Non-native Language Learners Research Articles

Cultural intelligence and acculturation among non-native Arabic learners: the impact of ‎learning apps.

Learning apps can be helpful to non-native language learners in learning Arabic, which includes speaking, writing, and speaking exercises. When learners become better in the language, they become more confident in interacting with the community, thus affecting their Cultural Intelligence (CQ) and Acculturation (AC). This study aimed to explore the relationship between the CQ and AC among non-native learners of Arabic. Additionally, the study aimed to investigate the potential impacts of learning apps and gender. This study used a correlational approach, involving a sample of 102 non-native Arabic language learners in Jordan. To assess these factors, this study used the Cultural Intelligence Scale and the Acculturation Survey. The findings of this study revealed a positive correlation between the CQ and AC. Furthermore, the use of apps can provide CQ and AC levels. In addition, the study determined that gender did not play a significant role in influencing learners. the utilization of educational apps has been shown to enhance both CQ and AC. Thus, it is imperative to encourage learners to engage with these apps, as they foster cultural awareness, thereby facilitating the process of learning Arabic.

¿(Está/Es) Difícil?: Variable Use of Ser and Estar by Heritage Learners of Spanish

The current study examines variation in copula selection in Spanish by looking at the written productions of three groups of language learners in the United States, including heritage learners, those with English as an L1, and international students with English as an L2. Research on copula variation in Spanish has pinpointed several key linguistic and social factors that influence selection; this study aims to apply these findings to heritage learners in order to determine how their acquisition differs from that of non-native language learners. This analysis used the COWS-L2H corpus of Spanish from the University of California, Davis. Examining over 8000 tokens of [adjective + copula] constructions in variable contexts where both ser and estar were used, the study tracks how linguistic and extralinguistic factors condition copula selection within the three learner groups and how these results compare to previous findings. Seven factors were predictive of copula selection: resultant state, frame of reference, adjective class, experience with study abroad, essay prompt, student age, and course level. Heritage learner copula use was found to be governed by a different set of predictors than that of learners, hinting at the variable motivations and backgrounds that influence use and reflect the identity goals of these speakers.

Test-taker self-assessment accuracy using the TOEIC speaking and writing can-do statements

Can-do statements have been integrated for decades into research and marketing strategies related to standardized tests of English for non-native language learners. For instance, while ETS indicated that TOEIC can-do statements are specifically for “decision making in organizations,” the Council of Europe created user-friendly statements that all stakeholders, including test takers, can use and understand. This study discusses a partial replication of a large-scale validity study with the purpose of developing a scale which can be used by examinees in combination with the TOEIC SW can-do statements for self-assessment. As part of an extracurricular program, 23 graduate-level EAL university students took the TOEIC SW and speaking and writing can-do self-assessment surveys. Results indicated that both self-assessment scales used in this study had moderate to strong correlations with TOEIC SW scores (r = 0.62–0.73) and TOEIC proficiency levels (r = 0.47–0.66). Self-assessment results using a Level Mean Average (LMA) scale correlated significantly with both speaking and writing test results and produced slightly higher percentages of test takers self-assessing within the true score zones of 1 SEM. For the most part, self-assessment predictive accuracy using these scales and true score zones was 52–57% for speaking and 43% for writing. Other findings were that EAL learners tended to underestimate their scores, and they more accurately self-assessed speaking than writing. If LMA scale accuracy at a particular level can be verified in future studies, claims could be made that TOEIC SW can-do statements have value for examinees.

Physical Education with Eduball Stimulates Non-Native Language Learning in Primary School Students

