The formulas that will be derived from the CLEAR corpus will be open-source and ostensibly based on more advanced natural language processing (NLP) features that better reflect our understanding of the reading process. The corpus is a collaboration between CommonLit, a non-profit education technology organization focused on improving reading, writing, communication, and problem-solving skills, and Georgia State University (GSU), with the end goal of promoting the development of more advanced and open-source readability formulas that government, state, and local agencies can use in testing, materials selection, material creation, and other applications commonly reserved for readability formulas. In this paper, we introduce the open-source CommonLit Ease of Readability (CLEAR) corpus. Commercially available readability formulas are not publicly available, may not have been tested rigorously for their reliability, and may be cost-prohibitive for many schools and districts, let alone teachers. Additionally, many traditional readability formulas were normed using readers from specific age groups on small corpora of texts taken from specific domains.
Traditional readability formulas lack construct and theoretical validity because they are based on weak proxies of word decoding (i.e., characters or syllables per word) and syntactic complexity (i.e., number or words per sentence) and ignore many text features that are important components of reading models including text cohesion and semantics. However, both types of readability formulas are problematic.
Most educational texts are calibrated using traditional readability formulas like Flesch–Kincaid Grade Level (FKGL Kincaid et al., 1975) or commercially available formulas such as Lexile (Smith et al., 1989) or the Advantage-TASA Open Standard (ATOS School Renaissance Inst.
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