Search Results (179)

Over the past decade, developments in artificial intelligence (AI) have sparked a new wave of debate and research across nearly all areas of life, including education. In English as a Foreign Language (EFL) education, AI-based technologies are also widely adopted to support learners and instructors. This trend has led to numerous studies focused on understanding AI’s role in identifying potential opportunities and challenges. This study offers a systematic review of relevant research, highlighting the benefits and obstacles of AI use in the Saudi EFL context. About 60 peer-reviewed articles were selected following PRISMA guidelines. The findings reveal multiple opportunities for AI integration in Saudi Arabia, such as improved language skills, personalized learning experiences, increased self-regulated learning, boosted motivation and confidence among learners, expanded learning opportunities, and support for pedagogy and institutional performance. Major challenges include biased and inaccurate data, students’ overdependence on technology, ethical concerns, and a lack of technological skills among users. The study also suggests future directions, including localizing AI tools, conducting long-term impact studies, providing faculty and student training, and establishing ethical guidelines within institutions. Full article

Reading has long been recognised as a central mechanism for second language development, particularly in English as a Foreign Language (EFL) contexts where exposure to the target language is limited. However, learners do not seem to benefit equally from comparable reading demands, suggesting that factors beyond linguistic competence influence developmental outcomes. This study examines the relationship between reading self-efficacy and English language proficiency among undergraduate students enrolled in a Degree in English Studies at a Spanish university. A cross-sectional quantitative design was employed with a sample of 141 participants and data were collected using the Reader Self-Perception Scale 2 (RSPS2) and a standardised multilevel English placement test aligned with the Common European Framework of Reference for Languages (CEFR). The results revealed a statistically significant positive relationship between reading self-efficacy and language proficiency, whereas literary epistemological beliefs did not show a comparable association. Among the RSPS2 dimensions, perceived Progress and Physiological States emerged as the strongest correlates of proficiency, indicating that learners’ sense of development and emotional comfort while reading is particularly relevant to language achievement. The study argues that reading self-efficacy is related to textual exposure and language development, shaping whether learners engage with texts in sustained and productive ways. By linking learner self-perception to measurable proficiency outcomes, the study contributes empirical evidence to current discussions on affective variables in language learning and offers pedagogical implications for fostering engagement in higher education EFL contexts. Full article

This study examines the integration of generative Artificial Intelligence (AI) tools within a Flipped Classroom model to enhance active learning and feedback processes in an English as a Foreign Language (EFL) teaching program. The participants were 242 pre-service EFL teachers enrolled in upper-level courses at a private university in southern Ecuador. Adopting a mixed-methods, design-based research approach, the study incorporated a diagnostic survey, written reflections, post-intervention survey, and focus groups. These instruments explored students’ prior knowledge, perceptions, and experiences regarding AI-supported learning. Findings showed that AI tools such as ChatGPT, Gemini, and Copilot strengthened students’ linguistic accuracy, writing performance, self-regulation, and understanding of pedagogical concepts. AI-generated feedback complemented teacher feedback by providing immediate and clear guidance, promoting iterative revision and deeper engagement with course content. Participants reported increased autonomy, improved time management, and greater readiness to integrate AI into future teaching practices. The results indicate that AI-supported flipped instruction fosters meaningful learning, enhances feedback quality, and develops both linguistic and pedagogical competencies. Full article

Augmented Reality (AR) has been found to produce significant effects on individual learning outcomes but its impact on collaborative applications remains moderate. Existing AR frameworks emphasize individual instructional design, whereas frameworks for collaborative learning rarely engage with the spatial and device-mediated affordances of mobile AR. In response to this inadequacy in the literature, we introduce the Mobile Augmented-Reality Storytelling for Vocational Education and Training (MARS-VET) framework, a four-dimensional conceptual architecture that integrates Computer-Supported Collaborative Learning (CSCL) scripting principles with mobile AR affordances for collaborative English as a Foreign Language (EFL) writing in Vocational Education and Training (VET) settings. MARS-VET synthesizes theoretical perspectives across four dimensions: contextual anchoring, which embeds activities within authentic workplace scenarios; collaborative orchestration, which structures group interaction through macro- and micro-level scripts; competency cultivation, which sequences writing progression from model-based reproduction toward autonomous professional text production; and capacity building, which addresses the professional-development requirements of implementing educators. Content validity was established through expert panel evaluation involving international specialists (N = 11) who rated the framework against 36 items using a four-point relevance scale and provided additional qualitative feedback. The Scale-level Content Validity Index (S-CVI/Ave = 0.91) exceeded established thresholds, with all four dimensions achieving satisfactory item-level indices. Experts reached unanimous agreement on items addressing workplace scenario identification and co-located access to linguistic resources. Qualitative feedback led to terminology refinements and clarification of orchestration mechanisms. The framework offers VET institutions and educators a reference for the design and evaluation of collaborative AR experiences in an area where integrative frameworks have so far been lacking. Full article

