Exploring generative AI use in EFL student writing through classroom observation and interviews
Amira Sid1
The rapid development of generative artificial intelligence (AI) has created new challenges for English as a Foreign Language (EFL) writing instruction and assessment. This study explores how AI writing tools may influence students' writing practices, confidence, and understanding of authorship. The study emerged from the researcher's classroom observations while teaching Written Expression to second-year EFL students at Mohamed Chérif Messaadia University, Souk Ahras, Algeria. During argumentative writing activities, differences were observed between students who appeared to rely mainly on classroom-taught writing procedures and students whose writing raised questions about possible AI assistance. In particular, some students showed strong adherence to the structure taught in class despite grammatical and spelling errors, while other writing appeared more linguistically polished but did not consistently follow the required structure. To explore these observations further, the study adopts a qualitative classroom-based design combining teacher observation with semi-structured interviews with six students. The study focuses on students' experiences with AI writing tools, their reasons for using or avoiding them, their confidence in writing, and their views of authorship. The study aims to contribute to current discussions of AI in EFL writing by considering not only the quality of the final written product but also students' engagement with the writing process and the structures taught in class.
Opportunities, challenges and the evolving role of the teacher
Milica M. Kočović Pajević1
Artificial intelligence is rapidly reshaping educational practice: it is no longer just a source of information for teachers, it is becoming an active participant in how teaching materials get designed and complemented. This shift is especially visible in English for Specific Purposes (ESP), where materials must respond to learners' professional needs and disciplinary contexts. Generative AI tools now enable teachers to create customized texts, communicative tasks, case studies, and assessment activities with unprecedented speed and flexibility, thus effectively turning AI into a kind of collaborative partner in instructional design rather than a threat to the teacher's job. However, the increasing use of AI-generated materials also raises important questions regarding their pedagogical quality, linguistic accuracy, contextual relevance, ethical use, and reliability. This paper examines the opportunities and challenges associated with AI as a co-designer of ESP learning materials. Drawing on research in ESP materials development, textbook evaluation, and the growing literature on generative AI in education, it considers how AI can support lesson planning and the creation of workplace communication tasks informed by authentic professional practices, without losing sight of why teacher judgment still matters in evaluating and adapting what AI produces. The paper argues that effective integration of AI into ESP teaching depends not only on technological competence but also on teachers' pedagogical judgment and AI literacy. Rather than reducing the teacher's role, AI expands professional responsibilities by requiring educators to critically evaluate, refine, and ethically implement AI-generated materials. The paper concludes by proposing key principles for the responsible use of AI in ESP materials design and discusses implications for teacher education, institutional policy, and future research.
A pilot framework using local LLM-as-judge evaluation
Edgar Eduardo Ceh-Varela1; Yitzen Mayitza Lizama-Peraza2; Sarbagya Ratna Shakya1
This work presents an ongoing pilot design-based project that explores the use of AI-generated personas for the development and evaluation of ESL/EFL instructional materials. Inspired by multiperspectivity approaches in humanities education, the project adapts the concept of multiple perspectives to foreign language learning by generating different versions of the same English text through distinct linguistic and communicative personas, including academic, informal, persuasive, simplified learner-oriented, and culturally sensitive variants. The framework is intended to support awareness of how register, tone, vocabulary choice, perspective, and communicative intent influence meaning construction in English discourse. The project also investigates the feasibility of using locally deployed large language models (LLMs) as preliminary evaluators of AI-generated educational materials while maintaining human oversight in pedagogical decision-making. Using Ollama as a local deployment environment, the proposed framework incorporates an LLM-as-judge evaluation pipeline in which generated outputs are assessed according to a shared rubric covering register appropriateness, CEFR-level suitability, clarity, pedagogical usefulness, and visibility of perspective-related linguistic features. A subset of outputs will additionally be reviewed by a human ESL/EFL expert to provide comparative validation. Rather than reporting the results of a classroom intervention, the paper presents a scalable and low-cost methodological framework for the preliminary development and evaluation of AI-assisted ESL/EFL learning materials. The discussion focuses on the project's design rationale, evaluation methodology, and the potential benefits and limitations of combining AI-generated instructional content with automated evaluation systems in language education.
EFL students' perceptions of AI writing assistants and the risk of academic dependence
Djouadi Djawhara1; Kerroum Fathia2
The rapid integration of artificial intelligence tools into higher education has fundamentally reshaped how students approach academic writing. While AI writing assistants offer substantial support in terms of grammar correction, text generation, and structural guidance, growing concerns have emerged regarding their potential to foster dependency rather than competence. This study investigates the perceptions of Algerian EFL university students toward AI-assisted academic writing, with a particular focus on the tension between productive scaffolding and passive reliance. Drawing on questionnaire data collected from 57 undergraduate students, the study explores the frequency and nature of AI tool use, students' self-reported awareness of dependency risks, and the implications for academic integrity and autonomous writing development. The findings reveal a paradox characteristic of AI-mediated learning: students acknowledge the cognitive convenience of AI tools while simultaneously recognising their undermining effect on independent writing skills. These results are discussed within the framework of Vygotsky's Zone of Proximal Development and critical digital pedagogy, offering practical recommendations for educators seeking to integrate AI tools responsibly. The study contributes to an emerging body of research on ethical AI use in EFL contexts across the Global South.
Mohammed Fouad Rebiai1; Mouna Fethiza Tedjani2
The emergence of generative artificial intelligence (AI) tools and their evolving integration into education has reshaped the vision of language learning. AI chatbots such as ChatGpt have been seen as facilitating tools that boost the learning process as they provide learners with immediate access to explanations, feedbacks, demonstrations, and communication opportunities. While the primary focus of previous investigations on AI and language learning have been highlighting its role with teaching grammar, vocabulary, and speaking and writing skills, its potential impact on learners' pragmatic competence remains underexplored. Pragmatic competence that centers on language in context emphasizes both its appropriate use and interpretation, and it has traditionally been requiring human guidance and cultural awareness. This study investigates Algerian EFL teachers' perceptions of the contribution of AI tools in pragmatic instruction and explores the potential influence of these digital tools on teachers' professional identity. In addition, this research examines whether EFL teachers perceive AI as a supportive tool or as a threat to their position in improving students' pragmatic competence. A perception-oriented qualitative design will be adopted for this investigation. Semi-structured interviews with Algerian EFL teachers from different higher education institutions will be conducted to collect the research data, which will then be analyzed thematically. The anticipated findings suggest that participants will consider the effectiveness of AI tools in developing students' pragmatic competence through providing relevant examples and interactive scenarios while still emphasizing the role of educators in contextualizing meanings, illuminating sociocultural norms, and explaining speakers' implied intentions. This study is also expected to shed light on the impact of emerging AI tools on reshaping teacher identity beyond mere pedagogical expertise. The findings may contribute not only to teacher preparation in the digital era, but also to current debates on the ethical integration of AI into academia.
A survey-based study of Algerian university learners' practices and experiences
Aggoune Amina1; Bennacer Fouzia1
The widespread integration of digital technologies in education has reshaped English as a Foreign Language (EFL) language learning. ChatGPT has emerged as one of the most widely adopted application, due to its ability to offer immediate feedback, facilitate communication, and assist learners in their learning process. Regardless of its popularity, research remains restricted concerning the outcomes of ChatGPT on learners engagement and learning experiences in EFL contexts. Therefore, the current study aims to explore the role of ChatGPT on Algerian university learners' participation and overall learning experience at the university level. It focuses on how learners interact with ChatGPT and how this interaction may support their participation, motivation, and learning process. In response to this, the present study adopts a quantitative survey-based design involving EFL university learners in Algeria who have previous experience using ChatGPT for learning English. In addition to this, Data are collected through an online structured questionnaire based on a 5-point Likert scale to measure two main variables: learners' engagement and learning experience. The study employs descriptive and inferential statistical techniques, including means, standard deviations, correlation analysis, and regression analysis, to examine the relationships between the uses of ChatGPT, engagement, and learning experience. The findings indicate a positive relationship between learners' use of ChatGPT and their participation, motivation and learning experience. These findings also suggest that AI-assisted language learning environments can create more flexible and interactive opportunities for learning beyond the traditional classroom. Moreover, it is recommended that optimizing the integration of ChatGPT and other AI tools in education requires leveraging their opportunities while systematically addressing associated challenges. Such effective integration has the potential to advance AI-assisted language learning and enhance the overall quality of language learning.
Algorithmic mediation and compulsory language self-rescue among adult Algerian learners in CNEFD distance education
Leila Aouam1; Leila Benstaali1
Adult basic education across the Global South typically excludes foreign languages. In Algeria, the Office National de l'Alphabétisation (ONEA) delivers this education exclusively in Arabic; however, graduates entering the Centre National de l'Enseignement à Distance (CNEFD) face a concealed structural contradiction: French and English are compulsory examination subjects, despite learners having no prior foreign language instruction. This qualitative study investigates this institutional barrier, introducing the concept of compulsory language self-rescue—a condition where digitally marginalized adult learners must construct improvised, invisible learning ecologies to survive systemic exclusion. While research addresses distance learning efficacy, empirical gaps remain regarding how Arabic-medium CNEFD enrollees navigate these mandatory foreign language demands. This study examines their autonomous strategies, specifically focusing on algorithmic mediation via translation tools alongside peer networks and pattern memorization. Employing Interpretative Phenomenological Analysis (IPA) and the Critical Incident Technique (CIT), the study explores the lived experiences of 30 purposively sampled ONEA graduates across Algeria, encompassing both examination passers and dropouts. Data collected through semi-structured interviews map educational trajectories, examination preparation rituals, and decisive crises where institutional absence intersects with algorithmic survival tools. The findings expose the concealed costs of linguistic exclusion, demonstrating that self-directed and resilient behaviors emerge from structural necessity rather than pedagogical preference. Practically, the study reveals that basic literacy credentials function as a trap disguised as opportunity, offering direct implications for ONEA curriculum reform, CNEFD policy, and broader ethical dialogues surrounding algorithmic dependency in marginalized educational settings.
