Literaturnachweis - Detailanzeige
| Autor/inn/en | Nese, Joseph F. T.; Alonzo, Julie; Biancarosa, Gina; Kamata, Akihito; Kahn, Joshua |
|---|---|
| Titel | Text Messages: Examining Different Estimates of Text Complexity Poster presented at the Annual Pacific Coast Research Conference (Feb 2017). |
| Quelle | (2017), (2 Seiten)
PDF als Volltext kostenfreie Datei |
| Zusatzinformation | Weitere Informationen |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Reading Comprehension; Difficulty Level; Readability; Sentence Structure; Lexicology; Syntax; Semantics; Text Structure; Reading Fluency; Reading Rate; Readability Formulas; Flesch Kincaid Grade Level Formula |
| Abstract | Text complexity has received increased attention due to the CCSS, which call for students to comprehend increasingly more complex texts as they progress through grades. Quantitative text complexity (or readability) indices are based on text attributes (e.g., sentence lengths, and lexical, syntactic, & semantic difficulty), quantified by mathematical formulas to estimate text. Researchers have warned that texts should not be created to reach particular readability scores, which is a frequent practice of "equating" ORF passages. Issues we encountered were: estimates often differ; estimates do not account for student variance; and many require texts of a certain length. The purpose of this study was to provide comparisons of quantitative text complexity estimates based on text features to estimates of "text difficulty" based on student performance. We found (a) moderate correlation among latent fluency and words correct per minute (WCPM); (b) the highest correlations were observed among ARI, Flesh-Kincaid, and WCPM, possibly an artifact of passage development, and partly a similarity between the formulas of ARI and Flesh-Kincaid (particularly for lower grade texts with less multisyllabic words); and (c) the text complexity measure with the lowest correlations among all measures was formality, perhaps suggesting it measures a different dimension of text complexity. (As Provided). |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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