students to the basics of quantitative research methods in education, and more broadly in social sciences. The students will be presented with the most common errors in the creation, analysis and interpretation of data from questionnaires, based on specific examples of educational research.
Other quantitative research methods (e.g. observation, experiment, semantic differential) will be discussed on an individual basis with the students interested in their use. The students will also be presented with the available paid collections of e-resources (EBSCO, Proquest, JSTOR, Willey InterScience e-journals, Science Direct, Sage fulltexts, ERIC) and their use in formulating research problems and the design of questionnaires.
The course aims to introduce doctoral students to the practical aspects of the preparation, implementation and analysis of quantitative research. The practical demonstrations will also contain a basic introduction to the statistical processing of research data (with a demonstration of processing using the SPSS statistical software), including multivariate methods; however, an introduction to statistics is neither the aim nor the content of the course.
The students will design their own research tools and carry out their own pilot studies. Both in personal meetings and in the e-learning environment, the course participants will hold a systematic discourse about their research experience, which will culminate in a final conference.