L1 mediation in Chinese English learners’ mental lexicon: Evidence from word association tests

2022 ◽  
pp. 136216882110660
Author(s):  
Li Xiang ◽  
Hyunjeong Nam

The study aimed to explore the evidence of first language (L1) mediation in second language (L2) word associations and the L2 learner-related factors affecting the extent of L1 mediation with the following approaches. First, different from previous research, word association tests (WATs) embraced both receptive and productive word associations in the study. Second, different from word-related variables such as cognates vs. non-cognates in previous research, the study examined learner-related factors. Third, it examined whether the methodological difference (receptive vs. productive test formats) may affect the extent of L1 mediation in L2 access. A total of 108 Chinese English learners varying in proficiency, learning experiences, input and motivation participated in WATs using 24 stimulus words. The results suggested, (1) from the findings of descriptive statistics and ANOVAs, the evidence of L1 mediation was found in all three L2 proficiency groups with different extent of higher L1 mediation in lower proficiency groups. (2) From the findings of Pearson product-moment correlation coefficients, significant correlations were found with L1-promoting learning environments, L2 input, integrative motivation and the learners’ awareness of L1 activation. (3) The findings of the paired-samples t-tests confirmed a significant difference between the two test formats. Based on the findings, the study suggested the promotion of L2-rich learning environments, integrative motivation, and receptive and productive word associations in the L2 network.

1968 ◽  
Vol 22 (3) ◽  
pp. 921-925 ◽  
Author(s):  
John Jung ◽  
Sonya Weber

The number of superordinate responses on a categorized word association test was lower when stimulus words from each category were presented in blocks or when there was no time pressure for responding. Both findings illustrate the susceptibility of word associations to the influence of variations in administrative procedures. The results are discussed in terms of their implications for the relationship between overt word-association-test responses and implicit associative responses.


2020 ◽  
Author(s):  
Arti Prihatini

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.   Keywords: word associations, constituents, language learning


2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Fei Ji

This study aims to test the validity of Critical Period Hypothesis (CPH) by investigating the influence of starting age on Chinese English learners’ pronunciation. The study compares the degree of foreign accent of native Chinese English learners with different starting ages in learning English, in an attempt to determine whether early Chinese English learners could outperform late ones in terms of English pronunciation when exposed to an English-speaking setting. Furthermore, this research also proposes to investigate other possible factors that affect Chinese English learners’ pronunciation. Participants were asked to provide spontaneous speech samples through semi-structured interviews conducted face-to-face or via Skype. In addition, an additional read-aloud task was required to ensure a more thorough and in-depth interpretation. The final results run counter to the Critical Period Hypothesis as there appeared to be late starters who also achieved native-like pronunciation, and there was no significant difference between early starters and late ones in terms of pronunciation. However, the study also yielded some results suggesting that greater efforts and stronger motivations were required for late starters in order to achieve the same pronunciation levels as early starters’, indicating that starting age can be a sensitive rather than critical factor for second language (L2) pronunciation acquisition.


2021 ◽  
Author(s):  
◽  
Ian Bloodworth

<p>Disruptive innovations have the potential to disrupt markets, and drive them in new directions. A common problem faced by business organizations is identifying such disruptive innovations. From a managerial perspective, there is real value in being able to accurately identify disruptive innovations early in the product life-cycle, as it affords the organization the opportunity to put in place business strategies that leverage this information, to gain maximal competitive advantage. This investigation was undertaken to determine if linguistic markers could be identified in ICT practitioner discourse that could be used to discriminate between traditional business intelligence (BI) - the legacy or incumbent technology, and software-as-a-service (SaaS) BI - a new technology and candidate disruptive innovation. Quantitative content analysis undertaken using the tool Veneficium WordFrequencyCounter, was used to analyze written practitioner discourse identified from within the Industry Newsgroup file of LexisNexis Academic universe. Analysis was undertaken using attribute sets derived deductively from the academic literature, and inductively from the data itself, which provided both manifest and latent meaning of component words. Individual relative word associations with both the traditional BI and SaaS BI corpora were also analyzed. Analysis of the attribute set usage data provided evidence that manifest and latent word meaning remained consistent for the time period investigated in this study (2000 to 2012), and so could support the purpose of this study, and was suggestive of the fact that SaaS BI could be a disruptive technology. The study also identified that there was a significant difference in vendor and industry attribute set usage between the SaaS BI and traditional BI corpora, consistent with the Abernathy-Utterback model. Analysis of individual word associations with the traditional BI and SaaS BI corpora identified a number of word association patterns that could discriminate between traditional BI and SaaS BI that may be transferable to other technologies. A crossover event pattern was also identified (in which the word association pattern switches between the incumbent and new technology), which may be able to provide an indication that a technology innovation is, or is about to become, disruptive. This study contributes a new approach for investigating disruptive innovation, and highlights the potential of using content analysis of practitioner discourse to identify linguistic markers for disruptive innovation. The key contribution of the study is the observation that discriminative linguistic markers can in fact be identified, and that such markers appear to have predictive capabilities. That is, they may allow organizations to identify disruptive innovations ex ante.</p>


Author(s):  
Hongling Lai ◽  
Dianjian Wang ◽  
Xiancai Ou

This empirical study investigates the effects of different caption modes on the content and vocabulary comprehension by Chinese English learners with different levels of English proficiency. The results show that the full captioned group performed better on content comprehension than the keyword group, while no significant difference was found on vocabulary comprehension between the two captioned groups. For the beginning-level learners, the full captioned groups did better both in content and vocabulary comprehension than the keyword caption group; meanwhile, for the advanced learners, both full captions and keyword captions similarly facilitated content and vocabulary comprehension. Therefore, the present findings suggest that keyword captioning is insufficient for foreign language learners' content comprehension, yet might be appropriate for their vocabulary learning. Furthermore, choosing the content caption mode for teaching EFL depends on students' English proficiency and their learning purpose.


