EDU-790: Quantitative Research in Education
Programs: M.Ed. in Education Policy and Leadership, and M.A. in International Training and Education, American University, School of Education, 2021
COURSE DESCRIPTION
Analysis of and practice in the design of quantitative educational research. Emphasizes the nature and function of quantitative data gathering and analysis and the statistical approaches and techniques used to obtain particular outcomes.
COURSE PREREQUISITES
This course builds on the foundational understanding of education research methods and ethics that students developed in EDU-610: Overview of Qualitative and Quantitative Research Strategies. Successful completion of EDU-610 or the equivalent is required for this course (including data analysis in Excel, research ethics; independent, dependent, and control variables; internal and external validity; experimental and descriptive research designs, and measures of central tendency and variance.)
COURSE LEARNING OUTCOMES
This course prepares students to apply statistics to research questions in education and related social sciences. Though it briefly covers the mathematical formulas for most of the methods presented, the course is not appropriate for students seeking mathematical derivations or proofs. Instead, the course emphasizes practical application using Stata 14, a statistical software package commonly employed by policy researchers and economists. Students will learn to:
- Input, clean, and merge data
- Describe individual variables in tables and graphs
- Examine bivariate relationships through tables and graphs
- Test for relationships among variables using chi-square tests, t-tests, linear regression models, and logistic regression models
- Understand the assumptions behind these approaches
- Interpret data-analytic results
Students will also complete and present a final data-analytic project of their choosing, working independently or in small groups.
READINGS AND MULTIMEDIA
There is no required textbook to purchase. In some weeks, I will post brief readings to explain technical concepts. In most weeks, I will include links to YouTube videos (roughly 10-30 minutes) that teach the statistical topics for that week. These are free references that you should watch carefully before class so you can bring to class questions you have about the concepts.