The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Overcoming Memory Limitations in Rule Learning
Open accessAbstract
Adults, infants, and other species are able to learn and generalize abstract patterns from sequentially presented stimuli. Rule learning of this type may be involved in children's acquisition of linguistic structure, but the nature of the mechanisms underlying these abilities is unknown. While inferences regarding the capabilities of these mechanisms are commonly made based on the pattern of successes and failures in simple artificial-language rule-learning tasks, failures may be driven by memory limitations rather than intrinsic limitations on the kinds of computations that learners can perform. Here we show that alleviating memory constraints on adult learners through concurrent visual presentation of stimuli allowed them to succeed in learning regularities in three difficult artificial rule-learning experiments where participants had previously failed to learn via sequential auditory presentation. These results suggest that memory constraints, rather than intrinsic limitations on learning, may be a parsimonious explanation for many previously reported failures. We argue that future work should attempt to characterize the role of memory constraints in natural and artificial language learning.
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Research on conceptual and perceptual category learning and artificial grammar rule learning has primarily focused on variable-constant KCs, which are essentially category-recognition rules with many-to-one mappings.
“While memory research has emphasized constant-constant KCs, research on conceptual and perceptual category learning (Medin & Schaffer, 1978) and artificial grammar rule learning (Frank & Gibson, 2011) has primarily focused on variableconstant KCs, which are essentially category-recognition rules with many-to-one mappings.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Frank & Gibson, 2011
Humans sometimes fail to learn rules not because of failures in induction, but failures in memory, as demonstrated by Frank and Gibson (2011) in artificial grammar learning tasks.
“On the other hand, humans sometimes fail to learn rules not because of failures in induction, but failures in memory -as was nicely demonstrated recently by Frank and Gibson (2011) in artificial grammar learning tasks.”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Frank and Gibson (2011)
Because the acquired category structure must also be remembered, instructional methods that effectively engage memory processes are also important.
“But, because the acquired category structure must also be remembered, instructional methods that effectively engage memory processes are also important (cf.Frank & Gibson, 2011).”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Frank & Gibson, 2011
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Koedinger, K. R., Corbett, A. T., & Perfetti, C. (2012) · Cognitive Science · doi:10.1111/j.1551-6709.2012.01245.x · Cited by 772
“But, because the acquired category structure must also be remembered, instructional methods that effectively engage memory processes are also important (cf. Frank & Gibson, 2011).”
BackgroundInfluential
Metadata
- Authors
- Frank, M. C., & Gibson, E.
- Affiliations
- Stanford University (US)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Frank, Michael C.
- Venue
- Language Learning and Development
- Publisher
- Informa UK Limited
- Published
- 2011-03-31
- Volume
- 7
- Issue
- 2
- Pages
- 130-148
- ISSN
- 1547-3341 (ISSN-L)
- 1547-5441
- OpenAlex
- W2031125651
- Cited by
- 23
- References
- 4
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 2 · 2018: 1 · 2016: 1 · 2015: 2 · 2014: 2 · 2013: 1 · 2012: 3
- FWCI
- 4.55
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-sa
- Locations
- Language Learning and Development (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- rule induction, memory constraints, artificial language learning, auditory presentation, visual presentation, pattern generalization, language learning
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