Context as an Organizing Principle of the Lexicon

Event-related brain potentials in lexical processing with Chinese characters show effects of contextual diversity but not word frequency

The diversity of contexts in which a word occurs, operationalized as CD, is strongly correlated with response times in visual word recognition, with higher CD words being recognized faster. CD and token word frequency (WF) are highly correlated but in behavioral studies when other variables that affect word visual recognition are controlled for, the WF effect is eliminated when contextual diversity (CD) is controlled. In contrast, the only event-related potential (ERP) study to examine CD and WF Vergara-Martínez et al., Cognitive, Affective, & Behavioral Neuroscience, 17, 461-474, (2017) found effects of both WF and CD with different distributions in the 225- to 325-ms time window. We conducted an ERP study with Chinese characters to explore the neurocognitive dynamics of WF and CD. We compared three groups of characters: (1) characters high in frequency and low in CD; (2) characters low in frequency and low in CD; and (3) characters high in frequency and high in CD. Behavioral data showed significant effects of CD but not WF. Character CD, but not character frequency, modulated the late positive component (LPC): high-CD characters elicited a larger LPC, widely distributed, with largest amplitude at the posterior sites compared to low-CD characters in the 400-to 600-ms time window, consistent with earlier ERP studies of WF in Chinese, and with the hypothesis that CD affects semantic and context-based processes. No WF effect on any ERP components was observed when CD was controlled. The results are consistent with behavioral results showing CD but not WF effects, and in particular with a "context constructionist" framework.

The Children and Young People's Books Lexicon (CYP-LEX): A large-scale lexical database of books read by children and young people in the United Kingdom

This article introduces the Children and Young People's Books-Lexicon (CYP-LEX), a large-scale lexical database derived from books popular with children and young people in the United Kingdom. CYP-LEX includes 1,200 books evenly distributed across three age bands (7-9, 10-12, 13+) and comprises over 70 million tokens and over 105,000 types. For each word in each age band, we provide its raw and Zipf-transformed frequencies, all parts-of-speech in which it occurs with raw frequency and lemma for each occurrence, and measures of count-based contextual diversity. Together and individually, the three CYP-LEX age bands contain substantially more words than any other publicly available database of books for primary and secondary school children. Most of these words are very low in frequency, and a substantial proportion of the words in each age band do not occur on British television. Although the three age bands share some very frequent words, they differ substantially regarding words that occur less frequently, and this pattern also holds at the level of individual books. Initial analyses of CYP-LEX illustrate why independent reading constitutes a challenge for children and young people, and they also underscore the importance of reading widely for the development of reading expertise. Overall, CYP-LEX provides unprecedented information into the nature of vocabulary in books that British children aged 7+ read, and is a highly valuable resource for those studying reading and language development.

CCLOOW: Chinese children's lexicon of oral words

In this article, we introduce the Chinese Children's Lexicon of Oral Words (CCLOOW), the first lexical database based on animated movies and TV series for 3-to-9-year-old Chinese children. The database computes from 2.7 million character tokens and 1.8 million word tokens. It contains 3920 unique character and 22,229 word types. CCLOOW reports frequency and contextual diversity metrics of the characters and words, as well as length and syntactic categories of the words. CCLOOW frequency and contextual diversity measures correlated well with other Chinese lexical databases, particularly well with that computed from children's books. The predictive validity of CCLOOW measures were confirmed with Grade 2 children's naming and lexical decision experiments. Further, we found that CCLOOW frequencies could explain a considerable proportion in adults' written word recognition, indicating that early language experience might have lasting impacts on the mature lexicon. CCLOOW provides validated frequency and contextual diversity estimates that complements current children's lexical database based on written language samples. It is freely accessible online at https://www.learn2read.cn/ccloow .

Diversity of narrative context disrupts the early stage of learning the meanings of novel words

High quality lexical representations develop through repeated exposures to words in different contexts. This preregistered experiment investigated how diversity of narrative context affects the earliest stages of word learning via reading. Adults (N = 100) learned invented meanings for eight pseudowords, which each occurred in five written paragraphs either within a single coherent narrative context or five different narrative contexts. The words' semantic features were controlled across conditions to avoid influences from polysemy (lexical ambiguity). Posttests included graded measures of word-form recall (spelling accuracy) and recognition (multiple choice), and word-meaning recall (number of semantic features). Diversity of narrative context did not affect word-form learning, but more semantic features were correctly recalled for words trained in a single context. These findings indicate that learning the meanings of novel words is initially boosted by anchoring them to a single coherent narrative discourse.

