Abstract

This study investigates applying the artificial intelligence tools in translating culture-specific items in literary works. A heated debate has been initiated among scholars since the beginning of using AI tools in translation; the core of this debate was about the ability of AI translation tools to convey cultural nuances compared to human translators. Furthermore, techniques are usually adopted by AI translators in case of a lack of equivalence. To investigate these queries, fourteen excerpts containing cultural elements have been chosen from three Libyan novels by Ibrahim Al-Koni, The Bleeding of the Stones, Dust Gold and Anubis, are utilized as a case study to compare the human translator's work with AI translation tools, namely, ChatGPT and DeepL. The major results of this study are the performance of AI tools almost the same as human translators. Although AI translation tools outperformed human translators' work in some situations, they still require specialized training on culture-specific items related to specific communities. A collaboration between human and AI tools results in significant translation rather than separating or substituting each other. The mixing between machine and human leads to important progression in the field of translation.

Abstract

Developing reading proficiency is essential for mastering English as a Foreign Language (EFL), yet many learners encounter difficulties due to restricted vocabulary and a lack of contextual understanding. To mitigate these issues, educators often suggest using picture books, which integrate visual imagery with text to help students decode meaning through multiple channels.

This study examines the influence of illustrated books on EFL reading comprehension using a quasi-experimental framework. The research involved 30 primary school pupils, divided into an experimental group using picture books and a control group receiving standard instruction. Results from pre- and post-test evaluations showed that students in the experimental group made significantly more progress than those in the control group.

These outcomes suggest that picture books are a powerful resource for enhancing comprehension and learner interest. Based on these findings, this study recommends EFL teachers incorporate  illustrated materials into their lessons  to enhance students’ understanding and engagement.

Keywords: picture books, reading comprehension, EFL learners, visual learning, young learners, language teaching.

Abstract

This study investigates how usually domestication and foreignization strategies are employed in literary works to convey cultural elements like ecology, material culture, religious ideas ….etc. It discusses the scholarly controversy about translation theories, especially with regard to how well each approach conveys cultural components and the motivations behind translators' decisions. These issues are considered by comparing the translations of two Arabic novels written by the Libyan author Ibrahim al-Koni (Anubis and The Bleeding of the Stone). Certain texts are extracted in order to apply the two strategies. The primary conclusions of the study show that although both domestication and foreignization techniques are used, translators tended to use domestication more often than foreignization. Most cultural elements were domesticated by replacing SL terminology with their TL equivalents.

Abstract

Vocabulary acquisition is a cornerstone of foreign language development, yet traditional instructional methods often fail to engage young learners or support long-term retention. This study investigates the effectiveness of using songs as a pedagogical tool for teaching English vocabulary to young English as a Foreign Language (EFL) learners. Employing a quasi-experimental quantitative design, the research compares the vocabulary acquisition of a group of primary school students (aged 6–10) instructed through songs with a control group receiving conventional instruction. Data were collected through pre- and post-tests, classroom observations and teacher feedback. The findings reveal that the experimental group demonstrated significantly greater improvement in vocabulary retention and recall compared to the control group. Furthermore, students in the song-based group exhibited higher levels of motivation, engagement and improved pronunciation. The study concludes that integrating songs into EFL instruction creates an interactive, stimulating and low-anxiety learning environment, making it a highly effective strategy for enhancing vocabulary acquisition among young learners.

Keywords: vocabulary acquisition, songs, young EFL learners, music-based instruction, vocabulary retention

Abstract

One of the most challenging  skills for English as a Foreign Language (EFL) learners is often the ability to speak, especially in environments where opportunities for authentic English exposure are scarce. This study focuses on prevalent linguistic errors found in the spoken English of third semester EFL students at the Faculty of Arts, Gharian University. . The three primary types of errors that are examined are phonological, grammatical, and lexical. The study also explores  the possible reasons behind these errors, such as first-language (L1) interference, limited English exposure, inadequate speaking practice in the classroom, fossilization, and emotional factors. Students often face difficulties with English phonemes that do not exist in Arabic, as well as with the correct grammatical forms, and suitable vocabulary choices, according to the results. The study emphasizes how important it is to implement focused interventions to improve students' spoken accuracy and fluency. It suggests pedagogical recommendations to enhance the accuracy and fluency of students’ spoken English, including increasing the number of opportunities for communicative practice, targeted pronunciation training, and the incorporation of authentic listening resources.

Keywords, English as a Foreign Language, linguistic errors, speaking skill

Abstract

This paper attempted to conduct a critical analysis of Donald Trump’s inauguration speech in 2025. The speech was analysed through Van Dijk’s socio-cognitive approach. Three levels of analysis were employed: textual, cognitive, and social. The findings revealed that Trump employed several rhetorical appeals, including logos and pathos. Additionally, various rhetorical devices such as hyperbole, metaphors, and parallel structures were utilised to reinforce his ideas. The analysis also revealed underlying ideologies within the speech, including nationalism, inequality, and protectionism. Trump depicted Americans as law-abiding citizens, while he portrayed immigrants as criminals posing a serious threat to America. Furthermore, Trump effectively employed linguistic tools and rhetorical devices to characterise Biden’s administration as weak and incompetent in managing social and economic issues, while presenting himself as a redeemer of America.

