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Latifi, Syed; Gierl, Mark – Language Testing, 2021
An automated essay scoring (AES) program is a software system that uses techniques from corpus and computational linguistics and machine learning to grade essays. In this study, we aimed to describe and evaluate particular language features of Coh-Metrix for a novel AES program that would score junior and senior high school students' essays from…
Descriptors: Writing Evaluation, Computer Assisted Testing, Scoring, Essays
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Rupp, André A.; Casabianca, Jodi M.; Krüger, Maleika; Keller, Stefan; Köller, Olaf – ETS Research Report Series, 2019
In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…
Descriptors: Automation, Foreign Countries, English (Second Language), Language Tests
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of writing proficiency generally includes analyses of the specific linguistic and rhetorical features contained in the singular essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing might more closely capture writing skill.…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Writing Skills
Madnani, Nitin; Burstein, Jill; Sabatini, John; O'Reilly, Tenaha – Grantee Submission, 2013
We introduce a cognitive framework for measuring reading comprehension that includes the use of novel summary-writing tasks. We derive NLP features from the holistic rubric used to score the summaries written by students for such tasks and use them to design a preliminary, automated scoring system. Our results show that the automated approach…
Descriptors: Computer Assisted Testing, Scoring, Writing Evaluation, Reading Comprehension
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
Neal, Michael – Teachers College Press, 2010
Writing and the teaching of writing is changing at a rapid pace. How can educators understand writing assessment "as" and "with" technology in the 21st-century classroom? Michael Neal contends that new technologies are neither the problem nor the solution. Instead, educators need to tap into digital resources only inasmuch as they promote writing…
Descriptors: Writing Evaluation, Holistic Evaluation, Writing Tests, Educational Technology
National Center for Education Statistics, 2012
This report presents results of the 2011 National Assessment of Educational Progress (NAEP) in writing at grades 8 and 12. In this new national writing assessment sample, 24,100 eighth-graders and 28,100 twelfth-graders engaged with writing tasks and composed their responses on computer. The assessment tasks reflected writing situations common to…
Descriptors: National Competency Tests, Writing Tests, Grade 8, Grade 12
Kobrin, Jennifer L.; Deng, Hui; Shaw, Emily J. – Journal of Applied Testing Technology, 2007
This study was designed to address two frequent criticisms of the SAT essay--that essay length is the best predictor of scores, and that there is an advantage in using more "sophisticated" examples as opposed to personal experience. The study was based on 2,820 essays from the first three administrations of the new SAT. Each essay was…
Descriptors: Testing Programs, Computer Assisted Testing, Construct Validity, Writing Skills