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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
Rossi, Maya; Martin-Chang, Sandra; Ouellette, Gene – Scientific Studies of Reading, 2019
Variations in the accuracy and stability of a word's spelling can be used to gauge the quality of its underlying orthographic representation. The Lexical Quality Hypothesis (LQH) contends that words with higher quality cognitive representations should be accessed more efficiently than those with lower quality representations. If this is the case,…
Descriptors: Spelling, Accuracy, Reading Rate, Adolescents
Say What? Automatic Modeling of Collaborative Problem Solving Skills from Student Speech in the Wild
Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Crossley, Scott; Kyle, Kristopher; Davenport, Jodi; McNamara, Danielle S. – International Educational Data Mining Society, 2016
This study introduces the Constructed Response Analysis Tool (CRAT), a freely available tool to automatically assess student responses in online tutoring systems. The study tests CRAT on a dataset of chemistry responses collected in the ChemVLab+. The findings indicate that CRAT can differentiate and classify student responses based on semantic…
Descriptors: Intelligent Tutoring Systems, Chemistry, Natural Language Processing, High School Students
Caplan, David; Waters, Gloria; Bertram, Julia; Ostrowski, Adam; Michaud, Jennifer – Reading Research Quarterly, 2016
The authors assessed 4,865 middle and high school students for the ability to recognize and understand written and spoken morphologically simple words, morphologically complex words, and the syntactic structure of sentences and for the ability to answer questions about facts presented in a written passage and to make inferences based on those…
Descriptors: Middle School Students, High School Students, Language Skills, Language Processing
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
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries