Poslední úprava: PhDr. Monika Kadrnožková, Ph.D. (26.10.2020)
This course builds on both parts of course Methodology of educational research I - educational research methods and statistical analysis of data. In the educational research methods part we focus on work with both Czech and foreign educational research literature . Next, we discuss in detail the most problematic topics for beginning researchers - sample collection, sample size and validity and reliability of research method. A new topic for students is conducting experiments and analysis of experimental data. In the statistical data analysis part we first revise selected parts of basics of descriptive and inferential statistics. Next, students will be introduced to advanced parts of statistics which are commonly used in educational research. These are multivariate linear regression, factor analysis and cluster analysis. The aim of this course is to prepare students to conduct high-quality educational research. Next, students should be able to critically evaluate both Czech and foreign studies using statistical analysis of data and advanced methods of educational research.
1. Work with educational research literature - steps for conducting a literature review, sample literature matrix, guidelines for technical writing.
2. Sampling strategies for educational research - types of random and nonrandom sampling strategies, examples of qualitative sampling. Advantages and disadvantages of the sampling strategies, examples of their use in educational research. Sample size.
3. Validity and reliability of research method.
4. Experiments in educational research - sources of internal and external invalidity (history, maturation, testing, instrumentation, regression, selection, mortality, selection-maturation interaction, pretest-treatment interaction, multiple treatment interference, treatment diffusion, experimenter effect, reactive arrangement). Pre-experimental design, true experiment, quasiexperiment and possible sources of invalidity in models of these designs. Example of factorial design.
5. Statistics - revision of the basics of descriptive and inferential statistics discussed in course Methodology of educational research I, multivariate linear regression, idea of factor analysis and cluster analysis.
Poslední úprava: PhDr. Monika Kadrnožková, Ph.D. (26.10.2020)
This course builds on both parts of course Methodology of educational research I - educational research methods and statistical analysis of data. In the educational research methods part we focus on work with both Czech and foreign educational research literature . Next, we discuss in detail the most problematic topics for beginning researchers - sample collection, sample size and validity and reliability of research method. A new topic for students is conducting experiments and analysis of experimental data. In the statistical data analysis part we first revise selected parts of basics of descriptive and inferential statistics. Next, students will be introduced to advanced parts of statistics which are commonly used in educational research. These are multivariate linear regression, factor analysis and cluster analysis. The aim of this course is to prepare students to conduct high-quality educational research. Next, students should be able to critically evaluate both Czech and foreign studies using statistical analysis of data and advanced methods of educational research.
1. Work with educational research literature - steps for conducting a literature review, sample literature matrix, guidelines for technical writing.
2. Sampling strategies for educational research - types of random and nonrandom sampling strategies, examples of qualitative sampling. Advantages and disadvantages of the sampling strategies, examples of their use in educational research. Sample size.
3. Validity and reliability of research method.
4. Experiments in educational research - sources of internal and external invalidity (history, maturation, testing, instrumentation, regression, selection, mortality, selection-maturation interaction, pretest-treatment interaction, multiple treatment interference, treatment diffusion, experimenter effect, reactive arrangement). Pre-experimental design, true experiment, quasiexperiment and possible sources of invalidity in models of these designs. Example of factorial design.
5. Statistics - revision of the basics of descriptive and inferential statistics discussed in course Methodology of educational research I, multivariate linear regression, idea of factor analysis and cluster analysis.
Literatura -
Poslední úprava: PhDr. Monika Kadrnožková, Ph.D. (26.10.2020)
Cohen, L., Manion, L., Morrison, K. (2017).Research Methods in Education. New York: Routledge.
Creswell, J. W., Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. London: Sage Publications.
Creswell, J. W. (2014). A Concise Introduction to Mixed Methods Research. London: Sage Publications.
Gay, L.R., & Mills, G.E. (2018). Educational Research: Competencies for Analysis and Application. New York: Pearson.
Hinkle, D.E., Wiersma, W., & Jurs, S.G. (2003). Applied Statistics for the Behavioral Sciences. Boston : Houghton Mifflin.
Shults, K.S., Whitney, D.J., & Zickar, M.J. (2014). Measurement Theory in Action: Case Studies and Exercises. New York: Routledge.
Poslední úprava: PhDr. Monika Kadrnožková, Ph.D. (26.10.2020)
Cohen, L., Manion, L., Morrison, K. (2017).Research Methods in Education. New York: Routledge.
Creswell, J. W., Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. London: Sage Publications.
Creswell, J. W. (2014). A Concise Introduction to Mixed Methods Research. London: Sage Publications.
Gay, L.R., & Mills, G.E. (2018). Educational Research: Competencies for Analysis and Application. New York: Pearson.
Hinkle, D.E., Wiersma, W., & Jurs, S.G. (2003). Applied Statistics for the Behavioral Sciences. Boston : Houghton Mifflin.
Shults, K.S., Whitney, D.J., & Zickar, M.J. (2014). Measurement Theory in Action: Case Studies and Exercises. New York: Routledge.
