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Word learning is guided by the statistical co-occurrence between spoken words and potential referents, through which learners gradually map labels to objects across situations. Given that word learning does not occur in a vacuum, rather in a communicative context, it is relevant to evaluate the role that speakers play. Because we do not evaluate the information provided by every person equally, it is reasonable to think that someone who makes lexical errors is not a reliable speaker from whom to learn new words. The current study focuses on speaker reliability in adult cross-situational word learning (CSWL). In two experiments we investigated the extent to  which  adults  attend  to  the  reliability  of  the  speaker  and  how  this  affects  word  learning  in  a CSWL task. We varied the consistency with which a speaker mapped novel words to familiar objects. We hypothesized (1) that the speakers’ reliability would be judged differently depending on their past object-labeling accuracy, and (2) that new words would be more difficult to learn when  presented  by  an  unreliable  speaker.  Experiment  1  shows  that  the  unreliable  speaker  was  assessed  as  less  reliable,  compared  to  the  reliable  speaker,  but  this  effect  disappeared  in  Experiment  2,  when  participants  were  taught  new  words  by  two  speakers,  a  reliable  and  an  unreliable  one.  Furthermore,  we  found  no  evidence  to  support  the  hypothesis  that  being  exposed  to  an  unreliable  speaker  impairs  CSWL  in  adults.  We  discuss  the  relevance  of  these  findings and the importance of further research on the role of speaker reliability in CSWL.

In the present paper, we assess whether website rating systems are useful for selecting educational apps for preschool age children. We selected the 10 highest scoring and 10 lowest scoring apps for 2-4-year-olds from two widely used websites (Good App Guide; Common Sense Media). Apps rated highly by the two websites had a higher educational potential as assessed by a validated questionnaire for evaluating the educational potential of apps and were more likely to include a learning goal and feedback compared to low scoring apps. However, high scoring apps scored on average just 9/20 for indicators of educational potential, and both high and low scoring apps had poor language quality as determined by psycholinguistic and construction type analyses. We argue that website rating systems should also include quality of feedback, adjustable content, social interactions, storyline and a more fine-grained analysis of language in their assessments.

Purpose: The aim of this study was to identify variability in word-learning mechanisms used by late-talking children using a longitudinal study design, which may explain variability in late-talking children's outcomes. Method: A cohort of typically developing children (n = 40) and children who were classified as late-talking children at age 2;0 (years;months; [less than or equal to] 10th percentile on expressive vocabulary, n = 21) were followed up at ages 3;0 and 3;6. We tested the cohort across tasks designed to isolate different mechanisms involved in word learning: encoding and producing spoken forms of words (using a nonword repetition task), identifying referents for words (using a fast mapping task), and learning associations between words and referents (using a cross-situational word-learning task). Results: Late-talking children had lower accuracy on nonword repetition than typically developing children, despite most of the sample reaching typical ranges for expressive vocabulary at age 3;6. There were no between-groups differences in fast mapping and retention accuracy; however, both were predicted by concurrent expressive vocabulary. Late-talking children performed less accurately than typically developing children on cross-situational word-learning retention trials, despite showing no between-groups differences during training trials. Combining performance across all three tasks predicted approximately 45% of the variance in vocabulary outcomes at the last time point. Conclusions: Late-talking children continue to have deficits in phonological representation that impact their word-learning ability and expressive language abilities but do not show difficulties in fast mapping novel words. Late-talking children may also struggle to retain associative information about word-referent mappings. Late-talking children thus use some, but not all, word-learning mechanisms differently than typically developing children.

Language in touchscreen apps could be useful as an additional source of children's language input, alongside child directed speech (CDS) and books. Here we performed the first analysis of language in apps, as compared with books and CDS. We analysed language in 18 of the most popular educational apps targeting pre-schoolers and compared their language content to children's books and CDS with respect to types of constructions and psycholinguistic features of words. We found that apps contained lower frequency words and had lower lexical diversity compared to CDS, and shorter utterances compared to books. Apps may thus provide an enriched supplementary form of input for young children, due to containing less frequent words. However, apps do not expose children to a high proportion of questions and complex sentences, both of which are crucial for supporting child's development of structurally rich constructions.