Environment Context Variability and Incidental Word Learning: A Virtual Reality Study

Previous research has shown that changes in the scenarios in which something is learned and recalled, respectively, may result in a subpar performance in memory recollection. The current study aimed to evaluate how changes in the visuo-perceptual environmental learning context impact incidental vocabulary learning. To this end, a highly immersive virtual reality setting was created, and participants were required to read eight distinct stories visually presented to them. A novel word was delivered twice in every paragraph and embedded in each story. Stories could be displayed either in a high variability condition, where each paragraph was shown in a new environment context (four different classrooms) or in a low variability condition, where each paragraph was shown in the same context. The findings obtained across four assessment tasks (free recall, recognition, picture matching, and sentence completion) demonstrated that significant visuo-perceptual variability did not bring about any disadvantages in word learning. Thus, perceptual information from a physically diverse environment could provide a variety of instructional and educational beneficial possibilities in the absence of a learning disadvantage.

CCLOWW: A grade-level Chinese children's lexicon of written words

In this article, we present the Chinese Children's Lexicon of Written Words (CCLOWW), the first grade-level database that provides frequency statistics of simplified Chinese characters and words for children. The database computes from a corpus of 34,671,424 character tokens and 22,427,010 word tokens (including single- and multicharacter words), extracted from 2131 books. It contains 6746 different character types and 153,079 different word types. CCLOWW provides several frequency indices of simplified Chinese for three grade levels (grade 2 and below, grades 3-4, grades 5-6) to profile children's experience with written Chinese in and outside of school. We describe in this article the distributions of frequency and contextual diversity of the characters and words, as well as word length and syntactic categories of the words in the corpus and the subcorpora. We also report results of correlation analyses with other written corpora and of several naming and lexicon decision experiments. The findings suggest that CCLOWW frequency measures correlate well with other corpora. Importantly, they could reliably predict children's and adults' naming and lexical decision performances. They could also explain variance in adults' visual word recognition, in addition to frequency measures computed in an adult corpus, indicating that early print exposure might influence readers' lexical processing later on beyond an age of acquisition effect. CCLOWW will help researchers in language processing and development as well as educators with selecting language materials appropriate for children's developmental stages. The database is freely available online at https://www.learn2read.cn/database/ .

Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity

Contextual diversity modifies word frequency by ignoring the repetition of words in context (Adelman, Brown, & Quesada,  2006, Psychological Science, 17(9), 814-823). Semantic diversity modifies contextual diversity by taking into account the uniqueness of the contexts that a word occurs in when calculating lexical strength (Jones, Johns, & Recchia,  2012, Canadian Journal of Experimental Psychology, 66, 115-124). Recent research has demonstrated that measures based on contextual and semantic diversity provide a considerable improvement over word frequency when accounting for lexical organization data (Johns, 2021, Psychological Review, 128, 525-557; Johns, Dye, & Jones, 2020a, Quarterly Journal of Experimental Psychology, 73, 841-855). The article demonstrates that these same findings generalize to word-level episodic recognition rates, using the previously released data of Cortese, Khanna, and Hacker (Cortese et al., 2010, Memory, 18, 595-609) and Cortese, McCarty, and Schock (Cortese et al., 2015, Quarterly Journal of Experimental Psychology, 68, 1489-1501). It was found that including the best fitting contextual diversity model allowed for a very large increase in variance accounted for over previously used variables, such as word frequency, signalling commonality with results from the lexical organization literature. The findings of this article suggest that current trends in the collection of megadata sets of human behavior (e.g., Balota et al., 2007, Behavior Research Methods, 39(3), 445-459) provide a promising avenue to develop new theoretically oriented models of word-level episodic recognition data.

Distributional social semantics: Inferring word meanings from communication patterns

Distributional models of lexical semantics have proven to be powerful accounts of how word meanings are acquired from the natural language environment (Günther, Rinaldi, & Marelli, 2019; Kumar, 2020). Standard models of this type acquire the meaning of words through the learning of word co-occurrence statistics across large corpora. However, these models ignore social and communicative aspects of language processing, which is considered central to usage-based and adaptive theories of language (Tomasello, 2003; Beckner et al., 2009). Johns (2021) recently demonstrated that integrating social and communicative information into a lexical strength measure allowed for benchmark fits to be attained for lexical organization data, indicating that the social world contains important statistical information for language learning and processing. Through the analysis of the communication patterns of over 330,000 individuals on the online forum Reddit, totaling approximately 55 billion words of text, the findings of the current article demonstrates that social information about word usage allows for unique aspects of a word's meaning to be acquired, providing a new pathway for distributional model development.

