| dc.contributor |
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
|
| dc.contributor |
Gibson, Edward A. |
|
| dc.creator |
Frank, Michael C. |
|
| dc.creator |
Gibson, Edward A. |
|
| dc.date |
2014-08-05T14:20:48Z |
|
| dc.date |
2014-08-05T14:20:48Z |
|
| dc.date |
2011-03 |
|
| dc.date.accessioned |
2023-03-01T18:11:44Z |
|
| dc.date.available |
2023-03-01T18:11:44Z |
|
| dc.identifier |
1547-5441 |
|
| dc.identifier |
1547-3341 |
|
| dc.identifier |
http://hdl.handle.net/1721.1/88534 |
|
| dc.identifier |
Frank, Michael C., and Edward Gibson. “Overcoming Memory Limitations in Rule Learning.” Language Learning and Development 7, no. 2 (March 31, 2011): 130–148. |
|
| dc.identifier |
https://orcid.org/0000-0002-5912-883X |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/279109 |
|
| dc.description |
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. |
|
| dc.description |
National Science Foundation (U.S.) (NSF DDRIG #0746251) |
|
| dc.description |
United States. Department of Education (Jacob K. Javits Graduate Fellowship) |
|
| dc.format |
application/pdf |
|
| dc.language |
en_US |
|
| dc.publisher |
Taylor & Francis |
|
| dc.relation |
http://dx.doi.org/10.1080/15475441.2010.512522 |
|
| dc.relation |
Language Learning and Development |
|
| dc.rights |
Creative Commons Attribution-Noncommercial-Share Alike |
|
| dc.rights |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
|
| dc.source |
MIT Web Domain |
|
| dc.title |
Overcoming Memory Limitations in Rule Learning |
|
| dc.type |
Article |
|
| dc.type |
http://purl.org/eprint/type/JournalArticle |
|