English Intelligibility Research Articles

Identifying Pronunciation Challenges for Cantonese EFL Learners: A Focus on Intelligibility

This study investigates the intelligibility of Cantonese-accented English by examining segmental pronunciation errors and their impact on native English listeners’ ability to accurately transcribe spoken sentences. Building on a previous production experiment, this research focuses on identifying which vowel and consonant mispronunciations most hinder intelligibility. Ten native English listeners transcribed 1,000 sentences produced by Cantonese speakers, and transcription accuracy was calculated for each target sound. The results reveal that dark /l/ (e.g., “cold”), final consonants like /g/ (e.g., “bag”), and the vowel /æ/ (e.g., “pan”) had the lowest accuracy rates, while sounds like /n/ (e.g., “no”) and /ʃ/ (e.g., “sheep”) were consistently transcribed correctly. These findings highlight the importance of targeting specific pronunciation difficulties in Cantonese EFL learners to improve intelligibility. The study supports the prioritization of intelligibility over accent reduction in pronunciation instruction, providing practical implications for teaching pronunciation in Cantonese-speaking contexts.

The Effectiveness of AI-Assisted Language Learning : Possibilities of Facilitating the Intelligibility of Korean-Accented English

The Effectiveness of AI-Assisted Language Learning : Possibilities of Facilitating the Intelligibility of Korean-Accented English

Affective Factors of Emotional Intelligence in Learning English among Saudi Female EFL Students

Affective Factors of Emotional Intelligence in Learning English among Saudi Female EFL Students

The relationship between trait emotional intelligence and English language performance among Chinese EFL university students: The mediating roles of boredom and burnout

With the wave of positive psychology in second language acquisition, more emotion factors are gaining scholarly attention. Despite extensive research on Trait Emotional Intelligence (TEI), burnout and boredom in English as a Foreign Language (EFL) studies, the interplay of these variables remains unknown and the related impact on EFL learner's English Language Performance (ELP) is still underexplored. Given this, in light of Control-Value Theory (CVT), the present study used a quantitative method to examine the mediating roles of boredom and burnout in the connection between TEI and ELP among Chinese university students engaged in EFL endeavor. Data were collected from 489 second-year EFL students. Structural equation modeling was utilized to analyze the relationships. Results revealed that TEI significantly influences ELP among Chinese EFL university students, through its correlation with both boredom and burnout. Higher levels of TEI are associated with reduced experiences of these negative states, which in turn are linked to improved language performance. These may imply that teacher educators should integrate emotional intelligence training into curricula and professional development to improve students' effectiveness and learning outcome.

Leveraging artificial intelligence (AI) in English as a foreign language (EFL) classes: Challenges and opportunities in the spotlight

The widespread use of Artificial Intelligence (AI) in language education contexts has motivated several scholars around the world to uncover the advantages and disadvantages of AI and AI-powered instruments in different language classrooms. Yet, as the review of earlier investigations revealed, few inquiries have been carried out to divulge the pros and cons of leveraging AI in EFL classes. To narrow this gap, using the phenomenological approach, this inquiry investigated the opportunities and challenges of implementing AI in EFL classes from the perspective of Chinese EFL students. To do so, through the criterion sampling technique, a total of 45 EFL students was recruited from different educational institutions in China. To collect the dataset, participants were asked to complete an open-ended questionnaire. For the sake of triangulation, among the 45 participants, 15 were randomly selected to engage in a follow-up interview session. With the aid of MAXQDA software (version 2023), participants’ perceptions of AI opportunities and challenges were carefully analyzed. Overall, the analysis findings uncovered that leveraging AI in EFL classes can bring numerous opportunities for EFL students, including individualized learning, timely and immediate feedback, rich educational resources, and an interactive learning atmosphere. However, as demonstrated by the analysis outcomes, implementing AI in EFL courses may also face students with a range of challenges and problems. The research outcomes would be of great help to teachers and educational leaders in mitigating the challenges of leveraging AI in language classrooms.

