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Gurantz, Oded

Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • My research focuses on gaps in college enrollment and completion between students from historically underserved groups and their more privileged peers, and has been published in some of the leading economic, policy, and education journals. With a background in economics and education policy, I use quantitative research methods, primarily quasi-experimental and experimental designs, to examine programs and policies that are both effective and efficient in ameliorating educational disparities. A key component of my research agenda is the development of long-term, collaborative partnerships with educational and government agencies. This approach helps my findings address not just theoretical questions in the literature, but ensures that the results are relevant to current public policy debates and well-positioned to lead to actionable change.

Teaching

courses taught

  • EDUC 4716 - Basic Statistical Methods
    Primary Instructor - Fall 2022 / Fall 2023
    Introduces descriptive statistics including graphic presentation of data, measures of central tendency and variability, correlation and prediction, and basic inferential statistics, including the t-test.
  • EDUC 5716 - Basic Statistical Methods
    Primary Instructor - Fall 2022 / Fall 2023
    Introduces descriptive statistics including graphic presentation of data, measures of central tendency and variability, correlation and prediction, and basic inferential statistics, including the t-test.
  • EDUC 7326 - Quasi-Experimental Design in Causal Inference in Social Sciences
    Primary Instructor - Fall 2024
    Focuses on experimental and quasi-experimental designs in educational research; applications of the general linear mode; power and statistical efficiency; randomization and control; multiple comparisons; factorial experiments and interaction with fixed-factor and mixed design; analysis of covariance; effects of assumption violations; and related computer programs for statistical analysis. Recommended prerequisite of a graduate-level introduction to stats course.
  • EDUC 7386 - Educational Evaluation
    Primary Instructor - Spring 2023
    Builds an understanding of the range of approaches taken by educational evaluators, focusing particularly on the evaluation of programs. Explores the nature of different evaluation perspectives and how these disparate views translate into methodological and conceptual models. Students develop a familiarity with the most common and influential approaches to evaluation.
  • EDUC 8240 - Applied Regression Analysis
    Primary Instructor - Spring 2024
    Statistical analysis can be a powerful tool for understanding social, educational, psychological, and developmental processes. In this course, we will learn to answer such questions using multiple regression analysis, to develop an understanding of the strengths and limitations of this approach, and practice communicating results clearly and accurately. By the end of the semester, students in this course should be able to critically examine published research using regression and carefully perform their own regression analyses using empirical data. Recommended prerequisites of EDUC 8230 or another course in basic statistical methods.

Background

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