The study aimed to systematically analyze studies published between 2013 and 2025 on the second-grade primary school EFL curriculum in Türkiye. The study identified the strengths and weaknesses of the components of the English curriculum and examined the suggestions proposed regarding implementation issues. In order to answer the research questions, 27 studies were analyzed using content analysis, and their methodological characteristics were reviewed. The analysis revealed that the objectives constituted the strongest component of the second-grade English curriculum, whereas the assessment component was the weakest. The problems with the curriculum implementation include the incompatibility of the curriculum with the Common European Framework of Reference (CEFR) for Languages, insufficient class hours, teachers’ inclusion of reading and writing skills even though they are not included in the learning outcomes, individual differences between students, students’ unpreparedness for foreign language learning, inadequate instructional materials, and parents’ lack of interest in foreign language education. The findings revealed that, while the curriculum is well-structured in terms of its objectives, its effectiveness is hindered by persistent challenges in assessment and implementation. This underscores the importance of improving the alignment between curricular intentions and instructional practices, highlights the need for targeted improvements in assessment practices, and offers practical insights for ongoing curriculum development efforts. Full article

This study examines how levels of emotional awareness are linguistically realized in preservice EFL teachers’ reflective discourse in a foreign language following simulation-based learning (SBL). The data consist of nine semi-structured interviews conducted in English approximately one month after an intercultural simulation workshop. Emotional awareness was assessed using the Levels of Emotional Awareness Scale (LEAS), while linguistic realization was analyzed through an emotionally colored language perspective and a Systemic Functional Linguistics framework. The findings reveal three developmental profiles. Higher emotional awareness was associated with richer emotionally colored language and more frequent hypotactic structures, enabling participants to articulate complex and sometimes conflicting emotional perspectives. Intermediate levels showed more balanced clause organization and greater reliance on repetition as an intensification strategy, reflecting a transitional stage in which the ability to articulate emotionally complex professional experiences is still emerging. Lower levels were characterized by limited emotional vocabulary, frequent repetition, and reduced hypotaxis, indicating an initial stage in which the discursive repertoire has not yet developed. Overall, the findings suggest that emotional awareness and its linguistic realization develop in tandem, and the analysis of these patterns offers insight into preservice teachers’ evolving capacity to process emotionally complex professional experiences in a foreign language. Full article

This qualitative study investigates the challenges teachers face when teaching English as a foreign language (EFL) to deaf (in this article, deaf (lower case) refers to the audiological condition of hearing loss, whereas Deaf (capitalized) is used to denote individuals who identify as members of the Deaf community and share a common sign language and distinct cultural values) and hard-of-hearing (DHH) students in German schools for the Deaf. The study is situated within a structural–theoretical professionalization framework, which focuses on the relationship between institutional conditions, teacher education structures, and professional action. Semi-structured interviews were conducted with 16 teachers of DHH students and the data were examined using qualitative content analysis. The findings reveal five central areas of challenge: (1) heterogeneity of the student body; (2) limited time (for preparing and adapting materials); (3) restricted subject-matter and sign-language competence, including missing links between EFL didactics and Deaf education in teacher training; (4) uncertainties surrounding the language design of EFL instruction, particularly the role of American Sign Language (ASL), German Sign Language (DGS), and written English; and (5) the lack of consistent, accessible exam formats and standards. Teachers report substantial insecurity due to the absence of coherent concepts, policy frameworks, and specialized training pathways, which fosters divergent classroom practices and tensions within teaching staff. The results highlight an urgent need for systematic integration of Deaf education, sign language training, and EFL pedagogy in teacher education, as well as for evidence-based guidelines on language classroom practice and assessment for DHH learners. Full article