Hebban olla vogala: An Eleventh-Century Link Between Dutch and English Literary History

The short eleventh-century lyric Hebban olla vogala is considered the earliest literary text in Dutch. Yet it only survives as a badly faded pen trial, written in England by a monk from the Low Countries. As a result, the exact reading of the text and even the language it was written in remain uncertain. Now, multispectral imaging of the manuscript has made it possible to provide an improved reconstruction of the text. An analysis of this new reading suggests that the scribe deliberately used the similarity between dialects of late Old English and Old Dutch to produce a rhyming verse text that was intelligible in both languages. As a multilingual and translingual poem, Hebban olla vogala must therefore be situated in English as well as Dutch literary history. The scribe’s other pen trials in the same manuscript demonstrate an interest in different Latin verse forms, indicating that Hebban olla vogala may also be a literary experiment. In exploiting the mutual intelligibility of Old Dutch and Old English, the poem points to an easily overlooked current of influence on late Old English and early Middle English literature. While this is hard to trace due to the similarities between the two languages, Dutch emerges as another potential influence, alongside Anglo-Norman French, on the development of rhyming verse in English after the Norman Conquest. In this way, Hebban olla vogala can be seen not only as a monument of Dutch literary history, but also as a testament to its interaction with English literature.

International intelligibility of English spoken by college students in the Bashu dialect area of China

Exploring English intelligibility in linguistically diverse environments, such as China, is crucial for improving cross-cultural dialog and tailoring language instruction to address the phonetic hurdles of non-native speakers. This research employed a phonetic experimental methodology to assess the intelligibility of English spoken by college students from the Bashu dialect region of Southwest China to an international audience. Data from 40 intermediate English-proficient students in Sichuan and Chongqing were analyzed using open-ended questionnaires and evaluative scales. The findings revealed that the influence of the Bashu dialect significantly impeded the accurate articulation of specific English phonemes, thereby exerting an impact on the international intelligibility of their spoken English. Notably, notwithstanding their conspicuous accents, the research concluded that the English enunciated by these students generally retained intelligibility for global audiences. The study identified a spectrum of pronunciation challenges, encompassing issues with phonetic sounds, recurrent mispronunciations, and variances in accent and prosody, collectively contributing to an overarching influence on intelligibility. Grounded in international listener feedback, this study proffers strategies to augment the intelligibility of spoken English among Chinese learners originating from dialect-specific regions, thereby fostering the amelioration of their communicative skills and bolstering their confidence when engaging with global audiences.

Enhancing ESL Education with AI: Innovations in Teaching Methods and Au-thentic Materials

This article explores the integration of Artificial Intelligence (AI) in English as a Sec-ond Language (ESL) education, focusing on innovative teaching methods and authen-tic materials. AI-powered gamification is discussed, highlighting the use of AI tools like ChatGPT to enhance the gamification of key terms and concepts in ESL educa-tion. The interactive and enjoyable nature of gamified learning, combined with AI-driven content curation, deepens student understanding, critical thinking skills, and retention. By personalizing the learning experience, AI tools cater to individual stu-dent needs, allowing for flexibility in difficulty and fostering a love for the subject. Reflection and self-assessment play a crucial role in solidifying knowledge and pro-moting deeper learning. The article also discusses the importance of authentic materials in ESL education, emphasizing the use of AI-driven content curation to select and organize relevant and meaningful language content. AI-powered tools can analyze vast amounts of data, un-derstand patterns, and make accurate predictions, enhancing the user experience and delivering content that is most relevant and valuable to each individual student. The integration of AI in ESL education offers numerous benefits, including increased engagement, improved retention and application of key terms and concepts, personal-ized learning experiences, and enhanced critical thinking skills. By embracing AI-powered gamification and content curation, educators can create dynamic, interactive, and engaging learning experiences that foster a love for language learning and pro-mote deeper understanding.

Integration of AI into the Distance Learning Environment: Enhancing Soft Skills

Soft skills have become increasingly essential for success in the modern world, especially in the labor market, where employers value employees’ social and communication skills. Online education, which is an integral part of the educational process in Ukraine, is adjusting to the development of students’ soft skills. Integrating artificial intelligence tools into English language learning is becoming a new direction in soft skills development. This approach opens up new teaching strategies that make learning more effective, engaging, and innovative. While learning English, students develop communication, creativity, and critical thinking skills, which contribute to their educational process and prepare the foundation for employment. The study aims to 1) evaluate the impact of artificial intelligence on the development of students’ soft skills in online learning; 2) identify the most essential soft skills for their effective learning and future employment based on a student survey; 3) develop criteria for an online course using artificial intelligence and outline strategies for integrating the ChatGPT tool into distance learning English classes. To achieve the objectives of our study, we developed and processed a questionnaire, collected quantitative data, and analyzed and interpreted qualitative data; the study sample included 304 students. The questionnaire results showed a generally positive attitude of students towards using artificial intelligence in English for Specific Purposes courses. They opened up prospects for introducing an online course in the English for Specific Purposes program and further research, including an experiment with the introduction of this online course.