This study presents a quantitative descriptive analysis comparing the performance of human simultaneous interpreters (H-SI) and AI-driven interpreting systems (AI-SI) using deep learning architectures specifically Transformer-based models (e.g., mBART, Wav2Vec 2.0 + NMT pipelines) in real-time multilingual contexts. Drawing on a corpus of 1,248 interpreted segments extracted from TED Talks (English–Spanish, English–Mandarin), we evaluate output quality across six empirically derived metrics: lexical accuracy, syntactic fluency, temporal alignment, semantic fidelity, discourse cohesion, and error density. Data were collected from 30 professional human interpreters and three state-of-the-art AI systems (Google Translate Live, DeepL Pro, and a fine-tuned mBART-50 model). Statistical analyses (descriptive statistics, Mann-Whitney U tests, and Kruskal-Wallis H tests) reveal that while AI-SI outperforms H-SI in lexical accuracy (M = 92.4%, SD = 3.1) and temporal alignment (M = 0.87s lag, SD = 0.21), human interpreters demonstrate significantly superior performance in semantic fidelity (M = 86.7% as well as. 71.3%, p < .001) and discourse cohesion (M = 84.1% as well as. 63.9%, p < .001). Error density was significantly lower in human output (Mean Rank = 47.3 as well as. 29.1, p = .002). Findings suggest that current AI systems, despite algorithmic advancements, remain deficient in pragmatic and contextual adaptation core competencies rooted in human cognitive-linguistic processing. The study contributes a validated metric framework for evaluating AI interpreting performance and calls for hybrid human-AI paradigms in professional settings. Implications for interpreter training curricula and machine translation pedagogy are discussed

Keywords: Simultaneous Interpreting، Artificial Intelligence، Deep Learning، Quantitative Descriptive Research، Machine Translation، Human-Machine Comparison، Interpreter Performance، Transformer Model

-This qualitative case study investigates the effectiveness of AI-driven translation technologies in mediating cultural understanding within English Language Teaching (ELT) contexts in Libyan higher education. Drawing on data from semi-structured interviews with 55 ELT instructors, 24 classroom observations across six universities, and document analysis of student translation outputs and institutional curricula, the study reveals a dualistic role of artificial intelligence in language pedagogy. While AI-powered tools such as Google Translate and Microsoft Translator significantly enhance lexical accessibility and reduce language anxiety among learners, their capacity to convey cultural nuance remains critically limited. Findings indicate that algorithmic biases, rooted in Anglo-American linguistic corpora, result in the systematic flattening of cultural meaning and misrepresentation of idioms, humor, politeness strategies, and socio-pragmatic cues, thereby reinforcing a form of digital linguistic imperialism. Students’ uncritical reliance on AI outputs has fostered a “copy-paste culture,” undermining opportunities for intercultural reflection and eroding pragmatic awareness. However, the study also identifies transformative potential when AI tools are pedagogically repurposed through “teaching against the machine” strategies. A subset of instructors successfully used AI-generated mistranslations as pedagogical moments to foster critical cultural awareness, metacognitive reflection, and intercultural dialogue. Despite this potential, widespread implementation is hindered by systemic barriers, including the absence of institutional policies, lack of professional development, curricular gaps, and infrastructural challenges. The research concludes that AI technologies are not inherently facilitative or obstructive to cultural understanding; rather, their effectiveness is contingent upon intentional pedagogical mediation, critical digital literacy, and context-sensitive integration. The study calls for curriculum reforms, ethical AI integration frameworks, and teacher training programs that

position AI as a scaffold, not a substitute for intercultural communicative competence in ELT contexts

KEYWORDS: AI-driven translation, cultural understanding,, English language teaching, higher education, Libya, intercultural competence, technology integration

driven translation technologies in mediating his qualitative case study investigates the effectiveness of AI

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ABSTRACT

This study aimed to explore EFL teachers’ perceptions of the 21st-century PD program in six primary schools in Al Jabal Al Gharbi district. 31 teachers participated in the study. The mixed-research approach was used to conduct the research. A structured questionnaire and a semi-structured interview were used to gather the data. The results revealed that participants acquired several teaching skills, such as new techniques for teaching vocabulary, speaking, and listening language skills, from the 21st-century PD program. Furthermore, the participants reported positive changes in their students’ outcomes, including improved speaking, listening and vocabulary. The findings also revealed some complications in implementing the PD program, including a lack of resources and administrative support at some schools.