While generative artificial intelligence (GenAI) is increasingly used by university students for writing support, less is known about its role in discipline-specific professional tasks. This study examines how pre-service primary teachers integrate and conceptualise GenAI when designing Teaching Units for English for Young Learners (EYL), with a focus on whether AI is positioned as a substitute for pedagogical reasoning or as a support within teacher decision-making. The qualitative study involved 75 fifth-year pre-service teachers at the Free University of Bozen-Bolzano (Italy), working in 23 groups. Data included 23 Teaching Units and 10 AI Use Reports, analysed through document analysis and thematic coding. GenAI was used mainly for material production (visual and text generation, idea generation, and text revision) and resource adaptation, with limited evidence of use for macro- or micro-planning decisions (objectives, sequencing, assessment). Prompts were often underspecified, but reports described iterative refinement and critical adaptation to improve age appropriateness and reduce lexical overload. Overall, within a transparent course framework, pre-service teachers retained pedagogical ownership while using GenAI as a supplementary resource, underscoring the need to develop pedagogically grounded AI literacy (prompt design, evaluation, and disclosure). Full article

Peer feedback is widely used in English as a foreign language (EFL) higher education, yet its benefits are often limited by uneven feedback quality and learners’ difficulty in interpreting and using comments. This theoretical paper synthesizes research on peer feedback, student feedback literacy, and recent developments in generative artificial intelligence (GenAI) to propose a theory-informed design framework that positions GenAI as Trainer and Synthesizer in L2 speaking peer feedback. Building on feedback literacy as a set of capacities (appreciating feedback, making judgments, managing affect, and taking action), the paper argues that speaking tasks create distinct constraints, including time pressure, fleeting performance, and heightened affect, which make real-time peer feedback promising but pedagogically challenging. To address these challenges, here we introduce two complementary roles for GenAI in peer feedback workflows: a Trainer that supports feedback quality through calibration with exemplars, rubric-guided practice, and feedback-on-feedback; and a Synthesizer that aggregates peer input into concise, actionable guidance linked to criteria and learning goals. The conceptual proposal specifies key design principles (e.g., transparency, learner agency, teacher-in-the-loop oversight, and privacy-conscious data practices) and outlines researchable propositions for evaluating learning, engagement, and equity outcomes. The paper concludes with implications for task design, training sequences, and responsible classroom implementation. Full article

Speaking proficiency remains one of the most challenging skills for learners of English as a Foreign Language (EFL), particularly in contexts where sustained spoken interaction is limited. This systematic review synthesises 36 empirical studies (2015–2025) identified through a PRISMA-guided Scopus search to examine how artificial intelligence (AI)-mediated instruction supports EFL speaking development. The included studies were analysed according to AI modality, pedagogical integration, instructional input characteristics, and linguistic and affective outcomes. Findings indicate that AI tools—such as chatbots, automatic speech recognition systems, and large language models—consistently support affective outcomes, including reduced speaking anxiety and increased willingness to communicate. Improvements in fluency, pronunciation, and accuracy were frequently reported, particularly when AI tools were embedded within task-based and pedagogically structured instructional designs. However, evidence for sustained development of higher-order communicative competence was more variable. The review proposes a mediated input framework conceptualising AI as a design-sensitive instructional resource rather than an autonomous teaching agent. Full article

This study investigates the pedagogical value of integrating AI-supported feedback with Error Analysis in university-level English as a Foreign Language (EFL) writing instruction, where English is the target language (TL). Adopting a comparative, corpus-based design, the research examines whether AI-mediated feedback can complement traditional teacher-led Error Analysis in reducing recurrent errors, improving grammatical accuracy, and supporting revision practices among Spanish L1 learners of English at the B2 (CEFR) level. Seventy participants completed two writing tasks over a twelve-week period, generating a learner corpus that was randomly assigned to two groups: AI-assisted feedback and teacher-mediated feedback. Quantitative Error Analysis and learner-perception surveys were conducted to assess both linguistic outcomes and attitudinal responses. Results indicate that students receiving AI-assisted feedback demonstrated lower rates of error repetition (25%) compared to those receiving teacher-based correction (40%), particularly in subject–verb agreement, preposition use, tense selection, and L1-induced lexical transfer in L2 English writing. Survey findings further reveal higher perceived levels of clarity, usefulness, and immediacy for AI-generated feedback, although participants continued to value teacher input for higher-order writing concerns. Overall, the findings suggest that AI-supported Error Analysis can contribute to short-term error reduction and foster learner autonomy. This study highlights the potential of blended and mixed feedback models within a focused pedagogical context and underscores the need for longitudinal research examining long-term retention, pragmatic development, and cross-context generalizability. Full article

