An Examination of the Corpus of USCIS.gov
dc.contributor.author | Norris, Christina | |
dc.creator | Norris, Christina | |
dc.date | 2021-11-24T14:05:45.000 | |
dc.date.accessioned | 2021-11-29T12:08:40Z | |
dc.date.available | 2021-11-29T12:08:40Z | |
dc.date.issued | 2021-05-01 | |
dc.date.submitted | 2021-08-11T11:12:03-07:00 | |
dc.identifier | researchday/2021/gradfacultypres/21 | |
dc.identifier.uri | http://hdl.handle.net/20.500.13013/1466 | |
dc.description.abstract | One topic that is of increasing relevance to many English learners (ELs) as the number of individuals hoping to gain lawful residence in the U.S. is that of immigration. In fiscal year 2019, USCIS received more than 7.6 million forms relating to the many types of applications that they oversee, such as immigrant petitions for working visas, asylum and refugee adjustments, family unity applications, and naturalization applications (“Number of Service-wide Forms Fiscal Year To- Date, by Quarter, and Form Status Fiscal Year 2019,” 2020). Many of the applicants are ELs who would appreciate and benefit from direct or indirect assistance from their ESL or EFL instructors to better understand the application process, a process that tends to begin by visiting the USCIS website, www.USCIS.gov. This study, therefore, applied corpus linguistics methods examine the vocabulary of the USCIS website and application materials with the goal of creating word lists to assist language teachers and learners to better navigate the language of the process. | |
dc.title | An Examination of the Corpus of USCIS.gov | |
dc.type | event | |
dc.legacy.pubstatus | published | |
dc.legacy.ssustatus | Graduate | |
dc.contributor.sponsor | González, Melanie | |
dc.date.display | May 2021 | en_US |
dc.legacy.pubtitle | Research Day | |
dc.legacy.identifieritem | https://digitalcommons.salemstate.edu/researchday/2021/gradfacultypres/21 | |
dc.legacy.identifierfile | https://digitalcommons.salemstate.edu/context/researchday/article/1268/type/native/viewcontent | |
dc.subject.keyword | corpus linguistics | |
dc.subject.keyword | TESOL | |
dc.subject.keyword | vocabulary |