Journal of Language and Education

Introduction: Oral corrective feedback (OCF) is widely recognized as crucial for second language learning, yet its effectiveness depends significantly on learners' receptivity and beliefs. Existing instruments for measuring OCF beliefs face methodological limitations: they rely on abstract, theory-driven terminology that may be misinterpreted by learners, impose researcher-generated factor structures that may not reflect authentic learner perspectives, and carry culture-bound interpretive burdens that limit cross-cultural comparability. Purpose: This study develops and validates a scenario-based instrument for measuring learner beliefs about OCF that prioritizes accessibility and ecological validity by presenting concrete classroom situations rather than abstract terminology. The two-phase validation approach employs exploratory factor analysis (EFA) to identify how learners naturally organize their beliefs, followed by confirmatory factor analysis (CFA) to validate the discovered structure. Method: A 50-item scenario-based questionnaire was developed through expert review and pilot testing, then administered to 668 B2-level English learners in a Turkish university preparatory program. The sample was randomly split: EFA was conducted on the first subsample (n = 334) using principal axis factoring with oblimin rotation, and CFA was performed on the holdout sample (n = 334) to validate the factor structure. Results: EFA identified a six-factor structure explaining 61.4% of variance: Affective Response to Correction (strongest dimension, α = .85), OCF Type Preferences (α = .87), Correction Timing Preferences (α = .81), Context-Sensitive Correction (α = .79), Correction Source Preferences (α = .72), and OCF Uptake and Response (α = .76). CFA confirmed the six-factor solution with acceptable fit indices (CFI = .91, TLI = .90, RMSEA = .06, SRMR = .07). Notably, learners organized correction types by experiential familiarity rather than theoretical distinctions (input-providing vs. output-prompting), and affective considerations emerged as central rather than peripheral to belief systems. Conclusion: The scenario-based approach yields accessible items that reduce culture-bound interpretive burden and enhance cross-cultural comparability. The identified dimensions—affect, type, timing, context, source, and uptake—map onto decision points common to EFL/ESL classrooms globally, offering a scalable measurement model for comparative research across educational systems. Findings encourage pedagogy that is adaptable to context, sensitive to affect, and aligned with how learners actually experience correction. Future research should test measurement invariance across diverse cultural and linguistic settings to establish international applicability.

Background. The problem of verb aspectual pairs in Russian studies remains relevant and still causes discussion, despite the large number of studies conducted. Triplets attract intense interest due to their special position in the system of aspectual forms and the implicitness of an aspectual pair of verbs in the triple. Another fundamental issue that causes a lot of discussion is the so-called hypothesis of empty prefix. Purpose. The purpose is to obtain objective quantitative evaluation of the semantic distance between the verbs in triplets: the basic imperfective verb, the perfective verb, and the secondary imperfective verb. The main problem we solve is which of the two imperfective verbs is semantically closer to the perfective verb, i.e. which pair is aspectual. Materials and Methods. So far, there have been no operational methods for determining verb aspectual pairs. With the advent of large text corpora and Language Models technology, it has become possible to evaluate the semantic similarity of words using rigorous methods. To solve the issues, the computational technique of embeddings (vector semantics) is used. The present study covers 440 triplets. The data on their frequency and collocations were taken from the Russian subcorpus of the Google Books Ngram database. Results. For both language models applied, statistical test shows greater semantic similarity for the pairs of perfective and secondary imperfective than for the pairs of basic imperfective and perfective. According to one or both of the models, for most of prefixes considered, the average distance between the pairs of basic imperfective and perfective is statistically significantly greater than between the pairs of perfective and secondary imperfective. Conclusion. The article presents quantitative analysis of identity of semantics in aspectual pairs of triplets. Secondary imperfective verb form is shown to be statistically closer to the perfective verb than basic imperfective form. This is an argument in favor of the point of view that secondary imperfective verbs form aspectual pairs with perfective verbs. Also, the models applied show that prefixes contribute to the semantics of the perfective verbs. This fact stands against the hypothesis of empty prefixes.

