Exploring the Role of Artificial Intelligence (AI) in Enhancing EFL Education in Saudi Arabia: A Review of Opportunities, Obstacles, and Future Directions

This paper investigates the relationship between gender bias and educational materials for teaching and learning English as a Foreign Language (EFL) in the Saudi EFL context by drawing on critical discourse analysis (CDA). The paper's objective is twofold: first, to explore the extent to which females are biased in the discourse of four EFL textbooks and the various reasons and ways of this biased gender representation. Second, to show the extent to which the disproportion of female gender representation is due to cultural values or to the gender bias of the textbooks’ authors. The study uses a qualitative critical discourse analysis to investigate four EFL textbooks used in Saudi Arabia. The analytical focus is on five topics: (a) gender visibility, (b) gender importance in sequences, (c) gender representation in occupations, (d) gender-attributed traits and (e) the relationship between both genders. Findings reveal that the selected EFL textbooks contain gender-stereotyped scenarios that are in favor of the male gender. Women are portrayed as stereotyped and marginalized as a result of this disparity. The study concludes that the four EFL textbooks used in Saudi Arabian schools displayed gender-biased content and recommends reevaluating the EFL textbooks to be gender-biased-free.

This article introduces the concept of teacher leadership in the Saudi EFL context. Teacher leadership is a commonly used term in the western school contexts which aims to empower teachers by making them part of a decision-making stream and giving them opportunities to exercise leadership and influence colleagues, students and school administrators in a bid to improve instructional practices. As Saudi educational institutions mainly operate in rigid hierarchical structures, teachers in leadership roles have limited or no powers to influence change. Keeping in view the significant role of teacher leaders in organisational effectiveness, this paper highlights the importance of teacher leadership in the English as a Foreign Language (EFL) of a Saudi Arabian university which has a typical top-down management model. It explains the nature of leadership practices in Saudi higher education institutions and how they may hinder the process of teacher leadership in EFL institutes. The paper also suggests ways that can help the top leadership to foster teacher leadership practices in the Saudi EFL context.

In recent years, the use of Artificial Intelligence (AI) in education has had a significant impact on foreign language learning, particularly for English as a Foreign Language (EFL) students in higher education. This paper examines how AI technologies are transforming language proficiency development in Azerbaijani and Indian universities. Utilizing a mixed-methods approach, the study analyses a simulated dataset that includes surveys and interviews with undergraduate and postgraduate EFL learners and educators from selected Azerbaijani and Indian institutions. The findings indicate that AI-driven tools, such as language learning applications, intelligent tutoring systems, speech recognition software,and chatbots, positively influence learner autonomy, vocabulary development, and pronunciation skills. However, the research also highlights challenges such as issues with technology access, disparities in digital literacy, and resistance to new teaching methods. The study is grounded in Vygotsky's Sociocultural Theory and Technological Pedagogical Content Knowledge (TPACK). Results suggest that AI not only improves language skills but also facilitates personalized and adaptive learning experiences, positioning it as a valuable resource in EFL education. The paper concludes with recommendations for AI-integrated strategies aimed at language curriculum developers, educators, and policymakers to enhance proficiency outcomes. This research contributes to the growing conversation about AI in language education and emphasizes the need for ethical and context-aware implementation within India's diverse educational landscape.