Opportunities, limitations, and learner perceptions
Mohammed Suhail Banqusly1
As more human interaction is exploding with AI machines, a humongous gate has opened for second language (L2) speaking practice, yet the pedagogical realities of implementing AI chatbots in actual classrooms remain underexplored. This case study investigates the integration of a customized AI chatbot into spoken English instruction for 82 male elementary and intermediate learners at a Syrian university. Drawing on Jeremy Harmer's (2015) pedagogical framework for speaking instruction and contemporary second language acquisition theory, the study examines both learner outcomes and pedagogical implications of AI chatbot use over an eight-week period. As the classroom teacher, I implemented random AI chatbots as a supplementary speaking practice tool, observing and documenting learner engagement, progress, and challenges. Findings reveal a rough 30% overall improvement in speaking proficiency, with a clear distinction between learner levels: intermediate students demonstrated some gains, communicating effectively with the AI chatbot and benefiting from independent practice. However, elementary students struggled significantly to communicate with the AI chatbot, requiring extensive teacher guidance and mediation to benefit from the tool. The study proposes pedagogical guidelines for responsible AI integration, emphasizing differentiated approaches based on proficiency level, structured teacher mediation for lower-level learners, and the complementary roles of AI and human instruction. Ethical considerations including data security and the risk of replacing rather than augmenting human instruction are addressed. The study concludes with practical recommendations for language educators seeking to integrate AI chatbots into their teaching practice.
A blessing or a curse?
Belmekki Asma1
Artificial intelligence is rapidly changing the way English as a Foreign Language is taught and learned in university classrooms. In Algeria, this change has created both opportunities and serious concerns. This study explores Algerian EFL university teachers' real views, experiences, and challenges regarding the use of AI in their classrooms. It particularly investigates whether AI is perceived as a blessing that supports teaching and learning, or as a curse that weakens students' autonomy, creativity, and effort. The study adopted a descriptive research design. Data were collected through a web-based questionnaire sent via email to EFL university teachers from different Algerian universities. Forty (40) teachers voluntarily responded to the questionnaire. The findings show that teachers view AI as an inevitable part of higher education, but they are concerned about students' overreliance on it and its negative effect on autonomy, creativity, effort, and critical thinking. The study concludes that AI is not harmful in itself, but its uncontrolled use may negatively affect EFL learning. Therefore, Algerian universities need clear guidelines to promote responsible, balanced, and critical AI use in EFL classrooms.
A focus on Algerian EFL students at Mostaganem university.
Belmokhtar Kheira1
Artificial Intelligence (AI) has inevitably become an essential criterion in English language learning, offering a myriad of tools that support students in developing their language skills. These tools, such as grammar checkers, translation systems, writing assistants, and vocabulary applications, are increasingly used by English as a Foreign Language (EFL) learners to enhance their academic performance. Although AI has become increasingly embedded in educational settings, limited research has examined how Algerian EFL students use these tools and perceive their effectiveness. This study investigates Algerian EFL students' attitudes towards the integration of AI in English language learning at Mostaganem university. Specifically, it explores the frequency of AI use, the language skills students seek to improve via AI tools, and their level of trust in AI-generated academic content. This study draws on a quantitative descriptive approach, using an online questionnaire administered to Licence and Master students in the English Department. The findings reveal a generally positive attitude toward the integration of AI in English language learning. AI tools are primarily utilized to support writing, grammar correction, translation, and vocabulary acquisition, reflecting their growing role in students' academic practices. Learners acknowledge the usefulness of AI in enhancing language performance and facilitating learning processes. Nevertheless, trust in AI-generated content is not unconditional; concerns regarding reliability, accuracy, and excessive dependence on technology continue to shape students' perceptions. The study contributes to the growing body of research on AI in EFL education by providing insights into the experiences of Algerian university students and offering recommendations for the effective and responsible use of AI technologies in higher education.
A study of student perceptions at the university of Oujda
Garti Rihab1; Jmad Sabrine2; Zizaoui Ikram3; Eddal Imane1
Moroccan higher education is rapidly transforming due to the development of technologies such as artificial intelligence, this technology which offers next opportunities to the field of language learning. However, the effect of this technology regarding oral communicative competency remains under-researched. The present study's aim is to investigate students' perceptions regarding AI's capacity to develop their communicative competencies. A quantitative design is employed, data is collected via an online questionnaire administered by 135 students. The Technology Acceptance Model (TAM) is used to assess adoption, and the CEFR guided the analysis of oral competency components.The findings revealed a positive perception of AI. Students mainly perceive AI as a collaborative tool to improve their oral communicative competency. The study concludes that AI is considered as a compagnon in the process of learning languages, not just as an optional tool.
A critical analysis of task vulnerability in the New Prospects textbook in the age of generative AI
Abdelali Berriche1
The arrival of Generative Artificial Intelligence (GenAI) poses a radical challenge to the pedagogical design of traditional English as a Foreign Language (EFL) textbook. This paper argues that GenAI induces a "Calculator Moment" in EFL, collapsing the necessary "productive friction" for language acquisition. The results of the study suggest that traditional EFL textbook tasks, especially those that focus on lower-order thinking skills, are highly susceptible to AI replacement. A detailed checklist was used to analyse all the six units of the Algerian Third Year Secondary textbook, New Prospects. This checklist is based on an extended theoretical model of Krashen's Input Hypothesis (i+1), Bloom's Revised Taxonomy and Vygotsky's Zone of Proximal Development. Results indicate questions aimed at Remembering, Understanding and Applying are highly susceptible to AI, reducing the i+1 gap to an unproductive i+0. This analysis provides empirical support for the need for a curriculum migration towards higher order cognitive tasks that require human agency, critical evaluation and contextualized communication, and, in so doing, makes the teacher into a designer of necessary productive friction.
A comparative study of traditional and technology-assisted learning preferences among Indian school students
Naveen Tokas1; Dhruv Kumar2; Aakriti Sahay2; Fahran Ali Khan2
In today's era, Artificial Intelligence and digital technologies are reshaping learning preferences in language education, particularly among Generation Z students. This study explores the comparative perspectives of Indian school students regarding technology-assisted foreign language learning and traditional classroom-based learning in the contemporary educational environment. The research focuses on students' learning preferences, engagement, and perceptions towards foreign language learning in schools.The study was conducted by Grade VIII and IX students, student-led research initiative, under the supervision of a guide, using an online survey questionnaire as a research tool. The survey was distributed to students from different regions of India. More than 2,000 responses were collected and analyzed using percentage analysis, frequency distribution, and graphical representation. The findings reveal that although Gen Z learners are growing up in the age of artificial intelligence, traditional methods of foreign language learning continue to have a significant impact on their learning experiences by improving understanding, interaction, and learner engagement. The responses further indicate a strong interest in learning foreign languages in India, such as French, Italian, and German, despite ongoing policy changes regarding foreign language education in Indian schools. The study highlights the importance of balancing traditional pedagogical practices with technology-assisted learning approaches in foreign language education. It also demonstrates the broader transformation of foreign language learning within AI-supported educational environments. The research contributes to current discussions on Gen Z learners, educational technology, and the evolving future of language education among school students. IndexTerms -Gen Z, Foreign Language Learning, Artificial Intelligence, Technology-Assisted Learning, Digital Education.
Purposes, benefits, and challenges
Ouadjeri Akila1
This study investigates EFL university students' use and perceptions of Generative Artificial Intelligence (GenAI) tools in English language learning contexts, focusing on their purposes of use, perceived benefits, and associated challenges. The study was conducted among students at the University Center of Barika, Algeria, using a quantitative descriptive research design. Data were collected through an adapted questionnaire based on the study of Almassaad, Alajlan, and Alebaikan (2024), which explored students' perceptions of generative AI technologies in higher education. The questionnaire examines students' awareness and familiarity with GenAI tools, the frequency of their use in English language learning, and the reasons behind either using or avoiding these technologies. It also identifies commonly used GenAI applications, including ChatGPT, Gemini, Copilot, and QuillBot. Furthermore, the study explores educational purposes for using GenAI tools, such as translation, concept clarification, literature search, summarization, idea generation, proofreading, assignment completion, project work, and multimedia presentation creation. The study also investigates students' perceptions of the benefits of GenAI tools, including ease of access, time efficiency, instant feedback, improved language proficiency, enhanced academic performance, increased learning engagement, and learner confidence. In addition, it addresses challenges associated with GenAI use, such as internet dependence, subscription costs, privacy and data security risks, unreliable information, reduced learning autonomy, decreased human interaction, plagiarism, cheating, and potential negative effects on learning. The study aims to provide an understanding of how GenAI tools are transforming English language learning experiences in higher education while highlighting pedagogical opportunities and ethical concerns related to their integration in EFL contexts.
ChatGPT between educational support and critical dependence in higher education
Wafia Tihal1
Fast development of artificial intelligence (AI) has revolutionized higher education. ChatGPT is among a number of AI technologies that are currently being extensively used for offering explanations, summaries, and aiding in writing (Kasneci et al., 2023; Lo, 2023). This study is motivated by an observed incident during a university graduation ceremony in Algeria, where a student wrote "ChatGPT" on her graduation cap. This symbolic gesture was interpreted differently by instructors. Some teachers viewed it as an implicit provocation or even an offence, suggesting that students were attributing their academic work, projects, assignments, and written tasks to ChatGPT rather than their own intellectual effort. Others interpreted it as a sign of the growing normalization of AI tools in students' academic practices and the increasing visibility of AI-assisted learning. The study adopts a qualitative exploratory approach based on interpretive analysis of teachers and students' reported academic practices regarding the use of ChatGPT in assignments and coursework. The results show a trend toward an increasing issue concerning academic integrity because the majority of students use ChatGPT to write papers but demonstrate little evidence of any critical engagement. Although the use of AI helps students understand things more easily, a clear trend is observable in terms of overreliance on the system's output. The study concludes that generative AI use ranges from academic support to dependency. It recommends clear institutional guidelines, integration of AI literacy, and assessment practices that promote critical thinking, process-based evaluation, and academic integrity.
A pedagogical framework for intentional prompt engineering in EFL material design
Krechich Fadoua1; Hairech Faiza1
The rapid integration of Generative Artificial Intelligence (GenAI) has transformed instructional design in English as a Foreign Language (EFL) education. While Large Language Models (LLMs) offer unprecedented efficiency in generating reading texts, vocabulary lists, and lesson plans, their mainstream educational usage often relies on superficial, ad-hoc prompting. This erratic approach frequently yields outputs that lack pedagogical scaffolding, cultural relevance, or alignment with established language acquisition frameworks. Consequently, there is an urgent need to shift the paradigm from passive, automated text generation to structured, intentional human-AI communication in curriculum development. This conceptual paper introduces a robust, teacher-facing framework designed to guide EFL educators in communicating systematically with GenAI tools. By treating prompt engineering as a form of specialized, pedagogical dialogue, the framework aims to ensure that AI-generated instructional materials strictly adhere to specific linguistic levels, task-based objectives, and communicative language teaching (CLT) principles. Utilizing a design-based conceptual approach, this study outlines a structured system-prompting matrix. The framework operates on four core linguistic constraints: target pedagogical framework alignment, lexicogrammar profiling, localized contextualization, and interactive scaffolding. To evaluate the framework's viability, a qualitative walkthrough is presented, illustrating how an instructor iteratively prompts an LLM to design a hyper-personalized, context-specific reading unit and an accompanying vocabulary assessment for advanced EFL learners. The generated artifacts are evaluated against traditional instructional design rubrics to determine their pedagogical soundness. The paper demonstrates that when educators engage in structured, constraint-driven dialogue with GenAI, the resulting materials exhibit higher instructional alignment and fewer algorithmic errors or generalizations. Ultimately, this framework contributes to the discourse on digital language policy by repositioning the teacher not as a bystander to automated automation, but as an active, agentic mediator of educational technology.
