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dc.contributor.authorCaldwell-Harris, Catherineen_US
dc.contributor.authorDiallo, S. Y.en_US
dc.contributor.authorWildman, W.en_US
dc.contributor.authorShults, F. L.en_US
dc.contributor.authorTolk, A.en_US
dc.date2019-01-01
dc.date.accessioned2019-08-28T13:57:36Z
dc.date.available2019-08-28T13:57:36Z
dc.date.issued2019-09
dc.identifierhttps://www.springer.com/gp/book/9783030170899#aboutBook
dc.identifier.citationCatherine Caldwell-Harris, S.Y. Diallo, W. Wildman, F.L. Shults, A. Tolk. 2019. "Language learning following immigration: Modeling choices and challenges." Volume 7, https://doi.org/10.1007/978-3-030-17090-5
dc.identifier.isbnISBN 978-3-030-17090-5
dc.identifier.urihttps://hdl.handle.net/2144/37429
dc.description.abstractNo agent-based model exists of language learning following immigration to a new country. Language learning has features that make it a good fit to ABMs, such as diffusion/adoption effects: people learn language via social interaction and are influenced by other social actors about how and when to invest in learning. Language learning involves positive and negative feedback loops, such that poor progress early in learning can spiral into negativity and avoidance, while early success can accelerate learning. Most importantly, the question of why language learning is difficult for adults is controversial. Should implementers program into models the equations that match the robust age effects observed in data, or should these patterns emerge from multiple factors and actors? To address this, the large literature on foreign language acquisition was reviewed as part of the background of making modeling decisions. Decisions were sufficiently challenging that it was decided to begin with a narrative description, using the Overview, Design Concepts and Details protocol (ODD). The ODD protocol provided an organizing framework in which many details were worked out. These included identifying outcome variables (frequency of use and fluency in the two languages), basic entities (representing individuals, families, neighborhood, global environment), defining rules for initiating and continuing conversation, and rules for agents to move to new locations. Considerable narrative space was used to discuss the rationale for simplifications, as well as decisions that were left for future extensions. Given the complexity of the domain, the narrative description was a necessary foundation to smooth the way for a working simulation.en_US
dc.language.isoen_US
dc.publisherSpringeren_US
dc.relation.ispartofHuman simulation: Perspectives, insights, and applications
dc.relation.ispartofseriesNew Approaches to the Scientific Study of Religion;
dc.subjectLanguage learningen_US
dc.subjectBilingualismen_US
dc.subjectImmigrationen_US
dc.subjectCritical perioden_US
dc.subjectMotivationen_US
dc.subjectFluencyen_US
dc.subjectODDen_US
dc.titleLanguage learning following immigration: modeling choices and challengesen_US
dc.typeBook chapteren_US
dc.description.versionAccepted manuscripten_US
pubs.elements-sourcemanual-entryen_US
pubs.notes978-3-030-17089-9; 2367-3494 [Language acquisition model]en_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Psychological & Brain Sciencesen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0002-9830-1156 (Caldwell-Harris, Catherine)
dc.identifier.mycv436060


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