This research aims to explore the integration of Artificial Intelligence (AI) in English as a Foreign Language (EFL) teaching within Indonesian Islamic Senior High Schools. Employing a Systematic Literature Review (SLR) methodology, the study synthesizes existing research to identify effective AI applications, challenges faced by educators and students, and the broader implications for educational reform. The findings reveal that AI can significantly enhance EFL instruction through personalized learning experiences, intelligent tutoring systems, and language learning applications, which improve student engagement and language proficiency. However, challenges such as inadequate teacher training, resource limitations, and ethical concerns regarding data privacy must be addressed to ensure successful implementation. The implications of this study highlight the need for a balanced approach that combines AI integration with human interaction in teaching practices. Additionally, it underscores the importance of professional development for educators and equitable access to technology for all students. This research contributes to the growing body of literature on AI in education and provides actionable insights for policymakers and educators seeking to enhance English language teaching in Indonesia's Islamic Senior High Schools. Keywords: Artificial intelligence, EFL teaching, Indonesia, Islamic senior high schools Penelitian ini bertujuan untuk mengeksplorasi integrasi Kecerdasan Buatan (AI) dalam pengajaran Bahasa Inggris sebagai Bahasa Asing (EFL) di Sekolah Menengah Atas Islam di Indonesia. Dengan menggunakan metodologi Tinjauan Literatur Sistematis (SLR), penelitian ini mensintesis penelitian yang sudah ada untuk mengidentifikasi aplikasi AI yang efektif, tantangan yang dihadapi oleh para pendidik dan siswa, dan implikasi yang lebih luas untuk reformasi pendidikan. Temuan tersebut mengungkapkan bahwa AI dapat secara signifikan meningkatkan pengajaran EFL melalui pengalaman belajar yang dipersonalisasi, sistem bimbingan belajar yang cerdas, dan aplikasi pembelajaran bahasa, yang meningkatkan keterlibatan siswa dan kemahiran bahasa. Namun, tantangan seperti pelatihan guru yang tidak memadai, keterbatasan sumber daya, dan masalah etika terkait privasi data harus diatasi untuk memastikan implementasi yang sukses. Implikasi dari penelitian ini menyoroti perlunya pendekatan yang seimbang yang menggabungkan integrasi AI dengan interaksi manusia dalam praktik pengajaran. Selain itu, penelitian ini juga menggarisbawahi pentingnya pengembangan profesionalisme bagi para pendidik dan akses yang adil terhadap teknologi untuk semua siswa. Penelitian ini berkontribusi pada literatur yang berkembang tentang AI dalam pendidikan dan memberikan wawasan yang dapat ditindaklanjuti bagi para pembuat kebijakan dan pendidik yang ingin meningkatkan pengajaran bahasa Inggris di Sekolah Menengah Atas Islam di Indonesia. Kata kunci: Kecerdasan buatan, pengajaran bahasa Inggris, Indonesia, sekolah menengah atas Islam

As part of a larger qualitative case study, this article explores the notion of teacher leadership in English as a Foreign Language (EFL) context and a higher educational institution in Saudi Arabia. Twelve EFL teacher leaders were interviewed to understand their perceptions of teacher leadership practices in the EFL context. Qualitative data were collected through semi-structured interviews and opened-ended questionnaires, and analysed using NVivo10. Data analysis led to 18 main categories and four overarching themes; however, four major categories and one key theme are part of this article that represent the EFL teacher-leaders’ perceptions of their leadership practices and roles at the English Language Institute (ELI). The findings reveal that teacher leadership is a novel concept at the ELI and teacher leaders operate in hierarchical leadership structures. However, their wide range of leadership roles, both instructional and operational match with the three historical waves of teacher leadership (Silva, Gimbert & Nolan, 2000) in the US context. The impact of hierarchical structures on teacher leadership practices is evidently found as EFL teacher leaders encounter various difficulties, such as heavy administrative workload and lack of autonomy. Nevertheless, their shared leadership practices within the groups help them deal with these challenges.

The aim of this paper is to explore the challenges to, and benefits of, fostering of critical thinking (CT) in the Saudi EFL (English as a foreign language) context. In the next section, the concept of CT will be clarified. In the following two sections, possible challenges or barriers to CT, whether religious or pedagogical, in the Saudi context are analyzed and refuted. After discussing the religious and the educational background of this issue, practices for promoting CT inside EFL classrooms are described. Finally, the benefits of incorporating CT strategies into language learning are outlined.

Artificial intelligence (AI) rapidly transforms education, offering adaptive and personalized learning experiences. In English as a Foreign Language (EFL) education, AI-powered tools such as chatbots, writing assistants, and translation software reshape teaching and learning. This study explores how 67 prospective EFL teachers envision the future role of AI in EFL instruction, examining its potential benefits and challenges. Using a descriptive qualitative approach and reflexive thematic analysis, the study identifies 6 themes and 52 nodes addressing the risk of AI replacing teachers and 5 themes with 31 nodes regarding AI’s future impact on EFL teaching and learning. Findings suggest a preference for a human-centered AI approach—AI-assisted EFL teaching and learning (AIaEFLtl)—where AI complements rather than replaces teachers. The study highlights key implications for AI-EFL teacher collaboration, advocating for teacher training in AI integration and ethical considerations. These insights contribute to the ongoing discourse on the evolving role of AI in education and its pedagogical implications for future EFL classrooms.

