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Showing 1 to 15 of 19 results Save | Export
Crossley, Scott A.; Kim, Minkyung; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2019
Summarization is an effective strategy to promote and enhance learning and deep comprehension of texts. However, summarization is seldom implemented by teachers in classrooms because the manual evaluation of students' summaries requires time and effort. This problem has led to the development of automated models of summarization quality. However,…
Descriptors: Automation, Writing Evaluation, Natural Language Processing, Artificial Intelligence
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Kyle, Kristopher; Crossley, Scott A.; Jarvis, Scott – Language Assessment Quarterly, 2021
Indices of lexical diversity have been used to estimate the size of a writer's vocabulary and/or a writer's lexical proficiency for some time. One issue with many commonly used indices of lexical diversity (e.g., TTR and index) is that they vary as a function of text length. Accordingly, much research has been devoted to the development of indices…
Descriptors: Decision Making, Vocabulary Development, Computational Linguistics, Persuasive Discourse
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Monteiro, Kátia R.; Crossley, Scott A.; Kyle, Kristopher – Applied Linguistics, 2020
Lexical items that are encountered more frequently and in varying contexts have important effects on second language (L2) development because frequent and contextually diverse words are learned faster and become more entrenched in a learner's lexicon (Ellis 2002a, b). Despite evidence that L2 learners are generally exposed to non-native input,…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Benchmarking
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Kyle, Kristopher; Crossley, Scott A. – Modern Language Journal, 2018
Syntactic complexity is an important measure of second language (L2) writing proficiency (Larsen--Freeman, 1978; Lu, 2011). Large-grained indices such as the mean length of T-unit (MLTU) have been used with the most consistency in L2 writing studies (Ortega, 2003). Recently, indices such as MLTU have been criticized, both for the difficulty in…
Descriptors: Syntax, English (Second Language), Language Tests, Second Language Learning
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Crossley, Scott A.; Rose, Dani Francuz; Danekes, Cassondra; Rose, Charles Wesley; McNamara, Danielle S. – Reading and Writing: An Interdisciplinary Journal, 2017
This paper examines the effects of attended and unattended demonstratives on text processing, comprehension, and writing quality in two studies. In the first study, participants (n = 45) read 64 mini-stories in a self-paced reading task and identified the main referent in the clauses. The sentences varied in the type of demonstratives (i.e., this,…
Descriptors: Nouns, Phrase Structure, Form Classes (Languages), Connected Discourse
Crossley, Scott A.; Kyle, Kristopher; McNamara, Danielle S. – Grantee Submission, 2015
This study investigates the relative efficacy of using linguistic micro-features, the aggregation of such features, and a combination of micro-features and aggregated features in developing automatic essay scoring (AES) models. Although the use of aggregated features is widespread in AES systems (e.g., e-rater; Intellimetric), very little…
Descriptors: Essays, Scoring, Feedback (Response), Writing Evaluation
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Crossley, Scott A.; Muldner, Kasia; McNamara, Danielle S. – Written Communication, 2016
Idea generation is an important component of most major theories of writing. However, few studies have linked idea generation in writing samples to assessments of writing quality or examined links between linguistic features in a text and idea generation. This study uses human ratings of idea generation, such as "idea fluency, idea…
Descriptors: College Freshmen, Freshman Composition, Essays, Concept Formation
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Skalicky, Stephen; Berger, Cynthia M.; Crossley, Scott A.; McNamara, Danielle S. – Advances in Language and Literary Studies, 2016
A corpus of 313 freshman college essays was analyzed in order to better understand the forms and functions of humor in academic writing. Human ratings of humor and wordplay were statistically aggregated using Factor Analysis to provide an overall "Humor" component score for each essay in the corpus. In addition, the essays were also…
Descriptors: Discourse Analysis, Academic Discourse, Humor, Writing (Composition)
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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
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Crossley, Scott A.; McNamara, Danielle S. – Grantee Submission, 2014
This study explores correlations between human ratings of essay quality and component scores based on similar natural language processing indices and weighted through a principal component analysis. The results demonstrate that such component scores show small to large effects with human ratings and thus may be suitable to providing both summative…
Descriptors: Essays, Computer Assisted Testing, Writing Evaluation, Scores
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Roscoe, Rod D.; Crossley, Scott A.; Snow, Erica L.; Varner, Laura K.; McNamara, Danielle S. – Grantee Submission, 2014
Automated essay scoring tools are often criticized on the basis of construct validity. Specifically, it has been argued that computational scoring algorithms may be unaligned to higher-level indicators of quality writing, such as writers' demonstrated knowledge and understanding of the essay topics. In this paper, we consider how and whether the…
Descriptors: Correlation, Essays, Scoring, Writing Evaluation
Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.; Guo, Liang; McNamara, Danielle S. – Grantee Submission, 2014
This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…
Descriptors: Computational Linguistics, Essays, Scoring, Writing Evaluation
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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
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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
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Crossley, Scott A.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2014
The study applied the Multi-Dimensional analysis used by Biber (1988) to examine the functional parameters of essays. Co-occurrence patterns were identified within an essay corpus (n=1529) using a linguistic indices provided by Co-Metrix. These patterns were used to identify essay groups that shared features based upon situational parameters.…
Descriptors: Essays, Writing (Composition), Computational Linguistics, Cues
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