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).

Autor/inn/en	Allen, Laura K.; Crossley, Scott A.; McNamara, Danielle S.
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 kostenfreie Datei Verfügbarkeit
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 + Suchen Sie Ihr Suchwort? Essay; Aufsatzunterricht; Natürliche Sprache; Interrater-Reliabilität; Sprachstil; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Unterscheiden; Aufnahmeprüfung
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