What is semantic diversity and why does it facilitate visual word recognition?

Previous research has speculated that semantic diversity and lexical ambiguity may be closely related constructs. Our research sought to test this claim in respect of the semantic diversity measure proposed by Hoffman et al. (2013). To this end, we replicated the procedure described by Hoffman et al., Behavior Research Methods, 45(3), 718–730 (2013) for computing multidimensional representations of contextual information using Latent Semantic Analysis, and from these we derived semantic diversity values for 28,555 words. We then replicated the facilitatory effect of semantic diversity on word recognition using existing data resources and observed this effect to be greater for low-frequency words. Yet, we found no relationship between this measure and lexical ambiguity effects in word recognition. Further analysis of the LSA-based contextual representations used to compute Hoffman et al. (2013) measure of semantic diversity revealed that they do not capture the distinct meanings of ambiguous words. Instead, these contextual representations appear to capture general information about the topics and types of written material in which words occur. These analyses suggest that the semantic diversity metric previously proposed by Hoffman et al. (2013) facilitates word recognition because high-diversity words are likely to have been encountered no matter what one has read, whereas many participants may not have encountered lower-diversity words simply because the topics and types of written material in which they occur are more restricted.

How do Spanish speakers read words? Insights from a crowdsourced lexical decision megastudy

Vocabulary size seems to be affected by multiple factors, including those that belong to the properties of the words themselves and those that relate to the characteristics of the individuals assessing the words. In this study, we present results from a crowdsourced lexical decision megastudy in which more than 150,000 native speakers from around 20 Spanish-speaking countries performed a lexical decision task to 70 target word items selected from a list of about 45,000 Spanish words. We examined how demographic characteristics such as age, education level, and multilingualism affected participants' vocabulary size. Also, we explored how common factors related to words like frequency, length, and orthographic neighbourhood influenced the knowledge of a particular item. Results indicated important contributions of age to overall vocabulary size, with vocabulary size increasing in a logarithmic fashion with this factor. Furthermore, a contrast between monolingual and bilingual communities within Spain revealed no significant vocabulary size differences between the communities. Additionally, we replicated the standard effects of the words' properties and their interactions, accurately accounting for the estimated knowledge of a particular word. These results highlight the value of crowdsourced approaches to uncover effects that are traditionally masked by small-sampled in-lab factorial experimental designs.

Mining a Crowdsourced Dictionary to Understand Consistency and Preference in Word Meanings

Big data approaches to psychology have become increasing popular (Jones, 2017). Two of the main developments of this line of research is the advent of distributional models of semantics (e.g., Landauer and Dumais, 1997), which learn the meaning of words from large text corpora, and the collection of mega datasets of human behavior (e.g., The English lexicon project; Balota et al., 2007). The current article combines these two approaches, with the goal being to understand the consistency and preference that people have for word meanings. This was accomplished by mining a large amount of data from an online, crowdsourced dictionary and analyzing this data with a distributional model. Overall, it was found that even for words that are not an active part of the language environment, there is a large amount of consistency in the word meanings that different people have. Additionally, it was demonstrated that users of a language have strong preferences for word meanings, such that definitions to words that do not conform to people’s conceptions are rejected by a community of language users. The results of this article provides insights into the cultural evolution of word meanings, and sheds light on alternative methodologies that can be used to understand lexical behavior.

Ending the Reading Wars: Reading Acquisition From Novice to Expert

There is intense public interest in questions surrounding how children learn to read and how they can best be taught. Research in psychological science has provided answers to many of these questions but, somewhat surprisingly, this research has been slow to make inroads into educational policy and practice. Instead, the field has been plagued by decades of "reading wars." Even now, there remains a wide gap between the state of research knowledge about learning to read and the state of public understanding. The aim of this article is to fill this gap. We present a comprehensive tutorial review of the science of learning to read, spanning from children's earliest alphabetic skills through to the fluent word recognition and skilled text comprehension characteristic of expert readers. We explain why phonics instruction is so central to learning in a writing system such as English. But we also move beyond phonics, reviewing research on what else children need to learn to become expert readers and considering how this might be translated into effective classroom practice. We call for an end to the reading wars and recommend an agenda for instruction and research in reading acquisition that is balanced, developmentally informed, and based on a deep understanding of how language and writing systems work.