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.

This study focuses on the employment of AI technology in regular, day-to-day activities, such as when Google Translate or Bing Translator are encouraged alongside various programs and applications. It also evaluates and empirically demonstrates the subjects of writing with AI technologies, computer-assisted language learning (CALL), machine translation (MT), and automatic evaluation systems (AESs) in order to offer solutions for enhanced communication training in Saudi Arabia's EFL system. Word tune is an artificial intelligence (AI)-driven writing assistant that can understand the writer's ideas and suggest alternative rewrites (e.g., shorten, expand). This program assists writers of English as a foreign language to maintain a steady flow and acquire useful English expressions. This research made use of questionnaires as a method for collecting data and then ran those responses through SPSS for analysis. The use of artificial intelligence (AI) technology in English as a foreign language (EFL) settings has been shown to facilitate the English language learning (ELT) process and to keep both teachers and students up to date on recent technological developments. This exploratory investigation demonstrated that all digital and AI-powered devices have the potential to assist in teaching and learning. Consequently, the pedagogical component of future education can be developed using an AI framework.

Self-assessment and reflective thinking (RT) can arm learners to monitor and evaluate their learning progress. Despite the long history of the core of self-assessment (CSA) and RT, little is known about how they may contribute to learner enjoyment (LE) and learner immunity (LI). Therefore, the current research attempted to propose a model to depict the interplay among CSA, RT, LE, and LI. To this end, the Core of Self-Assessment Questionnaire (CSAQ), Reflective Thinking Questionnaire (RTQ), Foreign Language Enjoyment Scale (FLES), and Language Student Immunity Instrument (LSIS) were administered to 518 Iranian EFL university students. The results of confirmatory factor analysis (CFA) and structural equation modeling (SEM) indicated that EFL university students with higher levels of CSA and RT skills experienced more enjoyment and were immunized productively. Furthermore, the critical role of RT in CSA was discovered. The implications of this study may unveil new prospects for implementing learning-oriented assessment in the classroom and RT practices in educational programs.

Utilizing artificial intelligence (AI) technology in educational institutions for students with mild intellectual disabilities offers promising avenues for enhancing this population’s learning outcomes and skill development. This study aims to investigate the effect of using generative conversational AI to improve English communication skills among students with mild intellectual disabilities. The study involved twelve students diagnosed with mild intellectual disabilities, divided equally into two groups. Six students engaged in guided conversations with AI, while the other six participated in free conversations with AI. These participants were randomly chosen from educational institutions specializing in intellectual disability education and mainstream schools. The results indicate that guided conversations significantly enhance English communication skills among participants. Additionally, the study highlights the development gains from engaging in guided conversations by AI applications. Statistical analysis reveals notable differences in the effect of guided versus free conversational approaches, with guided conversations yielding superior outcomes. This underscores the importance of structured guidance for comprehension and participation in different English communication skills among students with mild intellectual disabilities. Moreover, the study recommends the integration of AI tools in education to support students with disabilities, emphasizing the need for tailored AI applications to cater to diverse learning needs.

As artificial intelligence (AI) technologies are increasingly being adopted in educational contexts, it is essential to understand how key stakeholders perceive opportunities and challenges for responsible integration. This mixed-methods study explored EFL teachers' perspectives on utilizing AI tools for instruction, learning activities, and assessment. An online survey collected both quantitative and qualitative data from 150 EFL teachers regarding their experiences, attitudes, and beliefs about AI's pedagogical role and ethical considerations. Descriptive statistics revealed generally positive views of AI's potential for personalized learning and practice opportunities, though ongoing concerns around risks to human interaction, privacy, and bias. Teachers favored collaborative models, with AI playing a supporting role under educator oversight. Significant gaps in teachers' technical literacy and lack of training or support for integration emerged as barriers requiring attention. While potential applications for standardized assessment were acknowledged, ongoing validation of AI models against human judgment was deemed necessary. Qualitative analysis identified uncertainty around AI's impacts on higher-order skill development and communicative competence. Guidelines delineating appropriate roles and oversight frameworks were seen as imperative to ensure aligned, ethical usage maximizing opportunities. This study provides timely empirical insights to inform the development of policies, tools, programs, and practices facilitating the judicious adoption of AI as a partner in strengthening EFL education worldwide through collaborative human-AI partnerships grounded in evidence-based research.

English as a foreign language (EFL) instruction places special emphasis on students' active participation in class discussions. EFL learners encounter obstacles which prevent them from oral participation in the classroom. The purpose of this research is to discover why EFL students are not more engaged in class, as well as recognizing factors that impede students’ class engagement. Moreover, the study aims at casting the light on the Techniques and Strategies for Enhancing Students Participation. Data was gathered through an interview in this descriptive-analytical study and analyzed using SPSS. The samples of the study consist of forty EFL professors from two Saudi universities. Findings from the study urged educators to help their students form positive self and social perceptions. Better class participation can be achieved through good rapport and the enhancement of the targeted teaching practices. The study concludes that EFL students are often disinclined to be engaged in oral class participation due to a mélange of a poorly managed classroom, language anxiety, and lack of vocabulary.