Modeling Word Learning Trajectories
单词学习轨迹建模
基本信息
- 批准号:8432054
- 负责人:
- 金额:$ 17.94万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-02-01 至 2016-01-31
- 项目状态:已结题
- 来源:
- 关键词:2 year old3 year oldAgeCategoriesCharacteristicsChildComprehensionComputer SimulationDataDevelopmentDevelopmental ProcessEducational process of instructingExplosionFutureGrowthHearingIndividualIndividual DifferencesKnowledgeLanguageLearningMapsMeasuresModelingNamesOutcomePathway interactionsPerformanceProcessProductionPropertyRecording of previous eventsResearchSolidSorting - Cell MovementSpeedTestingTimeVocabularyWord Processingabstractingbaseexperiencelexicalobject shapeprogramspublic health relevancesuccessful interventiontooltrend
项目摘要
DESCRIPTION (provided by applicant): In typical development, word learning goes from slow and laborious to seemingly rapid and effortless. Typically developing 3-year-olds are so skilled at learning noun categories that they seem to intuit the whole range of things in the category from hearing a single instance named. As children learn these early vocabularies, they also seem to learn abstract generalities about how nouns map to different kinds of categories. These abstract kind-specific generalizations in turn speed up subsequent noun learning. This is not necessarily the case for children below the 15th-20th percentile on productive vocabulary (late talkers). Although there is continuity in vocabulary measures at the group level, the outcome for individual children cannot be accurately predicted on the basis of vocabulary production or comprehension. The proposed research seeks to understand the forces that create the developmental trajectories in the noun learning of individual children. To that end, I propose to 1) study different groups of children, including early and late talkers, 2) study individual developmental trajectories and the relation between experiences and the characteristics of those individual trends, 3) build and test computational models of noun learning through which we can predict the future word learning of a child from the composition of that child's current vocabulary and, 4) attempt to perturb these developmental trajectories by offering focused and enriching experiences. Understanding how different factors change the noun learning pathways in individual children with different developmental profiles should allow us to both predict the likely developmental trajectories for individual children and the sorts of experiences that may impact this trajectory.
描述(由申请人提供):在典型的发展中,单词学习从缓慢而费力到看似快速且毫不费力。通常,正在发育的三岁孩子非常擅长学习名词类别,他们似乎可以通过听到单个实例来直觉地了解该类别中的所有事物。当孩子们学习这些早期词汇时,他们似乎也学习了有关名词如何映射到不同类别的抽象概括。这些抽象的特定类别的概括反过来又加速了后续的名词学习。对于词汇量低于 15-20% 的儿童(说话较晚的人)来说,情况不一定如此。尽管团体层面的词汇测量具有连续性,但无法根据词汇产生或理解来准确预测个别儿童的结果。拟议的研究旨在了解在个别儿童的名词学习中创造发展轨迹的力量。为此,我建议:1)研究不同的儿童群体,包括早说话和晚说话的人,2)研究个体发展轨迹以及经验与这些个体趋势特征之间的关系,3)建立和测试名词学习的计算模型,通过该模型我们可以根据孩子当前词汇的构成来预测孩子未来的单词学习,4)尝试通过提供集中和丰富的体验来扰乱这些发展轨迹。了解不同因素如何改变具有不同发展概况的个别儿童的名词学习路径,应该使我们能够预测个别儿童可能的发展轨迹以及可能影响该轨迹的经历类型。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Eliana Colunga其他文献
Eliana Colunga的其他文献
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