Variability and detection of invariant structure
Variability and detection of invariant structure
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DOI：
10.1111/1467-9280.00476
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发表时间：
2002-09-01
影响因子：
8.2
通讯作者：
Gómez, RL
中科院分区：
文献类型：
--
作者：
Gómez, RL
两个实验研究了成人和18个月大的孩子对非相邻依赖关系的学习。每个学习者都接触到三个元素的字符串（例如，pel-kicey-jic）由两种人工语言之一产生。两种语言都包含相同的相邻依赖关系，因此学习者只能通过获取第一个和第三个元素之间的依赖关系（非相邻依赖关系）来区分这两种语言。从中提取中间元素的池的大小被系统地改变，以研究增加可变性（以相邻元素之间的可预测性降低的形式）是否会导致更好地检测非相邻依赖性。婴儿和成年人获得非相邻的依赖关系时，相邻的依赖关系是最不可预测的。结果指出，可能导致学习者专注于非相邻与相邻的依赖关系的条件，并建议如何学习可能会动态地指导统计结构是很重要的。
Two experiments investigated learning of nonadjacent dependencies by adults and 18-month-olds. Each learner was exposed to three-element strings (e.g., pel-kicey-jic) produced by one of two artificial languages. Both languages contained the same adjacent dependencies, so learners could distinguish the languages only by acquiring dependencies between the first and third elements (the nonadjacent dependencies). The size of the pool from which the middle elements were drawn was systematically varied to investigate whether increasing variability (in the form of decreasing predictability between adjacent elements) would lead to better detection of nonadjacent dependencies. Infants and adults acquired nonadjacent dependencies only when adjacent dependencies were least predictable. The results point to conditions that might lead learners to focus on nonadjacent versus adjacent dependencies and are important for suggesting how learning might be dynamically guided by statistical structure.