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Predicting Misalignment between Teachers' and Students' Essay Scores Using Natural Language Processing Tools

Authors :
Allen, Laura K.
Crossley, Scott A.
McNamara, Danielle S.
Source :
Grantee Submission. 2015Paper presented at the International Conference on Artificial Intelligence in Education (17th, 2015).
Publication Year :
2015

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.

Details

Language :
English
Database :
ERIC
Journal :
Grantee Submission
Publication Type :
Conference
Accession number :
ED586432
Document Type :
Speeches/Meeting Papers<br />Reports - Research