Cross-linguistic differences in morphological complexity could have important consequences for language learning. Specifically, it is often assumed that languages with more regular, compositional, and transparent grammars are easier to learn by both children and adults. Moreover, it has been shown that such grammars are more likely to evolve in bigger communities. Together, this suggests that some languages are acquired faster than others, and that this advantage can be traced back to community size and to the degree of systematicity in the language. However, the causal relationship between systematic linguistic structure and language learnability has not been formally tested, despite its potential importance for theories on language evolution, second language learning, and the origin of linguistic diversity. In this pre-registered study, we experimentally tested the effects of community size and systematic structure on adult language learning. We compared the acquisition of different yet comparable artificial languages that were created by big or small groups in a previous communication experiment, which varied in their degree of systematic linguistic structure. We asked (a) whether more structured languages were easier to learn; and (b) whether languages created by the bigger groups were easier to learn. We found that highly systematic languages were learned faster and more accurately by adults, but that the relationship between language learnability and linguistic structure was typically non-linear: high systematicity was advantageous for learning, but learners did not benefit from partly or semi-structured languages. Community size did not affect learnability: languages that evolved in big and small groups were equally learnable, and there was no additional advantage for languages created by bigger groups beyond their degree of systematic structure. Furthermore, our results suggested that predictability is an important advantage of systematic structure: participants who learned more structured languages were better at generalizing these languages to new, unfamiliar meanings, and different participants who learned the same more structured languages were more likely to produce similar labels. That is, systematic structure may allow speakers to converge effortlessly, such that strangers can immediately understand each other.

形态复杂性方面的跨语言差异可能会对语言学习产生重要影响。特别是，通常认为具有更规则，组成和透明语法的语言对于儿童和成人都更容易学习。而且，已经表明，这种语法在更大的社区中更可能发展。总之，这表明某些语言的获取速度比其他语言快，并且这种优势可以追溯到社区规模和语言的系统性程度。但是，尽管系统语言结构和语言可学习性之间的因果关系对于语言进化论，第二语言学习和语言多样性的起源具有潜在的重要性，但尚未经过正式检验。在此预先注册的研究中，我们通过实验测试了社区规模和系统结构对成人语言学习的影响。我们比较了在先前的交流实验中，由大小群体创建的不同但可比较的人工语言的习得情况，这些人工语言的系统语言结构程度各不相同。我们问（a）是否更容易学习更结构化的语言；（b）较大群体创造的语言是否更容易学习。我们发现成年人可以更快，更准确地学习高度系统化的语言，但是语言可学习性和语言结构之间的关系通常是非线性的：高度系统性对学习有利，但学习者不会从部分或半结构化语言中受益。社区规模不影响学习能力：在大小团体中演化的语言同样可以学习，并且由大型团体创建的语言除了其系统结构之外没有其他优势。此外，我们的结果表明，可预测性是系统结构的重要优势：学习更多结构化语言的参与者更擅长将这些语言归纳为新的陌生含义，而学习相同结构化语言的不同参与者则更有可能产生相似的标签。即，系统的结构可以允许说话者毫不费力地会聚，使得陌生人可以立即彼此理解。此外，我们的结果表明，可预测性是系统结构的重要优势：学习更多结构化语言的参与者更擅长将这些语言归纳为新的陌生含义，而学习相同结构化语言的不同参与者则更有可能产生相似的标签。即，系统的结构可以允许说话者毫不费力地会聚，使得陌生人可以立即彼此理解。此外，我们的结果表明，可预测性是系统结构的重要优势：学习更多结构化语言的参与者更擅长将这些语言归纳为新的陌生含义，而学习相同结构化语言的不同参与者则更有可能产生相似的标签。即，系统的结构可以允许说话者毫不费力地会聚，使得陌生人可以立即彼此理解。