Literaturnachweis - Detailanzeige
Autor/inn/en | Allen, Laura K.; Crossley, Scott A.; McNamara, Danielle S. |
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Titel | Predicting Misalignment between Teachers' and Students' Essay Scores Using Natural Language Processing Tools [Konferenzbericht] Paper presented at the International Conference on Artificial Intelligence in Education (17th, 2015). |
Quelle | (2015), (5 Seiten)
PDF als Volltext |
Zusatzinformation | Weitere Informationen |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Essays; Scores; Natural Language Processing; Interrater Reliability; Accuracy; Self Evaluation (Individuals); Language Styles; High School Students; Grade 10; Secondary School Teachers; Differences; Writing Evaluation; College Entrance Examinations |
Abstract | We investigated linguistic factors that relate to misalignment between students' and teachers' ratings of essay quality. Students (n = 126) wrote essays and rated the quality of their work. Teachers then provided their own ratings of the essays. Results revealed that students who were less accurate in their self-assessments produced essays that were more causal, contained less meaningful words, and had less argument overlap between sentences. (As Provided). |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2022/4/11 |