Gifted and Talented Services for EFL Learners in China: A Step-by-Step Guide to Propensity Score Matching Analysis in R

Shifang Tang, Fuhui Tong and Xiuhong Lu
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Shifang Tang: Center for Research and Development in Dual Language and Literacy Acquisition (CRDLLA), Department of Educational Psychology, College of Education and Human Development, Texas A&M University, College Station, TX 77843, USA
Fuhui Tong: Center for Research and Development in Dual Language and Literacy Acquisition (CRDLLA), Department of Educational Psychology, College of Education and Human Development, Texas A&M University, College Station, TX 77843, USA
Xiuhong Lu: School of Foreign Languages, Hubei University of Technology, Wuhan 430068, China

Data, 2019, vol. 4, issue 3, 1-15

Abstract: We sought to quantify the effectiveness of a gifted and talented (GT) program, as was provided to university students who demonstrated a talent for learning English as a foreign language (EFL) in China. To do so, we used propensity score matching (PSM) techniques to analyze data collected from a tier-1 university where an English talent (ET) program was provided. Specifically, we provided (a) a step-by-step guide of PSM analysis using the R analytical package, (b) the codes for PSM analysis and visualization, and (c) the final analysis of baseline equivalence and treatment effect based on the matching sample. Collectively, the results of descriptive statistics, visualization, and baseline equivalence indicate that PSM is an effective matching technique for generating an unbiased counterfactual analysis. Moreover, the ET program yields a statistically significant, positive effect on ET students’ English language proficiency.

Keywords: EFL; English Talent; propensity score matching (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
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