Coh-Metrix is an automated linguistics tool that analyzes higher-level features of language and discourse (Graesser et al., 2011; Graesser et al., 2004; McNamara et al., 2014). Unlike basic word counting systems, Coh-Metrix relies on more sophisticated methods of natural language processing, such as syntactic parsing and cohesion computation, to capture these higher-level language characteristics. These Coh-Metrix dimensions align with multilevel theoretical frameworks of language and discourse that differentiate language codes, structures, strategies, and cognitive processes at different levels of language and discourse (Graesser et al., 2011). Coh-Metrix analyzes texts on hundreds of measures of language and discourse that are aligned with the multilevel theoretical frameworks, but these funnel into five major factors that systematically vary as a function of types of texts (e.g., narrative versus informational) and grade level: narrativity, syntactic simplicity, word concreteness, referential cohesion, and deep (causal) cohesion. Texts are automatically scaled on these five factors with Coh-Metrix-TEA (Text Easability Assessor). There is a composite measure called formality, which increases with low narrativity, syntactic complexity, word abstractness, and high cohesion (Graesser et al., in press).