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Meng Cao; Philip I. Pavlik Jr.; Wei Chu; Liang Zhang – International Educational Data Mining Society, 2024
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…
Descriptors: Attention, Algorithms, Artificial Intelligence, Classification
Ménager, David H. – ProQuest LLC, 2021
This dissertation presents a novel theory of event memory along with an associated computational model that embodies the claims of view which is integrated within a cognitive architecture. Event memory is a general-purpose storage for personal past experience. Literature on event memory reveals that people can remember events by both the…
Descriptors: Artificial Intelligence, Computer Software, Models, Information Processing
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Sarsa, Sami; Leinonen, Juho; Hellas, Arto – Journal of Educational Data Mining, 2022
New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Memory
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Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
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Schuler, Kathryn D.; Kodner, Jordan; Caplan, Spencer – First Language, 2020
In 'Against Stored Abstractions,' Ambridge uses neural and computational evidence to make his case against abstract representations. He argues that storing only exemplars is more parsimonious -- why bother with abstraction when exemplar models with on-the-fly calculation can do everything abstracting models can and more -- and implies that his…
Descriptors: Language Processing, Language Acquisition, Computational Linguistics, Linguistic Theory
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Knabe, Melina L.; Vlach, Haley A. – First Language, 2020
Ambridge argues that there is widespread agreement among child language researchers that learners store linguistic abstractions. In this commentary the authors first argue that this assumption is incorrect; anti-representationalist/exemplar views are pervasive in theories of child language. Next, the authors outline what has been learned from this…
Descriptors: Child Language, Children, Language Acquisition, Models
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Simpson-Kent, Ivan L.; Fried, Eiko I.; Akarca, Danyal; Mareva, Silvana; Bullmore, Edward T.; Kievit, Rogier A. – Journal of Intelligence, 2021
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary…
Descriptors: Network Analysis, Brain Hemisphere Functions, Intelligence, Schemata (Cognition)
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Rogers, Timothy T.; McClelland, James L. – Cognitive Science, 2014
This paper introduces a special issue of "Cognitive Science" initiated on the 25th anniversary of the publication of "Parallel Distributed Processing" (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP…
Descriptors: Artificial Intelligence, Cognitive Processes, Models, Cognitive Science
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Biedron, Adriana; Pawlak, Miroslaw – Language Teaching, 2016
This state-of-the art paper focuses on the issue of linguistic giftedness, somewhat neglected in the second language acquisition (SLA) literature, attempting to reconceptualize, expand and update this concept in response to latest developments in the fields of psychology, linguistics and neurology. It first discusses contemporary perspectives on…
Descriptors: Language Aptitude, Gifted, Second Language Learning, Learning Strategies
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Murray, Catherine; Pattie, Alison; Starr, John M.; Deary, Ian J. – Intelligence, 2012
To test whether cognitive ability predicts survival from age 79 to 89 years data were collected from 543 (230 male) participants who entered the study at a mean age of 79.1 years. Most had taken the Moray House Test of general intelligence (MHT) when aged 11 and 79 years from which, in addition to intelligence measures at these two time points,…
Descriptors: Intelligence, Health Conditions, Older Adults, Memory
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Miller, Robert; Rammsayer, Thomas H.; Schweizer, Karl; Troche, Stefan J. – Learning and Individual Differences, 2010
Several memory processes have been examined regarding their relation to psychometric intelligence with the exception of sensory memory. This study examined the relation between decay of iconic memory traces, measured with a partial-report task, and psychometric intelligence, assessed with the Berlin Intelligence Structure test, in 111…
Descriptors: Intelligence, Memory, Psychometrics, Correlation
McKoon, Gai; Ratcliff, Roger – Grantee Submission, 2016
Millions of adults in the United States lack the necessary literacy skills for most living wage jobs. For students from adult learning classes, we used a lexical decision task to measure their knowledge of words and we used a decision-making model (Ratcliff's, 1978, diffusion model) to abstract the mechanisms underlying their performance from…
Descriptors: Reading Skills, Psycholinguistics, Memory, Decision Making
Hendy, Mohamed H. – Online Submission, 2016
Educational research and practice have proven that there are many benefits for applying learning theories' recommendations through teaching and learning of different subjects in all school levels. Based on interrelationships among learning theories of contextualism, connectivism, constructivism, and cognitivism, the researcher proposed an…
Descriptors: Science Instruction, Learning Theories, Models, Instructional Effectiveness
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Karagiannakis, Giannis N.; Baccaglini-Frank, Anna E.; Roussos, Petros – Australian Journal of Learning Difficulties, 2016
Through a review of the literature on mathematical learning disabilities (MLD) and low achievement in mathematics (LA) we have proposed a model classifying mathematical skills involved in learning mathematics into four domains (Core number, Memory, Reasoning, and Visual-spatial). In this paper we present a new experimental computer-based battery…
Descriptors: Mathematics Skills, Mathematical Aptitude, Skill Analysis, Learning Disabilities
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Li, Nan; Cohen, William W.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2013
The order of problems presented to students is an important variable that affects learning effectiveness. Previous studies have shown that solving problems in a blocked order, in which all problems of one type are completed before the student is switched to the next problem type, results in less effective performance than does solving the problems…
Descriptors: Teaching Methods, Teacher Effectiveness, Problem Solving, Problem Based Learning
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