Although the neuronal mechanisms of action and cognition are related, the division of intellectual and physical lessons is standard in schools. This is surprising, because numerous studies show that integrating physical education (PE) with teaching content stimulates critical skills. For example, several experiments indicate that Eduball-based PE (i.e., lessons in a sports hall during which students play team mini-games with educational balls with printed letters, numbers, and other signs) develops mathematical and language competencies. At the same time, the Eduball method does not slow down learners’ physical development. However, we have little knowledge about the effects of such techniques on non-native language learning. Consequently, the absence of incorporating core academic subjects into PE in dual-language schools or during foreign language education is exceptionally high. Here, we replicated the Eduball experiment, but with the goal of testing this method for non-native language learning. Thus, the intervention occurred in a dual-language primary school and we evaluated second language (L2) learning. As before, we used the technique of parallel groups (experimental and control); in both groups, there were three 45-min PE classes per week. In the experimental class, two of them were held using Eduball. After a half-year experiment, children from the experimental group (one second-grade, N = 14) improved their non-native language skills significantly more than their peers from the control group (one second-grade, N = 12). These findings demonstrate that Eduball-type intervention stimulates non-native language learning in children. Hence, our report suggests that specific body training forms can support L2 learning.

Oral Business English Recognition Method Based on RankNet Model and Endpoint Detection Algorithm

The prosodic feature of “stressed syllables” plays an important role in business English learning. For the majority of nonnative language learners learning English, the pronunciation of native language can easily affect the expression of spoken English. For those who cooperate and communicate in business, if they want to have more idiomatic and accurate spoken English, they need to control the necessary condition of stress first. This puts forward new requirements for the existing speech recognition technology: more accurate recognition of stressed syllables, reading complex and different emotional colors, and helping to correct oral expression. The experimental results show that (1) the higher the Fisher Ratio of the feature, the easier it is to distinguish the stressed syllables; adjusting the weight of features can effectively improve the recognition accuracy. (2) The recognition rate will decrease with the increase of noise. (3) InwMS method can distinguish features better than min-max method, but the recognition rate of stressed syllables is very low. Linear recognition based on single feature is not recommended. (4) The error rates of the two methods are 20.6% and 19.32%. If any feature of the fusion feature is removed, the error recognition rate of the model will increase by at least 3%. (5) For sentence stress recognition based on fusion features, the recognition error rate on RankNet model is as high as 42.51%. The final result of system operation is good, simple, and convenient.

Data Analysis Deep Learning Research on Spatiotemporal Preposition Construction Network

Chinese space-time prepositions (CSTPs) are a class of function words used to introduce space-time relations into motion or state, which have experienced the process of evolution from ancient Chinese. In recent years, the research on modern CTSPs shows the trend of grammaticalization research, cognitive semantic research, and research based on constructionalization and lexicalization. At present, there are few studies on the systematic semantic description of CTSPs in cognitive linguistics, and their semantic extension is closely related to the cognitive mechanism. This study is aimed at describing and explaining the functions of CSTPs in constructional networks, aiming to provide clearer semantic information for nonnative language learners. This is a comprehensive study combining qualitative and quantitative analysis. Qualitative analysis includes exploration of cognitive mechanisms, description of semantic networks, misinterpretation, and establishment of lexicographically definition model. Quantitative analysis includes data analysis of the Chinese corpus. The importance of qualitative analysis is far greater than that of quantitative analysis. It does not mean that quantitative analysis is not important. Quantitative analysis is important, and qualitative analysis is relatively more important.

An ear and eye for language: Mechanisms underlying second language word learning

AbstractTo become fluent in a second language, learners need to acquire a large vocabulary. However, the cognitive and affective mechanisms that support word learning, particularly among second language learners, are only beginning to be understood. Prior research has focused on intentional learning and small artificial lexicons. In the current study investigating the sources of individual variability in word learning and their underlying mechanisms, participants intentionally and incidentally learned a large vocabulary of Welsh words (i.e., emulating word learning in the wild) and completed a large battery of cognitive and affective measures. The results showed that, for both learning conditions, native language knowledge, auditory/phonological abilities and orthographic sensitivity all made unique contributions to word learning. Importantly, short-term/working memory played a significantly larger role in intentional learning. We discuss these results in the context of the mechanisms that support both native and non-native language learning.

