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Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing
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
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Open-ended comprehension questions are a common type of assessment used to evaluate how well students understand one of multiple documents. Our aim is to use natural language processing (NLP) to infer the level and type of inferencing within readers' answers to comprehension questions using linguistic and semantic features within their responses.…
Descriptors: Natural Language Processing, Taxonomy, Responses, Semantics
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
Roettger, Timo B.; Franke, Michael – Cognitive Science, 2019
Intonation plays an integral role in comprehending spoken language. Listeners can rapidly integrate intonational information to predictively map a given pitch accent onto the speaker's likely referential intentions. We use mouse tracking to investigate two questions: (a) how listeners draw predictive inferences based on information from…
Descriptors: Cues, Intonation, Language Processing, Speech Communication
Keezhatta, Muhammed Salim – Arab World English Journal, 2019
Natural Language Processing (NLP) platforms have recently reported a higher adoption rate of Artificial Intelligence (AI) applications. The purpose of this research is to examine the relationship between NLP and AI in the application of linguistic tasks related to morphology, parsing, and semantics. To achieve this objective, a theoretical…
Descriptors: Models, Correlation, Natural Language Processing, Artificial Intelligence
Radulescu, Silvia; Wijnen, Frank; Avrutin, Sergey – Language Learning and Development, 2020
From limited evidence, children track the regularities of their language impressively fast and they infer generalized rules that apply to novel instances. This study investigated what drives the inductive leap from memorizing specific items and statistical regularities to extracting abstract rules. We propose an innovative entropy model that…
Descriptors: Linguistic Input, Language Acquisition, Grammar, Learning Processes
Sharp, Rebecca Reynolds – ProQuest LLC, 2017
We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…
Descriptors: Computation, Natural Language Processing, Inferences, Questioning Techniques
Ryan D. Kopatich; Joseph P. Magliano; Keith K. Millis; Christopher P. Parker; Melissa Ray – Grantee Submission, 2019
A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…
Descriptors: Inferences, Reading Comprehension, Models, College Students
Ryan D. Kopatich; Joseph P. Magliano; Keith K. Millis; Christopher P. Parker; Melissa Ray – Discourse Processes: A Multidisciplinary Journal, 2019
A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…
Descriptors: Reading Tests, Intelligence Tests, Inferences, Reading Comprehension
McNamara, Danielle S.; Roscoe, Rod; Allen, Laura; Balyan, Renu; McCarthy, Kathryn S. – Grantee Submission, 2019
Literacy is a critically important and contemporary issue for educators, scientists, and politicians. Efforts to overcome the challenges associated with illiteracy, and the subsequent development of literate societies, are closely related to those of poverty reduction and sustainable human development. In this paper, the authors examine literacy…
Descriptors: Literacy, Reading Comprehension, Language Processing, Discourse Analysis
Phillips, Lawrence; Pearl, Lisa – Cognitive Science, 2015
The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's "cognitive plausibility." We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition…
Descriptors: Language Acquisition, Models, Computational Linguistics, Credibility
Tu, Yuancheng – ProQuest LLC, 2012
The fundamental problem faced by automatic text understanding in Natural Language Processing (NLP) is to identify semantically related pieces of text and integrate them together to compute the meaning of the whole text. However, the principle of compositionality runs into trouble very quickly when real language is examined with its frequent…
Descriptors: English, Verbs, Computational Linguistics, Natural Language Processing
Boyd-Graber, Jordan – ProQuest LLC, 2010
Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…
Descriptors: Language Patterns, Semantics, Linguistics, Multilingualism
McKoon, Gail; Ratcliff, Roger – Journal of Memory and Language, 2013
In the domain of discourse processing, it has been claimed that older adults (60-0-year-olds) are less likely to encode and remember some kinds of information from texts than young adults. The experiment described here shows that they do make a particular kind of inference to the same extent that college-age adults do. The inferences examined were…
Descriptors: Accuracy, Theory Practice Relationship, Young Adults, Inferences
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