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The present study investigates the patterns of word associations among Arab EFL learners and compares these patterns with those of native speakers of English. The study also examines the influence of increased language exposure and word characteristics on the learners' association patterns. To this end, 45 native speakers of English and 421 Arab learners of English at a Saudi university with two distinct levels of English language exposure completed a multiple-response word association test and their responses were analyzed, examined and compared. The results revealed strong influence for language exposure and word characteristics on the learners' associations and support a developmental approach to the second language lexicon where an increase in language exposure and word knowledge enhances mental word connectivity and increases its native-like similarity.

One of the most significant recent advances in the study of semantic processing is the advent of models based on text and other corpora. In this study, we address what impact both the quantitative and qualitative properties of corpora have on mental representations derived from them. More precisely, we evaluate models with different linguistic and mental constraints on their ability to predict semantic relatedness between items from a vast range of domains and categories. We find that a model based on syntactic dependency relations captures significantly less of the variability for all kinds of words, regardless of the semantic relation between them or their abstractness. The largest difference was found for concrete nouns, which are commonly used to assess semantic processing. For both models we find that limited amounts of data suffice in order to obtain reliable predictions. Together, these findings suggest new constraints for the construction of mental models from corpora, both in terms of the corpus size and in terms of the linguistic properties that contribute to mental representations.

The aim of this research is to present a Spanish Word Association Norms (WAN) database of concrete nouns. The database includes 234 stimulus words (SWs) and 67,622 response words (RWs) provided by 478 young Mexican adults. Eight different measures were calculated to quantitatively analyze word-word relationships: 1) Associative strength of the first associate, 2) Associative strength of the second associate, 3) Sum of associative strength of first two associates, 4) Difference in associative strength between first two associates, 5) Number of different associates, 6) Blank responses, 7) Idiosyncratic responses, and 8) Cue validity of the first associate. The resulting database is an important contribution given that there are no published word association norms for Mexican Spanish. The results of this study are an important resource for future research regarding lexical networks, priming effects, semantic memory, among others.

How words are associated within the linguistic environment conveys semantic content; however, different contexts induce different linguistic patterns. For instance, it is well known that adults speak differently to children than to other adults. We present results from a new word association study in which adult participants were instructed to produce either unconstrained or child-oriented responses to each cue, where cues included 672 nouns, verbs, adjectives, and other word forms from the McArthur–Bates Communicative Development Inventory (CDI; Fenson et al., 2006). Child-oriented responses consisted of higher frequency words with fewer letters, earlier ages of acquisition, and higher contextual diversity. Furthermore, the correlations among the responses generated for each pair of cues differed between unconstrained (adult-oriented) and child-oriented responses, suggesting that child-oriented associations imply different semantic structure. A comparison of growth models guided by a semantic network structure revealed that child-oriented associations are more predictive of early lexical growth. Additionally, relative to a growth model based on a corpus of naturalistic child-directed speech, the child-oriented associations explain added unique variance to lexical growth. Thus, these new child-oriented word association norms provide novel insight into the semantic context of young children and early lexical development. [ABSTRACT FROM AUTHOR]

S.A. Mednick (1962) proposed a theory of creativity suggesting that highly creative individuals can produce more word associations to a stimulus than less creative individuals. Numerous studies have supported this theory using the Remote Associates Test (RAT) as the measure of creativity. Additionally, some studies have suggested that high‐frequency words elicit more word associations overall than low‐frequency words, and concrete words elicit more associations overall than abstract words. The current study further investigated Mednick's theory by (a) creating controlled lists of stimuli that can better uncover how word type (abstract versus concrete) and word frequency (high versus low) affect the number of word associations produced to a stimulus, (b) including several creativity tasks besides the RAT, and (c) examining the role of other factors in creative thinking, including intelligence and verbal fluency. Participants first completed a word association task with four different types of words (i.e., high‐frequency concrete, low‐frequency concrete, high‐frequency abstract, and low‐frequency abstract), and then completed a variety of tasks, including several creativity tasks. Participants were categorized as highly creative or less creative based on a composite measure of the creativity tasks. Highly creative individuals produced more associations overall, supporting Mednick's theory. Furthermore, high‐frequency stimuli resulted in higher overall associative responses compared to low‐frequency stimuli, but contrary to previous research, no differences emerged for concrete versus abstract stimuli. There was also no difference in intelligence scores between the two creativity groups, and only a marginally significant difference in verbal fluency scores. [ABSTRACT FROM AUTHOR]

