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M.Ed. Education Assessment(EA): EDUEA5 - Quantitative Research Design and Analysis

Course Description

This course prepares students to be users and critical consumers of quantitative research. Students will be trained in various statistical methods in order to conduct rigorous, scientific quantitative research. Students completing the course will be able to: design effective experimental and quasi-experimental studies, manage and use large scale datasets, analyse various types of datasets (e.g., nested data, longitudinal data) with the appropriate modelling techniques, apply advanced statistical methods (e.g., structural equation modelling, multilevel modelling) in their own research, critically review studies that make use of a diverse set of statistical methods, and conduct educational measurement and assessment related studies using techniques such as factor analysis or Rasch analysis or item response theory.

Additional Resources

• Quantitative Research for the Qualitative Researcher by Laura M. ODwyer; James A. Bernauer
• Encyclopedia of Research Design by Neil J. Salkind (Editor)
• Multivariate Statistics by Tonu Kollo
• Applied Multivariate Statistics for the Social Sciences by James P. Stevens

Books

• Structural Equation Modeling by Natasha K. Bowen; Shenyang Guo
• Structural Equation Modeling by Jichuan Wang; Xiaoqian Wang
• Handbook of Structural Equation Modeling by Rick H. Hoyle (Editor)
• Structural Equation Modeling with Mplus by Barbara M. Byrne
• Item Response Theory by Christine DeMars
• Handbook of Item Response Theory by Wim J. van der Linden (Editor)
  • Volume 1. Models
  • Volume 2. Statistical tools
  • Volume 3. Applications
• Multidimensional Item Response Theory by Reckase
• Exploratory Factor Analysis by Leandre R. Fabrigar; Duane T. Wegener
• Discovering Statistics Using IBM SPSS Statistics by Andy Field

References

• Harrington, D. (2008). Confirmatory factor analysis. Oxford University Press
• Vogt, P. W. (2007). Quantitative research methods for professionals. Pearson
• Robson, K., & Pevalin, D. (2016). Multilevel modelling in plain language. Sage
• Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson
• Reading statistics and research by Schuyler W. Huck

Resources

• IBM SPSS Statistics GradPack
• Resources to help you learn and use SPSS
• Sage Edge
• Discovering Statistics
• Statistics: Unlocking the Power of Data
• Highly recommended SPSS textbooks
• Student Resources
• MATLAB from MathWorks

e-Journals

• Behavior Research Methods
• Nepalese Journal of Qualitative Research Methods
• Social Research Update
• Survey Research Methods
• International journal of social research methodology