Introduction

Essex County, New Jersey is the home of Montclair State University and currently over 800,000 people from a wide variety of diverse backgrounds. This project takes a look at languages spoken at home in Essex County households, using data from the 2015 American Community survey. By investigating where ESL speakers are most in need, local libraries and schools can better direct their efforts to provide learning resources to these communities, specialized for the students’ native languages.

Languages Spoken at Home

Identifying ESL Need

Certain municipalities may benefit from increased availability of English as a Second language educational resources and at local schools and libraries. To identify which areas may be in need, we will look for places where the language spoken at home is not English and the residents were rated Speak English less than “very well” on the American Community Survey. By investigating the primary language spoken at home, we can better provide ESL materials in the native languages of the learners, improving accessibility.

There may be an area in need between Livingston and South Orange. However, this may be due to the location of the South Mountain Reservation park skewing population data. Information about how this tract/PUMA was determined could not be ascertained, but it seems to be a red herring. An examination of this county on a by-language basis follows.

Population by Language Spoken at Home by English Ability

Italian

Spanish

French

Portuguese

Chinese

Vietnamese

Arabic

Referring to Google Maps for approximate municipality names

We can now observe specific areas correspond to the hotspot locations previously highlighted in the overall “limited English” Essex county map shown at the start. The following regions could benefit from increased ESL resources for…

Questions and Concerns About the Census Data

How can we be sure these populations actually “speak English less than very well”? The criteria was arbitrarily assigned by the census taker, so it may be subject to bias. For example, were the speakers rated poorly just for having a non-standard accent, even if they could be easily understood? This subjective judgement should be taken with a grain of salt.

Next Steps

Survey data can be used to effectively ascertain locales in need of English as a Second Language educational resources. How can we customize resources to best assist ESL learners based on their personal native languages?

Investigating a Learner Corpus

PELIC blahh blahhh

References

Data provided by: * Juffs, A., Han, N-R., & Naismith, B. (2020). The University of Pittsburgh English Language Corpus (PELIC) [Data set]. http://doi.org/10.5281/zenodo.3991977 https://github.com/ELI-Data-Mining-Group/PELIC-dataset/blob/master/PELIC_compiled.csv

  • United States Census Bureau, (2015).