@inproceedings{191d9c4c691f4b89aa4ba8d409a4064f,
title = "Predicting misalignment between teachers{\textquoteright} and students{\textquoteright} essay scores using natural language processing tools",
abstract = "We investigated linguistic factors that relate to misalignment between students{\textquoteright} and teachers{\textquoteright} 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.",
keywords = "Cohesion, Computational linguistics, Corpus linguistics, Intelligent tutoring systems, Natural language processing, Writing pedagogy",
author = "Allen, {Laura K.} and Crossley, {Scott A.} and Danielle McNamara",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 17th International Conference on Artificial Intelligence in Education, AIED 2015 ; Conference date: 22-06-2015 Through 26-06-2015",
year = "2015",
doi = "10.1007/978-3-319-19773-9_54",
language = "English (US)",
isbn = "9783319197722",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "529--532",
editor = "Cristina Conati and Neil Heffernan and Antonija Mitrovic and {Felisa Verdejo}, M.",
booktitle = "Artificial Intelligence in Education - 17th International Conference, AIED 2015, Proceedings",
}