The introduction of generative artificial intelligence (GenAI) has created new opportunities to support L2 speaking instruction and development. However, empirical evidence is needed to establish its pedagogic value in higher education contexts, particularly for cognitively demanding second-language (L2) speaking tasks. This study investigates the effects of ChatGPT-mediated instruction on the use of oral communication strategies (OCSs) and discourse markers (DMs) during an academic debate session. Using a quasi-experimental design, a total of 56 Hungarian English as a Foreign Language (EFL) undergraduates were assigned to two instructional conditions: a GenAI-assisted experimental group and a non-GenAI-assisted control group. Data were collected through a posttest debate task and analysed using a combination of quantitative and qualitative techniques. The results indicated significant differences in the deployment of OCSs and DMs between the two instructional conditions. In particular, our analysis revealed an interesting contrast between the strong focus on fluency-maintenance and discourse-organisational devices in the control group as opposed to the preponderance of direct-interactional strategies alongside a wide range of DMs in the experimental group. The findings suggest a potentially beneficial role for ChatGPT-mediated instruction in the development of strategic competence and discourse-level awareness. These GenAI affordances, however, presuppose careful teacher mediation within a progressive instructional design that moves from AI-supported rehearsal to peer- and group-based interaction.
Although feedback is widely regarded as one of the most influential variables in student learning, its effects on writing development remain highly variable and poorly understood, partly because the relational dimensions of feedback delivery have received limited empirical attention. This quasi-experimental, explanatory sequential mixed-methods study examined whether an Empathic Feedback Protocol (EFP), operationalising teacher empathy through three theoretically grounded dimensions (Seeing, Understanding, and Caring), produces superior outcomes in writing quality, self-efficacy, and feedback receptivity compared to conventional rubric-based feedback. Post Foundation undergraduate students in a Technical Writing course at a university in Oman were assigned to experimental or comparison conditions across an eight-week email writing programme. Writing quality was assessed using an institutional rubric; self-efficacy and receptivity were measured at three time points using validated scales; and student perceptions of feedback empathy were assessed using the EFRS-S, an instrument developed for this study. Qualitative data from semi-structured interviews and written reflections were analysed through reflexive thematic analysis and integrated with quantitative findings via joint display. Results indicated large condition effects on writing quality, with the greatest gains on higher-order criteria. Self-efficacy and feedback receptivity trajectories diverged significantly across conditions after the midpoint, with the experimental group sustaining growth while the comparison group plateaued. Hierarchical regression revealed a theoretically meaningful dissociation: Understanding was the dominant predictor of writing quality, while Caring predicted motivational outcomes. Qualitative themes corroborated these patterns and surfaced an emergent metacognitive transfer effect, with students spontaneously applying the EFP framework as a self-monitoring strategy during drafting. Findings suggest that teacher empathy, when systematically operationalised, is a consequential and teachable pedagogical variable with direct implications for feedback practice in EFL technical writing contexts.
Generative artificial intelligence (GenAI) is among the most consequential recent innovations in language education, yet little is known about how teachers sustain engagement with it over time. Research has documented teachers' initial perceptions of and attitudes toward AI tools, but how teachers continuously regulate the emotional tensions arising as GenAI becomes embedded in everyday professional practice remains underexplored. This mixed-methods study examines emotional regulation as an ongoing professional process through which language teachers negotiate GenAI integration. Using a sequential explanatory design, survey data from 34 language teachers working in varied international settings, from schools to universities and private language institutes, mapped how teachers engaged with GenAI and the emotional tensions this generated. These findings then informed in-depth interviews with seven participants at two time points approximately six months apart, tracing how emotional tensions shifted as professional engagement deepened. Guided by the Language Teacher Emotion Model (LTEM), the findings reveal sustained emotional ambivalence as the defining feature of teachers' experience: the creative possibilities GenAI opened up were persistently shadowed by anxiety, ethical unease, and professional uncertainty. These tensions were seldom resolved through acceptance or rejection; instead, teachers drew on regulatory practices that allowed them to incorporate GenAI selectively while protecting their sense of professional competence and identity. Emotional regulation, in this sense, functioned as a form of active professional positioning. The study reframes GenAI integration as a process of affectively mediated professional adaptation and points to the need for institutional support that attends to the emotional dimensions of innovation in language teaching.
The psychological well-being of language teachers has increasingly been recognized as a critical factor influencing both instructional quality and professional sustainability. However, limited attention has been given to empirically grounded interventions tailored to the specific needs of English as a Foreign Language (EFL) teachers. This study examined the effects of an eight-week mindful journaling and reflection program on the well-being and resilience of Iranian EFL teachers using a randomized controlled trial design. Forty teachers were assigned to either an intervention or wait-list control group, with outcomes measured at baseline, post-intervention, and four weeks later. Psychological well-being was assessed using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and resilience was measured using the 25-item Connor-Davidson Resilience Scale (CD-RISC). Mixed-design ANOVAs revealed statistically significant improvements in well-being (F (1, 38) = 13.89, p = .001, η2 = .268) and resilience (F (1, 38) = 20.99, p < .001, η2 = .356) in the intervention group, with gains maintained at follow-up. Thematic analysis of participants' journal entries and open-ended responses revealed three key domains of change: emotional self-regulation and inner calm, reconnection with professional purpose, and awareness of personal growth and strength. These findings suggest that structured mindful journaling can serve as a feasible, low-cost intervention to enhance psychological resilience and well-being among language teachers. The study contributes to the growing body of literature on language teachers' well-being by providing context-specific evidence for the use of reflective writing as a vehicle for teacher mental health support.
Digital Multimodal Composing (DMC) represents a significant pedagogical shift in Second Language (L2) writing, transitioning from monomodal text to multimodal semiotic orchestration. While DMC has gained global traction, research on its application in Vietnam remains limited, indicating a need to understand how individual lecturers make sense of its still peripheral status in their own teaching contexts. This qualitative multiple-case study (Stake, 2006) examines how three Vietnamese English as a Foreign Language (EFL) lecturers conceptualize DMC integration through metaphor analysis. Treating each participant as a bounded case, cross-case synthesis identified three metaphorical frameworks: the "Staircase" (systematic institutionalization), the "Evening Gown versus Swimsuit" (context-appropriate selection), and the "Spiral" (iterative refinement). Across these three cases, the metaphors point to an emergent "structural trilemma". This trilemma is conceptualized as an interpretive construct rather than a fully established model, encompassing institutional barriers such as assessment misalignment and infrastructure gaps, pedagogical integrity concerns related to skill-erosion fears, and tensions between engagement and academic rigor. Findings indicate that, for these participants, DMC was positioned as supplementary rather than a replacement for print-based writing, reflecting a locally rational adaptation to systemic constraints. Implications emphasize cautious assessment reform and genre-differentiated application, with the recognition that broader multi-site research is needed before stronger claims can be made.