THE IMPACT OF EMOTIONAL INTELLIGENCE ON LANGUAGE LEARNING ACHIEVEMENTS IN UNIVERSITY EFL STUDENTS

Language learning is not merely a cognitive endeavour but a complex interplay of emotions, perceptions, and social dynamics. This article explores the relationship between emotional intelligence (EI) and language learning outcomes in university English as a Foreign Language (EFL) students. The study investigates the potential moderating influences of gender, field of study, and language background on this relationship. The research uses the Emotional Quotient Inventory (EQ-I) to assess emotional intelligence levels and correlates them with English language learning achievements. The study finds that, on a broad scale, emotional intelligence does not have a statistically significant impact on language learning achievements, suggesting that language proficiency is influenced by various cognitive and non-cognitive factors. However, the results suggest that the influence of emotional intelligence on language learning may be subtler and context-dependent. Specific components of EI, such as intrapersonal and interpersonal skills, may have nuanced effects on distinct language skills. This study enhances our understanding of the complex interplay between emotional intelligence and language learning outcomes among university EFL students, debunking simplistic assumptions about the direct impact of EI on language proficiency.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0708/a.php" alt="Hit counter" /></p>

Intelligibility of British and American English in different listening conditions

Communication specialists frequently hear complaints from patients that unfamiliar accents are more difficult to understand, particularly in background noise. Previous work (Schilaty et al., 2021) has indeed shown that when presenting American listeners with both American and British accents, intelligibility in noise is poorer for the unfamiliar accent across age and hearing status. However, Schilaty et al. (2021) examined relatively easy sentence materials (Basic English Lexicon [BEL] sentences; Calandruccio & Smiljanic, 2012) in only one type of noise. The current study expands on previous work by comparing the intelligibility of American and British accents for a more difficult sentence set (Harvard sentences; Rothauser et al., 1969) in young adult American listeners across two noise types (speech-shaped noise and 12-talker babble). Stimuli consisted of 180 Harvard sentences produced by two male talkers: one with an American (Northwestern) dialect and one with a Southern British dialect. Young adult listeners with normal hearing transcribed the sentences in quiet, in speech-shaped noise at −3 dB SNR, and in 12-talker babble at −3 dB SNR. Listeners also completed a dialect familiarity questionnaire. The results will shed additional light on the interactions between talker and listener dialect, dialect familiarity, and background noise type.

Assessing artificial intelligence and professors’ calibration in English as a foreign language writing courses at a Costa Rican public university

This article paper explores the evaluation of artificial intelligence (AI) in English as a Foreign Language (EFL) writing courses and the importance of calibration in writing evaluations. The role of calibration has received little attention in language contexts, while the role of artificial intelligence has gained increased attention in the last couple of years. This investigation, conducted from August 2022 to March 2023, involved eight TESOL students enrolled in an English as a Foreign Language (EFL) major at a Costa Rican public university, ten TESOL university professors, and one AI piece of software. It used a quantitative, quasi-experimental design, and a language elicitation data collection process. Data was collected by means of a rubric-based writing assessment. Quantitative data were analyzed using descriptive statistics. Data analyses indicate that: 1) human-created paragraphs (X̄ = 7,56) and AI writing (X̄ = 7,61) yield similar results when evaluated; 2) some criteria may favor human creativity or computer, rule-oriented writing; and 3) professors’ ratings reveal inconsistencies when grading human writing in particular. These findings demonstrate that AI matches, at least to a basic level, human writing skills. Furthermore, data show that students may be falling behind in aspects such as grammar, vocabulary, and mechanics. Finally, the analysis indicates that professors’ grading lacks consistency, and a calibration model should be incorporated as part of regular training workshops.

