Increasing United States College Access for Native Arabic Speakers: Applying a Simplification Intervention and Evaluating Machine and Human Translations

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Texas Education Review


Across many language backgrounds, a consistent hurdle to accessing United States higher education is understanding the basic information necessary to apply for admission and financial aid and complete the many enrollment management processes necessary to begin one’s college career (apply for housing, receive and submit vaccinations, register for classes, etc.). However, to date, no studies have explored how this type of higher education information can be simplified and translated into Arabic, one of the most widely spoken languages in the world and a linguistic background shared by tens of thousands of prospective international students (and their families) seeking higher education in the United States. This case study reports on research-to-practice work conducted with the University of Iowa, specifically how the university simplified their enrollment management information and how that information was translated into Arabic for native Arabic speakers seeking access to the University of Iowa. Findings reveal that the institution simplified text to speak more directly to prospective student audiences by using second person pronouns and simpler sentence structure and diction to engage this audience. Moreover, analyses of machine and human translations of English to Arabic suggest that human translation should be the preferred mechanism of translating higher education information, as Google Translate and Chat GPT [A1] provided adequate but not perfect translations of Iowa’s information. Implications for practice and college access are addressed.



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