مطالب

Listening comprehension remains a persistent challenge for non-English major students, often due to passive learning approaches, limited interactive engagement, and ineffective assessment methods. Traditional formative assessment lacks real-time feedback and adaptive mechanisms, hindering students’ ability to monitor progress and develop effective listening strategies. To address these drawbacks, the current study examines the implementation of an AI-integrated gamified formative assessment in enhancing listening comprehension among the 38 first-semester students at Universitas PGRI Delta Sidoarjo, a private university in East Java, Indonesia. Employing a sequential mixed-methods approach, data were collected from a closed-ended questionnaire measuring dimensions of engagement, motivation, and self-regulation, alongside structured interviews with six selected students to gain deeper insights. The findings reveal that the AI-integrated gamified platform fosters a more interactive and engaging learning experience, with students demonstrating increased autonomy and strategic listening behaviors. The instant feedback and adaptive challenges contributed to improved comprehension, particularly in recognizing key information and inferring meaning from context. However, some participants expressed difficulties in adapting to the dynamic nature of the platform, citing cognitive overload and challenges in managing time constraints within the game-based environment. Additionally, variations in AI-generated feedback quality occasionally led to confusion in interpreting certain listening tasks. These findings suggest that while AI-integrated gamification enhances listening comprehension, further refinements in feedback accuracy and cognitive load management are essential to optimize its pedagogical impact. The study provides critical insights for educators and developers in designing AI-driven gamified assessment tools that effectively support listening comprehension development for non-English majors.

The rapidly growing influence of artificial intelligence (AI) is poised to fundamentally transform the realm of English as a Foreign Language (EFL) instruction. This research studied this emerging trend through a qualitative research synthesis of 24 peer-reviewed articles published between 2021 and 2024. It examined them to highlight the diverse applications, challenges, and teaching practices associated with AI in EFL education. Methodological rigor was ensured through established inclusion and exclusion criteria for selecting the articles. The qualitative synthesis and thematic analysis revealed five prominent themes that illuminate the current landscape of AI in EFL instruction: 1) conceptualizations of AI within EFL settings; 2) factors influencing its adoption; 3) challenges faced when integrating AI into EFL settings; 4) limitations of AI-based tools and methods; and 5) potential avenues for future investigation. Although integrating AI into EFL pedagogy is still in its early stages and presents various challenges, the findings provide valuable insights and practical recommendations for effectively using AI in EFL education, enhancing teaching methods, and improving student learning outcomes. Educators can make informed decisions regarding its implementation while navigating the evolving EFL instruction landscape by cultivating an understanding of AI's potential benefits and inherent limitations.

Jam (2020) attempts to provide an Optimality-Theoretic analysis of Persian vowel harmony. As to cases where backness harmony does not appear to occur, his explanation appeals to Lexically Specific Constraint Theory, treating these instances as exceptional rather than systematic. In this reply, I argue that such an appeal to exceptionality is unnecessary, and I propose an alternative analysis in which regressive vowel harmony in Persian can be accounted for in a principled, unified manner without recourse to lexically indexed constraints. By introducing an appropriately formulated markedness constraint, it becomes possible to capture the full range of observed patterns while maintaining the parsimony and explanatory elegance expected of an Optimality-Theoretic framework. In addition to this central point, I identify several further weaknesses in Jam’s analysis. These include a conflation of rule ordering with constraint ranking, which obscures the theoretical distinction between derivational and constraint-based approaches, the problematic assumption that the phonological representation of loanwords should mirror their source-language forms, and the omission of critical information in both the representations and tableaux.

Objective : Athlete burnout remains a significant concern in competitive sports, with growing evidence highlighting its detrimental effects on performance and mental health. This study examined the efficacy of a Choice Theory-based intervention in reducing burnout symptoms by enhancing autonomy and psychological need satisfaction among elite athletes. Method: Using a longitudinal, randomized controlled design, 156 elite athletes (aged 18–32) from endurance, team, and skill-based sports were allocated to either an 8-week Choice Theory intervention group or a control group receiving standard mental skills training. The intervention incorporated weekly workshops on need identification, cognitive restructuring ("choose to" vs. "have to" thinking), and autonomy-supportive goal setting, alongside coach training in autonomy-supportive communication. Burnout was assessed using the Athlete Burnout Questionnaire (ABQ), while psychological needs were measured via the Basic Psychological Needs Satisfaction in Sport Scale (BPNSSS). Physiological markers (salivary cortisol, heart rate variability) provided objective stress indicators. Results : Results demonstrated significant reductions in emotional exhaustion (p < 0.01, d = 0.72) and sport devaluation (p < 0.05, d = 0.54) in the intervention group compared to controls at 12-month follow-up. Mediation analysis revealed that increased autonomy (β = -0.38, p < 0.001) and competence (β = -0.29, p < 0.01) fully mediated burnout reduction. Physiological data corroborated these findings, with improved HRV recovery (p < 0.05) and lower cortisol levels (p < 0.01) in the intervention group. Conclusions : These findings support Choice Theory as an effective framework for athlete burnout prevention, emphasizing the critical role of autonomy-supportive environments in sustaining long-term athlete well-being. The study advances current practice by demonstrating that structural changes in coaching approaches—particularly empowering athletes with meaningful choices—can significantly mitigate burnout risk. Future research should explore the generalizability of these effects across diverse athletic populations and cultural contexts.