Search Results (241)

Teachers in increasingly multilingual EFL classrooms must select tasks that align with language-learning evidence, learner diversity, and classroom feasibility. Yet we know comparatively little about the real-time criteria teachers use when choosing between task options that differ in multilingual pedagogical affordances. This exploratory qualitative study used concurrent think-aloud protocols to examine EFL teachers’ in-action reasoning during task selection. Ten secondary-school EFL teachers from southern Germany and Austria evaluated eight paired task scenarios, each presenting two options that differed in their potential to leverage learners’ multilingual repertoires, for example, through cross-linguistic comparison and support for form–meaning mapping. Transcripts were coded using an iterative scheme capturing methodological orientation, language-related considerations (learner repertoire, teacher language competence, and languages involved), perceived cognitive manageability, and feasibility concerns. Teachers’ selections were analysed as alignment with the option classified by the authors as higher in multilingual pedagogical affordances, rather than as objectively “correct” versus “incorrect” choices. Cross-case analyses indicate that decisions clustered around recurring constraints between perceived clarity and manageability, target-language-only norms, and openness to multilingual mediation. The findings contribute a process-orientated account of teacher decision-making in multilingual task selection and identify reasoning patterns that may constrain uptake of multilingual pedagogical opportunities in everyday EFL instruction. By applying concurrent think-alouds to scenario-based task selection, we identify three recurring influencing factors of decision-making (manageability filtering, target-language legitimacy norms, rule-first ‘teachability’ cues) that appeared to constrain multilingual task uptake in the present scenario-based protocols whose process-oriented account of teacher reasoning is the primary focus of the project, while the methodological and practical implications are secondary. Full article

Critical thinking (CT) is a core competence that schools are expected to cultivate, yet whether it reaches classrooms depends on teachers’ readiness to teach it. Using an explanatory sequential mixed methods design, we surveyed 312 primary English-as-a-foreign-language teachers in Shandong Province, China, across seven dimensions of readiness and interviewed five teachers. Latent profile analysis identified four profiles organized by two weakly related dimensions—the capacity teachers bring to CT teaching and the constraints they perceive around them: Empowered-Engaged (15%), Willing-but-Constrained (28%), Moderate-Unobstructed (20%), and Committed-but-Under-resourced (37%). Endorsement of CT was near-universal, so the profiles differed in capacity and circumstance rather than in commitment. The central finding is a disconnection between what teachers believe and what they report doing: Willing-but-Constrained teachers wanted further professional learning as much as their Empowered-Engaged peers did, yet reported teaching CT less often. The divergence held under methods that account for classification uncertainty and under alternative measurement specifications, though not under all of them, and profile membership was largely unrelated to teachers’ background characteristics. The interview findings help explain why positive beliefs about CT did not always correspond to classroom practice. Teachers reported limited CT-specific training, examination pressure, time constraints, and norms that discouraged questioning, despite generally recognizing the value of CT. This suggests that the main barriers to CT instruction may lie not in teachers’ attitudes toward CT, but in their opportunities, preparation, and working conditions for implementing it. Full article

The intersection of artificial intelligence (AI) and gamification in language education has attracted increasing attention, but its link to sustainability is still largely unexamined. This study looks at whether and how much this area of research tackles two aspects of sustainability: the ability of AI-driven gamified tools promoting lasting independent language learning (pedagogical sustainability) and their potential to reduce educational inequalities in line with Sustainable Development Goal 4 (SDG 4) (social sustainability). Using a sequential explanatory mixed-methods design, a bibliometric analysis of 105 documents retrieved from Scopus and Web of Science (WoS) (2018–2026), processed with bibliometrix R package (4.6.0) and VOSviewer (1.6.20), and a thorough qualitative content analysis of 27 studies were combined. The bibliometric mapping uncovered four thematic clusters around gamification design, motivational theory, serious games, and AI-driven vocabulary learning. No sustainability-related terms had enough density to form a clear cluster. The qualitative analysis showed that SDG 4 is missing from all 27 reviewed documents. Only three (11.1%) operationalizing pedagogical sustainability and mediation as a CEFR competence are absent. These findings suggest that sustainability is still on the fringe of this field and support a research agenda focusing on long-term measurement, self-directed learning support, low-resource design and mediation in AI-driven gamified environments. Full article