AI and Chat GPT in Language Teaching: Enhancing EFL Classroom Support and Transforming Assessment Techniques

The integration of artificial intelligence (AI) and Chat GPT technology in English as a Foreign Language (EFL) instruction has ushered in transformative changes in language learning and assessment. This essay explores the multifaceted impact of AI and Chat GPT on EFL education, emphasizing their role in personalized language learning, real-time language practice, and examination techniques. AI facilitates personalized language learning by tailoring lessons to individual students' needs, promoting deeper language understanding. Real-time language practice is enhanced through dynamic interactions with AI-powered chatbots, which provide immediate feedback, boosting proficiency and confidence. In examination techniques, AI automates grading and feedback, improving efficiency and consistency, while also enhancing test security. The integration of AI and Chat GPT raises ethical considerations regarding privacy, equity, and responsible AI usage. Successful case studies, including Duolingo's language learning platform, Chat GPT in EFL classrooms, and ExamSoft's examination software, highlight the practical benefits of AI integration. The future of EFL education lies in a collaborative relationship between human teachers and AI, addressing challenges and limitations while prioritizing ethical considerations, equitable access, and meaningful human interaction. The potential for a more effective and engaging EFL learning experience is achievable with a commitment to these principles.

Can Artificial Intelligence (AI) like QuillBot AI Assist Students’ Writing Skills? Assisting Learning to Write Texts using AI

At present, it is undeniable that the influence of Artificial Intelligence (AI) in learning English is increasing. AI helps students develop English sentences. This study aims to assist eleventh-grade students’ skills in creating hortatory exposition texts using QuillBot AI. It was Classroom Action Research (CAR) using the Kemmis, McTaggart, and Nixon paradigm conducted in two cycles, each consisting of three meetings. Each cycle included planning, acting, observing, and reflecting. The participants of this study were students from XI IPA 2A, consisting of 20 students. The data collection technique employed was a test. Before giving treatment, the students did a pre-test in the form of a writing test. Then, the researcher taught the students using Quillbot AI in several meetings. A paired sample t-test was administered using the SPSS version 25 to analyze the obtained data. The findings revealed that using QuillBot AI in the writing class considerably improved students’ writing skills. It was demonstrated by the results of the students’ writing test scores. In the pre-test, the students’ mean score was 53.55. Then, after utilizing QuillBot AI, the students’ mean post-test score was 78.90. In addition, the significance of the difference could also be seen in the acquisition of a sig. (2-tailed) value of 0.000, which meant it was smaller than 0.05. Based on the statistics presented, Ho was refused, and Ha was approved, indicating that QuillBot AI’s usage impacted the students’ ability to create hortatory exposition texts.

The Intelligibility of Korean-Accented English in the Lingua Franca Context

This study aimed to establish an empirical basis for prioritizing English as a Lingua Franca (ELF) instruction by evaluating the importance of “intelligibility” in communication with accented English speakers. It specifically examined the claims surrounding the Lingua Franca Core (LFC) features as the minimum requirements for intelligibility in ELF contexts. The experiment focused on the intelligibility of Korean-accented English (KoE) and general American English (AmE) to Korean-Speaking Learners (KSLs) and Japanese- Speaking Learners (JSLs). The findings indicated that AmE was more intelligible to both non-native English speaker groups. In contrast, KoE’s intelligibility was hindered by non- LFC features such as the pronunciation of the dark /l/ sound and specific vowel qualities. These results challenge the LFC proposal and suggest the need for a modified set of LFC features in ELF teaching and learning. The implications of this study are significant for English language education, highlighting the necessity of considering different accents and non-LFC features in ELF communication. By incorporating these aspects into instruction, teachers can better prepare learners for real-world interactions in diverse linguistic contexts. This approach enhances learners’ confidence and proficiency in understanding and being understood by individuals from various linguistic backgrounds, fostering successful intercultural exchanges.

Exploring the Impact of AI on The EFL Context: A Case Study of Saudi Universities

This research aims to determine whether or not it is possible to use artificial intelligence (AI) in English for speakers of other languages (ESOL) courses and review previous research pertinent to artificial intelligence in EFL/ESL instruction to present a comprehensive picture of the current degree of artificial intelligence in EFL/ESL instruction. Utilization of intelligent teaching systems, self-regulated learning, virtual reality, immersive virtual environment, and natural language processing in teaching English as a foreign language classroom. The study adopted the questionnaire as a tool for data collection then data was analyzed and discussed to reach the results. The results showed that the ethical responsibility for making the most effective use of AI in the classroom now falls on both educators and students themselves. The article also concludes that artificial intelligence (AI) positively impacts the field of English language teaching (ELT) and learning; however, it needs to be better integrated into educational settings. Teachers and students need to be more aware of the new applications and tools that have flooded the field of AI in recent years. This conclusion was reached in the context of the article.