Use of Virtual Reality in Non-Native Language Learning and Teaching

New emerging technologies, particularly in this COVID-19 era, have increased in their use more than ever. This concerns also their use in educational settings. At present, virtual reality (VR) has become a powerful and invaluable tool in teaching and learning processes. Although VR is not used in non-native language learning and teaching (NLLT) as much as in natural sciences, the use of VR technologies in NLLT is growing. In fact, language immersion is considered to be the most effective way of learning a foreign language. The purpose of this article is to review and discuss a potential of VR in NLLT. The findings of this review study reveal that VR technologies penetrate NLLT, but their use is still limited due to certain barriers, such as a lack of technical skills among teachers or higher costs. Consequently, research in NLLT is then small-scale. Nevertheless, VR technologies thanks to their immersive and authentic/real-life environment have a lot to offer to a second language learner, e.g. development of learner autonomy, achievement of better learning results, or personalized approach to learning. However, more attention should be paid to the development of collaborative learning.

English Grammar Error Correction Algorithm Based on Classification Model

English grammar error correction algorithm refers to the use of computer programming technology to automatically recognize and correct the grammar errors contained in English text written by nonnative language learners. Classification model is the core of machine learning and data mining, which can be applied to extracting information from English text data and constructing a reliable grammar correction method. On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of English grammar error correction algorithm, elaborated the development background, current status, and future challenges of the classification model, introduced the methods and principles of feature extraction method and dynamic residual structure, constructed a basic model for English grammar error correction based on the classification model, analyzed the classification model and translation model of English grammar error correction, proposed the English grammar error correction algorithm based on the classification model, performed the analyses of the model architecture and model optimizer of the grammar error correction algorithm, and finally conducted a simulation experiment and its result analysis. The study results show that, with the continuous increase of training samples and the continuous progress of learning process, the proposed English grammar error correction algorithm based on the classification model will continue to increase its classification accuracy, further refine its recognition rules, and gradually improve correction efficiency, thereby reducing processing time, saving storage space, and streamlining processing flow. The study results of this paper provide a certain reference for the further research on English grammar error correction algorithm based on the classification model.

Verbal Working Memory but Not Attention Is Related to Language Proficiency: Evidence from Multilingual Speakers.

Numerous studies have shown a consistent relationship between verbal working memory (WM) and native-language as well as non-native language learning abilities. However, the role of attentional abilities has been rarely explored, although these abilities have been shown to be associated both with verbal working memory and oral language proficiency. This study investigated the association between WM, attention and language proficiency in young adults raised with three different languages (Luxembourgish, German and French). Auditory-verbal WM abilities were assessed via an immediate serial recall task. Attentional abilities were assessed via auditory-verbal and visuo-spatial attentional tasks. Using a Bayesian correlational approach, we observed robust evidence for an association between auditory-verbal WM abilities and non-native language proficiency. At the same time, we observed no reliable evidence in favor of an association between language proficiency and auditory-verbal/visuo-spatial attentional measures. These results suggest that auditory-verbal WM and non-native language proficiency are strongly linked in young multilingual adults, irrespective of auditory-verbal or visuo-spatial attentional abilities.

Enhancing Cognitive Performance of Healthy Czech Seniors through Non-Native Language Learning-A Mixed-Methods Pilot Study.

The aim of this article is to discuss the effect of learning a non-native language on the enhancement of cognitive performance in healthy native Czech elderly. In addition, special emphasis is put on the qualitative assessment. To do this, 42 Czech cognitively unimpaired seniors were enrolled into the study. These were then divided into an experimental group (i.e., 20 healthy elderly studied English as a non-native language for three months) and a passive control group (22 healthy elderly, who did not undergo any non-native language intervention). The main outcome measures included the Montreal Cognitive Assessment, statistical processing of the data, and a qualitative content analysis. The results indicate that the cognitive performance of the intervention group did not differ from the control group. Therefore, no cognitive enhancement through non-native language learning was achieved. However, the findings of the qualitative analysis show that such non-native language learning with the peers of the same age is especially beneficial for the overall well-being of healthy seniors, especially as far as their social networks are concerned. Furthermore, participant’s subjective feelings from their self-reports indicate that foreign language learning also contributes to acquiring new English words and phrases. However, as there are very few empirical studies on this research topic, further research is needed in order to confirm or refute the present research findings on the enhancement of cognitive performance through non-native language learning in healthy seniors.