Gesture is important for language acquisition, but how gesture and its temporal aspects integrate with other informationis not fully known. We manipulated referential ambiguity, and the availability and timing of a deictic gesture duringtraining on a word-learning task with adults to assess how gestural cues alter learning when tested on those words. Wedemonstrate that the presence of a gestural cue during training in a condition with two potential referents can reducereferential ambiguity sufficiently to produce performance at test similar to a condition with only one referent. We furthershow that learners demonstrate better performance at test with gestures that occur prior to, rather than after, the verballabel in training. Gesture during learning thus appears better at predicting, rather than confirming the referent. Theseresults offer insight into how cues can facilitate the disambiguation of meaning during word learning. Pre-registration:https://osf.io/exq7d/?view only=8b28001e56404ff79c2258f3b66d7474 Keywords: word learning; language acquisition;multiple cues; gestures; temporal; word-referent mapping

Children learn words in environments where there is considerable variability, both in terms of the number of possible referents for novel words, and the availability of cues to support word-referent mappings. How caregivers adapt their gestural cues to referential uncertainty has not yet been explored. We tested a computational model of cross-situational word learning that examined the value of a variable gesture cue during training across conditions of varying referential uncertainty. We found that gesture had a greater benefit for referential uncertainty, but unexpectedly also found that learning was best when there was variability in both the environment (number of referents) and gestural cue use. We demonstrated that these results are reflected behaviourally in an experimental word-learning study involving children aged 18-24-month-olds and their caregivers. Under similar conditions to the computational model, caregivers not only used gesture more when there were more potential referents for novel words, but children also learned best when there was some referential ambiguity for words. Thus, caregivers are sensitive to referential uncertainty in the environment and adapt their gestures accordingly, and children are able to respond to environmental variability to learn more robustly. These results imply that training under variable circumstances may actually benefit learning, rather than hinder it.

Language is infinitely productive because syntax defines dependencies between grammatical categories of words and constituents, so there is interchangeability of these words and constituents within syntactic structures. Previous laboratory-based studies of language learning have shown that complex language structures like hierarchical center embeddings (HCE) are very hard to learn, but these studies tend to simplify the language learning task, omitting semantics and focusing either on learning dependencies between individual words or on acquiring the category membership of those words. We tested whether categories of words and dependencies between these categories and between constituents, could be learned simultaneously in an artificial language with HCE's, when accompanied by scenes illustrating the sentence's intended meaning. Across four experiments, we showed that participants were able to learn the HCE language varying words across categories and category-dependencies, and constituents across constituents-dependencies. They also were able to generalize the learned structure to novel sentences and novel scenes that they had not previously experienced. This simultaneous learning resulting in a productive complex language system, may be a consequence of grounding complex syntax acquisition in semantics.

First language acquisition is implicit, in that explicit information about the language structure to be learned is not provided to children. Instead, they must acquire both vocabulary and grammar incrementally, by generalizing across multiple situations that eventually enable links between words in utterances and referents in the environment to be established. However, this raises a problem of how vocabulary can be acquired without first knowing the role of the word within the syntax of a sentence. It also raises practical issues about the extent to which different instructional conditions -- about grammar in advance of learning or feedback about correct decisions during learning -- might influence second language acquisition of implicitly experienced information about the language. In an artificial language learning study, we studied participants learning language from inductive exposure, but under different instructional conditions. Language learners were exposed to complex utterances and complex scenes and had to determine the meaning and the grammar of the language from these co-occurrences with environmental scenes. We found that learning was boosted by explicit feedback, but not by explicit instruction about the grammar of the language, compared to an implicit learning condition. However, the effect of feedback was not general across all aspects of the language. Feedback improved vocabulary, but did not affect syntax learning. We further investigated the local, contextual effects on learning, and found that previous knowledge of vocabulary within an utterance improved learning but that this was driven only by certain grammatical categories in the language. The results have implications for theories of second language learning informed by our understanding of first language acquisition as well as practical implications for learning instruction and optimal, contingent adjustment of learners' environment during their learning.

