Journal of Psycholinguistic Research最新文献

The aim of the study is to analyse contemporary postmodern literary works of Kazakhstan through the conceptual prism of Freudian and Jungian psychoanalysis. To achieve research goals, the following methods were used: axiomatic, content analysis, and comparative. The results of the study determined that contemporary Kazakh writers characterise a large field of motives and ideas that are revealed through text, symbols, and characters. Strong tools for their interpretation were the psychological approaches of Freud and Jung, which are the standards of psychoanalysis and have their own specific features of semantic content. Content analysis of postmodern materials has established that Kazakh stories trace the motives of mythology, religion, relationships and inner spiritual development, which consider the mental differences of the heroes of the storylines. During the psychoanalysis of the works, it was emphasised that postmodernism in the literature of Kazakhstan reflects the rejection of absolute truths, blurring the boundaries between genres, playing with traditional forms and content. Many of the characters in the stories are experiencing an identity crisis, which has been analysed through the Freudian triad and Jung’s archetypal images. Kazakh literature, being woven into the cultural and historical heritage of the nation, reflects the features of mentality, socio-cultural transformations, identity and spiritual quest of heroes.

The outbreak of Covid-19 has led to the need for institutions to provide online learning to their students. In this context, it is important to understand the views of both students and teachers regarding online classes. This study aims to explore the opinions of English teachers and students in vocational colleges in China about online English learning. A convenience sampling technique was used in the study. Data was collected using a questionnaire survey from the respondents. Data were analyzed using SPSS statistical software. Focused on the perceptions of English teachers and students in vocational colleges about online English learning. The results of the study revealed negative perceptions of both students and teachers about vocational English education in an online learning environment. This study highlights the importance of addressing both teachers’ and students’ negative feelings about online learning. The findings of this study are useful for educators and academic departments in improving the online learning experience for vocational students. It also emphasizes the need for effective implementation of ICT modules to improve the quality of online education. The study suggested that ICT modules should be implemented in various media platforms and applications to improve the quality of online learning by academic departments. Overall, this study emphasizes the importance of understanding stakeholder perceptions in online learning environments and provides insights for improving the quality of online education.

Artificial grammar learning (AGL) is an experimental paradigm frequently adopted to investigate the unconscious and conscious learning and application of linguistic knowledge. This paper will introduce ENIGMA (https://enigma-lang.org) as a free, flexible, and lightweight Web-based tool for running online AGL experiments. The application is optimized for desktop and mobile devices with a user-friendly interface, which can present visual and aural stimuli and elicit judgment responses with RT measures. Without limits in time and space, ENIGMA could help collect more data from participants with diverse personal and language backgrounds and variable cognitive skills. Such data are essential to explain complex factors influencing learners’ performance in AGL experiments and answer various research questions regarding L1/L2 acquisition. The introduction of the core features in ENIGMA is followed by an example study that partially replicated Chen (Lang Acquis 27(3):331–361, 2020) to illustrate possible experimental designs and examine the quality of the collected data.

This study aims to investigate the efficacy of self-narrative as a tool for identifying personality traits conducive to motivation for success. The research employs several methodologies, including the “Readiness for Self-Development” test by V.L. Pavlov, the Achievement Motivation Diagnosis test, and the katathym imaginative psychotherapy motive “Mountain” as a form of self-narrative. Psycholinguistic analysis tools such as the verbosity coefficient, embolism coefficient, and correlation coefficient are utilized. Through empirical analysis of self-narratives, criteria for evaluating motivational potential are established. Quantitative and qualitative analyses of respondent narratives reveal distinct patterns. Coefficients derived from psycholinguistic analysis indicate a correlation between self-narratives and motivation for achievement. Respondents demonstrating motivation for success and readiness for self-development exhibit lower verbosity and embolism coefficients. Conversely, those with a tendency to avoid failure and low readiness for self-development tend to employ narratives rich in superficial language elements. The findings suggest that self-narrative analysis can effectively gauge an individual’s motivational tendencies and readiness for personal development. This method holds promise as a tool for identifying and nurturing talent within organizations, particularly in the context of forming a vertical personnel reserve. By understanding the motivational drivers revealed through self-narratives, organizations can better tailor their approaches to talent management and development.

