样例变异性对多重映射远距离规则内隐学习的影响
Effect of Example Variability on the Implicit Learning of Multiple Non-Adjacent Rule
郭秀艳 1孙鹏 2凌晓丽 3张庆云 4郑丽1
作者信息
- 1. 复旦大学老龄研究院;教育部哲学社会科学实验室——复旦大学国家发展与智能治理综合实验室
- 2. 山东财经大学大学生心理健康教育与研究中心
- 3. 山东师范大学心理学部;山东省脑科学与心理健康重点实验室
- 4. 上海市脑机协同信息行为重点实验室;上海外国语大学国际工商管理学院
- 折叠
摘要
多重映射远距离规则因其可包含多重远距离对应关系而具有无限生成能力，是构建层次复杂的自然语言结构和句子的基础，也是语言习得中最具挑战的部分。研究表明，该规则主要通过内隐方式获得，但如何有效促进其习得仍是关键问题。样例变异性作为影响学习的重要因素，其对多重映射远距离规则内隐学习的作用模式及机制尚不明确，特别是能否促进学习者从具体的值—值映射提升到抽象的变量—变量映射水平，从而获得可迁移的抽象规则。为此，本研究以汉语声调为载体构建多重映射远距离规则，设置低、中、高三种样例变异水平，系统考察不同样例变异水平与内隐学习成绩提升之间的关系模式，并进一步在测验阶段引入学习阶段未出现过的声调映射迁移材料，探讨样例变异性的促进作用是否发生在抽象的变量—变量映射层面。结果发现，样例变异性与内隐学习效应呈U型曲线关系：在高、低变异条件下，被试表现出更强的内隐学习效应，并习得可迁移的变量—变量映射抽象规则；而在中等变异条件下，学习效果较弱，仅习得值—值映射，难以迁移。本研究揭示了样例变异性与多重映射远距离规则内隐学习之间的非线性关系，明确了其作用于变量—变量映射的抽象表征层面；也从样例变异性的角度指出，抽象规则的内隐习得存在特定边界条件。这些发现不仅深化了对内隐学习机制的理解，也为优化教学设计提供了科学依据。
Abstract
Learning multiple non-adjacent dependencies is fundamental to processing the hierarchical structures of natural language and constitutes one of the most challenging aspects of language acquisition. Such dependencies are typically acquired automatically and implicitly; however, how to effectively facilitate their learning remains unresolved. A particularly powerful factor in improving learning and generalization is variability in the input examples. However, its role in the implicit learning of multiple non-adjacent dependencies remains unclear, particularly whether such variability enables learners to move beyond valuevalue mappings to operations over variables, thereby acquiring transferable abstract rules. Accordingly, this study first examines how different levels of example variability influence implicit learning performance (Experiment 1) and then explores whether the effect of variability operates at the level of abstract variablevariable mappings (Experiment 2).The study employed multiple non-adjacent rules defined over the tones with which Chinese syllables were spoken. Specifically, the tone types (ping or ze) of the first five syllables predicted those of the final five by an inversion relation in strings of length ten. In Experiment 1, three conditions of variability (low, medium, and high) were established by manipulating the number of syllable types used in the strings. The experiment comprised a training phase and a test phase. During the training phase, participants listened to a series of tonesyllable strings that followed the multiple non-adjacent rules and repeated them. In the test phase, participants were told that all strings they heard during the training phase followed a grammatical rule, and were asked to judge whether a set of new strings conformed to the learned rule. In Experiment 2, to further examine the level at which variability facilitates learning, two types of materials were constructed. One included only partial tone mappings (e.g., Tone 13 or Tone 24), while the other included complete tone mappings between level tones (Tones 1/2) and contour tones (Tones 3/4). Unlike in Experiment 1, during the training phase of Experiment 2, participants were exposed only to strings containing partial mappings. They were then tested in a non-transfer test (strings with the same partial mappings as in training), and either a mixed transfer test (strings with complete mappings; Experiment 2a) or a novel transfer test (strings with novel partial mappings that conflicted with training; Experiment 2b).The results revealed a U-shaped relationship between example variability and implicit learning performance in Experiment 1: participants showed significant implicit learning effects in both the low- and high-variability conditions, whereas no learning effect was observed in the medium-variability condition. Performance was greater in the low- and high-variability conditions than in the medium-variability condition. In Experiment 2, the participants demonstrated implicit learning in the non-transfer test (Experiment 2a) across all variability conditions. However, their ability to transfer this learning to new materials varied significantly by condition. Participants in the low- and high-variability conditions were able to implicitly extract abstract rules from partial mappings and generalize them to complete mappings (Experiment 2a). Remarkably, this transfer ability was maintained even when participants were confronted with novel partial mappings that directly contradicted the training material (Experiment 2b). In contrast, participants in the medium-variability condition failed to transfer their knowledge to new materials in either transfer tests. This indicates that both low and high variability facilitated the implicit learning of transferable abstract rules (variablevariable mapping level), whereas participants in the medium-variability condition implicitly learned only surface-level valuevalue mappings.Taken together, this study provides a comprehensive account of how example variability influences the implicit learning of multiple non-adjacent dependencies. It reveals a nonlinear relationship between example variability and implicit learning and identifies that this effect operates primarily at the level of abstract variablevariable mappings. From the perspective of example variability, the findings further indicate that the implicit acquisition of abstract rules is constrained by specific boundary conditions. The findings not only deepen the understanding of the mechanisms underlying implicit learning, but also provide theoretical implications for optimizing instructional design.关键词
样例变异性/内隐学习/多重映射远距离规则/迁移/U型曲线Key words
variability/implicit learning/multiple non-adjacent dependencies/transfer/U-shaped relationship引用本文复制引用
郭秀艳,孙鹏,凌晓丽,张庆云,郑丽.样例变异性对多重映射远距离规则内隐学习的影响[EB/OL].(2026-05-09)[2026-05-13].https://chinaxiv.org/abs/202605.00076.学科分类
语言学/汉语
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