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Duta, Mihaela; Plunkett, Kim – Child Development, 2023
We present a neural network model of referent identification in a visual world task. Inputs are visual representations of item pairs unfolding with sequences of phonemes identifying the target item. The model is trained to output the semantic representation of the target and to suppress the distractor. The training set uses a 200-word lexicon…
Descriptors: Networks, Models, Brain, Child Language
Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – Grantee Submission, 2024
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
Kumar, Abhilasha A.; Balota, David A.; Steyvers, Mark – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
We examined 3 different network models of representing semantic knowledge (5,018-word directed and undirected step distance networks, and an association-correlation network) to predict lexical priming effects. In Experiment 1, participants made semantic relatedness judgments for word pairs with varying path lengths. Response latencies for…
Descriptors: Semantics, Networks, Correlation, Semitic Languages
McClelland, James L. – First Language, 2020
Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…
Descriptors: Models, Language Processing, Artificial Intelligence, Language Usage
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
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
Jones, Michael N.; Gruenenfelder, Thomas M.; Recchia, Gabriel – Grantee Submission, 2017
Recent semantic space models learn vector representations for word meanings by observing statistical redundancies across a text corpus. A word's meaning is represented as a point in a high-dimensional semantic space, and semantic similarity between words is quantified by a function of their spatial proximity (typically the cosine of the angle…
Descriptors: Semantics, Computational Linguistics, Spatial Ability, Proximity
Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N. – Cognitive Science, 2016
We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…
Descriptors: Memory, Semantics, Associative Learning, Networks
Engle, Kelley M. – ProQuest LLC, 2013
Researchers in the medical domain consider the double-blind placebo controlled clinical trial the gold standard. The data for these clinical trials are collected for a specifically defined hypothesis and there is very little in the realm of secondary data analyses conducted. The underlying purpose of this work is to demonstrate the value and…
Descriptors: Medical Research, Data Analysis, Statistical Analysis, Autism
Steyvers, Mark; Tenenbaum, Joshua B. – Cognitive Science, 2005
We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…
Descriptors: Semantics, Internet, Associative Learning, Statistical Analysis
Dixit, R. K. – Online Submission, 2009
Articles in this issue of "Global Journal of Computer Science and Technology" include: (1) Input Data Processing Techniques in Intrusion Detection Systems--Short Review (Suhair H. Amer and John A. Hamilton, Jr.); (2) Semantic Annotation of Stock Photography for CBIR Using MPEG-7 standards (R. Balasubramani and V. Kannan); (3) An Experimental Study…
Descriptors: Knowledge Management, Photography, Semantics, Computer Software
Brandt, Richard C. – 1988
The Computer-Based Memorization System (CBMS), which specifies the facts that students are to know and how well the facts are to be known, uses a compiled form of an associative network for its knowledge database. (An associative network is a knowledge representation that uses associations for its basic representation of knowledge.) The CBMS…
Descriptors: Authoring Aids (Programing), Computer Games, Computer Graphics, Computer System Design
Yang, Stephen J. H. – Educational Technology & Society, 2006
A ubiquitous learning environment provides an interoperable, pervasive, and seamless learning architecture to connect, integrate, and share three major dimensions of learning resources: learning collaborators, learning contents, and learning services. Ubiquitous learning is characterized by providing intuitive ways for identifying right learning…
Descriptors: Management Systems, Group Discussion, Educational Environment, Models

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