Literaturnachweis - Detailanzeige
| Autor/inn/en | Crossley, Scott; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. |
|---|---|
| Titel | Pssst… Textual Features… There Is More to Automatic Essay Scoring than Just You! |
| Quelle | (2015), (5 Seiten)
PDF als Volltext kostenfreie Datei |
| Zusatzinformation | Weitere Informationen |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Automation; Scoring; Essays; Evaluation Methods; Student Characteristics; Intelligent Tutoring Systems; Natural Language Processing; High School Students; Reading Tests; Writing Apprehension; Educational Technology; Technology Uses in Education; Arizona (Phoenix); Gates MacGinitie Reading Tests; Writing Apprehension Test |
| Abstract | This study investigates a new approach to automatically assessing essay quality that combines traditional approaches based on assessing textual features with new approaches that measure student attributes such as demographic information, standardized test scores, and survey results. The results demonstrate that combining both text features and student attributes leads to essay scoring models that are on par with state-of-the-art scoring models. Such findings expand our knowledge of textual and nontextual features that are predictive of writing success. [This paper was published in: "LAK '15" (Poughkeepsie, New York, March 16-20, 2015). ACM. (ISBN 978-1-4503-3417-4)] (As Provided). |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2022/4/11 |
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