Children learning language in multilingual settings have tolearn that objects take different labels within each differentlanguage to which they are exposed. Previous research hasshown that adults can learn one-to-one and two-to-one word-object mappings via cross-situational statistical learning(CSSL), and that socio-pragmatic cues may differentiallyinfluence monolingual and bilingual adults’ learning of suchmappings. However, the extent to which monolingual andbilingual learners can keep track of multiple labels frommultiple speakers has not yet been investigated. Wemanipulated the number of speakers in a CSSL task thatinvolved learning both mapping types. We successfullyreplicated previous studies that found that both monolingualsand bilinguals could learn both types of mappings via CSSL.In addition, we found that bilinguals showed a steeper learningrate for two-to-one mappings than monolinguals, andbilinguals were more likely to accept two words for the sameobject than monolinguals. These results show that the effect ofspeaker identity on tracking word-object mappings variesaccording to language experience.

Achieving linguistic proficiency requires identifying wordsfrom speech, and discovering the constraints that govern theway those words are used. In a recent study of non-adjacentdependency learning, Frost and Monaghan (2016)demonstrated that learners may perform these tasks together,using similar statistical processes — contrary to priorsuggestions. However, in their study, non-adjacentdependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influencedlearning. Here, we test the necessity of these cues bycomparing learning across three conditions; fixed phonology,which contains these cues, varied phonology, which omitsthem, and shapes, which uses visual shape sequences toassess the generality of statistical processing for these tasks.Participants segmented the sequences and generalized thestructure in both auditory conditions, but learning was bestwhen phonological cues were present. Learning was aroundchance on both tasks for the visual shapes group, indicatingstatistical processing may critically differ across domains

How infants determine correct word-referent pairings withincomplex environments is not yet fully understood. Thecombination of multiple cues, including gestures, may guidelearning as part of a communicative exchange between parentand child. Gesture use and word learning are interlinked, withearly child gesture predicting later vocabulary size, andparental gesture predicting child gesture. However, the extentto which parents alter gesture cues during word learningaccording to referential uncertainty is not known. In this study,we manipulated the number of potential referents acrossconditions during a word learning task with 18–24-month-olds,and explored how changes in parental gesture use translatedinto infant word learning. We demonstrate that parents altertheir gesture use according to the presence, but not the degree,of referential uncertainty. We further demonstrate that a degreeof variability in the number of potential referents appears tobenefit word learning.

To acquire language, learners have to map the language onto the environment, but languages vary as to how much information they include to constrain how a sentence relates to the world. We investigated the conditions under which information within the language and the environment is combined for learning. In a cross‐situational artificial language learning study, participants listened to transitive sentences and viewed two scenes, and selected which scene was described by the sentence. There were three conditions, involving different language variants. All variants had free word order but varied as to whether or not they contained morphosyntactic information that defined the subject and object roles of nouns in the sentence. We found that participants were able to learn information about word order and vocabulary from each variant, demonstrating that learners are not reliant on information within a language only, but can combine constraints from language and environment to support acquisition. Data and analyses are available at: https://osf.io/hxqzc/?view_only=ea6ba6fff6bb468e8de2e8596f029dca A one‐page Accessible Summary of this article in nontechnical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

Learning language requires acquiring the grammatical categories of words in the language, but learning those categories requires understanding the role of words in the syntax. In this study, we examined how this chicken and egg problem is resolved by learners of an artificial language comprising nouns, verbs, adjectives, and case markers following syntactic rules. We also measured individual differences in declarative and procedural memory processing, which have been linked to vocabulary and grammar learning, respectively. The results showed that grammar and vocabulary can be acquired simultaneously, but with distinctive patterns of acquisition: the syntactic role of verbs and their referents first, then other lexical categories, and finally the syntactic function of case markers. Interdependencies in learning were found for word order and verbs, which related to verbal declarative memory, and also for nouns, adjectives, and case markers, which related to procedural memory.

