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Kim, Dan; Opfer, John E. – Grantee Submission, 2021
Perceptual judgments result from a dynamic process, but little is known about the dynamics of number-line estimation. A recent study proposed a computational model that combined a model of trial-to-trial changes with a model for the internal scaling of discrete numbers. Here, we tested a surprising prediction of the model--a situation in which…
Descriptors: Numbers, Computation, Children, Adults
Wu, Jennifer; Wingard, Audra; Golan, Shari; Kothari, Manish – Grantee Submission, 2021
Even when innovations have rigorous evidence of impact, they often are not widely adopted by the field, or their use is not sustained. To support more successful transitions of educational research to the field, SRI researchers modified its Invent-Apply-Transition (I-A-T) framework that has been successfully used to scale research to practice in…
Descriptors: Educational Innovation, Educational Research, Technology Transfer, Research and Development
De Los Reyes, Andres; Makol, Bridget A. – Grantee Submission, 2021
Individuals often vary in how they display signs and symptoms of personality disturbances and psychopathology. As such, comprehensive assessments of these signs and symptoms ought to capture how they manifest within and across time and contexts (e.g., community, home, work). Contexts may vary in the degree to which they influence personality and…
Descriptors: Personality, Psychopathology, Individual Differences, Adults
Butterfuss, Reese; Kendeou, Panayiota – Grantee Submission, 2021
The aim of this paper is two-fold. The first aim is to review the core representational and processing aspects of influential accounts of single-document and multiple-document comprehension with a particular emphasis on how readers negotiate conflicting information during reading. This review provides the groundwork for the second aim--to expand…
Descriptors: Reading Comprehension, Cognitive Processes, Conflict, Misconceptions
Li, Chenglu; Xing, Wanli; Leite, Walter – Grantee Submission, 2021
To support online learners at a large scale, extensive studies have adopted machine learning (ML) techniques to analyze students' artifacts and predict their learning outcomes automatically. However, limited attention has been paid to the fairness of prediction with ML in educational settings. This study intends to fill the gap by introducing a…
Descriptors: Learning Analytics, Prediction, Models, Electronic Learning
Kothalkar, Prasanna V.; Datla, Sathvik; Dutta, Satwik; Hansen, John H. L.; Seven, Yagmur; Irvin, Dwight; Buzhardt, Jay – Grantee Submission, 2021
Speech and language development in children are crucial for ensuring effective skills in their long-term learning ability. A child's vocabulary size at the time of entry into kindergarten is an early indicator of their learning ability to read and potential long-term success in school. The preschool classroom is thus a promising venue for…
Descriptors: Word Frequency, Questioning Techniques, Language Acquisition, Vocabulary Development
Batley, Prathiba Natesan; Hedges, Larry V. – Grantee Submission, 2021
Although statistical practices to evaluate intervention effects in SCEDs have gained prominence in the recent times, models are yet to incorporate and investigate all their analytic complexities. Most of these statistical models incorporate slopes and autocorrelations both of which contribute to trend in the data. The question that arises is…
Descriptors: Bayesian Statistics, Models, Accuracy, Computation
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; McNamara, Danielle S.; Crossley, Scott Andrew – Grantee Submission, 2021
The ability to objectively quantify the complexity of a text can be a useful indicator of how likely learners of a given level will comprehend it. Before creating more complex models of assessing text difficulty, the basic building block of a text consists of words and, inherently, its overall difficulty is greatly influenced by the complexity of…
Descriptors: Multilingualism, Language Acquisition, Age, Models
Corlatescu, Dragos-Georgian; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…
Descriptors: Reading Comprehension, Memory, Inferences, Syntax
Ruseti, Stefan; Dascalu, Maria-Dorinela; Corlatescu, Dragos-Georgian; Dascalu, Mihai; Trausan-Matu, Stefan; McNamara, Danielle S. – Grantee Submission, 2021
Dialogism is a philosophical theory centered on the idea that life involves a dialogue among multiple voices in a continuous exchange and interaction. Considering human language, different ideas or points of view take the form of voices, which spread throughout any discourse and influence it. From a computational point of view, voices can be…
Descriptors: Dialogs (Language), Computational Linguistics, Semantics, Models
Apel, Kenn – Grantee Submission, 2021
The simple view of reading (SVR) framework has been used for decades to explain two general component skills considered to contribute to reading comprehension: decoding and linguistic comprehension. In the past, researchers have assessed the linguistic comprehension component using a wide range of language and/or listening comprehension measures…
Descriptors: Reading Comprehension, Decoding (Reading), Listening Comprehension, Models
Magooda, Ahmed; Litman, Diane – Grantee Submission, 2021
This paper explores three simple data manipulation techniques (synthesis, augmentation, curriculum) for improving abstractive summarization models without the need for any additional data. We introduce a method of data synthesis with paraphrasing, a data augmentation technique with sample mixing, and curriculum learning with two new difficulty…
Descriptors: Data Analysis, Synthesis, Documentation, Models
Magooda, Ahmed; Elaraby, Mohamed; Litman, Diane – Grantee Submission, 2021
This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…
Descriptors: Data Analysis, Synthesis, Documentation, Training
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Keller, Brian T. – Grantee Submission, 2021
In this paper, we provide an introduction to the factored regression framework. This modeling framework applies the rules of probability to break up or "factor" a complex joint distribution into a product of conditional regression models. Using this framework, we can easily specify the complex multivariate models that missing data…
Descriptors: Regression (Statistics), Models, Multivariate Analysis, Computation

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