Artificial Intelligence (AI) holds transformative potential to revolutionize teaching and learning, yet its rapid integration poses significant challenges for teacher preparation. While AI competencies—encompassing knowledge, skills, and attitudes—are critical for effective integration, limited research has holistically addressed these three interconnected domains. To bridge this gap, this quasi-experimental study (N = 259) evaluated a triadic instructional design synergizing the intelligent technological, pedagogical, and content knowledge (Intelligent-TPACK) framework, Synthesis of Qualitative Data model, and curated AI tools. Pre-service English as a foreign language (EFL) teachers were assigned to an experimental group (n = 137) receiving the structured intervention or a control group (n = 122) engaging in self-directed AI exploration. Results reveal that the experimental group achieved greater gains across all Intelligent-TPACK dimensions and demonstrated higher-order AI applications in lesson planning. Furthermore, the experimental group experienced a significant reduction in perceived pressure and reported higher perceived usefulness regarding AI integration. Qualitative data revealed that hands-on AI tasks enhanced participants’ confidence, yet challenges with prompts and critical adaptation persisted. The findings demonstrate that systematic training is essential for transforming pre-service teachers’ passive awareness into competent AI integration. Finally, this paper proposes practical implications for integrating this triadic framework into teacher education curricula to facilitate sustainable AI adoption. Full article

This study examines the effectiveness of a purposefully constructed Foreign Language Learning Environment (FLLE) in developing foreign language communicative competence within Kazakhstani higher education. Focusing on four interrelated components—pedagogical resources, physical learning space, motivational strategies, and ICT integration—the study addresses the limited opportunities for authentic English communication characteristic of EFL contexts. A quasi-experimental design involving 69 undergraduate students was employed, with participants divided into experimental and control groups. Statistical analysis using the Mann–Whitney U test revealed significantly higher post-test results in the experimental group, particularly in speaking performance. The findings demonstrate that communicative competence development can be significantly enhanced when (1) instructional materials prioritize authentic, task-based communication, (2) classroom spaces are organized to facilitate face-to-face interaction, (3) motivational support is provided through speaking activities and extracurricular activities, and (4) ICT tools, including conversational AI, are used to extend communicative interaction beyond classroom time. Full article

Recent research suggests that artificial intelligence (AI) tools allow EFL (English as a Foreign Language) learners to exert greater control over their language-learning process. Furthermore, these tools enhance their language skills by providing them with elements often absent in traditional classroom settings, such as autonomy and individual pace of learning. Specifically, AI-based tools, such AI chatbots, have the potential to facilitate learning and streamline tasks for both students and instructors in language-learning contexts. These digital companions (i.e., chatbots) can be methodically crafted and equipped with the required essential materials to support students in practising language skills independently, regardless of time or location. The current study presents an experiment conducted with undergraduate students at a university in Saudi Arabia to assess the effectiveness of a customised AI chatbot, WritePro (GPT-4), in improving their writing skills. Learners in the experimental group were instructed to use WritePro to navigate through their writing stages, focusing their queries on four key components: content and organisation, grammar mechanics, vocabulary usage, and sentence structure. The findings showed that WritePro serves as an effective tool for EFL learners to overcome several challenges in developing writing competencies. Therefore, the significance of these findings lies in the potential of AI tools to enable EFL instructors to effectively integrate chatbots into classroom instruction, supporting the development of students’ writing skills. Furthermore, these findings can be used as a basis for advocacy with university policymakers regarding the use of AI chatbots in language classrooms. Full article

Language Assessment Literacy (LAL) is critical for teachers to perform their assessment tasks, but many teachers in low-resource contexts do not receive adequate assessment training. This qualitative multiple-case study examined the impact of a short-term Professional Development (PD) program on three in-service English as a Foreign Language (EFL) teachers in developing their LAL and in shaping their assessment conceptions, knowledge and practices as assessors. The PD training program consisted of a 30 h workshop delivered over one week and integrated theory, practice, collaborative learning, reflection, and feedback. Data collection instruments included classroom observations and interviews. Findings showed that the PD program improved teachers’ LAL by developing their assessment conceptions, knowledge, skills, and confidence, although the degree of improvement varied across participants. The findings also identified challenges teachers encountered in their assessment practices, including limited time, large class sizes, insufficient resources, and sociocultural factors that constrained teachers’ assessment conceptions and restricted their LAL development. The findings showed that PD programs could strengthen teachers’ professional identity as assessors by incorporating relevant content, practice opportunities, feedback, a supportive learning community, and self-reflection. The study findings have broader implications for professional development of LAL in other low-resource and exam-oriented EFL contexts with strong sociocultural constraints. Full article