Learning a language involves learning how to map specificforms onto their associated meanings. Such mappings canutilise arbitrariness and non-arbitrariness, yet, ourunderstanding of how these two systems operate at differentstages of vocabulary development is still not fully understood.The Sound-Symbolism Bootstrapping Hypothesis (SSBH)proposes that sound-symbolism is essential for word learningto commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It maybe the case that sound-symbolism supports acquisition ofcategories of meaning, or that it enables acquisition ofindividualized word meanings. In two Experiments whereparticipants learned form-meaning mappings from eithersound-symbolic or arbitrary languages, we demonstrate thechanging roles of sound-symbolism and arbitrariness fordifferent vocabulary sizes, showing that sound-symbolismprovides an advantage for learning of broad categories, whichmay then transfer to support learning individual words,whereas an arbitrary language impedes acquisition ofcategories of sound to meaning.

A common assumption in the cognitive sciences is thatartificial and natural language learning rely on sharedmechanisms. However, attempts to bridge the two haveyielded ambiguous results. We suggest that an empiricaldisconnect between the computations employed duringlearning and the methods employed at test may explain thesemixed results. Further, we propose statistically-basedchunking as a potential computational link between artificialand natural language learning. We compare the acquisition ofnon-adjacent dependencies to that of natural languagestructure using two types of tasks: reflection-based 2AFCmeasures, and processing-based recall measures, the latterbeing more computationally analogous to the processes usedduring language acquisition. Our results demonstrate thattask-type significantly influences the correlations observedbetween artificial and natural language acquisition, withreflection-based and processing-based measures correlatingwithin – but not across – task-type. These findings havefundamental implications for artificial-to-natural languagecomparisons, both methodologically and theoretically.

Learning to read has a substantial effect on the representationsof spoken and meaning forms of words. In this paper weassess literacy effects beyond representational changes,focusing on adaptations to the architecture of the readingsystem that maps between these representations. We present aconnectionist model of reading that predicted distinctprocessing of pre- and post-literacy acquired words. Forreading for meaning, words learned prior to literacy wereprocessed more indirectly via phonological representations,whereas for post-literacy acquired words, processing wasmore direct along the orthography to semantics pathway. Thismore computationally intensive route was prioritised becauseindirect phonology to semantics mappings were unavailable.Such an effect was less apparent for naming, because learningdirect orthography to phonology mappings is lesscomputationally intensive. These results were confirmed in ananalysis of naming and lexical decision behavioural data. Theeffect of literacy onset remains an observable artefact in adultreading.

Learning how words refer to aspects of the environment is acomplex task, but one that is supported by numerous cueswithin the environment which constrain the possibilities formatching words to their intended referents. In this paper wetested the predictions of a computational model of multiplecue integration for word learning, that predicted variation inthe presence of cues provides an optimal learning situation. Ina cross-situational learning task with adult participants, wevaried the reliability of presence of distributional, prosodic,and gestural cues. We found that the best learning occurredwhen cues were often present, but not always. The effect ofvariability increased the salience of individual cues for thelearner, but resulted in robust learning that was not vulnerableto individual cues’ presence or absence. Thus, variability ofmultiple cues in the language-learning environment providedthe optimal circumstances for word learning.

Learning syntax requires determining relations between thegrammatical categories of words in the language, but learningthose categories requires understanding the role of words inthe syntax. In this study, we examined how this chicken andegg problem is resolved by learners of an artificial languagecomprising nouns, verbs, adjectives and case markersfollowing syntactic rules. We found that the language couldbe acquired through cross-situational statisticalcorrespondences with complex scenes and without explicitfeedback, and that knowledge was maintained after 24 hours.Results also showed that verbs and word order were the firstto be acquired, followed by nouns, adjectives and finally casemarkers. Interdependencies in learning were found for wordorder and verbs, and also for nouns, adjectives and casemarkers. Grammar and vocabulary can be acquiredsimultaneously, but with distinctive patterns of acquisition –grammar and the role of verbs first, then the vocabulary ofother lexical categories.