Effects of L1 and L2 Communication Apprehension on Speaking Skills of Japanese University Students

This study explores the effect of communication apprehension in both L1 and L2 on proficiency in word stress of Japanese university students. Two structured, closed-ended questionnaires, the Personal Report of Communication Apprehension (PRCA) and the Foreign Language Classroom Anxiety Scale (FLCAS) were utilized along with speaking scores. A target word in an exclamatory sentence was used to examine word stress that affects intelligibility in spoken English. Acoustic correlates of the differences between stressed and unstressed syllables were investigated with four acoustic parameters: fundamental frequency (fo) range, fo slope, duration, and intensity. Results showed that of the four parameters, word stress represented by fo range and fo slope showed a significant negative correlation with L1 communication apprehension. In addition, speaking scores were related to L1 communication apprehension and word stress proficiency represented by fo range. These findings also suggest the effect of communication apprehension on English prosody as demonstrated by fo. In addition, speaking scores were related to L1 communication apprehenison and proficiency in word stress represented by fo range. These findings suggest the effect of communication apprehension on English speaking skills.

Relationships Between Acoustic Characteristics and Intelligibility Scores: A Reanalysis of Japanese Speakers' Productions of American English Liquids.

The primary purpose of this research report was to investigate the relationships between acoustic characteristics and perceived intelligibility for native Japanese speakers' productions of American English liquids. This report was based on a reanalysis of intelligibility scores and acoustic analyses that were reported in two previous studies. We examined which acoustic parameters were associated with higher perceived intelligibility scores for their productions of /l/ and /ɹ/ in American English, and whether Japanese speakers' productions of the two liquids were acoustically differentiated from each other. Results demonstrated that the second formant (F2) was strongly correlated with the perceived intelligibility scores for the Japanese adults' productions. Results also demonstrated that the Japanese adults' and children's productions of /l/ and /ɹ/ were indeed differentiated by some acoustic parameters including the third formant (F3). In addition, some changes occurred in the Japanese children's productions over the course of 1 year. Overall, the present report shows that Japanese speakers of American English may be making a distinction between /l/ and /ɹ/ in production, although the distinctions are made in a different way compared with native English speakers' productions. These findings have implications for setting realistic goals for improving intelligibility of English /l/ and /ɹ/ for Japanese speakers, as well as theoretical advancement of second-language speech learning.

The Use of The Theory of Multiple Intelligence in Learning English Pronouncing When Suffering from Learning Difficulties

The study planned to research First: Is there any relationship among Various Insights in gaining English articulation while experiencing learning troubles? Second: Is there any distinction between Different Insights and English articulating capability between male students and female students? A sum of 300 university English majors filled in as subjects of the review, including 125 guys and 175 females. just 22 were avoided, they assisted with finishing up the poll of numerous Insights. Moreover, their English scores or/and levels of School Selection tests were embraced as their English capability. Besides, illustrative investigation and relapse examination were broken down by the Factual Bundle for Sociology (SPSS). All came to the response to the inquiry assuming great English articulating students were more grounded with Verbal/Phonetic insight. Obviously, in the review, the response was negative, and involving the Hypothesis of Different Insight in learning English Articulating, is an exceptionally effective language learning device, and has an extremely sure relationship to beat any challenges in learning English articulating. Furthermore, In regards to distinctions in sexual orientation, guys would be wise to English articulating capability than females. However, the distinctions didn't arrive at a critical level.

Channeling Voices to Improve L2 English Intelligibility

AbstractIn commercial materials for the teaching of second language (L2) pronunciation, common bottom‐up approaches segment phonology into a series of discrete and decontextualized linguistic components with rules that students are encouraged to internalize. Such approaches seem out of step with recent second language acquisition (SLA) theory and research that emphasize the central influence of social context, interlocutor, empathy, and nonverbal elements on the meaningful use of L2 forms. Research showing that these factors profoundly influence the pronunciation of an L2 in social discourse suggests a more top‐down, holistic pedagogy to better harness the agentive energy of motivated and goal‐oriented L2 learners. Drawing on findings in interlanguage phonology and Bakhtinian sociocultural theory, this article documents ways that 7 adult L2 learners in an intensive English program improved their English intelligibility, while some of them also improved their delivery, as they all mirrored and subsequently channeled the voices of model speakers in rehearsed oral presentations over the course of a short 7‐week pedagogical treatment. The findings of this study support the view that the construct of voice and the influence of social contextual factors in SLA are critical in shaping interlanguage phonology and raise a number of important pedagogical implications for addressing learning outcomes in L2 pronunciation.