Nourelhouda Latreche1; Houda Bouhadjar1
The demanding nature of literary studies often poses challenges for teachers in literature classrooms. A vast number of literary texts are lengthy, complex, and require deep interpretation; thus, they require learners to engage deeply with the material in order to achieve the objectives of literature instruction and develop literary competence, all within limited classroom time. In this context, microlearning can offer focused and manageable learning activities that support engagement with literary texts while preserving their depth and nature. This conceptual paper explores the potential of AI-powered microlearning as an instructional approach in literature classes. Specifically, the paper examines how artificial intelligence can assist teachers in designing microlearning activities for literary themes, characterization, literary devices, and textual interpretation, while also considering the pedagogical opportunities and challenges associated with such integration.It aims to demonstrate how artificial intelligence can support the design of flexible and personalized microlearning activities that break literary texts into manageable learning units, such as character analyses, theme exploration tasks, and guided reflections, thereby assisting teachers in achieving the instructional objectives of literature classes.
A framework for teaching grammatical cohesion in text linguistics using Qwen Chat
Imane Bahri1
Since its emergence, artificial intelligence (AI) has generated considerable interest regarding its integration into language education. However, existing research has largely focused on how students utilize AI to assist with their own writing, paying limited attention to how language educators can actively incorporate AI into the explicit teaching of complex textual features. This paper proposes an AI-assisted pedagogical framework for teaching grammatical cohesion in text linguistics courses. The theoretical framework draws on Vygotsky's sociocultural theory of dynamic scaffolding and Halliday and Hasan's framework of grammatical cohesion (reference, substitution, ellipsis, and conjunction). Within this framework, large language models such as Qwen Chat are positioned not as substitutes for instructors expertise, but as flexible pedagogical scaffolds. Specifically, the framework demonstrates how instructors can employ AI to: (1) generate contrastive linguistic data (minimal pairs highlighting cohesive shifts), (2) analyse cohesive errors in learner texts, and (3) facilitate critical AI literacy by having students evaluate the semantic coherence of AI-generated cohesive ties. This framework is evaluated through a qualitative action research study involving 25 Master's 1 linguistics students in the English Department at Blida 2 University in Algeria, utilizing structured Qwen Chat prompts over a focused 3-week instructional module.] Preliminary findings indicate that when AI is strategically mediated by the instructor, it significantly enhances learners' meta-linguistic awareness of cohesive devices while preserving the teacher's fundamental role in guiding critical discourse analysis. This paper concludes with practical guidelines for linguistics educators seeking to integrate generative AI into advanced discourse analysis instruction.
A quasi-experimental study on the impact of AI on quiet EFL learners' classroom participation.
Matallah Taous1; Ouis Hanen2
In traditional classrooms, many shy students struggle to engage because of their fear of making mistakes. However, artificial intelligence (AI) can empower quiet EFL learners to engage in classroom instructions. The researcher highlights the importance of AI voice assistant tools in creating an enthusiastic approach. Accordingly, the researcher scrutinizes the use of AI chatbots and voice assistants to create a low-pressure environment where learners embrace their confidence and power to encounter their fears and feel at ease in sharing their ideas. Using a one-group pretest-posttest design aligned with an intervention, a group of EFL students with low levels of classroom participation was identified based on prior classroom performance. This study aims to determine whether interaction with AI tools may enhance learners' willingness to engage in classroom instructions. In the same vein, the findings are expected to provide insights into the impact of AI on creating an entertaining environment that boosts less active learners to indulge more confidently in language learning with a big smile and great desire. Accordingly, many future recommendations are proposed. AI tools should be embraced in EFL classrooms, especially in oral sessions. Besides, giving attention to shy low-confident students will enhance the teaching outcomes at the end of the educational course. In addition, an AI classroom should be linked with a traditional classroom, highlighting the crucial role of the teacher's guidance to ensure a balanced communicative development.
Adapting EFL writing pedagogy for the AI-mediated composition process
Radia Bouguebs1; Nadira Bouguebs2
The post-2022 paradigm shift in educational technology has transitioned Artificial Intelligence from a basic grammar-checking tool into an active partner in "generative authorship." This evolution challenges traditional notions of student agency, assessment integrity, and text ownership in English as a Foreign Language education. This paper presents an evidence-based pedagogical framework that merges deep cognitive learning theories with empirical qualitative data to address this disruption. Theoretically, the study adapts Vygotsky's Zone of Proximal Development, Cognitive Load Theory, and Self-Determination Theory to re-evaluate the human-AI collaborative writing loop. It frames the central tension as a choice between AI acting as a cognitive scaffold that aids developmental growth or a cognitive bypass that masks underlying learning gaps with sterile, algorithmic text perfection. Empirically, the paper draws on a Reflexive Thematic Analysis exploring university teachers' confidence, anxieties, and trust regarding the assessment of AI-mediated writing. The qualitative findings reveal significant fractures in traditional grading criteria, driven by an inability to distinguish developmental, "approximate language" from automated generation, which severely undermines teacher assessment confidence. To bridge this divide, this study proposes an Adaptive Writing Ecosystem that moves beyond screen-level prompt engineering to prioritize the internal cognitive and affective states of the writer. The framework advocates for a structural shift from product- to process-based rubrics, institutional guidelines separating brainstorming from drafting phases, and the integration of oral verification protocols. Ultimately, the study concludes that while technology personalizes the text, only humanized pedagogy can personalize the meaning-making process.
The role of voice-based AI in promoting speaking self-efficacy among EFL students
Fatma Zohra Boukehili1
The implications of artificial intelligence (AI) in education have extended beyond the linguistic domain to encompass the psychological dimensions of both learners and teachers. Nowadays, AI tools, particularly chatbots, are no longer limited to linguistic capabilities; rather, they show signs of emotional intelligence (EI). In the EFL context, while AI has shown real promise in supporting different areas of learning, there remains a noticeable lack of research examining its impact on learners' emotional state, especially in relation to spoken language development. Therefore, the present study seeks to investigate the role of an emotionally intelligent voice-based chatbot (Pi) in enhancing EFL students' speaking self-efficacy. The study mainly focused on three dimensions of self-efficacy: performance, self-regulatory and linguistic self-efficacy. Thirteen Algerian EFL students enrolled at the University of Souk-Ahras participated in the study through convenience volunteer sampling. The study employed a quantitative one-group pre-test-post-test pre-experimental design where a modified version of the Self-Efficacy for English Speaking Scale (SEESS) was administered as both a pre-test and a post-test to examine changes in students' speaking self-efficacy before and after the intervention. The experiment ran over seven sessions, each lasting about three hours. During each session, students engaged in spoken conversations with Pi on various topics and frequently asked it for feedback on their speaking. The findings revealed statistically significant improvements across all dimensions of self-efficacy, with the greatest gains observed in performance self-efficacy, followed by self-regulatory efficacy and linguistic self-efficacy, indicating that the AI tool enhanced students' confidence in performing speaking tasks, managing their own learning, and using the language effectively.
A theoretical examination of learner self-efficacy in academic writing
Khaoula Atmani1; Mehdi Kaddouri2; Abdellatif Belkadi3; Amal Zerouali2
The growing integration of AI-powered writing tools in higher education has introduced new and underexplored challenges for academic writing development. While these tools are considered as valuable feedback resources capable of enhancing students' writing quality, this presentation argues that their systematic tendency to suggest modifications to already correct and academically appropriate writing constitutes a form of overcorrection with serious pedagogical consequences. Unlike traditional corrective feedback, which targets genuine errors, AI tools such as ChatGPT and Gemini consistently propose alternative vocabulary, restructured sentences, and stylistic changes regardless of whether the original writing meets academic standards. This pattern of unnecessary intervention risks sending students a misleading message — that their language choices are perpetually insufficient. Drawing on Bandura's (1997) self-efficacy theory, Truscott's (1996) critique of written error correction, Hyland's (2002) academic voice framework, and Holec's (1981) learner autonomy theory, this presentation theorizes that persistent AI suggestion creates a false impression of inadequacy in students, which leads them to distrust their own linguistic judgments and undermine their confidence as academic writers. Constant AI intervention further erodes learner autonomy and silences the development of an authentic scholarly voice, carrying direct negative consequences for long-term academic writing performance. This presentation calls for raising critical awareness among teachers and students regarding the overcorrective nature of AI feedback tools, advocating for a balanced and reflective approach that encourages students to trust their own competence rather than developing an uncritical over-reliance on AI-generated suggestions.
A pilot study on AI-assisted speaking and foreign language anxiety
Firdevs Bozdemir1; Mehmet Aslan2
This pilot study, which adopts a mixed-methods research design, explores the instructional impact of Praktika, an artificial intelligence-supported speaking practice tool, on reducing foreign-language speaking anxiety among beginner-level high school students. Quantitative data were collected through an adapted version of the Foreign Language Speaking Anxiety Scale from Horwitz et al. (1986), administered as pre- and post-tests. Qualitative data were gathered through semi-structured interviews exploring learners' affective responses, confidence in speaking, and perceptions of Praktika. The participants were comprised of 12 ninth graders in a state high school in Türkiye. Throughout the four-week intervention process, the students participated in speaking activities with Praktika besides regular classroom activities. The findings gathered from the quantitative analysis pointed to a significant decrease in participants' foreign language speaking anxiety scores after the intervention. Qualitative results indicated that students reported enhanced speaking confidence, reduced fear of negative evaluation, and a tendency to accept errors as a component of the learning process. Participants attributed these improvements to Praktika's non-judgmental atmosphere, immediate feedback function, and opportunity to practice at their own pace. Although this research is constrained by a limited sample and a short-term intervention, it offers preliminary evidence that Praktika can function as a beneficial complementary tool to reduce spelling anxiety and foster speaking proficiency.
