This study explores the extent to which Grammarly can be a reliable assessment tool for academic English writing. Ten articles published in high-status scholarly Q.1 journals and written by specialist English native speakers were used to evaluate the accuracy of Grammarly's flagged issues. The results showed that Grammarly tends to over-flag many issues resulting in many false positives; besides, it does not take into consideration optional usage in English. The study concluded that although Grammarly can identify many ambiguous instances of language use that writers would do well to review and consider for revision, it does not seem to be a reliable tool for assessing academic written English.

This article aims to explore the effect of applying gamification in English language skills as a pedagogical approach to enhance students’ academic performance in university settings. The researchers employed a mixed-method approach to examine the impact of gamification on English language skills. Gamification involves integrating game elements and mechanics into non-game contexts, such as educational activities. The article examined the effect of gamification and its implementation in teaching English language skills in university settings. The study finds out that gamification offers a promising avenue for promoting engagement, motivation, and proficiency in teaching English language skills. However, further research is needed to investigate gamified learning environments' long-term effects and optimal design principles.

The passive voice represents a marked syntactic construction in language, and its usage requires a systematic analysis to fully comprehend its complexities. The role of the passive voice in the Holy Quran has not been adequately explored in previous studies. This research aims to provide a comprehensive analysis of all passive verbs found in the Holy Quran. We identified 1107 passive verbs using the categorization provided by the Quranic Corpus. These verbs were analyzed in terms of tense, agents, and functions. The results indicate that the passive voice is employed sparingly in the Quran, accounting for only approximately 5% of the total 19,356 verbs. Furthermore, the agent-less passive form emerged as the default, while the most frequently occurring agents were Allah (the Almighty), indefinite agents, Satan or the self, prophets, unbelievers, and believers. The findings suggest that the passive voice in the Quran serves multiple functions, often operating simultaneously. The primary functions of passive constructions include brevity and conciseness, emphasizing the action or object, and expanding meaning.

Machine translation has undergone remarkable evolution since its early rule-based systems in the 1950s, progressing through statistical models in the 1990s to neural machine translation (NMT) in the 2010s. The introduction of large language models, such as OpenAI’s GPT series, has marked a new era in translation technology, enabling systems to understand context, tone, and meaning beyond literal word substitution. These developments have reshaped translation research and practice, especially in academic and professional settings. This article explores the effectiveness of ChatGPT as a translation tool in academic contexts, particularly within the fields of humanities and social sciences. Drawing on recent literature, the study reviews advances in prompt engineering, comparative evaluations with traditional machine translation systems, and domain-specific translation challenges. Structured prompts are shown to significantly enhance translation accuracy, with BLEU scores improvingas prompt complexity increases. Comparative studies reveal that ChatGPT generally produces more fluent and contextually appropriate translations than tools like Google Translate, especially for high-resource languages and conversational texts. However, its performance declines with specialized terminology, low-resource languages, and culturally embedded expressions. Results show that ChatGPT can be a reliable translation tool that captures the intended meaning rather than offering word-for-word translations, making it a valuable resource in academic and professional settings. Nonetheless, challenges remain, particularly in accurately translating culture-bound expressions, technical jargon, and dialectical variations. Examples from Arabic–English translations underscore these limitations, highlighting instances where ChatGPT succeeded in conveying nuanced meaning and others where it produces awkward or inaccurate renderings. The study concludes by emphasizing the need for ongoing refinement in prompt design and hybrid human–AI translation approaches to enhance translation quality and cultural sensitivity in academic discourse.

This study aims to identify the use of the word Allah ‘God’in Jordanian spoken Arabic and its pragmatic functions. The ethnography of communication method, as proposed by Gumperz and Hymes, alongside Speech Act Theory and Politeness Theory were adopted to collect the data for this study. The data, gathered with the help of six native-speaking assistants and identifies (123) Allah-based phrases and compiled them into a list of (37) pragmatic functions used in Jordanian spoken Arabic. The researchers recorded real-life conversations across various social settings such as homes, universities, coffee shops, and workplaces. The findings reveal that Allah-based phrases serve a wide range of communicative purposes in Jordanian Arabic, including expressing admiration, praise, surprise, politeness, and emotional support. These expressions are idiomatic and culture-bound, functioning as speech acts and forming a specialized register deeply embedded in Jordanian society. The study underscores the religious and sociolinguistic significance of these phrases, highlighting their role in maintaining social harmony and expressing shared cultural values. This research contributes to the understanding of how faith-related language operates pragmatically in Arabic discourse and suggests avenues for further investigation in other Arabic dialects and cross-cultural contexts to broaden insights into religious expressions in communication.

The rapid growth of social media has significantly shaped education, particularly in language learning across Saudi Arabia. This study examines how platforms such as TikTok, Instagram, and X (formerly Twitter) are being integrated into English language teaching. Using a mixed-methods approach, data were collected through surveys from 150 university students, interviews with 10 English instructors, and content analysis of some followed English-learning accounts on these platforms. Findings showed that around 75% of students use TikTok for learning English, mainly to improve vocabulary and pronunciation, while 65% rely on Instagram for similar purposes. Instructors see the potential of these platforms to enhance student engagement but also express concerns about cultural appropriateness, digital distractions, and the lack of institutional support. Content analysis showed that successful educational accounts attract higher engagement when they include interactive features, visually rich content, and culturally relevant topics. Despite these benefits, challenges remain, such as unequal access to devices and limited digital literacy. While some studies have examined social media in education, there is a noticeable gap in research focusing on its practical use in English language instruction within the Saudi Arabian context. In line with Saudi Arabia’s Vision 2030, which prioritizes English proficiency, this study concludes that social media can serve as a useful supplement to traditional language instruction. It also provides recommendations for educators and content creators to better integrate these tools into English education while addressing current limitations.