This chapter examines the lexical availability of students of Spanish as a foreign language (SFL) and observes how their semantic networks change as their proficiency in Spanish increases. The analysis focuses on 150 students with different levels of proficiency and the two centres of interest: "acciones y actividades habituales"…

In many domains, learners extract recurring units from continuous sequences. For example, in unknown languages, fluent speech is perceived as a continuous signal. Learners need to extract the underlying words from this continuous signal and then memorize them. One prominent candidate mechanism is statistical learning, whereby learners track how…

Associative learning strategy (ALS) is an important means of acquiring vocabulary--especially in L2 learning. This study proposes a method to identify the associative learning mechanism based on complex network theory. First, a distributed association strategy (DAS) for the associative learning of L2 learners based on distributed language learning…

We examined 3 different network models of representing semantic knowledge (5,018-word directed and undirected step distance networks, and an association-correlation network) to predict lexical priming effects. In Experiment 1, participants made semantic relatedness judgments for word pairs with varying path lengths. Response latencies for…

This study aimed to determine the cognitive structures of preservice primary school teachers for basic biology concepts using Word Association Test (WAT). The study group consists of 50 preservice teachers studying in a university in Western Black Sea Region in Turkey. Four separate cut-off points were determined and analysed. Organ, living…

The purpose of this study was to investigate the bibliometric analysis of number sense studies over the past 30 years and monitor the trend regarding the nomological network accordingly. All the published articles in Web of Science database, containing the term number sense between 1990 and 2019, constituted the focus of the study. In the analysis…

In this application briefing we describe an inductive learning activity designed for an executive-level leadership development session on leadership networks. We separated participants into nine teams of different sizes and varying access to collaborative networks among the teams. Each team was given the same word association challenge consisting…

Human word learning is remarkable: We not only learn thousands of words but also form organized semantic networks in which words are interconnected according to meaningful links, such as those between "apple," "juicy," and "pear." These links play key roles in our abilities to use language. How do words become…

Background: We adopted a theoretical framework that the acquisition of a scientific concept comprises the development of connections among conceptual elements associated with a scientific term within a mental semantic network. Given this framework, the hypothesis that the surrounding words connected with a scientific term are relevant to the…

Recent semantic space models learn vector representations for word meanings by observing statistical redundancies across a text corpus. A word's meaning is represented as a point in a high-dimensional semantic space, and semantic similarity between words is quantified by a function of their spatial proximity (typically the cosine of the angle…

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

The present research approached a problem which has a twofold aspect: the concept of angle and the techniques needed to represent how pupils construct that concept in their cognitive structure during their years in school. In order to access the knowledge of the concept of angle, we used the pathfinder associative networks. This technique provided…

Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual's semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals…

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…

We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…