Comprehension of metaphorical expressions differs with their degree of novelty. Conventional metaphors are typically comprehended as easily as literal sentences, while novel metaphors are responded to less quickly than their conventional counterparts. However, the influence of metaphor signals on the interpretability and acceptability of sentences with metaphors, especially their potential interaction with novelty, remains an open question. We conducted six online experiments among 1,694 native speakers of American English to examine how interpretability and acceptability ratings of individually presented sentences were affected by metaphor novelty and different types of metaphor signals. Across all six experiments, we consistently found that novel metaphors decreased the interpretability and acceptability of sentences compared to both conventional metaphors and literal controls. Signals, on the contrary, did not impact the interpretability or acceptability of the sentences. Moreover, only in experiment 3b did we find an interaction between metaphor type and signals. Specifically, when a metaphor was marked by double signals (i.e., both lexical signals and a typographical signal were added around the metaphorical keywords) vs. no signals, acceptability of novel metaphors increased, but acceptability of conventional metaphors decreased. We hypothesize that the double signaling of novel metaphors marks their novelty, making them more acceptable. By contrast, the double signaling of conventional metaphors may have been perceived as redundant, leading to a lower acceptability.

The issues of depth vocabulary knowledge and Willingness to Communicate (henceforth, WTC) are among the most important issues in second language learning. The present study set out to empirically look into the contribution of WTC to depth of vocabulary knowledge in L2 learning. To this end, 88 English L2 learners, divided into two groups in terms of their WTC, were given two depth vocabulary tests. The Word Association Test (WAT) was first administered to make a comparison between the depth vocabulary knowledge of the two WTC groups. Then, to triangulate the results, the Word Part Levels Test (WPLT) was administered to check whether the obtained results confirmed those of WAT. Analyzing data through independent t-test and MANOVA indicated that learners with higher levels of WTC had deeper vocabulary knowledge than those with lower levels of WTC on the WAT. Further, the triangulation results evinced that although the two groups did not differ significantly on the form-section and meaning-section of the WPLT, they significantly differed on the use-section of the test. The relevant pedagogical implications of the study are discussed.

Previous research has shown that moral choice depends on language, a phenomenon known as the moral foreign language effect (mFLE). The current study examines the influence of social distance on the mFLE. In Experiment 1, 200 participants were randomly assigned to either close or distant social distance in English or Chinese. In Experiment 2, 188 participants were randomly assigned to either English or Chinese and were presented with eight moral dilemmas, each with five different levels of social distance. After reading the dilemma, participants made a choice on a binary scale (Yes/No) in both Experiments 1 and 2 or on a more sensitive 100-point scale in Experiment 2. The results showed that the mFLE was present in distant social distance but absent in close social distance. Finally, a meta-analysis of the results from both studies confirmed the effect of social distance on the mFLE. These findings demonstrate that social distance might play an important role in moderating the mFLE in moral judgment.

The purpose of this study was to consider the core of the mental lexicon of the Kazakh language based on the analysis of associative dictionaries, to determine the basic lexico-semantic groups of words and to compare the basic lexical layer with value categories. This study uses the following methods of linguocultural, comparative, lexico-semantic, and conceptual analysis, as well as analytical and synthetic analysis, with the help of which the main conceptual values of the Kazakh people were studied: spiritual, mental and material. The lexico-semantic categories of words in the Kazakh language were identified: names of people; adjectives with an assessment of reality; basic action verbs; nouns with abstract meanings. An idea was formed about the differences between the conceptual cores of the mental lexicon of the Kazakhs, the British, and the Spaniards. The principles of intercultural communication and ways of its implementation were considered on the example of the study of the Kazakh language from the point of view of linguistic culture. The basic concepts and their semantic meanings were compared based on the analysis of the linguistic nature of lexemes in the Kazakh, English and Spanish languages. Tables with the results of the study were presented to illustrate the results obtained. This study can be used in further scientific practice, for example, in linguocultural, sociocultural, historical, lexicographic, and conceptual studies.

This study uses a data-driven approach to mine the distribution of personality traits among Chinese people in the Chinese social context. Based on the hypothesis of personality lexicology, word embedding technology was employed in machine learning to mine personality vocabulary from Tencent's word embedding database. More than 10,000 Chinese personality descriptors were extracted and analyzed using Gaussian Mixture Model Cluster and Hierarchical clustering analysis. The data was collected from 658 Chinese people randomly from all parts of China through an online questionnaire method. The results reveal six personality traits in the Chinese context, expanding the personality thesaurus and providing examples to illustrate each trait. The findings coincide with previous research on the five-factor model, which partially describes the personality traits of Chinese people, but does not offer a complete explanation of their typical social behavior patterns. Additionally, the study supports the notion of cultural particularity in personality traits. The approach used in this study offers a richer personality vocabulary than traditional personality mining methods, and word embedding technology captures richer semantic information in Chinese. The six Chinese personality traits identified in this study will also be used to explore how to quantify and evaluate personality traits based on word embedding and personality descriptors.