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Access to higher education is critical for minority populations and emergent bilingual students. However, the language used by higher education institutions to communicate with prospective students is often too complex; concretely, many institutions in the US publish admissions application instructions far above the average reading level of a typical high school graduate, often near the 13th or 14th grade level. This leads to an unnecessary barrier between students and access to higher education. This work aims to tackle this challenge via text simplification. We present PSAT (Professionally Simplified Admissions Texts), a dataset with 112 admissions instructions randomly selected from higher education institutions across the US. These texts are then professionally simplified, and verified and accepted by subject-matter experts who are full-time employees in admissions offices at various institutions. Additionally, PSAT comes with manual alignments of 1,883 original-simplified sentence pairs. The result is a first-of-its-kind corpus for the evaluation and fine-tuning of text simplification systems in a high-stakes genre distinct from existing simplification resources. 

Abstract Background While there have been numerous calls to increase the participation of people with disabilities in STEM, many postsecondary institutions are not equipped to support students with disabilities. We examined the accessibility of 139 webpages from 73 postsecondary institutions in the USA that contained information about the undergraduate physics curriculum and graduate research programs. We selected these webpages as they are common entry points for students interested in pursuing a physics degree. We used Tenon and Mac OS X’s VoiceOver software to assess the level of accessibility of these webpages as measured by alignment with the Web Content Accessibility Guidelines (WCAG) 2.0. Results We found that only one webpage had minimal accessibility errors (i.e., 10 errors), while the other webpages had numerous accessibility errors. Five specific error types accounted for the majority of all errors. The five most common errors were related to information, structure, and relationships of content (1.3.1 Level A; 39.7%); text alternatives for non-text content (1.1.1 Level A; 27.0%); information about link purpose (2.4.4 Level A; 14.7%); capability to resize text (1.4.4 Level AA; 10.0%); and information about the name, role, and value of user interface components (4.1.2 Level A; 11.2%). Conclusions We present and describe the five common accessibility errors we identified in the webpages in our sample, suggest solutions for these errors, and provide implications for students with disabilities, instructors and staff, institutional administration, and the broader physics community.