MENINGKATKAN PENGUASAAN SEBUTAN BAHASA CINA DALAM KALANGAN PELAJAR BUKAN PENUTUR JATI DI SEKOLAH KEBANGSAAN [INCREASING NON-NATIVE LEARNERS TOWARDS CHINESE LANGUAGE PRONUNCIATION IN NATIONAL PRIMARY SCHOOLS

Subject of Bahasa Cina Sekolah Kebangsaan (BCSK) is a first choice for students in the elective language offered in the national school. Dokumen Standard Kurikulum Pentaksiran (DSKP) in Bahasa Cina Sekolah Kebangsaan (BCSK), students are required to master the listening skills, speaking skills and writing skills. This paper is to identify factors that cause pronunciation error in Chinese Language done by non-native language learners in national primary schools. Factors of pronunciation error are divided into interlingual factors, intralingual factors and developmental error. Furthermore, effective teaching and learning (pdp) strategies to correct pronunciation errors are also proposed to increase to mastery the pronunciation among non-native students.

Language learning experience and mastering the challenges of perceiving speech in noise

Given the ubiquity of noisy environments and increasing globalization, the necessity to perceive speech in noise in a non-native language is common and necessary for successful communication. In the current investigation, bilingual individuals who learned their non-native language at different ages underwent magnetic resonance imaging while listening to sentences in both of their languages, in quiet and in noise. Sentence context was varied such that the final word could be of high or low predictability. Results show that early non-native language learning is associated with superior ability to benefit from contextual information behaviourally, and a pattern of neural recruitment in the left inferior frontal gyrus that suggests easier processing when perceiving non-native speech in noise. These findings have implications for our understanding of speech processing in non-optimal listening conditions and shed light on how individuals navigate every day complex communicative environments, in a native and non-native language.

Phonological feature-based speech recognition system for pronunciation training in non-native language learning.

The authors address the question whether phonological features can be used effectively in an automatic speech recognition (ASR) system for pronunciation training in non-native language (L2) learning. Computer-aided pronunciation training consists of two essential tasks-detecting mispronunciations and providing corrective feedback, usually either on the basis of full words or phonemes. Phonemes, however, can be further disassembled into phonological features, which in turn define groups of phonemes. A phonological feature-based ASR system allows the authors to perform a sub-phonemic analysis at feature level, providing a more effective feedback to reach the acoustic goal and perceptual constancy. Furthermore, phonological features provide a structured way for analysing the types of errors a learner makes, and can readily convey which pronunciations need improvement. This paper presents the authors implementation of such an ASR system using deep neural networks as an acoustic model, and its use for detecting mispronunciations, analysing errors, and rendering corrective feedback. Quantitative as well as qualitative evaluations are carried out for German and Italian learners of English. In addition to achieving high accuracy of mispronunciation detection, the system also provides accurate diagnosis of errors.

Mandarin Chinese Speakers’ Production of English Vowel Duration as a Function of Coda Voicing and Syllable Number

The current study compared native English-speaking adults’ and native Mandarin-speaking adults’ ability to produce context-specific vowel duration differences under the assumption that variability is higher in non-native language learners’ production. A total of twenty native Mandarin and English speakers produced real English words in a frame sentence multiple times. The mean vowel and consonant closure duration and vowel duration variability were analyzed. The results were that Mandarin Chinese speakers produced considerably smaller contrasts but greater temporal variability than English speakers in their production of individual words. The results indicated that the phonological knowledge of L1 is likely to interfere with the temporal patterns of L2 production.

Deficient non-native speakers or translanguagers?

This study investigated how the experience of a multilingual and multimodal English as a lingua franca (ELF) online intercultural exchange (OIE) influenced Taiwanese university students’ linguistic identities. Data was drawn from 26 Taiwanese students who had 10 weekly one-hour video live-chats with 18 Japanese students in 2 semesters. Taiwanese participants were interviewed on their language use and issues related to identities before, during, and after the exchange. Students’ language use patterns in the OIE and reflections on the OIE were also analyzed. Interviews revealed that the multilingual ELF experience had a liberating and empowering effect for students’ English use. In multimodal communication, they felt more comfortable using English together with other languages, evidenced by increasing productions of code-mixing utterances in later weeks. However, the anxiety of using Japanese with a native Japanese speaker still persisted. In particular, the native-speaker (NS)–nonnative-speaker (NNS) interactions constrained them to pay more attention to form and accuracy, which positioned both Taiwanese and Japanese students as either native speakers or deficient nonnative language learners.