This small scale, quantitatively based, research study aimed at exploring one of the most debated areas in the field of Teaching English to Speakers of Other Languages (TESOL); and that is, the perceptions and attitudes of English as a Foreign Language (EFL) teachers as well as EFL learners at an English Language Institute (ELI) at a major university in the Western region of Saudi Arabia, King Abdulaziz University, towards second language writing assessment. The research study involved, randomly selected twenty-two EFL teachers and seventy-eight EFL students between the period of September 2016 and December 2016. Two, purposefully designed, twenty-item, Likert scale questionnaires were distributed amongst the teachers and students. One for the participating EFL teachers and one for the participating EFL students. Data analysis using descriptive statistical methods indicated several concerns which EFL teachers and students have with regards to the writing assessment in general and to the obstacles EFL teachers face when teaching and assessing writing. In addition, there was an indication of general resentments and strong feelings amongst the EFL students where the majority indicated that they are sometimes graded unfairly and writing assessment should take another, more holistic approach rather a narrow one. The study makes recommendations for future research.

This research aims to evaluate the possible positive aspects of Artificial Intelligence (AI) technologies in English language teaching that occur when training learners of English as a Foreign Language (EFL) or English as a Second Language (ESL). The study seeks to understand how AI technology and methodologies enhance language learning and teaching, including the unique possibilities that arise when considering learners and educators with an evolving role in increasingly larger education systems and educational environments. It seeks to understand the potential of AI for personalizing English language training. Also, by asking the question study, if there are methods including Natural Language Processing (NLP), Machine Learning (ML), and AI-based analytics or tools, can they personalize learning experiences for EFL-ESL learners? A qualitative study was completed through interviews with learners from different experience levels engaged in EFL or ESL programs that used AI-based tools in the pedagogy. The results demonstrate that AI has positive opportunities for personalized language education in the EFL and ESL contexts, the ability to enhance language skills in specific domains, and offer customized language learning experiences. This research has indicated challenges that surround cultural elements, technical challenges, and distinctly human teaching and learning elements. The research also offers helpful information for English language learning and recognizes the shifting nature of personal learning experience whether enhanced through AI, the practical requirement of incorporating AI will also provide a unique lens and perspective in English language learning and teaching, recognize the affordances AI can offer, alongside students and language learning never being exclusively cultural or human.

The article is devoted to the history of the development of Information and Communication Technologies (ICT) and Artificial Intelligence (AI), their current and probable future achievements, and the problems (which have already arisen, but will become even more acute in the future) associated with the development of these technologies and their active introduction in society. The close connection between the development of AI and cognitive science, the penetration of ICT and AI into various fields, in particular the field of health care, is shown. A significant part of the article is devoted to the analysis of the concept of ‘artificial intelligence’, including the definition of generative AI. We analyze recent achievements in the field of Artificial Intelligence, describe the basic models, in particular the Large Linguistic Models (LLM), and forecast the development of AI and the dangers that await us in the coming decades. We identify the forces behind the aspiration to create artificial intelligence, which is increasingly approaching the capabilities of the so-called general/universal AI, and also suggest desirable measures to limit and channel the development of artificial intelligence. The authors emphasize that the threats and dangers of the development of ICT and AI are particularly aggravated by the monopolization of their development by the state, intelligence services, large corporations and those often referred to as globalists. The article forecasts the development of computers, ICT and AI in the coming decades, and also shows the changes in society that will be associated with them. The study consists of two articles. The first, presented below, provides a brief historical overview and characterizes the current situation in the field of ICT and AI, it also analyzes the concepts of artificial intelligence, including generative AI, changes in the understanding of AI related to the emergence of the so-called large language models and related new types of AI programs (ChatGPT). The article discusses the serious problems and dangers associated with the rapid and uncontrolled development of artificial intelligence. The second article, to be published in the next issue of the journal, describes and comments on current assessments of breakthroughs in the field of AI, analyzes various forecasts, and the authors give their own assessments and forecasts of future developments. Particular attention is given to the problems and dangers associated with the rapid and uncontrolled development of AI, the fact that achievements in the field of AI are becoming a powerful means of controlling the population, imposing ideology and choice, influencing the results of elections, and a weapon for undermining security and geopolitical struggle.

Teachers’ beliefs play a key role in their selection of language teaching methodologies; they affect teachers’ pedagogical practices and behaviours and are consequently integral in shaping the language learning classroom environment. This study investigated the beliefs of teachers of English as a foreign language (EFL) in relation to the concept of ‘language socialisation’ (LS) and its pedagogical application through the use of social networking technologies (SNTs) in a Saudi university language learning context. Data comprised a survey, which was administered to a total of 28 EFL teachers, of whom five male instructors were interviewed. Findings showed that the majority of teachers reported positive associations with LS as a teaching method, as well as positive responses towards the use of SNTs in the EFL classroom despite the fact that most participants had never used SNTs in their teaching. It can be concluded that, while the EFL teachers in this study acknowledged the potentially important role that SNTs could play in enhancing students’ language learning and socialisation, their lack of first-hand classroom experience with SNTs reflected the fact that there was little access to and training in the use of these technologies. This lack of provision needs to be addressed as a matter of urgency to ensure that Saudi EFL teachers and their students are given an opportunity to engage critically with innovative technologies that may enhance the quality of their pedagogical experiences.
 Keywords: English as foreign language teachers in higher education in Saudi Arabia, English as a foreign language, language socialisation, social networking technologies