Teachers' attitudes and challenges in inclusive EFL classrooms
Khouane Abbassia Hanane1
In today's EFL classrooms, where learner heterogeneity is the defining characteristic, the implementation of one-size-fits-all instruction is no longer pedagogically viable. Designing interactive lessons that meet the multifarious needs of learners and their learning paces, in what is known as differentiated instruction, has been one of the essential yet daunting tasks for teachers, not to mention providing timely, tailored feedback. However, with the swift advancements of artificial intelligence in education, the implementation complexity might be minimized. Effectively integrating AI may help educators mitigate several challenges while offering personalized learning experiences that, in turn, may foster interaction patterns. This study is, therefore, an attempt to examine the major challenges that teachers encounter in inclusive classrooms. Moreover, it seeks to highlight their attitudes towards using AI as a co-assistant to alleviate their workloads. Furthermore, it aims to explore whether teachers who are already using AI in planning their lessons find any improvement in their teaching methods and in their classroom interaction. To reach this end, a mixed-methods case study will be employed, using an online questionnaire administered to EFL teachers from different Algerian universities, alongside classroom observations. The triangulation of the results is expected to shed light on the myriad difficulties that teachers face in adapting their instructional practices to their students' needs. The findings may also reveal that educators hold positive attitudes towards using artificial intelligence in reducing planning burdens while increasing interactive opportunities.
A systematic review of applications, outcomes, and challenges in higher education
Mohd Shahbaz Khan1; Sameer Babu M1
The rapid adoption of Artificial Intelligence (AI) into higher education is transforming pedagogical methodologies, especially in language instruction. English for Specific Purposes (ESP), a needs-oriented methodology centred on discipline-specific communication, is particularly shaped by these advancements. despite increasing interest, a systematic synthesis of empirical evidence regarding AI applications in ESP contexts is still scarce. This study offers a systematic review of research published from 2020 to 2026, adhering to the PRISMA framework. The review examines three primary inquiries: (1) What categories of AI tools are employed in English for Specific Purposes (ESP) within higher education? What learning experiences and outcomes have been documented? What advantages and obstacles arise from their utilization? A systematic search of the Scopus database identified 15 peer-reviewed studies that fulfilled the inclusion criteria. Data relevant to AI tools, research methodologies, educational outcomes, and implementation obstacles were systematically extracted and synthesized. The results demonstrate a rapidly changing AI environment, characterized by a significant increase in publications from 2024 to 2026, indicative of the ascendance of generative AI technologies. The findings indicate that the AI ecosystem in ESP has evolved from conventional corrective tools to generative AI applications like ChatGPT, in addition to specialized tools that facilitate research and oral communication. Secondly, learning outcomes are significantly influenced by pedagogical design: a structured and guided application of AI correlates with enhancements in writing proficiency, critical thinking, and learner autonomy, while unguided use may result in overreliance, diminished skill development, and issues related to academic integrity. Third, AI exerts a dual influence, providing personalized feedback, enhancing motivation, and alleviating language anxiety, while simultaneously introducing challenges concerning accuracy, disciplinary relevance, teacher-student perception discrepancies, and socio-emotional engagement. The review asserts that the efficacy of AI in ESP is contingent not solely on technology but also on its pedagogical integration.
Hafsa Abbou1; Ghobrini Rafik El Amine2; Zouar Houda2
This pedagogical action research explores the experiences of learning among master students with a particular focus on the integration of AI in oral expression module. While there is a growing awareness of the role of AI in enhancing language skills among English language university students, little is known about its use within the Algerian context to enhance students speaking skills particularly when English is becoming a primordial language in Algeria. This study was guided by sociocultural theory of Vygotsky as well as Gamification and motivation theory to explore the extent to which the learning experiences within oral expression module is mediated and supported through AI-generated games. To this end, observation and questionnaires were collected from 30 master students. The analysis of the data reported an increased students' engagement, peer collaboration and a greater willingness to participate in speaking activities. These findings suggest that integrating AI-driven gamified tools can create a more dynamic and supportive environment for developing oral proficiency in English. This study holds relevance for higher education contexts seeking to ethically integrate AI into Oral Expression classrooms, particularly in settings undergoing a linguistic shift where English is emerging as a primary language of instruction and communication.
Rasha Jadou1
As artificial intelligence (AI) becomes more central to global communication, protecting endangered and marginalized languages is becoming increasingly important. This paper argues that AI should not be used only for translation. Instead, it should serve as a tool that helps languages survive, grow, and stay active in the digital world. This means treating language technology as a long‑term investment, not just an optional technical feature. Today, more than 6,000 languages are missing from modern AI systems. This problem is not only caused by a lack of data. It also results from limited funding, scattered efforts, and the absence of strong, coordinated plans to support languages with fewer digital resources. To address this imbalance, we need AI strategies that reduce the gap between well‑supported languages and those that are digitally disadvantaged. This includes creating fairer algorithms and ensuring equal access to digital tools. A key part of this approach is building technology that centers on the communities who speak these languages. When local speakers lead the development of digital tools, the results are more culturally accurate, meaningful, and useful. Community‑driven design ensures that AI systems respect cultural knowledge and adapt to local needs. The paper also highlights the importance of collaboration. Protecting linguistic diversity requires partnerships between communities, researchers, cultural organizations, and international institutions. Language preservation is not only a technical task—it is a long‑term effort to protect cultural heritage. Through these combined efforts, AI can help reduce digital inequality and give endangered languages a stronger presence in the rapidly evolving digital world.
Opportunities, challenges, and ethical frontiers
Doaa Ahmad Hawa1
Linking Human Language and Artificial Intelligence: Opportunities, Chal Recent advances in artificial intelligence (AI) have significantly altered how machines understand and generate human language. Large language models have made it possible for natural language processing (NLP) systems to perform complex linguistic tasks like sentiment analysis, translation, summarization, and dialogue generation with near-human proficiency. This paper explores the dynamic relationship between language and Al, focusing on how computational models learn language, interpret meaning, and deal with contextual variation using large-scale datasets.The study looks at important technological developments that have spurred progress in this field, particularly transformer-based architectures and deep learning techniques. It also addresses enduring problems like training data bias, cultural and contextual knowledge gaps, and concerns about accountability and transparency in automated systems. The study also looks at how Al-driven language technologies may affect society more broadly in areas like digital communication, healthcare, and education.By critically analyzing both the advantages and disadvantages of existing Al language systems, this study advances our understanding of how these systems impact human interaction and knowledge production. In addition to highlighting future research directions, the paper's conclusion emphasizes the significance of developing inclusive, understandable, and morally sound Al systems that are consistent with human values.
Ashwaq Ahmad Hammash1
Artificial intelligence (AI) is increasingly influencing English language learning in higher education by providing innovative tools that support skill development and personalized learning. This paper examines the role of AI applications such as ChatGPT and language correction systems in improving learners' English proficiency, particularly in writing, vocabulary, and communication skills. The study highlights that AI enhances self-directed learning by offering instant feedback and flexible learning opportunities outside the classroom. It also increases student engagement and confidence in using the English language in academic contexts. In addition, the paper includes a brief international comparison of AI integration in English language education. It suggests that some educational systems have adopted AI more systematically and effectively, while others are still in the early stages of implementation despite growing interest. The findings indicate that AI can significantly improve language learning outcomes when used appropriately, but it should be balanced with traditional teaching methods to ensure critical thinking and academic integrity.
Pedagogical evidence, classroom realities, and human limits
Swati Arora1
This paper examines the integration of Artificial Intelligence tools into English Language Teaching (ELT) in Japanese university classrooms, focusing on what is pedagogically effective, what falls short in practice, and where human teaching remains irreplaceable. Drawing on classroom observation and educators, this study critically evaluates AI-assisted language learning tools, including writing assistants, automated feedback systems, and conversational AI, within the specific sociolinguistic and cultural context of Japan. Japan presents a distinctive case: a high-technology society with deeply rooted traditional pedagogical norms, where learner anxiety, cultural expectations around error and performance, and institutional conservatism shape how AI tools are received and used. The paper identifies pedagogical gains in areas such as grammar feedback, vocabulary reinforcement, and learner autonomy, while also documenting consistent limitations: AI tools frequently fail to address pragmatic competence, intercultural communication, and the affective dimensions of language learning that skilled teachers navigate intuitively. Crucially, this study argues that the boundary between productive AI assistance and over-reliance is not merely technical but ethical and pedagogical. Teachers must actively mediate AI use to preserve student agency, critical thinking, and authentic communicative development. The paper concludes with evidence-informed recommendations for ELT practitioners and institutional policymakers on how to integrate AI responsibly, sustainably, and in ways that keep human judgment at the center of language education.
Navigating the pedagogical friction of EMI in Algerian medical education
Lallaouna Mounir1; Ounis Salim2
While the recent adoption of English-Medium Instruction (EMI) in Algerian higher education aims for globalization, it has sparked significant pedagogical friction. This study moves beyond traditional perspectives to investigate "Shadow Didactics"- the survival strategies students use to navigate this shift. It posits that EMI is mediated through peer-led networks and AI tools, forming an informal pedagogy that bridges the gap between students' linguistic reality and policy demands. Employing a convergent mixed-methods case study at Abbas Laghrour University (2024–2025), the research focused on first- and second-year students in the faculty of medicine. The research used a questionnaire which measured self-reported proficiency, peer mediation frequency, Telegram and WhatsApp usage, and attitudes toward translanguaging. Additionally, an interview was conducted with the students to deepen the investigation.Preliminary findings reveal that academic success in this transitional phase results from a hybridized mixture of informal methods rather than English-only instruction. Peers and AI serve as focal mediators; proficient classmates act as pillars connecting less proficient peers to contentknowledge. Success in Algerian EMI classrooms depends on belonging to interconnected networks that offer immediate, contextualized mediation—a reflection of social competence rather than linguistic deficit. The study concludes that the role of the peer mediator is salient for translating complex terminology. Consequently, policymakers should move away from rigid models and adopt a translanguaging pedagogy that integrates peer-mediated scaffolding. "Shadow Didactics" serves as a critical alert: the gap between formal policy and pedagogical reality remains significant.
The impact of artificial intelligence on literary terms acquisition in the English classroom
Boutkhil Guemide1
This study examines the impact of AI-powered tools and applications on the learning and retention of literary terminology among 1st year EFL students of Msila University. The research employs a mixed-methods approach, combining quantitative data on student performance and qualitative insights from teacher and student perspectives. English classrooms were divided into control and experimental groups, with the experimental group utilizing AI-assisted learning modules focused on literary terms. Pre- and post-assessments were conducted to measure the acquisition and long-term retention of key literary concepts. Results showed the AI group achieved significantly higher post-test scores (M=18.2 vs. M=15.6, p<0.01) and retention scores after three months (M=17.5 vs. M=14.8, p<0.01). Qualitative data revealed enhanced engagement and confidence in the AI group. These findings suggest AI can enhance literary education by improving knowledge acquisition, engagement, and retention. In addition, the findings of the study suggest that the integration of AI in the learning process significantly improved students' understanding and recall of literary terms compared to traditional instructional methods. AI-powered applications provided personalized feedback, adaptive practice, and immersive learning experiences that enhanced engagement and knowledge retention. Moreover, the qualitative data revealed that both teachers and students perceived the AI-augmented approach as more effective, efficient, and enjoyable than conventional literary instruction. The study's implications highlight the potential of AI to transform the teaching and learning of literary analysis in EFL classrooms. By leveraging the strengths of AI, educators can foster deeper comprehension, increase student motivation, and better prepare learners for the demands of literary study.