The impact of input quality on early sign development in native and non-native language learners

There is debate about how input variation influences child language. Most deaf children are exposed to a sign language from their non-fluent hearing parents and experience a delay in exposure to accessible language. A small number of children receive language input from their deaf parents who are fluent signers. Thus it is possible to document the impact of quality of input on early sign acquisition. The current study explores the outcomes of differential input in two groups of children aged two to five years: deaf children of hearing parents (DCHP) and deaf children of deaf parents (DCDP). Analysis of child sign language revealed DCDP had a more developed vocabulary and more phonological handshape types compared with DCHP. In naturalistic conversations deaf parents used more sign tokens and more phonological types than hearing parents. Results are discussed in terms of the effects of early input on subsequent language abilities.

Improved mispronunciation detection with deep neural network trained acoustic models and transfer learning based logistic regression classifiers

Mispronunciation detection is an important part in a Computer-Aided Language Learning (CALL) system. By automatically pointing out where mispronunciations occur in an utterance, a language learner can receive informative and to-the-point feedbacks. In this paper, we improve mispronunciation detection performance with a Deep Neural Network (DNN) trained acoustic model and transfer learning based Logistic Regression (LR) classifiers. The acoustic model trained by the conventional GMM-HMM based approach is refined by the DNN training with enhanced discrimination. The corresponding Goodness Of Pronunciation (GOP) scores are revised to evaluate pronunciation quality of non-native language learners robustly. A Neural Network (NN) based, Logistic Regression (LR) classifier, where a general neural network with shared hidden layers for extracting useful speech features is pre-trained firstly with pooled, training data in the sense of transfer learning, and then phone-dependent, 2-class logistic regression classifiers are trained as phone specific output layer nodes, is proposed to mispronunciation detection. The new LR classifier streamlines training multiple individual classifiers separately by learning the common feature representation via the shared hidden layer. Experimental results on an isolated English word corpus recorded by non-native (L2) English learners show that the proposed GOP measure can improve the performance of GOP based mispronunciation detection approach, i.e., 7.4% of the precision and recall rate are both improved, compared with the conventional GOP estimated from GMM-HMM. The NN-based LR classifier improves the equal precision–recall rate by 25% over the best GOP based approach. It also outperforms the state-of-art Support Vector Machine (SVM) based classifier by 2.2% of equal precision–recall rate improvement. Our approaches also achieve similar results on a continuous read, L2 Mandarin language learning corpus.

The bilingual advantage in phonetic learning

Numerous factors are thought to be advantageous for non-native language learning although they are typically investigated in isolation, and the interaction between them is not understood. Firstly, bilinguals are claimed to acquire a third language easier than monolinguals acquire a second. Secondly, closely related languages may be easier to learn. Thirdly, certain phonetic features could be universally more difficult to acquire. We tested these hypotheses used as explanations by having adults learn vocabularies that differentiated words using foreign phonetic contrasts. In Experiment 1, Mandarin–English bilinguals outlearned English monolinguals, and the Mandarin-like (retroflex) artificial language was better learned than the English-like (fricative voicing). In Experiment 2, bilinguals again outlearned English monolinguals for the Mandarin-like artificial language. However, only Korean–English bilinguals showed an advantage for the more difficult Korean-like (lenition) language. Bilinguals, relative to monolinguals, show a general advantage when learning ‘easy’ contrasts, but phonetic similarity to the native language is useful for learning universally ‘difficult’ contrasts.

Transformative Learning: Teaching Vocabulary To Disadvantaged Non-Native Language Learners

Teaching English as a foreign language to students from disadvantaged situations requires focus on vocabulary building through contextualization, development of student-teacher relationships, and building the curriculum around collaborative activities.