Poster Paper: The Impact of English Language Proficiency on Math Achievement

Thursday, November 7, 2019
Plaza Building: Concourse Level, Plaza Exhibits (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Xue Gong, University of Wisconsin, Madison

Research Question

Research has drawn attention to the importance of language proficiency in students’ mathematical achievement (Abedi, 2004; Abedi & Lord, 2001; Fry 2007). It is not surprising to find that limited language proficiency is associated with comparatively low math achievement because language proficiency can affect students’ understanding and mastery of the mathematical content and further affect math achievement (Abedi, 2004; Martiniello, 2008). However, language proficiency alone does not account for all the variation in students’ math achievement. For example, socioeconomic status (SES), school factors such as teacher quality, and gender are all factors that are associated with math performances (Abedi, 2004; Friend et al, 2009; Han & Bridglall, 2009; Henry et al, 2014; Leahey & Guo, 2001).

The purpose of this study is to investigate the predictive power of English language proficiency on math achievement considering both individual characteristics and school contexts.


Data come from two sources: 1) the Florida Education Data Warehouse (FEDW) with a rich set of information on both student level and school level, and 2) surveys of teacher and school leaders from a large and representative sample of schools across the state.


To empirically examine the association between English language proficiency on math achievement, I fit two-level hierarchical linear models (HLM), which nested students within schools. Level 1 (student level) models contained controls for individual student characteristics and level 2 (school level) models contained controls for school characteristics, and cross-level interactions of variables of interest. All analysis was conducted using R programming.


Results show that limited English proficient (LEP) students who have low SES (receiving free lunch) and who are either Hispanic or black tend to be the most disadvantaged group in math performance, even after accounting for the interaction effects between language proficiency, race, and SES. In addition, results suggest that Hispanic or black students with high English language proficiency and high SES tend to be the most heterogeneous group and non-Hispanic and non-black students with low SES and high English proficiency tend to be the most homogeneous group.


There are four aspects to justify the potential significance of this study, which can provide implications for future research and policy. First, there is an increasing number of ELL students in the United States. Therefore, it becomes salient to develop objective criteria for exiting ELLs out of special language programs. This can be achieved by understanding the effects of English language proficiency on other academic assessments. Second, understanding the relationship between English language proficiency and success on academic achievement tests is pivotal in developing accountability systems that fit the needs of the population of ELLs. Third, studies of the relationship between English language proficiency and academic assessments, like this paper, are useful to inform and to set standards for English language proficiency tests. Finally, this study helps move the field forward in illuminating factors interacted with English language proficiency and academic assessments, so that educators can draw meaningful information to provide effective instruction.