Enhancing language learning through adaptive technologies
Kherroubi Hassiba1
The rapid development of Artificial Intelligence (AI) has transformed educational practices and created innovative opportunities for multilingual learning environments. This paper explores the role of AI-driven technologies in enhancing language acquisition, improving learner engagement, and supporting personalized education. Through adaptive learning systems, intelligent tutoring platforms, speech recognition tools, and automated feedback mechanisms, AI enables learners from diverse linguistic and cultural backgrounds to access more inclusive and effective educational experiences. The study examines how AI contributes to developing communicative competence, vocabulary acquisition, pronunciation accuracy, and intercultural understanding among students in multilingual classrooms. It also discusses the challenges associated with the integration of AI in education, including ethical concerns, data privacy, algorithmic bias, and the potential reduction of human interaction in language learning processes. By analyzing recent educational applications and digital learning practices, this paper argues that AI can serve as a valuable pedagogical tool when implemented responsibly and collaboratively with educators. The research highlights the importance of balancing technological innovation with human-centered teaching approaches to ensure equitable and meaningful learning experiences. Ultimately, the paper demonstrates that AI has the potential to reshape multilingual education by fostering accessibility, personalization, and intercultural communication in the digital age.
Learners multimodal apprenticeship in vlog-based oral communication
Nurul Nazira Binti Hamzah1; Esther Binti Jawing2
Video-based multimodal production and generative artificial intelligence (GenAI) tools are increasingly reshaping how learners plan, perform and refine multimodal texts in language education. While vlogging and GenAI chatbots have individually gained traction in ESL research, limited empirical work has examined how learners experience their combined use within vlog-based oral communication tasks. Addressing this gap, the present study explored Malaysian ESL undergraduates' written reflections following a semester-long vlog-based English oral communication project where generative AI (GenAI) were introduced as an optional support tool. Drawing on reflective thematic analysis of 34 reflections, the findings illustrate how learners engaged with multimodal apprenticeship encompassing idea generation, script structure, refining language and supporting production decisions, while selectively adapting AI output to maintain personal voice and authenticity. Interpreted through the Self-Determination Theory (SDT) and Zone of Proximal Development (ZPD), the analysis shows how GenAI chatbots functioned as a form of cognitive scaffolds and co-creators that supported autonomy, competence and relatedness; and confidence without replacing human modelling. Peer collaboration, online examplars and teacher guidance remained central sources to the learning process. At the same time, learners demonstrated emerging critical AI literacy by recognising limitations related to accuracy, reliability, time and technical constraints. Overall, the findings challenge deficit narratives that portray GenAI as undermining learner agency, instead of highlighting its role as a supportive tool within a guided multimodal apprenticeship.
A case study of academic staff at Belhadj Bouchaib University
Khalladi Meriem1
Since artificial intelligence continues to reshape higher education, international academic mobility no longer requires linguistic competence alone. Academic staff, including teachers, researchers, and students involved in mobility programmes, are expected to develop intercultural, digital, and social skills that enable them to communicate and adapt effectively across diverse academic environments. Similarly, English language training curricula should move beyond traditional language instruction and respond to the communicative, cultural, and technological realities of contemporary higher education. Nevertheless, many curricula implemented in home universities still focus primarily on general English proficiency, with limited attention to AI-mediated communication, intercultural preparedness, and the social experiences encountered in host universities. This study explores the extent to which AI-enhanced English language curricula can support academic and intercultural integration during international mobility experiences. It examines the relationship among curriculum design, digital transformation, and the communicative challenges participants face as they transition from home to host university settings. Particular attention is paid to the roles of artificial intelligence tools, technology-enhanced learning environments, and innovative curriculum practices in developing intercultural awareness, academic communication skills, and social adaptability in multilingual, digitally mediated educational contexts. The study uses an online questionnaire that aims to investigate the perceptions and experiences of university mobility participants at Belhadj Bouchaib University in Ain Temouchent regarding the effectiveness of existing English language training programmes. The findings are expected to reveal the importance of developing more context-sensitive, AI-oriented curricula that integrate authentic mobility experiences, intercultural communication practices, and digital competencies aligned with the evolving demands of global higher education.
Students', parents', and teachers' perspectives on AI-supported education and language learning
Md. Saddam Hossain1
The use of generative artificial intelligence for learning practices is increasing day by day. Now, Bangladeshi students, parents, and teachers are using ChatGPT, and AI tool, for academic support, language learning, writing assistance, problem solving, and knowledge verification. This study explores how ChatGPT is integrated into Bangladeshi educational practices, with particular attention to its role in AI-supported education, multilingual learning, and subscription-based access. Using an exploratory mixed-methods approach, structured questionnaires with Likert-scale items, multiple-choice questions, and open-ended responses were administered to three key user groups: students, who use ChatGPT for different purposes, including writing essays and applications, finding answers of subject-based questions, practicing English grammar, pronunciation and vocabulary, and solving critical mathematical problem, etc.; parents, who use it to respond to children's questions at home; and teachers, who employ it for preparing lesson, , making hand notes, providing explanation, feedback, and classroom support. The study examines perceived opportunities, challenges, ethical concerns, and the impact of free versus paid access on learning equity. Findings show that ChatGPT can play a great role for learning languages. Besides, it can act as a digital learning companion across home and classroom contexts. However, its use raises concern about overdependence, accuracy, academic integrity, digital literacy, and unequal access. By situating ChatGPT within the Bangladeshi learning ecosystem, this study contributes to current debates on responsible AI use, equitable access, multilingual education, and pedagogical transformation in the Global South.
A Human-Centred approach to English language teaching
Khawla Mohammed Al Hamoud1
Artificial intelligence is becoming an important topic in English Language Teaching, especially as students and teachers increasingly use tools such as ChatGPT, translation applications, writing assistants, and speech recognition systems. My proposed paper, "From Artificial Intelligence to Augmented Teaching: A Human-Centered Approach to English Language Teaching," explores how AI can support English language teaching without replacing the essential role of the teacher. The paper argues that AI should be understood not as a threat to teachers but as a tool that can enhance and extend the teaching-learning process. The study focuses on augmented teaching, in which AI helps learners improve their writing, pronunciation, vocabulary, speaking skills, and communicative competence through individualized practice and immediate feedback. It also considers how AI can assist teachers in preparing materials, designing classroom activities, and responding to different learner needs more effectively. However, the paper also addresses the challenges of AI use, including plagiarism, learner overdependence, inaccurate information, privacy concerns, and the possible weakening of students' critical thinking. The main argument of this paper is that successful AI integration in English Language Teaching depends on teacher guidance, ethical awareness, clear classroom policies, and critical digital literacy. The English teacher remains central in motivating learners, managing classroom interaction, interpreting students' needs, and developing cultural and communicative competence. Therefore, this paper concludes that the future of English Language Teaching should be teacher-guided and AI-supported, preserving the human values of education while benefiting from the possibilities of artificial intelligence.
A TAM-extended analysis of foreign language anxiety, trust, and learner experience in the Tunisian context
Leila Najeh1
Artificial intelligence has been gradually integrated into foreign language learning settings, mainly with the use of generative AI tools like ChatGPT, automated feedback systems, and language learning applications. While these technologies offer new pedagogical opportunities, their influence on learners' emotional experiences, particularly foreign language anxiety, has not been adequately examined in the Tunisian context. This study examines the effect of artificial intelligence on foreign language anxiety of Tunisian EFL learners who study technical majors. In particular, it discusses the opportunities and challenges of AI-assisted language learning. The current study was conducted on 60 Tunisian students enrolled in technical majors . The questionnaire was developed based on the Technology Acceptance Model (TAM) extended with the trust and anxiety constructs to investigate learners' perception, attitude, and experiences with ChatGPT in English language learning. The study aims to find out if AI-based interaction helps to reduce anxiety by providing personalized feedback, flexible learning environments, and a safe space for communication, or if it generates more stress by creating dependence on technology, reducing human interaction, and facing challenges of precision and academic integrity. The expected findings indicate that artificial intelligence may have a positive impact on learners' confidence and participation by reducing the fear of negative evaluation and promoting autonomous learning. But it also anticipates a number of pedagogical and ethical problems associated with over-dependence on AI technologies. The study contributes to the ongoing debates on the role of AI in language learning by emphasizing the affective aspect of technology integration and highlighting the importance of responsible and balanced AI implementation in the Tunisian EFL educational context.
Opportunities, ethical challenges, and pedagogical implications
Ahmad Jabr1
Generative artificial intelligence (AI) is rapidly reshaping English Language Teaching (ELT) by offering new possibilities for personalized learning, automated feedback, material development, and communicative practice. Tools such as AI chatbots, text generators, and writing assistants can support learners in developing vocabulary, grammar, writing fluency, pronunciation awareness, and intercultural communication skills. For teachers, generative AI may reduce workload by assisting with lesson planning, assessment design, content adaptation, and differentiated instruction. However, its integration into ELT also raises significant ethical challenges, including academic dishonesty, data privacy, algorithmic bias, overdependence on technology, unequal access, and the authenticity of learner-produced work. These concerns require careful pedagogical planning rather than uncritical adoption. This paper examines the opportunities, ethical risks, and pedagogical implications of generative AI in English language education. It argues that generative AI should be used as a supportive tool rather than a replacement for teachers, with emphasis on critical digital literacy, transparent assessment practices, responsible use policies, and learner autonomy. The study highlights the need for teachers to develop AI literacy and redesign classroom practices to balance innovation with ethical responsibility. Ultimately, generative AI can enhance ELT when implemented thoughtfully, critically, and inclusively within clear pedagogical frameworks.
