Constraints on Learning from Inconsistent Input

从不一致的输入中学习的限制

• 批准号: 7212176
• 负责人: CARLA L HUDSON KAM
• 金额: $ 18.67万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7212176
• 关键词: Address; Adult; Affect; Age; Animals; Child; Childhood; Cognitive; Complex; Computer information processing; Data; Development; Disease; Elements; Goals; Human; Knowledge; Language; Language Development; Lead; Learning; Machine Learning; Modality; Nature; Numbers; Pattern; Positioning Attribute; Principal Investigator; Process; Property; Research; Research Design; Research Personnel; Series; Short-Term Memory; Source; Specificity; Time; Variant; Work; age related; design; programs; research study; stem

DESCRIPTION (provided by applicant): All human learners with normal cognitive capacities who are exposed to language input in childhood manage to acquire a language that looks very much like their input. However, at present we have little idea how, exactly, learners accomplish this feat. We have little understanding of the nature of the learning mechanisms that underlie and support language learning. This is the focus of the research in this proposal. Three general questions guide the research. (1) What are the constraints on language learning mechanisms? (2) Are the learning mechanisms involved in language acquisition specific to language or are they of a more general nature? (3) Do these mechanisms change over time as learners age, and if 'so, how? The proposed research examines these questions by investigating the learning of probabilistic and inconsistent patterns in the input using miniature artificial languages. This provides a rather unique view of the constraints on learning mechanisms, examining the limits of what can and cannot be learned. Previous work has shown that learners can acquire probabilistic patterns, however they sometimes impose consistency on variation. Moreover, children are more likely to change such patterns than are adults. The present research expands on the earlier results, asking about the nature of the interaction between learners and input. Series 1 asks about the nature of the input that makes some inconstancy learnable and some not. The studies examine the limits of veridical learning of inconsistent patterns in languages, asking questions about the specificity of computations learners can perform, the representations over which such computations can be performed, and the effect of prior domain-specific knowledge. Series 2 asks about the nature of the learner, asking why learners regularize over inconsistency at all. In particular, the studies examine whether working memory constraints, rather than constraints stemming directly from the learning mechanisms themselves, are an important factor influencing whether learners acquire the variation or instead impose regularity. Both series will be conducted with adults and children to examine how learning changes over development. Although the input in the proposed studies is somewhat atypical, the results from these studies will contribute to our understanding of the learning mechanisms involved in language acquisition more generally, and ultimately, this increases our understanding of both normal and disordered acquisition.

描述（由申请人提供）：所有具有正常认知能力的人类学习者，他们在童年时期接受语言输入的人都可以获得看起来非常类似于其输入的语言。但是，目前，我们几乎不知道学习者如何完成这一壮举。我们对基于和支持语言学习的学习机制的本质几乎没有理解。这是该提案中研究的重点。三个一般问题指导研究。 （1）对语言学习机制有什么限制？ （2）语言获取的学习机制是特定于语言的，还是它们具有更一般的性质？ （3）随着学习者的年龄，这些机制会随着时间的流逝而变化，如果是的话，如何？拟议的研究通过研究使用微型人工语言在输入中研究概率和不一致的模式来研究这些问题。这为学习机制的限制提供了一个相当独特的看法，研究了可以学习和无法学习的限制。以前的工作表明，学习者可以获取概率模式，但是他们有时会对变化施加一致性。此外，与成年人相比，儿童更有可能改变这种模式。本研究扩展了较早的结果，询问学习者与输入之间相互作用的性质。系列1询问有关输入的性质，这使一些不稳定的知识是可学习的，有些则不能学习。研究研究了语言中不一致模式的垂直学习的局限性，询问学习者可以执行的计算特异性，可以执行此类计算的表示以及先前特定领域的知识的影响。系列2询问了学习者的性质，询问为什么学习者完全规范矛盾。特别是，研究检查工作记忆约束是直接源于学习机制本身的约束是影响学习者是否获得变异还是施加规律性的重要因素。这两个系列都将与成人和儿童一起进行，以检查学习如何对发展的变化。尽管拟议的研究中的输入有些非典型，但这些研究的结果将有助于我们更广泛地了解语言获取所涉及的学习机制，最终，这增加了我们对正常和无序习得的理解。