This study explored the relationship between Chinese graduate students’ English language proficiency (ELP) and intercultural communicative competence (ICC). With the acceleration of globalization, an increasing number of Chinese students choose to study abroad, making it crucial to enhance their intercultural communication ability and language skills. However, China’s exam-oriented education system to some extent limits students’ holistic development and poses challenges for them in intercultural exchange. A quantitative survey method was employed, collecting questionnaire data from 249 Chinese English-major graduate students to analyze the relationship between their English ability and intercultural competence. The results indicated a certain positive correlation between English proficiency and intercultural competence but also pointed to the need for further unpacking of complexity and influencing factors. Future research with more robust methodology is still warranted to provide deeper insights into the linkage between the two constructs in the Chinese graduate context.

The study investigates the role of foreign language enjoyment (FLE) and engagement in the context of English language learning among Chinese students, emphasizing the significance of positive emotions in enhancing academic success. Utilizing a sample of 249 students majoring in international trade, the research employs the foreign language enjoyment scale to count their enjoyment level and foreign language engagement scale to assess various dimensions of student engagement, including cognitive, emotional, behavioral, and social engagement. By conducting regression analysis, the findings reveal that FLE positively influencing learners’ learning outcome while engagement doesn’t pose significant impact on their learning outcome. The study highlights the importance of fostering positive emotions in educational settings to improve language learning outcomes and suggests that understanding the interplay between FLE and other affective factors can lead to more effective teaching strategies in foreign language education. 

Shared education has the potential to foster pluralistic values and improve relations between individuals from diverse ethno-linguistic backgrounds. This study aims to contribute to the understanding of how shared learning experiences can promote pluralism and social equality by examining the pedagogical factors that influence their success. This study focuses on a shared English learning model implemented with 8th-grade Arab and Jewish students in homogenous Israeli cities. This qualitative study, involving observations, interviews, focus groups, and transcript analysis, engaged 42 students, two teachers, and two administrators. The findings suggest that shared education has positive social implications. It facilitated interaction between Arab and Jewish students and challenged negative stereotypes. Notably, the Jewish students’ limited Arabic language proficiency led to complex interactions, stimulating critical thinking about linguistic inequality and increasing motivation to learn Arabic. While shared education improved intergroup relations, it also encountered logistical challenges that necessitated institutional support to optimize its effectiveness.

Arabic rhetoric has traditionally relied on ancient texts and human interpretation for teaching purposes. The study investigates ChatGPT’s ability to analyze and interpret Arabic rhetorical devices, specifically examining its capacity to handle cultural and contextual elements in rhetorical analysis. Drawing on institutional implementation frameworks and recent educational technology research, this study examines policy considerations for Arabic rhetoric education in an AI-driven environment, with a particular focus on sustainable digital infrastructure development and systematic reforms needed to support AI integration. The study employed the comparative approach to analyze eight rhetorical examples, including metaphors (“Zaid is a lion”), similes (“Someone is a sea”), and metonymy (“A person full of ash”), then compare ChatGPT’s interpretations with traditional explanations from classical Arabic rhetoric texts, particularly “Dala’il al-I’jaaz” by al-Jurjani. The results demonstrate that ChatGPT can provide basic interpretations of simple rhetorical devices, but it struggles with understanding cultural contexts and multiple layers of meaning inherent in Arabic rhetoric. The findings indicate that AI tools, despite their potential for modernizing rhetoric education, currently serve best as supplementary teaching aids rather than replacements for traditional interpretative methods in Arabic rhetoric instruction.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.