Preserving pedagogical values and teacher-student relationships via the Human-Centered writing triangle
Fatima Zohra Bekheira1; Kouider Makhlouf2
The rapid integration of AI-powered writing tools into educational settings is reshaping how EFL students write and communicate within the classroom. While AI is increasingly praised for enhancing efficiency and language support, excessive dependence on AI-mediated writing may gradually replace the human pedagogical qualities that make learning transformative. This paper suggests that overreliance on AI writing tools may lead to classroom silence, diminished student voice, reduced intellectual confidence, weakened peer interaction, and the loss of productive struggle for writing development. Growing dependence on AI-generated language and immediate responses may shift students' trust away from their own thinking, creativity, and linguistic identity toward artificial systems, and may disrupt teacher-student relationships and the social ecology of the writing classroom. If EFL students interact more with AI systems than with teachers or classmates throughout the writing process, core pedagogical elements such as dialogue, empathy, collaborative learning, feedback exchange, and emotional support may become progressively compromised, raising a critical question about whether future AI-mediated classrooms will educate human thinkers or learners shaped by machine-oriented cognition. Grounded in Humanistic Theory and Social Constructivism, the paper introduces a practical conceptual framework entitled "The Human-Centered Writing Pedagogy Triangle," which positions AI as a complementary educational aid rather than a replacement for human interaction and pedagogy, emphasizing a balanced relationship between teachers, students, and AI to rehumanize classroom relationships and preserve central pedagogical values within technology-mediated learning environments.
Diana Hornoiu1; Alina Buzatu1; Veronica-Cristina Nedelcu1
Situated at the intersection of contemporary theoretical debates on intelligent technologies and the humanistic imperative to rethink academic education, this study examines the blind spots of artificial intelligence - what AI does not see, or it sees only partially - in order to assess the conditions of its pedagogical legitimacy. We argue that new theoretical, critical, and pedagogical instruments are necessary, but that their development must be accompanied by a rigorous concern for what remains specific to human thought: hermeneutic subtlety, critical discernment, pragmatic sensitivity, and intercultural understanding. The first case study examines literary and fictional texts, showing that AI tends to neutralise ambiguity, reduce symbolic density, overlook aesthetic singularity, and transform interpretation into stereotypical paraphrases. The second case study focuses on pragmatics, where AI frequently fails to calculate implicature, grasp irony, humour, interpret silence, indirectness and culturally coded forms of interaction. The third case study addresses Romanian as a foreign language, where these limitations become particularly visible in contexts involving intercultural mediation, idiomatic expression, pragmatic politeness, aspectual nuance, register variation, and the symbolic value of culturally embedded texts. Reflecting together on these blind spots is crucial for the formation of younger generations and early-career researchers. Rather than being regarded merely as operational limitations of intelligent technologies, the blind spots of AI must be consciously identified, critically examined, and methodologically integrated into academic disciplines. Students need to distinguish algorithmic processing from human thought: how algorithms generate, classify, and predict information, and how human understanding interprets, contextualises, evaluates, questions, and assumes responsibility for meaning. In this sense, the blind spots of AI should become part of the very process through which students learn to read, interpret, assess, contextualise, and produce knowledge. Such an approach transforms AI literacy into a broader pedagogical competence: the capacity to understand its limits, to question its outputs, and to preserve the contextual, ethical, pragmatic, symbolic, aesthetic, and intercultural dimensions of human understanding.
Ninuk Lustyantie1; Yunilis Andika1; Anim Putranto1; Muhamad Arbian Fahriza Putra1; Falisha Dinar Rustandi1; Tengku Ratna Soraya2; Dian Damayanti3
This study aims to examine the contribution of Français Immersif A1, a Virtual Reality (VR) and Artificial Intelligence (AI) learning environment, in improving A1-level French listening comprehension skills in Indonesia. The focus is directed toward pedagogical innovation, immersive experiences, and support for equitable quality of foreign language learning aligned with SDGs Methodology: A mixed-methods sequential design was employed following the ADDIE instructional framework (Analysis, Design, Development, Implementation, Evaluation) at Universitas Negeri Jakarta and Universitas Negeri Medan with A1 French learners. Quantitative data from pre-post listening tests were analyzed using inferential statistics. Qualitative data from semi-structured interviews, classroom observations, and policy document analysis were analyzed thematically. Results: Quantitative findings revealed a statistically significant improvement in listening comprehension with a very large effect size. Qualitative thematic analysis yielded three major impacts aligned with SDGs: First, VR immersion provided authentic, contextualized visual environments that reduced comprehension anxiety and enhanced inferencing skills (SDG 4 – Quality Education). Second, AI-powered adaptive feedback with speed control and multimodal scaffolding functioned as a non-judgmental "patient tutor," reducing the affective filter for anxious learners (SDG 9 – Responsible Innovation). Third, peace education-infused dialogues modeled non-violent communication and intercultural respect, developing empathy and prosocial behaviors that transferred to daily interactions (SDG Target 4.7 – Peace Education). The system operationalized all three principles of Indonesia's national AI policy—safe, inclusive, and ethical. Significance: This R&D study demonstrates that VR-AI frontiers, grounded in ADDIE methodology, transform digital learning frictions into cognitive, affective, and intercultural gains, advancing SDGs through inclusive, innovative, and peaceful education.
Integrating AI tools into anglo-american literature teaching — a georgian–european comparative perspective
Tamari Iremadze1
The growing presence of artificial intelligence tools in educational settings raises urgent questions not only about pedagogy and assessment, but about the future of literary reading itself. This paper examines the practical and theoretical implications of integrating AI language tools into the teaching of Anglo-American literature across secondary and tertiary educational contexts in Georgia, drawing on empirical classroom experience and a dual perspective as both a secondary school English teacher and a university lecturer. The paper situates this inquiry within a comparative Georgian–European framework. Georgia occupies a distinctive position between post-Soviet educational legacies and active integration into European pedagogical networks — including eTwinning, within which the author has led internationally recognised projects. This cross-contextual vantage point illuminates how educators in European partner countries navigate AI adoption within curricula shaped by both local traditions and supranational frameworks, offering perspectives of broader relevance to the EU and Balkan educational space. The paper argues that AI tools, when approached critically and pedagogically, can deepen student engagement with Anglo-American literary texts while simultaneously fostering critical thinking and media literacy. It also addresses attendant risks: the flattening of interpretive nuance, overreliance on machine-generated readings, and the erosion of student hermeneutic agency. Grounded in Universal Design for Learning principles and inclusive pedagogy, the paper proposes a framework for responsible AI integration that keeps the human reader — and the text — at the centre. Implications for curriculum policy, teacher professional development, and assessment integrity are discussed.
Case of Algerian high school EFL teachers.
Romaissa Ouail1
The rise of AI-powered Large Language Models (LLMs) such as Chat GPT, Gemini, and Claude has opened novel pedagogical possibilities in English as a Foreign Language (EFL) Education. Indubitably, the use of LLMs in EFL lesson planning is increasing, yet the cultural appropriateness of AI-generated/enhanced lesson plans has received limited attention from both teachers and scholars. As such, a discussion is due about how teachers evaluate the extent to which their AI-generated lesson plans' content, examples, names, norms, values and practices align with Algerian high school students cultural background in order to mitigate the risk of confusion, offense or disengagement among students, prior to the actual lesson implementation. As a result, this mixed method study examines how 20 Algerian high school EFL teachers evaluate and mediate lesson plans designed or enhanced with the use of AI tools namely LLMs. Data were collected through document analysis of paired materials; the initial AI output and the teachers' final version used in class. Informed by document analysis results, semi-structured interviews with few EFL teachers will follow for further explanation of the matter. The present study concludes that teacher evaluation of lesson plans'cultural appropriateness is essential for customizing them to local contexts and eventually for enhancing the overall pedagogical practice. Moreover, it highlights implications for EFL teacher training on critical AI literacy as well as cultural adaptation.
Ouchene Nourelhouda1
Artificial intelligence is increasingly influencing English as a Foreign Language teaching, especially in vocabulary learning. This paper examines how AI-based tools can support vocabulary development in EFL classrooms by helping learners practice new words, receive instant feedback, and study vocabulary according to their individual needs. AI applications such as chatbots, vocabulary learning apps, automated feedback systems, and adaptive learning platforms can provide learners with repeated exposure to words in meaningful contexts. They can also help teachers design activities, track learners' progress, and identify vocabulary difficulties more easily. However, the use of AI in vocabulary teaching also raises some concerns, including overdependence on technology, unequal access to digital tools, and the need for teacher guidance. The paper argues that AI should not replace the teacher, but should be used as a supporting tool that makes vocabulary instruction more interactive, personalized, and engaging. It concludes that the effective integration of AI in EFL classrooms requires clear pedagogical aims, teacher supervision, and a balanced combination of traditional teaching methods and digital learning tools.
AI tools and assessment practices in Algerian EFL classrooms
Amira Sid1
The rise of AI writing tools has fundamentally changed the way university students write, raising urgent questions about authenticity, academic integrity, and the future of writing assessment in higher education. This shift is particularly felt in EFL contexts, where writing already represents one of the most challenging academic skills for language learners. This study examines how EFL teachers at Souk Ahras University perceive and respond to the growing influence of AI on student writing and its implications for assessment practices. Through semi-structured interviews with EFL instructors, the study explores teachers'observations of changes in student writing, the challenges AI-generated texts create for fair evaluation, and how teachers are adapting their assessment practices in response. Preliminary findings suggest that teachers are increasingly encountering written work that is linguistically polished yet lacking genuine student voice and original thinking. Teachers also report growing uncertainty about how to evaluate AI-assisted writing fairly and consistently, and many express a need for clearer institutional guidelines and professional development support. Furthermore, findings indicate that AI use is prompting teachers to reconsider what writing tasks they assign and how they design assessments that genuinely capture student thinking. The study argues that meaningful responses to AI in writing education require more than detection tools — they demand a fundamental rethinking of writing pedagogy and assessment in Algerian EFL higher education.
Evidence from an Algerian teacher training institution
Dalia Itak Torche1
The rapid advancement of Artificial Intelligence (AI) is reshaping educational practices and opening new avenues for language learning. In English as a Foreign Language (EFL) contexts, AI-powered tools such as ChatGPT are increasingly drawn upon to support idea generation, content organization, and writing development. As these technologies become more widely accessible, understanding how ready students are to integrate AI into their learning has grown into a pressing concern. This study investigates Algerian EFL students' readiness for AI-supported writing practices and examines their perceptions of AI as a resource for writing development. Using a quantitative descriptive design, an online questionnaire was administered to 32 first-year EFL students at ENS Assia Djebar of Constantine. The instrument explored students' perceptions of writing difficulties, their current use of AI in writing-related tasks, and their openness to AI-supported learning practices. The findings reveal that writing is widely regarded as a demanding skill, with idea generation and organization standing out as particular pain points. Students were found to hold positive attitudes toward AI and reported drawing on AI tools to support their writing. They perceived these tools as helpful for improving writing quality, developing ideas, and refining written content. Participants also expressed a clear willingness to incorporate AI-supported approaches into future writing tasks, pointing to a growing acceptance of AI integration in language learning settings. Taken together, the findings underscore the potential of AI-supported writing practices as an innovative, learner-centered response to writing challenges in EFL contexts, while offering practical pedagogical insights into the meaningful integration of AI in higher education.
