The basis of transfer in artificial grammar learning. Gómez, R. L, Gerken, L., & Schvaneveldt, R. Mem Cognit, 28(2):253-63, 2000.
abstract   bibtex   
In two experiments, we examined the extent to which knowledge of sequential dependencies and/or patterns of repeating elements is used during transfer in artificial grammar learning. According to one view of transfer, learners abstract the grammar's sequential dependencies and then learn a mapping to new vocabulary at test (Dienes, Altmann, & Gao, 1999). Elements that are repeated have no special status on this view, and so a logical prediction is that learners should transfer as well after exposure to a grammar without repetitions as after exposure to a grammar with them. On another view, repetition structure is the very basis of transfer (Brooks & Vokey, 1991; Mathews & Roussel, 1997). Learners were trained on grammars with or without repeating elements to test these competing views. Learners demonstrated considerable knowledge of sequential dependencies in their training vocabulary but did not use such knowledge to transfer to a new vocabulary. Transfer only occurred in the presence of repetition structure, demonstrating this to be the basis of transfer.
@Article{Gomez2000,
  author   = {Rebecca L G\'{o}mez and LouAnn Gerken and RW Schvaneveldt},
  journal  = {Mem Cognit},
  title    = {The basis of transfer in artificial grammar learning.},
  year     = {2000},
  number   = {2},
  pages    = {253-63},
  volume   = {28},
  abstract = {In two experiments, we examined the extent to which knowledge of sequential
	dependencies and/or patterns of repeating elements is used during
	transfer in artificial grammar learning. According to one view of
	transfer, learners abstract the grammar's sequential dependencies
	and then learn a mapping to new vocabulary at test (Dienes, Altmann,
	& Gao, 1999). Elements that are repeated have no special status on
	this view, and so a logical prediction is that learners should transfer
	as well after exposure to a grammar without repetitions as after
	exposure to a grammar with them. On another view, repetition structure
	is the very basis of transfer (Brooks & Vokey, 1991; Mathews & Roussel,
	1997). Learners were trained on grammars with or without repeating
	elements to test these competing views. Learners demonstrated considerable
	knowledge of sequential dependencies in their training vocabulary
	but did not use such knowledge to transfer to a new vocabulary. Transfer
	only occurred in the presence of repetition structure, demonstrating
	this to be the basis of transfer.},
  keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, Association Learning, Child Psychology, Habituation (Psychophysiology), Probability Theory, Analysis of Variance, Semantics, Symbolism, Behavior, Eye Movements, Macaca mulatta, Prefrontal Cortex, Cats, Dogs, Haplorhini, Photic Stimulation, Electroencephalography, Nervous System Physiology, Darkness, Grasshoppers, Light, Membrane Potentials, Neural Inhibition, Afferent, Picrotoxin, Vision, Deoxyglucose, Injections, Microspheres, Neural Pathways, Rhodamines, Choice Behavior, Speech Perception, Verbal Learning, 10790980},
}

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