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Precision communication: Physicians’ linguistic adaptation to patients’ health literacy
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In: Sci Adv (2021)
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Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
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In: Artificial Intelligence in Education (2020)
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Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study
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In: Health Serv Res (2020)
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Extended Multi-document Cohesion Network Analysis Centered on Comprehension Prediction
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In: Artificial Intelligence in Education (2020)
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Sequence-to-Sequence Models for Automated Text Simplification
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In: Artificial Intelligence in Education (2020)
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Challenges and solutions to employing natural language processing and machine learning to measure patients’ health literacy and physician writing complexity: The ECLIPPSE study
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In: J Biomed Inform (2020)
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Secure Messaging with Physicians by Proxies for Patients with Diabetes: Findings from the ECLIPPSE Study
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In: J Gen Intern Med (2019)
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Incorporating Learning Characteristics into Automatic Essay Scoring Models: What Individual Differences and Linguistic Features Tell Us about Writing Quality ...
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Incorporating Learning Characteristics into Automatic Essay Scoring Models: What Individual Differences and Linguistic Features Tell Us about Writing Quality ...
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Abstract:
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 features and individual differences increases the accuracy of automatically assigned essay scores over using either individual differences or text features alone. The findings presented here have important implications for writing educators because they reveal that essay scoring methods can benefit from the incorporation of features taken not only from the essay itself (e.g., features related to lexical and syntactic complexity), but also from the writer (e.g., vocabulary knowledge and writing attitudes). The findings have implications for educational data mining researchers because they demonstrate new natural language processing approaches that afford the automatic ... : The file is in PDF format. If your computer does not recognize it, simply download the file and then open it with your browser. ...
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Keyword:
automated essay scoring; individual differences; intelligent tutoring systems; natural language processing; writing quality
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URL: https://dx.doi.org/10.5281/zenodo.3554594 https://zenodo.org/record/3554594
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To Aggregate or Not? Linguistic Features in Automatic Essay Scoring and Feedback Systems
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In: Journal of Writing Assessment, vol 8, iss 1 (2015)
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Linguistic microfeatures to predict L2 writing proficiency: A case study in Automated Writing Evaluation
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In: Journal of Writing Assessment, vol 7, iss 1 (2014)
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What's so simple about simplified texts? A computational and psycholinguistic investigation of text comprehension and text processing
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