Fostering critical awareness, AI literacy and digital citizenship among EFL students f English department, Mostaganem, Algeria
Malika Benyoub1
Digital media literacy remains a persistent challenge in Algerian EFL classrooms, particularly when it comes to navigating artificial intelligence (AI) and algorithm awareness. Despite high exposure to technology, many learners find it difficult to evaluate automated content critically and responsibly. This study aims to examine the cognitive and ethical barriers that affect students' academic research performance in English, with a particular focus on AI literacy and the development of twenty first-century skills (the 4Cs: Critical Thinking, Communication, Collaboration, and Creativity). To achieve this, a mixed-methods approach was employed, combining student questionnaires and classroom observation checklists. The data were collected from forty-two students (N=42) in the English Department at Abdelhamid Ibn Badis University in Mostaganem. The analysis reveals patterns of uncritical reliance on generative outputs, algorithmic dependency, and gaps in digital ethics awareness, as well as observed improvements in structured collaborative tasks. Rather than providing a single, universal explanation, the study explores the intricacies of critical literacy in real classroom settings and interactive workshops. The results confirm the hypotheses that AI and algorithmic awareness have significant effects on students' critical evaluation skills, which in turn affect their overall learning outcomes. In this research, the importance of explicit and context-specific digital pedagogy is highlighted and the foundation for improved instructional and curriculum design in Algerian settings of English language teaching is laid.
Opportunities, challenges and ethical implications
Agam Kumar Verma1; Mehak Jonjua2
- Artificial Intelligence (AI) has significantly affected communication, education, and learning methods in higher education institutions around the world. The use of technology that includes intelligent tutoring systems, chatbots, adaptive learning programs, and generative artificial intelligence has brought new possibilities into play. However, the institutions involved in higher education involve individuals representing different generations with varied digital literacies, technophobia, and communication styles. Therefore, this paper aims to examine the involvement of AI in human communication between generations in higher education institutions internationally and especially in the Global South region. The paper analyzes existing literature on AI-driven learning, digital communication, and intergenerational interaction using an interpretative and theoretical methodology. While special emphasis is placed on the experience gained in developing countries such as India, it places the analysis within the context of wider international discourse on the role that AI could play in universities. This research considers ways in which AI can be used to facilitate better communication, promote inclusiveness in learning environments, and foster cooperation between different participants of the education process. In addition, it raises ethical questions in terms of privacy, bias, digital divide, academic cheating, and dependence on technology. In light of the findings presented, artificial intelligence is able to serve as an efficient intermediary of education communication as long as there is digital literacy, readiness, and human-focused approaches to teaching and learning. The contribution of this paper to the global debate on responsible applications of AI in education lies in its emphasis on the relationship between technology and social responsibility.
A pedagogically mediated framework for developing communicative competence
Athmane Boufes1
The rapid proliferation of generative artificial intelligence has transformed the landscape of language education, creating new possibilities for multimodal meaning-making, learner engagement, and communicative practice. Nevertheless, current discussions frequently oscillate between technological enthusiasm and concerns regarding automation, often neglecting the indispensable pedagogical role of the teacher in orchestrating meaningful learning experiences. This paper proposes a pedagogically mediated framework that integrates human and artificial intelligence creative expressions within multimodal English Language Teaching (ELT). Drawing on multimodal pedagogy, sociocultural theory, and contemporary perspectives on human–AI collaboration, the framework conceptualizes artificial intelligence not as a substitute for human agency but as a complementary creative and cognitive resource operating under informed pedagogical mediation. Through the integration of AI-generated textual, visual, auditory, and audiovisual resources into communicative learning tasks, the proposed framework seeks to enhance learners' communicative competence while fostering creativity, critical thinking, interaction, and learner autonomy. Methodologically, the study adopts a qualitative-prevalent mixed-methods orientation and reports the iterative development of the framework through successive design and refinement phases. Particular attention is devoted to the balance between technological affordances, ethical responsibility, and educational objectives in order to ensure meaningful and responsible AI integration. By advancing a human-centered approach to multimodal language instruction, the study contributes to ongoing debates concerning the pedagogical implications of artificial intelligence and offers a theoretically grounded model for the design of communicative learning environments in the emerging era of human–AI co-creativity.
Opportunities, challenges, and ethical considerations
Mechraoui Nouha Manal1
The growing integration of artificial intelligence (AI) into educational settings is reshaping how students learn, interact with information, and develop academic skills. In English as a Foreign Language (EFL) higher education, AI-powered tools such as conversational agents, writing assistants, and automated feedback systems offer new opportunities for supporting self-regulated learning. These technologies can assist learners in setting goals, monitoring progress, managing learning strategies, and receiving immediate feedback. However, the increasing reliance on AI also raises important pedagogical and ethical concerns related to academic integrity, learner autonomy, data privacy, and critical thinking. This conceptual paper explores the relationship between artificial intelligence and self-regulated learning in EFL higher education. Drawing on recent literature from educational technology, language learning, and AI-assisted instruction, the paper examines how AI tools can support the key dimensions of self-regulation, including planning, monitoring, reflection, and self-assessment. It also discusses potential risks associated with excessive dependence on AI-generated content and highlights the need for responsible and ethical integration of these technologies into language education. The paper argues that AI should be viewed not as a replacement for human learning processes but as a supportive tool that can enhance learner autonomy when used appropriately. Finally, recommendations are proposed for educators, institutions, and researchers seeking to maximize the benefits of AI while preserving the fundamental goals of language learning and student development.
EFL students' use of AI tools for understanding academic discourse
Lasmeur Nihad1
The rise of artificial intelligence (AI) in higher education has transformed the way learners engage with academic discourse and interpret academic content. In EFL (English as a Foreign Language) contexts, students rely on AI-powered systems to facilitate academic discourse comprehension, including lectures and academic texts. This leads to AI functioning as a mediator that support learners' comprehension. This study explores the role of human-AI mediation in higher education by investigating EFL university students' use of AI tools for understanding academic discourse. Specifically, it examines students' attitudes, perceptions and experiences regarding AI effectiveness in facilitating academic discourse comprehension by simplifying academic language, explaining complicated concepts, and fostering independent learning. This research also seeks to identify the challenges students face regarding accuracy when using AI as a mediator in academic settings. This study adopted a descriptive qualitative approach, employing a structured questionnaire administered to EFL university students at ENS "Assia Djebar" of Constantine, Algeria. It explored the students' attitudes toward AI tools for understanding academic lectures, their experiences with these technologies, and the challenges encountered regarding precision. The findings suggested frequent use by students of AI as a mediator in facilitating discipline- specific terminology encountered in their academic texts, summarizing lectures, and clarifying complicated concepts in academic content. Moreover, the results displayed an overall positive attitude towards the use of AI tools for understanding academic discourse. However, the findings displayed a degree of critical awareness as students expressed concerns regarding the accuracy and precision of AI-generated responses. This work prompts ongoing discussion surrounding human–AI communication and mediation in educational environments with a focus on a dual perspective of both finding value in human-AI mediation and using it cautiously in academic contexts.
Omenia Meriem Djafri1; Nawal Mebitil2
In an increasingly globalised and digitally mediated hospitality sector, effective communication is a fundamental competence for frontline hospitality employees, as they are expected to communicate effectively with guests from diverse linguistic and cultural backgrounds, often using English as a lingua franca. Hence, recent advances of educational technologies, particularly gamification and interactive digital AI-powered learning platforms, are regarded as promising tools for enhancing frontline employees' communication skills through providing engaging and practice-oriented learning environments. This paper seeks to synthesize existing research on gamification, AI-enhanced interactive learning platforms, and technology-mediated communication training to highlight their contribution in enhancing communication skills among frontline hospitality professionals within English for Professional Purposes (EPP) training. The data are gathered through a critical review of the existing literature on gamification in language learning, AI-driven platforms in EPP training, and communication training in hospitality to explore how these technologies can supportprofessional communication. The review of previous research suggests that gamification and AI-powered interactive platforms have the potential to reshape communication training in hospitality contexts. Gamification elements such as missions, rewards, and progress systems appear to significantly enhance learners'-workers' motivation and persistence in online training contexts. Interactive AI-driven digital platforms provide opportunities for experiential learning through simulations and scenario-based activities that mirror real-world hospitality encounters. The integration of gamified mechanisms with interactive AI-powered platforms fosters learner autonomy and engagement, and contributes to more dynamic and context- relevant training. This study recommends incorporating gamification principles and interactive digital platforms into hospitality EPP training programmes to create more engaging and practice-oriented learning environments and to bridge the gap between theoretical language education and practical workplace proessional communication. This research contributes to ongoing discussions on AI-enhanced and technology-mediated EPP training and highlights implications for hospitality professionals, EPP practitioners, course designers, and other stakeholders involved in EPP training programmes.
A conceptual analysis based on Byram's ICC framework.
Chafiaa Chebbat1; Fouad Boulkroun2
Language teaching and learning has known a remarkable change with the integration of generative AI (GenAI) and large language models (LLMs). While much research has focused on developing linguistic proficiency through GenAI, less attention has been given to their role in enhancing intercultural communicative competence (ICC). Grounded in Byram's model of ICC, this conceptual paper examines the potential of GenAI tools in intercultural communicative language teaching, addressing a critical gap in research on the intercultural dimensions of AI-mediated language learning. Two research questions are put forward: (1) how can GenAI tools and LLMs enhance the learner's ICC as introduced by Byram's model? (2) What are the ethical and cultural issues that may arise from the integration of generative AI tools into intercultural language teaching? The study adopts a conceptual analytical design based on a systematic review of GenAI tools in language education. It uses a conceptual analysis to examine the incorporation of these tools in relation to Byram's five dimensions namely attitudes, knowledge, skills of interpreting and relating, skills of discovery and interaction, and critical cultural awareness. This paper also highlights both the opportunities and the issues associated with integrating GenAI and LLMs into intercultural communicative language teaching, including algorithmic bias, cultural stereotyping, hallucination, and cultural homogenization. The paper concludes by emphasizing the need for critical engagement with GenAI tools, and the design of intercultural tasks that support the cognitive processes essential for intercultural language learning. It conceptualizes GenAI as a complex tool that can support intercultural language learning, yet its potential depends mainly on careful integration to reduce cultural bias and ethical risks.
