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Research on the acquisition of morphology commonly predicts that agglutinating systems should be easier to learn than fusional systems. This is argued to be due to compositional transparency: the mapping between morphemes and meanings is one-to-one in agglutinating systems, but not in fusional systems. This is supported by findings in first and second language learning (Goldschneider & DeKeyser 2001, Slobin 1973), typology (Dressler 2003, Haspelmath & Michaelis 2017), and language evolution (Brighton 2002). We present findings from a series of artificial language learning experiments which complicate this picture. First, we show that when only two features (e.g., NOUN CLASS and NUMBER) are morphologically encoded, the learnability of fusional and agglutinating systems does not differ significantly. This finding holds when learners are given an additional cue to morpheme segmentation–which in principle should make the agglutinating system easier. However, the error patterns of the two groups provide some evidence that learners might have a bias for transparent structures. Our results suggest that the advantages of agglutinating over fusional systems may be overstated, particularly when a small number of features are encoded. Since agglutinating systems likely bear additional costs (e.g., segmentation, longer word length, and the online cost of mapping between morphemes and meanings), such systems do not guarantee learning ease under all circumstances.

Human languages contain very little unconditioned variation.In contexts where language learners are exposed to input thatcontains inconsistencies, they tend to regularise it, either byeliminating competing variants, or conditioning variant use onthe context. In the present study we compare regularisationbehaviour across linguistic levels, looking at how adult learn-ers respond to variability in morphology and word order. Ourresults suggest similar strengths in regularisation between lin-guistic levels given input languages whose complexity is com-parable.

Recent studies using artificial language learning have arguedthat the cross-linguistic frequency of harmonic word orderpatterns–in which heads are ordered consistently before or af-ter dependents across syntactic categories–reflects a cognitivebias (Culbertson, Smolensky, & Legendre, 2012; Culbertson& Newport, 2015a). These studies suggest that English speak-ing adults and children favor harmonic orders of nouns anddifferent nominal modifiers (adjectives, numerals). However,because they target English learners, whose native languageis harmonic in the nominal domain (Num-Adj-N), this pref-erence may be based on transfer rather than a universal biasfor harmony. We present new evidence from French-speakingchildren, whose native language is non-harmonic in this do-main (Num-N-Adj). Our results reveal clear effects of nativelanguage transfer, but also evidence that a harmonic pattern isfavored even in this population of learners.

Zipf (1935) observed that word length is inversely proportionalto word frequency in the lexicon. He hypothesised that thiscross-linguistically universal feature was due to the Principleof Least Effort: language-users align form-meaning mappingsin such a way that the lexicon is optimally coded for efficientinformation transfer. However, word frequency is not the onlyreliable predictor of word length: Piantadosi, Tily, and Gib-son (2011) show that a word’s predictability in context is infact more strongly correlated with word length than word fre-quency. Here, we present an artificial language learning studyaimed at investigating the mechanisms that could give rise tosuch a distribution at the level of the lexicon. We find thatparticipants are more likely to use an ambiguous short form inpredictive contexts, and distinct long forms in surprising con-texts, only when they are subject to the competing pressures tocommunicate accurately and efficiently. These results supportthe hypothesis that language-users are driven by a least-effortprinciple to restructure their input in order to align word lengthwith information content, and this mechanism could thereforeexplain the global pattern observed at the level of the lexicon.

Though most documented sign languages make use of spaceto denote relationships between predicate arguments, studiesof emerging sign languages suggest that spatial reference doesnot emerge fully-formed but takes time to develop. We presentan artificial sign language learning experiment that expandsthe cultural evolutionary framework to investigate complexlinguistic constructions. Our results demonstrate the gradualemergence of consistent devices to distinguish between sen-tence arguments, some of which rely on iconic spatial con-trasts. These findings mirror data from emerging sign lan-guages and point to the cultural mechanisms that facilitate theevolution of complex linguistic structures.

Structural priming occurs when interlocutors copy the syntactic structure of their partners’ utterances, and is di-agnostic of their underlying representations. We trained adult participants on an artificial ‘alien’ language in which nounsappeared with adjectives or numerals in two-word phrases; participants then used that language to communicate with an alieninterlocutor. Input languages had variable word-order with the two modifier types tending to appear on the same side of thenoun (harmonic) or on different sides of the noun (non-harmonic). Participants in all conditions acquired the dominant or-der of their input; however, structural priming only occurred within modifier types (e.g. encountering Numeral-Noun primedNumeral-Noun order only, not Adjective-Noun), even for participants exposed to harmonic input where both modifier typespatterned the same way. This suggests that the abstract representations tapped by structural priming in rapidly-learnt artificiallanguages encode distinctions that are not based purely on distributional properties of the input.

In this paper we investigate a hypothesized cognitive bias forisomorphic mappings between conceptual structure and linearorder in the noun phrase. This bias has been proposed as a pos-sible explanation for a striking asymmetry in the typology ofthe noun phrase–linear orders which place the adjective clos-est to the noun, then the numeral, then the demonstrative, areover-represented in the world’s languages. Previous experi-mental work has provided evidence that an isomorphism biasaffects English-speaking learners’ inferences about the relativeorder of modifiers in an artificial language. Here, we use thesilent gesture paradigm to explore whether the isomorphismbias influences spontaneous gestures innovated by participantsin a modality with which they have relatively little prior experi-ence. We find that gesture string order largely conforms to thesame striking pattern found in noun phrase typology, support-ing the role of the isomorphism bias in shaping the emergenceof language (and language-like) systems.