To become a proficient reader, children have to learnmappings between print, sound and meaning. There isdebate over whether reading instruction should focus on therelations between print and sound, as in phonics, or on therelationship between print and meaning, as in sight wordreading. In a study where participants learned a novelartificial orthography, Taylor, Davis and Rastle (2017)compared print to sound focused or print to meaningfocused reading training, demonstrating that sound trainingwas superior for learning to read. However, a benefit fromsound focused training is likely dependent on prioracquisition of effective sound to meaning relations of words.To explore this issue, we developed a connectionist modelof reading. We exposed the model to a sound or a meaningfocused training, but varied the model’s pre-acquired orallanguage skills. The simulation results showed thatproficiency in oral language is a determinant of theadvantage of print to sound focused reading training,suggesting that reading training should address both orallanguage skills and print to sound mappings.

High frequency words have been suggested to benefit both speech segmentation and grammatical categorization of the words around them. Despite utilizing similar information, these tasks are usually investigated separately in studies examining learning. We determined whether including high frequency words in continuous speech could support categorization when words are being segmented for the first time. We familiarized learners with continuous artificial speech comprising repetitions of "target words," which were preceded by high-frequency "marker words." Crucially, marker words distinguished targets into 2 distributionally defined categories. We measured learning with segmentation and categorization tests and compared performance against a control group that heard the artificial speech without these marker words (i.e., just the targets, with no cues for categorization). Participants segmented the target words from speech in both conditions, but critically when the marker words were present, they influenced acquisition of word-referent mappings in a subsequent transfer task, with participants demonstrating better early learning for mappings that were consistent (rather than inconsistent) with the distributional categories. We propose that high-frequency words may assist early grammatical categorization, while speech segmentation is still being learned.

Diversity of vocabulary knowledge and quantity of language exposure prior to literacy are key predictors of reading development. However, diversity and quantity of exposure are difficult to distinguish in behavioural studies, and so the causal relations with literacy are not well known. We tested these relations by training a connectionist triangle model of reading that learned to map between semantic; phonological; and, later, orthographic forms of words. The model first learned to map between phonology and semantics, where we manipulated the quantity and diversity of this preliterate language experience. Then the model learned to read. Both diversity and quantity of exposure had unique effects on reading performance, with larger effects for written word comprehension than for reading fluency. The results further showed that quantity of preliteracy language exposure was beneficial only when this was to a varied vocabulary and could be an impediment when exposed to a limited vocabulary.

This document is an introduction to a collection of letters discussing various themes and topics in cognitive science. The letters cover a range of subjects, including pragmatic explanations, grammatical systems, consciousness, social dimensions of cognition, diversity in cognitive science, core aspects of cognition, language and learning, high-level cognition, technology and cognitive science, and more. The document emphasizes the importance of empirical and theoretical substance in the field of cognitive science and invites readers to engage in lively discussion and collaboration. [Extracted from the article]

The past 15-20 years have witnessed a particularly stronginterest in our ability to rapidly extract structuredinformation from the environment. This fundamentalprocess of human cognition is widely believed to underpinmany complex behaviors – from language development andsocial interaction to intuitive decision making and musiccognition – so this interest spans practically all branches ofcognitive science. Research on this topic can be found intwo related, yet traditionally distinct research strands,namely "implicit learning" (Reber, 1967) and "statisticallearning" (Saffran, Aslin, & Newport, 1996).Both lines of research focus on how we acquireinformation from complex stimulus domains and both relyheavily on the use of artificial systems (e.g., finite-stategrammars, pseudoword lexicons). In typical experiments,participants are initially exposed to stimuli generated by anartificial system and then tested to determine what they havelearned. Given these and other significant similarities,Perruchet and Pacton (2006) argue that these distinct linesof research actually represent two approaches to a singlephenomenon, and Conway and Christiansen (2006) proposecombining the two in name: "implicit-statistical learning".Yet, despite frequent acknowledgements that researchers inimplicit learning and statistical learning might essentially belooking at the same phenomenon, there is surprisingly littlealignment between the two strands.This symposium seeks to remedy this situation bybringing together leading researchers from both areas inorder to promote a shared understanding of researchquestions and methodologies, to discuss similarities anddifferences between the two approaches, and to worktowards a joint research agenda. The symposium comprisesfour presentations, followed by a thematic discussion, whichprovide coverage of these phenomena in terms ofdevelopment (children and adults), different languagelearning tasks (sublexical phonotactics, word acquisition,grammar learning), and their role in both production andcomprehension, each integrating multidisciplinaryperspectives. Gomez focuses on implicit-statistical learningin early development, identifying words and grammaticalsequences and the memory systems that underlie thislearning. Monaghan and Rebuschat measure word learningand grammar learning in adults, while varying theknowledge that participants have of the structure they areacquiring. Dell and Anderson demonstrate how their workon acquisition of phonotactic constraints is exhibited inspeakers’ productions, and discuss the inter-relation inspeech between implicit and statistical learning. Finally,Conway provides an overview of the two fields, andproposes a novel framework that unifies implicit learningand statistical learning.

