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Allen, Laura K.; Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2015
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…
Descriptors: Essays, Scores, Natural Language Processing, Interrater Reliability
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Journal of Educational Data Mining, 2016
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
Descriptors: Essays, Scoring, Writing Evaluation, Natural Language Processing
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Journal of Learning Analytics, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays
Snow, Erica L.; Allen, Laura K.; Jacovina, Matthew E.; Crossley, Scott A.; Perret, Cecile A.; McNamara, Danielle S. – Grantee Submission, 2015
Writing researchers have suggested that students who are perceived as strong writers (i.e., those who generate texts rated as high quality) demonstrate flexibility in their writing style. While anecdotally this has been a commonly held belief among researchers and educators, there is little empirical research to support this claim. This study…
Descriptors: Writing (Composition), Writing Strategies, Hypothesis Testing, Essays
Crossley, Scott A.; Roscoe, Rod; McNamara, Danielle S. – Written Communication, 2014
This study identifies multiple profiles of successful essays via a cluster analysis approach using linguistic features reported by a variety of natural language processing tools. The findings from the study indicate that there are four profiles of successful writers for the samples analyzed. These four profiles are linguistically distinct from one…
Descriptors: Essays, Natural Language Processing, Computational Linguistics, Multivariate Analysis
Roscoe, Rod D.; Varner, Laura K.; Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2013
Various computer tools have been developed to support educators' assessment of student writing, including automated essay scoring and automated writing evaluation systems. Research demonstrates that these systems exhibit relatively high scoring accuracy but uncertain instructional efficacy. Students' writing proficiency does not necessarily…
Descriptors: Writing Instruction, Intelligent Tutoring Systems, Computer Assisted Testing, Writing Evaluation
Crossley, Scott A.; Varner, Laura K.; Roscoe, Rod D.; McNamara, Danielle S. – Grantee Submission, 2013
We present an evaluation of the Writing Pal (W-Pal) intelligent tutoring system (ITS) and the W-Pal automated writing evaluation (AWE) system through the use of computational indices related to text cohesion. Sixty-four students participated in this study. Each student was assigned to either the W-Pal ITS condition or the W-Pal AWE condition. The…
Descriptors: Intelligent Tutoring Systems, Automation, Writing Evaluation, Writing Assignments