Self-efficacy, a person’s belief in their capability to carry out a given task, shapes whether teachers attempt, persist with, and transfer new practices. Yet teachers’ perceived capability to use generative AI (GenAI) is often treated as a single general readiness rather than examined across the distinct domains in which it is now used. Guided by Bandura’s self-efficacy theory, this study provides a domain-differentiated account of GenAI competency self-efficacy among university teachers of English as a Foreign Language (EFL) in the Saudi higher-education context. A sample of 232 EFL teachers at Saudi public universities completed a contextually adapted version of the Generative AI Competency Self-Efficacy Scale for Teachers and Researchers (GAICS-TR). Data were analysed using repeated-measures analysis of variance, correlational analyses, and hierarchical multiple regression. Overall self-efficacy was only slightly above the scale midpoint, and the overall score concealed an uneven pattern across domains. Teachers felt most capable in Basic GenAI Understanding and Teaching with GenAI, less so in Professional Engagement, and least confident in Research with GenAI, with the lowest confidence reported for data analysis. Prior AI training and frequency of GenAI use were associated with overall self-efficacy, whereas teaching experience and academic rank were not. The findings suggest that overall measures of GenAI readiness can mask lower-confidence areas within specific domains, especially in research-facing uses such as data analysis. Accordingly, supporting teachers’ development in using GenAI calls for targeted, domain-sensitive professional development that reaches teachers at all career stages rather than broad familiarisation with the tools. Full article

A persistent challenge in teacher education is that intern teachers often struggle to effectively apply theoretical knowledge to classroom practice. While constructing practical knowledge is key to bridging this gap, current research has paid insufficient attention to the dynamic processes and triggering mechanisms through which such knowledge develops among Chinese as a Foreign Language (CFL) intern teachers during the internship stage. This study focuses on the “key events” encountered by 7 CFL intern teachers participating in an online internship program at a teacher education institution in Northeast China, through 83 class observations and semi-structured interviews. Using qualitative analysis methods, it explores the content, influencing factors, and mechanisms of practical knowledge construction. The results show that CFL intern teachers generated seven types of practical knowledge. Among them, teaching belief knowledge was the most frequently coded category (20.5%), while teaching context knowledge was the least frequently constructed (6.7%)—a pattern largely attributable to the online teaching environment in which all internships were conducted. Negative key events outnumber positive events in terms of quantity, depth of reflection, and persistence of impact. Reflection is the core mediating mechanism connecting key events and knowledge construction, but the “reflection-in-action” ability of intern teachers is weaker than that of expert teachers. This study reveals the dynamics and cross-cultural particularity of practical knowledge construction for CFL intern teachers, providing empirical evidence for optimizing teacher education internship training. Full article

Learning vocabulary is central to learning a second or foreign language (henceforth L2). L2 vocabulary research shows how individual differences (IDs), such as metacognitive elements, motivational factors, and strategy use, contribute to vocabulary learning and acquisition. L2 vocabulary learning that incorporates IDs is often discussed in relation to the internalized vocabulary learning process, including how L2 learners acquire vocabulary by sustaining motivation, using vocabulary learning strategies, and regulating learning processes. The associations between the IDs and vocabulary learning have often been examined within the framework of self-regulated learning (SRL). However, discussions on how SRL processes are reinforced through co-regulated or socially shared learning with others and within social contexts remain scarce. In this article, we introduce a sociocultural perspective on strategic vocabulary learning. Specifically, we discuss how the internalized processes of self-regulated vocabulary learning can be socially constructed through co-regulation and socially shared regulation. The proposed framework has the potential to provide future research agendas and instructional practices in L2 vocabulary learning and teaching. We conclude by proposing directions for future research on the socially constructed nature of strategic vocabulary learning. 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

Visual learning is a valuable resource in inclusive educational settings. This study aims to analyse the effectiveness of using visual tools and media in the teaching process in primary schools, with a particular focus on foreign pupils. A mixed-methods approach was employed, integrating quantitative (pre–post tests) and qualitative (interviews and observations) methods to evaluate the impact of visual teaching on language comprehension, participation, and sense of belonging to the school. The results revealed significant improvements in learning and motivation, particularly among students from migrant backgrounds. 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