This empirical study investigates the effects of different caption modes on the content and vocabulary comprehension by Chinese English learners with different levels of English proficiency. The results show that the full captioned group performed better on content comprehension than the keyword group, while no significant difference was found on vocabulary comprehension between the two captioned groups. For the beginning-level learners, the full captioned group did better both in content and vocabulary comprehension than the keyword captioned group; meanwhile, for the advanced learners, both full captions and keyword captions similarly facilitated content and vocabulary comprehension. Therefore, the present findings suggest that keyword captioning is insufficient for foreign language learners’ content comprehension, yet might be appropriate for their vocabulary learning. Furthermore, choosing the content caption mode for teaching EFL depends on students’ English proficiency and their learning purpose.


2021 ◽  
Author(s):  
◽  
Ian Bloodworth

<p>Disruptive innovations have the potential to disrupt markets, and drive them in new directions. A common problem faced by business organizations is identifying such disruptive innovations. From a managerial perspective, there is real value in being able to accurately identify disruptive innovations early in the product life-cycle, as it affords the organization the opportunity to put in place business strategies that leverage this information, to gain maximal competitive advantage. This investigation was undertaken to determine if linguistic markers could be identified in ICT practitioner discourse that could be used to discriminate between traditional business intelligence (BI) - the legacy or incumbent technology, and software-as-a-service (SaaS) BI - a new technology and candidate disruptive innovation. Quantitative content analysis undertaken using the tool Veneficium WordFrequencyCounter, was used to analyze written practitioner discourse identified from within the Industry Newsgroup file of LexisNexis Academic universe. Analysis was undertaken using attribute sets derived deductively from the academic literature, and inductively from the data itself, which provided both manifest and latent meaning of component words. Individual relative word associations with both the traditional BI and SaaS BI corpora were also analyzed. Analysis of the attribute set usage data provided evidence that manifest and latent word meaning remained consistent for the time period investigated in this study (2000 to 2012), and so could support the purpose of this study, and was suggestive of the fact that SaaS BI could be a disruptive technology. The study also identified that there was a significant difference in vendor and industry attribute set usage between the SaaS BI and traditional BI corpora, consistent with the Abernathy-Utterback model. Analysis of individual word associations with the traditional BI and SaaS BI corpora identified a number of word association patterns that could discriminate between traditional BI and SaaS BI that may be transferable to other technologies. A crossover event pattern was also identified (in which the word association pattern switches between the incumbent and new technology), which may be able to provide an indication that a technology innovation is, or is about to become, disruptive. This study contributes a new approach for investigating disruptive innovation, and highlights the potential of using content analysis of practitioner discourse to identify linguistic markers for disruptive innovation. The key contribution of the study is the observation that discriminative linguistic markers can in fact be identified, and that such markers appear to have predictive capabilities. That is, they may allow organizations to identify disruptive innovations ex ante.</p>


2021 ◽  
Vol 13 (14) ◽  
pp. 8006
Author(s):  
Till Schmäing ◽  
Norbert Grotjohann

The Wadden Sea ecosystem is unique in many respects from a biological perspective. This is one reason why it is protected by national parks in Germany and by its designation as a UNESCO World Heritage Site. In biology didactics, there are only a few studies that focus on the Wadden Sea. This work investigates students’ word associations with the two stimulus words “national park” and “UNESCO World Heritage Site”. The survey was conducted among students living directly at the Wadden Sea and among students from the inland. The analysis of the identified associations (n = 8345) was carried out within the framework of a quantitative content analysis to be able to present and discuss the results on a group level. A statistically significant difference was found between the two groups. Overall, results showed that the students made subject-related associations as well as a large number of associations to both stimulus words that could be judged as non-subject-related. In some cases, a connection with the region of residence could be found, but this was not generally the case. Even students’ immediate residential proximity to the Wadden Sea is no guarantee that they have knowledge of the two considered protection terms.


Author(s):  
Minjung Lee ◽  
Myoungsoon You

Avoidance of healthcare utilization among the general population during pandemic outbreaks has been observed and it can lead to a negative impact on population health. The object of this study is to examine the influence of socio-demographic and health-related factors on the avoidance of healthcare utilization during the global outbreak of a novel coronavirus (COVID-19) in 2020. Data were collected through an online survey four weeks after the Korea Centers for Disease Control and Prevention (KCDC) confirmed the first case in South Korea; 1000 subjects were included in the analysis. The logit model for regression was used to analyze the associations between sociodemographic and health-related factors regarding the avoidance of healthcare utilization. Among the participants, 73.2% avoided healthcare utilization, and there was no significant difference in the prevalence of healthcare avoidance between groups with (72.0%) and without (74.9%) an underlying disease. Sociodemographic characteristics (e.g., gender, age, income level, and residential area) were related to healthcare avoidance. Among the investigated influencing factors, residential areas highly affected by COVID-19 (i.e., Daegu/Gyeoungbuk region) had the most significant effect on healthcare avoidance. This study found a high prevalence of healthcare avoidance among the general population who under-utilized healthcare resources during the COVID-19 outbreak. However, the results reveal that not all societal groups share the burden of healthcare avoidance equally, with it disproportionately affecting those with certain sociodemographic characteristics. This study can inform healthcare under-utilization patterns during emerging infectious disease outbreaks and provide information to public health emergency management for implementing strategies necessary to improve the preparedness of the healthcare system.


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