Walaa Shekho1
MAS University Dr. Walaa Shekho, Ph. D Abstract Artificial Intelligence (AI) has developed to be a transformative force in English for Specific Purposes (ESP) training, shifting the focus from passive understanding to active, appropriate and contextual discourse. This research examines the reception and efficacy of generative AI tools as a primary method for enhancing conversation skills within highly specialized professional and academic spheres. While old traditional ESP frameworks often struggle to provide scalable, authentic domain-specific dialogue, modern AI-driven conversational agents offer personalized, real-time interactive frameworks. following a mixed-method approach, this study explores how learners perceive and apply these virtual interlocutors to practice industry-specific terminology, simulate high-stakes workplace scenarios, and receive immediate feedback as a correction on conversational register and fluency. The findings suggest that AI tool reception is largely helpful, significantly increasing learner self-sufficiency, reducing foreign language anxiety, and enhancing contextual communication confidence. However, the data also highlights persistent challenges, particularly concerning algorithmic generalization, a lack of human-to-human cultural orientation, and the risk of over-dependence. Ultimately, this paper argues that while AI tools work as powerful mechanisms for linguistic reception and conversational skills, they are most effective when arranged as supplementary accelerators rather than complete replacements for human-guided expert interaction. The study ends up with methodological recommendations for instructors seeking to improve human-AI collaboration within contemporary ESP course books.
Madina Kushukova1
Artificial Intelligence (AI) has significantly influenced secondary education. By incorporating AI, secondary school teachers of foreign languages have opportunities to raise the standards of instruction. In English language teaching, several longstanding challenges persist, particularly in traditional, teacher-centered approaches that often lack interactivity and real-time feedback, especially in rural schools. The advent of mobile learning platforms and AI-driven technologies offer a promising solution to these challenges. The article discusses how the language learning platform 'Edvibe' facilitates personalized learning, overcome educational inequality in rural areas during English learning process. This research aims to examine the impact of using 'Edvibe' platform on English language proficiency levels of rural secondary school students. Employing quasi experimental pre-test/post- test design, the study involved 30 middle school students. The research concludes that the platform 'Edvibe' is an effective tool for improving English teaching standards in rural areas and for increasing students' motivations. The study provides practical implications for schools and educators searching cost-effective methods to enhance language learning results.
Student well-being in AI-mediated EFL distance education
Nachida Babchikh1
Incorporating Artificial intelligence (AI) into the educational sector is altering the nature of teaching and learning profoundly. While contemporary research has increasingly focused on AI literacy and technological adaptation, students' psychological implications for AI-mediated learning is a topic, often ignored, to which we return presently. This thorny issue is particularly relevant in EFL distance educational milieus where meaningful engagement is highly dependent on students' ability to manage digitally-orientated interactions. However, research continues to rely on emotional conception developed for human-to-human interaction. As learners interact with intelligent systems through generative AI tools, automated feedback, and adaptive learning platforms, they encounter different emotional and psychological challenges related to dependency, trust, uncertainty, and human presence. This leads us to discuss the psychological well-being of learners who are increasingly involved in AI interactions. To this end, the current research highlights the importance of reconsidering the significance of understanding learners' psychological well-being in AI-enhanced learning environment. Grounded on scholarly research in distance education, educational psychology, and human-AI interaction, the paper argues that student well-being should be recognised as a central condition for effective AI integration rather than a secondary outcome of technological innovation. The study concludes by outlining implications for transferring the issue from techno-centric approaches to human-centred perspectives in distance education and highlighting future research on the psychological dimensions of educational transformation.
Challenges and recommendations.
Bouchenak Sarah1; Fathi Djerouane2
Algeria has undergone a recent educational reform at the primary school level under the Algerian President's instructions to introduce English language subject at this level starting from the third year of primary school in the school year 2022-2023. This major step leads towards promoting Algeria's position on the global linguistic landscape, and enhancing English language teaching in our country. Due to the tremendous developments taking place globally, English proficiency has become an urgent necessity in all fields and at all levels. This initiative faces several challenges in terms of methods, curricula, and human resources. Through employing a descriptive-analytical approach, this paper seeks to examine the current situation of English language teaching in Algerian primary schools in light of these recent educational reforms, and analyze the challenges hindering the success of this project, particularly the pedagogical training of teachers, the availability of resources, and the adopted curricula. This paper concludes by proposing a set of practical and well-considered recommendations that take into account the specificities of the Algerian school environment aiming to improve their quality and ensure the success and effectiveness of this reform.
Rima Belouari1; Wafa Dich1
Artificial intelligence is increasingly revolutionizing the field of English as Foreign Language. As a consequence, the use of AI tools has become a significant learning habit for the EFL students. Using them particularly outside the classroom, the EFL students generally use such tools to practice speaking, check grammar, learn vocabulary and translate expressions from the mother language to English. Such AI tools provide the students with an engaging, immersive, personalized and adaptive learning environment. This learning habit doesn't only allow the students to improve their English proficiency and fluency, but it also enhances their confidence and motivation. This study aims to investigate EFL students' use of and attitudes towards the integration of AI tools in learning English. More specifically, it examines the types of AI tools which are commonly employed, the linguistic purposes for which the students use these tools as well as their perceptions towards the effectiveness of these tools in developing their language skills. To this end, a questionnaire was administered to L1 students at Ahmed Zabana University of Relizane. The findings indicated that the use of AI tools has become an important learning practice for most of the EFL learners, employing them with different frequencies for several purposes. In addition, most of the students perceive these tools as both motivating and limiting for their critical thinking. Finally, the it was found that the students encounter some challenges when using such tools and they showed awareness toward their effective use.
Enhancing learner engagement through ethical and inclusive classroom practices
Uzma Bilal1
Artificial Intelligence is changing the way we teach English now a days. It is making learning personal and fun for students. Artificial Intelligence tools like computer programs that can talk to students, help them for writing and online learning platforms that adjust to each students needs are very useful. These tools help teachers give feedback, teach students in ways and make learning more interesting. In Cambridge classrooms, where the goals to help students communicate well think critically and learn on their own Artificial Intelligence can help teachers come up with new and exciting ways to teach. There are some problems with using Artificial Intelligence in language teaching. We need to think about things like cheating keeping student information making sure the computer programs are fair. We also do not want students to rely much on technology and must be creative in their own ways. These are issues that we need to address. Teachers have a role to play in making sure Artificial Intelligence is used in a way that is fair, transparent and helps students learn about technology. This paper looks at how Artificial Intelligence can be used in English Language Teaching in a way that's fair and inclusive. It explores ways to use Artificial Intelligence in the classroom that put the student first and make sure everyone has a chance to learn. The paper says that teachers need to use Artificial Intelligence in a way that combines technology with good teaching methods. This way Artificial Intelligence can be a tool for teachers, not a replacement for them. This discussion is part of a conversation about using Artificial Intelligence in language teaching in a responsible way. It gives teachers ideas, about how to prepare students for a world that's increasingly digital.
Code-switching fatigue and lexical gaps in AI-mediated mother tongue instruction
Pethias Siame1
Mother tongue education in rural Zambia faces a paradoxical challenge: AI tools promise scalable literacy support, but their training data exclude Mambwe (spoken in Northern Province, districts of Mbala and Mpulungu) and Lungu (around Lake Tanganyika). This paper reports on a participatory design study with 45 Grade 5 teachers and 320 learners across three zone schools, where a prototype chatbot was deployed for Mambwe reading comprehension exercises. The chatbot, fine-tuned on a small corpus of Mambwe folktales and church primers, produced two unanticipated outcomes. First, learners exhibited code-switching fatigue: the chatbot's inability to handle natural Mambwe-English alternations forced learners into artificial monolingual production, reducing spontaneous language use by 58%. Second, lexical gaps emerged in domains such as digital navigation (kupenda – to click; absent) and emotional expression (chilowola – confusion after a riddle; present but misused). The paper argues that current mother-tongue AI tools replicate colonial language ideologies by privileging standardised, written varieties over oral, heteroglossic practices. In response, the study proposes a minimally supervised lexicon expansion protocol using community radio recordings. In foreign-language English education, LLMs inadvertently penalise Lungu learners whose English shows substrate transfer (e.g., omitted articles), flagging them as errors rather than as transitional competences. The paper offers a bilingual ethical framework for AI deployment in Zambian mother-tongue classrooms.
Rethinking English language teaching in higher education
Sougand Akbarian1
Artificial intelligence (AI) is reshaping higher education by transforming how students access knowledge, engage with learning materials, and demonstrate academic competencies. Traditional language teaching approaches, often grounded in content acquisition and memorization, require reconsideration in light of AI-assisted learning environments. This study examines how AI can support competency-based English language education while fostering critical thinking, communication, collaboration, creativity, and ethical AI literacy. This conceptual study employs a comprehensive review and synthesis of recent scholarly literature on artificial intelligence, competency-based education, English language teaching (ELT), and higher education. Drawing on contemporary educational theories and emerging AI pedagogies, the paper develops an integrative framework that connects AI technologies with competency-oriented language learning outcomes. The analysis indicates that AI-powered tools can enhance personalized learning, formative assessment, academic writing support, speaking practice, and learner autonomy. However, effective implementation depends on pedagogically informed instructional design, ethical AI use, digital literacy, and the development of authentic assessment strategies that prioritize demonstrated competencies over rote knowledge reproduction. The study argues that AI should function as a pedagogical partner rather than a replacement for educators. It proposes a competency-based model that integrates AI to cultivate higher-order thinking, intercultural communication, and responsible technology use in English language education. The findings offer practical implications for educators, curriculum designers, and policymakers seeking to align language education with the evolving demands of AI-enabled higher education while maintaining academic integrity and human-centered learning.
How learner agency and AI integration shape motivation, interaction, and accuracy in LSP language learning
Tilen Smajla1
Through a survey of 513 university students in a criminal justice and security LSP course, this study investigates the effects of LLMs on language learning and instruction. Four hypotheses on motivation, interaction quality, critical assessment, and integration are tested using non-parametric techniques. Compared to peers who perceive AI as neutral or harmful, students who believe it eases learning report far greater enthusiasm and active involvement (p < 0.001). Interaction quality, prompt effectiveness, and comprehension of AI output are considerably greater among students using AI proactively and autonomously rather than responding to teacher-directed prompts (p < 0.001). No discernible difference emerged in self-reported grammatical correctness between those who critically check AI replies and those who accept them without question (p = 0.72), indicating verification alone does not ensure increased accuracy. Deeper AI integration shows a favorable correlation with overall satisfaction (rho = 0.529) and perceived efficacy (rho = 0.543), both significant at p < 0.001. These results suggest learner satisfaction and engagement in AI-supported language learning are driven by learner agency and perceived utility rather than mere access to AI technologies. Proactive, self-directed AI use may improve interaction quality and motivation more effectively than teacher-controlled, prescriptive adoption. The findings add empirical support to discussions on the pedagogical significance of LLMs while cautioning that critical assessment skills may need pairing with explicit accuracy-focused teaching to produce measurable grammatical gains. Implications for task design, evaluation, and teacher preparation in LLM-integrated courses are examined, offering curriculum designers recommendations for balancing autonomy with pedagogical scaffolding.