Background: Artificial Intelligence (AI) is increasingly integrated into school-based English as a Foreign Language (EFL) instruction, yet the mechanisms through which it shapes learners’ engagement, achievement, and satisfaction remain insufficiently theorised. Although prior studies report positive effects, they rarely explain how AI influences learning processes within authentic classroom conditions. Purpose: This systematic review synthesizes empirical evidence to explain how and under what conditions AI technologies shape engagement, achievement, and satisfaction in school EFL contexts. Specifically, it aims to identify the mediating cognitive, affective, and behavioural mechanisms through which AI operates, examine contextual moderators influencing its effectiveness, and develop an integrative AI Impact Pathways Framework to guide theory-driven research and context-sensitive pedagogical design. Method: A comprehensive search across seven databases yielded 99 records; following PRISMA 2020 procedures, 23 empirical studies involving direct AI use by K–12 EFL learners were retained. Thematic synthesis was employed to identify cross-study patterns and inductively develop a multi-pathway explanatory framework. Findings: AI tools—including NLP-based feedback systems, intelligent tutoring systems, conversational agents, gamified applications, and adaptive learning platforms—enhanced engagement by increasing interactivity, reducing anxiety, and sustaining time-on-task. Achievement gains were associated with personalised scaffolding, iterative feedback loops, and opportunities for authentic language use across speaking, reading, writing, and vocabulary learning. Satisfaction improved when AI supported autonomy, emotional reassurance, and perceptions of usefulness. Three interrelated pathways—cognitive, affective, and behavioural—mediated these outcomes, while teacher readiness, digital infrastructure, cultural–linguistic fit, student digital literacy, and cognitive load served as five significant contextual moderators. Implications: The review advances theoretical understanding by proposing the AI Impact Pathways Framework in School EFL Learning, which clarifies how AI affordances interact with pedagogical processes and contextual conditions to shape learner outcomes. The findings provide guidance for designing equitable, context-sensitive AI integration in schools and highlight the need for longitudinal, cross-cultural, and theory-driven research.

Background: The rapid global expansion of English-Medium Instruction (EMI) has transformed higher education, particularly in business programs that require students to master complex disciplinary knowledge while overcoming language-related barriers. EMI students must simultaneously overcome linguistic, cognitive, and cultural barriers, which can increase academic stress, reduce participation, and negatively impact learning outcomes. Despite these challenges, most EMI research has relied on correlational models emphasizing self-efficacy, motivation, or language proficiency, while overlooking psychological constructs that capture students’ ability to manage daily academic stressors. Academic buoyancy, as the capacity to persist through routine academic setbacks offers a theoretically robust and practically relevant lens for understanding student adaptation in multilingual learning environments. Purpose: This study examines academic buoyancy as a mediating mechanism linking teaching effectiveness to deep learning outcomes in EMI business education. Drawing on academic resilience theory, interaction theory, and self-regulated learning theory, we investigated predictors of academic buoyancy and tested whether it mediates the relationship between teaching effectiveness and deep learning. Method: Data were collected via cross-sectional survey from 215 international students enrolled in EMI business courses at a South Korean university. Multiple regression analysis identified predictors of academic buoyancy, and Hayes’ PROCESS macro with 5,000 bootstrap samples tested mediation pathways. Results: Learner-professor interaction (β = .163, p < .001), teaching effectiveness (β = .146, p < .001), and cognitive engagement (β = .102, p = .006) significantly predicted academic buoyancy, collectively explaining 30.6% of the variance. Mediation analysis demonstrated that academic buoyancy fully mediated the relationship between teaching effectiveness and deep learning (indirect effect = .071, p < .05; 95% CI [.012, .130]), with no significant direct effect (β = -.023, p > .05). Notably, peer interactions, content engagement, and metacognitive self-regulation did not significantly predict academic buoyancy after controlling for other variables. Conclusion: Academic buoyancy served as a key psychological mechanism through which teaching effectiveness influences deep learning in EMI contexts. The findings suggest that effective EMI pedagogy operates primarily by fostering student resilience rather than through direct content transmission, with practical implications for faculty development emphasizing both relational and pedagogical dimensions of instruction.