In this study, the word association method was applied in relation to municipalities in Eastern Hungary (Hajdú-Bihar county), where the Sustainable Energy and Climate Action Plan (SECAP) already exists, and where the SECAP has not yet been introduced. In addition to the six municipalities examined, Debrecen, a county seat with the SECAP, was also included in the survey. The aim was to explore the conceptual networks related to climate change and the strength of the relationship between the stimulus word and the associated concepts. The associations representing a common meaning were categorised. The results show that the distribution of conceptual networks and that of categories related to climate change exhibit a similar picture in the group of municipalities with (3 villages) and without the SECAP (3 villages), although significant differences were found when the settlements were examined separately (7 municipalities). Studying the distribution of categories by demographic groups, it was found that educational attainment determines, to the greatest extent, the answers. [ABSTRACT FROM AUTHOR]

We examined word associations in Swedish children with Developmental Language Disorder (DLD) compared to their typically developing (TD) peers. Furthermore, the study aimed to explore the dimensions of vocabulary knowledge (breadth, depth, and fluency) in these children. Fifty children (15 DLD and 35 TD) participated in the study, aged six to nine years. This age span is commonly associated with substantial lexical reorganisation, by some referred to as the syntagmatic-paradigmatic shift. Fifty items from the Kent-Rosanoff list were used to elicit word associations (say the first word that comes to mind). Word associations were coded as paradigmatic (lion-tiger), syntagmatic (chair-sit), phonological (moon-poon), and other/no answer (foot-hello/bed- -). A semantic depth score (paradigmatic and syntagmatic associations) was calculated and analysed. The children with DLD showed significantly lower semantic depth scores than their TD peers, in line with previous research in English-speaking children. However, the vocabulary dimensions were uniformly affected for the DLD group, contradicting previous findings of semantic depth as a particular area of weakness in this group. [ABSTRACT FROM AUTHOR]

In recent years, word associations have played a key role in cognitive research. The goal of this study is to propose a new system called Tarvajeh to construct and analyze the association norms found in the Persian language. In this paper, we present Tarvajeh, a data set for Persian words in a continuous word association task. For data collection, cue words have been categorized into groups and then, 30 of them were presented to each participant in two phases. Afterward, the participants were asked to write the first three words that are related to the initial cue words. After data collection, Tarvajeh included 240 frequent Persian cues and more than 20,000 different responses. Furthermore, we also propose a method that allows participants to compare their responses as well as their subconscious mind with those of their peers using a unique graph that is tailored to their responses and is displayed to them. Finally, we compared our data with those of associated words in other languages. The comparison reveals that, for some cues, most associated words are the same, while for others, the most frequent responses are unique within each data set. In addition, some gender-related differences were observed with male participants spending more time on their responses than female participants. [ABSTRACT FROM AUTHOR]

This paper aimed at describing word association and its function at the constituent understanding on the language learning. Word association is a relation between a word with other words because of the semantic relationship. A word association test appears when there is a stimulus word and someone mentions a response word that comes to mind firstly based on the stimulus word. The response words show someone's mental lexicon as a result of language acquisition and language learning. Word associations can be used in the process of understanding constituents (linguistic units) with word association tests, they are (1) words, (2) phrases, and (3) sentence patterns. In word constituent learning, word association tests are carried out by asking questions so that the result can show the semantic networks of words that are classified by word type. Phrase constituent learning is also held by asking questions, but response words are included before or after the stimulus word so that these words form a phrase. Meanwhile, sentence constituent learning is held by presenting words that are located as predicate and then asking questions that bring up the subject, object, complement, or additional information that accompany the predicate. With this method, students do not only learn constituents as units that have levels from small (words) to large ones (sentences), but also understand that constituents have a patterned and interconnected system. [ABSTRACT FROM AUTHOR]

