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Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
Shin, Jinnie; Gierl, Mark J. – International Journal of Testing, 2022
Over the last five years, tremendous strides have been made in advancing the AIG methodology required to produce items in diverse content areas. However, the one content area where enormous problems remain unsolved is language arts, generally, and reading comprehension, more specifically. While reading comprehension test items can be created using…
Descriptors: Reading Comprehension, Test Construction, Test Items, Natural Language Processing
Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2020
A key writing skill is the capability to clearly convey desired meaning using available linguistic knowledge. Consequently, writers must select from a large array of idioms, vocabulary terms that are semantically equivalent, and discourse features that simultaneously reflect content and allow readers to grasp meaning. In many cases, a simplified…
Descriptors: Natural Language Processing, Writing Skills, Difficulty Level, Reading Comprehension
McCarthy, Kathryn S.; Allen, Laura K.; Hinze, Scott R. – Grantee Submission, 2020
Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…
Descriptors: Reading Comprehension, Prediction, Responses, College Students
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing may more accurately capture their…
Descriptors: Writing (Composition), Persuasive Discourse, Essays, Language Usage
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
Pirnay-Dummer, Pablo; Ifenthaler, Dirk – Instructional Science: An International Journal of the Learning Sciences, 2011
Our study integrates automated natural language-oriented assessment and analysis methodologies into feasible reading comprehension tasks. With the newly developed T-MITOCAR toolset, prose text can be automatically converted into an association net which has similarities to a concept map. The "text to graph" feature of the software is based on…
Descriptors: Concept Mapping, Reading Comprehension, Graphs, Natural Language Processing
Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification