Doctoral Dissertation Research: Learning attitude verb meanings

拥有强大的语言能力是成为社会生产力成员的关键。然而，关于幼儿如何从没有任何语言开始学习这种复杂而关键的能力，仍然有许多未解之谜。这些问题的答案不仅具有教育影响，而且还可能提供重要的见解，了解认知语言障碍和基于社会经济地位的学习成果差异等问题的根源。本论文项目中研究的问题涉及幼儿如何学习动词的含义：动词构成语言句子的核心，因此了解动词是如何学习的是了解儿童如何更普遍地学习语言的关键。 有些动词对孩子来说比其他的更难学。例如，像“跑”和“打”这样的动作动词比像“相信”和“想要”这样的心理动词更早学习。“相信”和“想要”可能是后来才学会的一个原因是，虽然我们可以看到和听到跑步和击球事件，但我们不能看到或听到思考和想要。然而，孩子们学习这些动词，所以除了感官之外，一定还有其他途径。本研究使用语言学理论、认知科学和计算机科学的方法来研究这条路线是什么，以检验一个有希望的建议：儿童使用动词出现的句子上下文来推断其含义。这项研究将探讨儿童如何利用句子上下文的相似性似乎对应于动词意义的相似性这一事实的理论。为了回答这个问题，本研究将采用实验方法来测量语境信息对动词学习的影响。研究人员将使用Mechanical Turk进行数据收集，在人工语法学习实验中测量这些对表现的影响。研究人员将把这些实验的发现纳入一个认知过程的计算模型，让孩子们学习单词。 这第二步在科学上和实践上都是有用的。一方面，它将导致对语言学习背后的心理过程有更深的理解。另一方面，它将提供一个认知发展的模型，有助于预测对儿童所说的语言的差异-例如，受社会经济地位影响的语言-对语言学习结果的影响。

Having strong linguistic ability is crucial for becoming a productive member of society. However, there remain many unanswered questions regarding how young children, who start out with no language whatsoever, learn this complex and crucial ability. The answer to these questions not only has educational ramifications but may also provide important insights into the root causes of such matters as the increased prevalence of cognitive-linguistic disorders and socioeconomic-status-based differences in learning outcomes. The issues examined in this dissertation project relate to how young children learn the meanings of verbs: Verbs constitute the core of a language's sentences, so understanding how verbs are learned is key to understanding how children learn language more generally. Some verbs are harder for children to learn than others. For instance, action verbs like "run" and "hit" are learned earlier than mental verbs like "believe" and "want". One reason "believe" and "want" might be learned later is that, whereas we can see and hear running and hitting events, we can't see or hear thinking and wanting. Children nevertheless learn these verbs, so a route other than the senses must exist. This research investigates what that route is using methods from linguistic theory, cognitive science, and computer science to examine one promising proposal: that children use the sentence contexts a verb occurs in to infer its meaning. The research will examine theories of how children leverage the fact that similarity in sentence context seems to correspond to similarity in verb meaning. To answer this question, this research will exploit experimental methods for measuring the effect of contextual information on verb learning. The investigators will measure these effects on performance in artificial grammar learning experiments using Mechanical Turk for data collection. The researchers will incorporate the findings from these experiments into a computational model of the cognitive processes that allow children to learn words. This second step is useful both scientifically and practically. On the one hand, it will result in a deeper understanding of the mental processes that underlie language learning. On the other, it will provide a model of cognitive development that will help predict the effect that differences in the language spoken to children--for instance, those conditioned by socioeconomic status--have on language learning outcomes.