There is considerable evidence showing that age ofacquisition (AoA) is an important factor influencing lexicalprocessing. Early-learned words tend to be processed morequickly compared to later-learned words. The effect could bedue to the gradual reduction in plasticity as more words arelearned. Alternatively, it could originate from differenceswithin semantic representations. We implemented the trianglemodel of reading including orthographic, phonological andsemantic processing layers, and trained it according toexperience of a language learner to explore the AoA effects inboth naming and lexical decision. Regression analyses on themodel’s performance showed that AoA was a reliablepredictor of naming and lexical decision performance, and theeffect size was larger for lexical decision than for naming.The modelling results demonstrate that AoA operatesdifferentially on concrete and abstract words, indicating thatboth the mapping and the representation accounts of AoAwere contributing to the model’s performance.

There is substantial variation in language experience betweenlearners, yet there is surprising similarity in the languagestructure they eventually acquire. While it is possible that thiscanalisation of language structure may be due to constraintsimposed by modulators, such as an innate language system, itmay instead derive from the broader, communicativeenvironment in which language is acquired. In this paper, thelatter perspective is tested for its adequacy in explaining therobustness of language learning to environmental variation. Acomputational model of word learning from cross-situational,multimodal information was constructed and tested. Key tothe model’s robustness was the presence of multiple,individually unreliable information sources that could supportlearning when combined. This “degeneracy” in the languagesystem had a detrimental effect on learning when compared toa noise-free environment, but was critically important foracquiring a canalised system that is resistant to environmentalnoise in communication.

Lexical items in the vocabulary of a language undergo dramatic changes over time, explaining the mechanismsthat cause this change has been an important topic for the cognitive sciences. One particular focus for researchers has beenunderstanding the dynamics of change in word forms. The rate (or half-life) at which word forms change over time variesgreatly, and corpus-based cladistic studies have shown that certain properties, such as word frequency, length and age ofacquisition, can be used to predict this variation. We test through the use of an artificial language learning paradigm the extentto which these psycholinguistic factors affect accurate learning of word forms, linking processes of acquisition with processesof evolutionary change. Our findings provide an insight into the underlying mechanisms that drive diachronic change within alanguage’s vocabulary, highlighting the important role that the learning process has on lexical change.

Understanding the process of adult language learning has recently undergone advances due to the consideration ofhow individual differences (IDs) in cognitive processing, such as working memory (WM), affect acquisition. We know thatimplicit versus explicit learning conditions also influence learning, however, the potential interactions between IDs, the efficacyof implicit versus explicit learning, and different types of linguistic information are largely unknown. In this study, we testedlearning of syntax and grammatical case under two conditions: incidental and explicit rule-provision (“instructed”). We alsoassessed individuals’ WM, phonological working memory (PWM), and learning styles. Significant learning effects were foundfor word order and case in both learning conditions. For case, but not for word order, the instructed group outperformed theincidental group. Regarding IDs, incidental learning of case was marginally related to individuals’ WM; instructed learning ofcase was related to PWM. For learning styles, there was a negative relationship between learning of word order in the instructedcondition and a deductive learning style. These results reveal the complex relationships among cognitive processes in explicitand implicit language learning across different aspects of language structure, and in relation to cognitive IDs.