The Common Core set a standard for all children to read increasingly complex texts throughout schooling. The purpose of the present study was to explore text characteristics specifically in relation to early-grades text complexity. Three hundred fifty primary-grades texts were selected and digitized. Twenty-two text characteristics were identified at 4 linguistic levels, and multiple computerized opera tionalizations were created for each of the 22 text characteristics. A researcher-devised text-complexity outcome measure was based on teacher judgment of text complexity in the 350 texts as well as on student judgment of text complexity as gauged by their responses in a maze task for a subset of the 350 texts. Analyses were conducted using a logical analytical progression typically used in machine-learning research. Random forest regression was the primary statistical modeling technique. Nine text character istics were most important for early-grades text complexity including word structure (decoding demand and number of syllables in words), word meaning (age of acquisition, abstractness, and word rareness), and sentence and discourse-level characteristics (intersentential complexity, phrase diversity, text density/information load, and noncompressibility). Notably, interplay among text characteristics was im portant to explanation of text complexity, particularly for subsets of texts.

No abstract

The Common Core raises the stature of texts to new heights, creating a hubbub. The fuss is especially messy at the early grades, where children are expected to read more complex texts than in the past. But early-grades teachers have been given little actionable guidance about text complexity. The authors recently examined early-grades texts to discover what makes them complex and now report that there is a lot that can help teachers, specifically, young children’s texts are special, a handful of text characteristics can signal text-complexity level, sometimes the interplay of text characteristics modulates text-complexity level, and knowing why a text is complex can facilitate text selection.

No abstract