Teacher boredom is a significant yet underexplored issue in English as a Foreign Language (EFL) classrooms in Saudi Arabia, often intertwined with student disengagement, particularly in the context of dual teaching modalities: offline and online. This qualitative study aimed to investigate the factors contributing to teacher boredom, the strategies employed to mitigate it, and the interrelationship between teacher and student boredom in both teaching environments. Seventy one EFL teachers from diverse backgrounds participated in the study, completing an open-ended questionnaire. Thematic analysis revealed that monotonous routines, technological challenges, and student disengagement were the primary factors contributing to teacher boredom. Teachers employed various coping strategies, including interactive activities, multimedia tools, and humour, to address these challenges. However, the effectiveness of these strategies varied between offline and online settings. In offline classrooms, teachers relied on direct interaction and relational pedagogical methods, while online environments necessitated the use of technological and multimedia resources. The findings also revealed a cyclical relationship between teacher and student boredom, showing the need for targeted interventions that address the needs of both groups. This study contributes to a nuanced understanding of teacher boredom in the Saudi EFL context and provides practical insights for fostering engagement in diverse teaching modalities. The findings call for professional development, curriculum flexibility, and stronger technological infrastructure to support effective teaching.

In Saudi Arabia’s increasingly bilingual academic environment, Arabic-English code-switching has become a common phenomenon, especially among university students. This study investigates the translation dynamics of such code-switched texts, comparing the performance of Artificial Intelligence (AI), represented by ChatGPT 4, and English as a Foreign Language (EFL) university students at Imam Mohammed Ibn Saud Islamic University. Despite technological advancements, there remains a gap in understanding how both AI and EFL students handle the cultural and contextual complexity of bilingual communication. The study aims to evaluate the accuracy, fluency and contextual appropriateness of translations produced by both AI and EFL students, identifying translation challenges and strategies employed. Grounded in Koehn’s (2010) Statistical Machine Translation (SMT) model, this qualitative study engaged ten purposively selected EFL students. Participants collaboratively translated ten validated Arabic-English code-switched texts and were later interviewed to reflect on their translation experiences. These translations were compared to AI-generated outputs through qualitative textual analysis and thematic coding. The findings revealed that while AI produced fluent and grammatically accurate translations, it often failed to interpret cultural references, emotional tone and idiomatic expressions. In contrast, EFL students demonstrated greater flexibility, cultural mediation and pragmatic sensitivity. The study recommends enhancing AI systems with contextual-awareness capabilities and integrating AI tools into EFL translation pedagogy for guided post-editing. It also calls for training programs to prioritize cultural competence alongside linguistic skills. These findings have implications for the development of more adaptive translation technologies and enriched translator education in bilingual settings.

The increasing prevalence of Artificial Intelligence (AI) in higher education underscores the necessity to explore its implications on ethical, social, and educational dynamics within the sector. This study aims to comprehensively investigate the impact of AI on higher education in Saudi Arabia, delving into stakeholders’ attitudes, perceptions, and expectations regarding its implementation. The research hones in on key facets of AI in higher education, encompassing its influence on teaching and learning, ethical and social implications, and the anticipated role of AI in the future. Employing a quantitative approach through an online survey questionnaire (N = 1113), this study reveals positive attitudes toward AI in higher education. Stakeholders recognize its potential to enhance teaching and learning, streamline administration, and foster innovation. Emphasis is placed on ethical considerations and guidelines for AI implementation, highlighting the imperative need to address issues such as privacy, security, and bias. Participants envision a future characterized by personalized learning experiences, ethically integrated AI, collaboration, and ongoing support for lifelong learning. Furthermore, the results illuminate the intricate interplay between AI usage, purposes, difficulties, and their impact on attitudes, perceptions, and future implications. Accordingly, the research underscores the necessity for a comprehensive understanding of AI integration, considering not only its technical aspects but also the ethical, social, and educational dimensions. By acknowledging the role of AI uses, AI usage purposes, and addressing associated difficulties, educational stakeholders can work towards harnessing the benefits of AI while ensuring responsible and effective implementation in teaching and learning contexts.

Exploring EFL Teacherss Beliefs and Practices Regarding Pronunciation Teaching in a Saudi Setting