One avenue for developing second language (L2) vocabulary knowledge is through Extensive Reading (ER). ER can provide opportunities for incidental learning to occur. Class time is often too restricted for sufficient attention to deliberate learning (Hunt & Beglar, 2005) meaning ER is important for L2 vocabulary development. This article builds on ideas in the recent two-part Reading in a Foreign Language ER discussion forum by investigating two implementations of ER and their effects on L2 vocabulary development: a traditional ER-only approach, and an ER-plus approach which supplements ER with postreading discussion implemented in small groups. L2 English learners enrolled at a university in Aotearoa New Zealand read five graded readers during normal class time. Latent Semantic Analysis was used to measure the development of word association knowledge of 60 target words. The findings revealed facilitative effects of both ER approaches. Supplementing ER with discussion provided opportunities for further development. [ABSTRACT FROM AUTHOR]

Word associations have been used widely in psychology, but the validity of their application strongly depends on the number of cues included in the study and the extent to which they probe all associations known by an individual. In this work, we address both issues by introducing a new English word association dataset. We describe the collection of word associations for over 12,000 cue words, currently the largest such English-language resource in the world. Our procedure allowed subjects to provide multiple responses for each cue, which permits us to measure weak associations. We evaluate the utility of the dataset in several different contexts, including lexical decision and semantic categorization. We also show that measures based on a mechanism of spreading activation derived from this new resource are highly predictive of direct judgments of similarity. Finally, a comparison with existing English word association sets further highlights systematic improvements provided through these new norms. [ABSTRACT FROM AUTHOR]

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The present study is an attempt to empirically test and compare the results of three methods of word association (WA) analysis. Two of the methods – namely, associative commonality and nativelikeness, and lexico-syntactic patterns of associative organization – have been traditionally used in both first language (L1) and second language (L2) associative research and the third one – collocational aspect of associative responses – is a more recent perspective on associative connections. The central assumption behind the study is that each method captures a different aspect of language users’ lexical organization and, in that, their findings may paint a different picture of how the L1 and L2 lexicons compare as proficiency increases. At the same time, the sensitivity of each method to reflect differences related to proficiency may also point to their potential as a research and assessment tool.Three equal size groups of participants (N = 180) at different proficiency levels – native speakers (NSs), second language (L2) advanced and intermediate learners of English – completed a familiarity and a WA test in writing. The tests contained 36 items equated for lexical class (nouns, verbs, and adjectives) and frequency of occurrence (high, mid, and low). The participants’ WAs generated to familiar vocabulary were analysed in three different ways, following the methods of analysis practiced by each of the three traditions under investigation. In the main, the results showed that examining the lexico-syntactic patterns of associative organization as well as the collocational aspect of associative links are two more ‘promising’ ways of looking at WAs than examining them with respect to their nativelike associative commonality. [ABSTRACT FROM PUBLISHER]

The assessment of so-called depth of word knowledge has been the focus of research for some years now. In this article the construct of deep word knowledge is further specified as the decontextualized knowledge of word meanings and word associations. Most studies so far have involved adolescent and adult second language learners. In this article, we extend the focus to younger first and second language learning children in primary school in the Netherlands. A well-established test format involving word associations has been adapted for this younger target group and the feasibility of assessing deep word knowledge in primary school children is evaluated empirically. The results showed that the test provides a reliable and efficient method of assessing the children's vocabulary knowledge. Evidence of validity was obtained from a concurrent definition task, and from an analysis of the scores in terms of language background, which is known to be associated with different levels of vocabulary knowledge. [ABSTRACT FROM AUTHOR]

An astronomical set of sentences can be produced in natural language by combining relatively simple sentence structures with a human-size lexicon. These sentences are within the range of human language performance. Here, we investigate the ability of simple recurrent networks (SRNs) to handle such combinatorial productivity. We successfully trained SRNs to process sentences formed by combining sentence structures with different groups of words. Then, we tested the networks with test sentences in which words from different training sentences were combined. The networks failed to process these sentences, even though the sentence structures remained the same and all words appeared on the same syntactic positions as in the training sentences. In these combination cases, the networks produced work-word associations, similar to the condition in which words are presented in the context of a random word sequence. The results show that SRNs have serious difficulties in handling the combinatorial productivity that underlies human language performance. We discuss implications of this result for a potential neural architecture of human language processing. [ABSTRACT FROM AUTHOR]