Education for Sustainable Development (ESD) plays a vital role in addressing global sustainability changes, and foreign language teaching may contribute to this process. Nevertheless, studies on the incorporation of Sustainable Development Goals (SDGs) in materials related to teaching Turkish as a Foreign Language (TTFL) are limited. This study examines the representation of the 17 SDGs in TTFL textbooks. A qualitative document analysis was conducted on the A1, B1, and C1 levels of the “Yeni İstanbul” textbook series across the social, economic, and environmental dimensions of sustainability. The findings indicate a hierarchical distribution of SDG-related content across proficiency levels. At the beginner (A1) level, the social dimension with emphasis on urban integration themes (78.09%) is dominant, while at the advanced (C1) level, the economic dimension becomes more prominent (43.17%). The most striking result is that the environmental dimension remains the weakest area at all levels (A1: 6.67%; B1: 9.95%; C1: 10.93%). Environmental issues primarily appear as contextual vocabulary rather than critical sustainability content. Although the textbooks support socio-economic integration, they show limited alignment with sustainability literacy goals. The findings highlight the need for a more comprehensive integration of environmental sustainability themes in foreign language curricula. Full article

This study explores the digital competence of foreign language teachers in Bulgarian secondary education by focusing on the institutional context of which they are a part, the strengths and gaps of their competence, and their levels of competence. It draws upon empirical data that were collected and analyzed within an integrated, dual-instrument framework, combining the SELFIE (Self-reflection on Effective Learning by Fostering the Use of Innovative Educational Technologies) and SELFIE for TEACHERS (Self-reflection on Effective Learning by Fostering the Use of Innovative Educational Technologies for Teachers) EU-aligned assessment tools. The results from the questionnaire data show that the foreign language teachers state that they work in a relatively good technological environment and evaluate the usage of digital technologies for teaching and communication purposes within the school context as a salient aspect of their digital competence. The results also reveal three areas in the study participants’ digital competence that are in need of improvement: (1) empowering learners/personalizing the educational process, (2) assessment and (3) facilitating learners’ digital competence. In addition, the findings indicate that the foreign language educators rate their digital competence at a low to medium level. By blending institutional and teacher-oriented perspectives into a single integrated study of Bulgarian secondary school foreign language teachers, this investigation extends the existing research and makes evidence-based recommendations for institutional capacity building, teacher education policy and targeted professional development aimed at improving the educators’ digital competence. 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

The pedagogical efficacy of artificial intelligence (AI) technologies in education heavily depends on cultural, technological, and cognitive contexts. Prior studies examined AI-driven learning outcomes without accounting for cultural variability or sufficiently anchoring their analyses in robust theoretical frameworks. The current study discusses the interconnection between AI technologies, learner competencies, and educational outcomes, in addition to the significance of digital and media literacy in secondary foreign language teaching. It employs Hofstede’s cultural dimensions theory, the technology acceptance model, and sociocultural learning theory to examine how AI technologies affect learning outcomes of English as a foreign language among Lebanese high school students. One hundred and eighty high school students in Mount Lebanon were given a 20-item survey using a quantitative research design. The results were analyzed using statistical tests and analyses in SPSS version 27.0.1. The findings indicate that AI technologies significantly enhance student learning outcomes: affective and motivational outcomes (45%), social and collaborative competencies (35%), and English language proficiency (accounting for 43% of variance). Furthermore, these relationships are strongly moderated by digital and media literacy, which increases the beneficial effects of AI on learning outcomes. The findings also show that students’ opinions, engagement, and acceptance of AI-supported language learning are influenced by cultural traits. Full article

This study comparatively assessed the quality of organically and commercially produced turkey meat roasted to internal temperatures of 72 ± 2 °C, 80 ± 2 °C, and 88 ± 2 °C. The evaluation encompassed physical characteristics (pH, WHC, and colour), nutritional value (protein, ash, dry matter, fat and fatty acid profile and caloric value), and sensory characteristics. Thermal processing caused significant differences in the properties of the meat depending on the production system. After thermal processing, organic meat had a more favourable lipid profile (higher MUFA, PUFA and n-3 PUFA content and lower SFA content) compared to conventional meat, which indicates its potential nutritional advantage. The most favourable technological and sensory parameters, in this system, were obtained at an internal temperature of 80 ± 2 °C, while an increase to 88 ± 2 °C resulted in a deterioration in tenderness and juiciness. In commercially farmed meat, the best tenderness was found at 72 ± 2 °C and the highest aroma and flavour ratings at 80 ± 2 °C. The use of a temperature of 88 ± 2 °C led to an increase in cutting force, greater loss and reduced sensory quality. The results indicate the validity of differentiating the heat treatment parameters depending on the origin of the raw material. Full article