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This study aims to investigate the relationship between cognitive failures, sense of coherence, and academic resilience in children with speech impairments. The objective is to determine how cognitive and psychological factors predict resilience in this population. A cross-sectional design was employed, involving 376 children with speech impairments, aged 8 to 12 years. Participants were recruited from special education centers and mainstream schools. Academic resilience, cognitive failures, and sense of coherence were measured using the Academic Resilience Scale (ARS-30), Cognitive Failures Questionnaire (CFQ), and Sense of Coherence Scale (SOC-29), respectively. Pearson correlation analysis examined the relationships between variables, and linear regression analysis determined the predictive value of cognitive failures and sense of coherence on academic resilience. Data analysis was conducted using SPSS version 27. Descriptive statistics indicated moderate levels of academic resilience (M = 78.45, SD = 11.32) among participants. Cognitive failures (M = 43.29, SD = 9.87) negatively correlated with academic resilience (r = -0.56, p < .001), while sense of coherence (M = 65.14, SD = 10.45) positively correlated (r = 0.63, p < .001). The regression model was significant (F(2, 373) = 173.27, p < .001), explaining 48% of the variance in academic resilience (R² = 0.48). Cognitive failures (B = -0.45, p < .001) and sense of coherence (B = 0.59, p < .001) were significant predictors of academic resilience. The findings underscore the significant roles of cognitive failures and sense of coherence in predicting academic resilience in children with speech impairments. Interventions targeting cognitive improvement and psychological support can enhance resilience, thereby promoting better academic outcomes. Future research should explore longitudinal trajectories and the effectiveness of specific interventions to further support these children.

This study aims to explore teachers' narratives on implementing AI-based learning tools for students with severe disabilities. The objective is to understand the challenges faced, the impacts on students, and the experiences of teachers using these technologies in special education settings. A qualitative research design was employed, using semi-structured interviews to gather data from 16 certified special education teachers with experience in using AI-based learning tools. Participants were selected through purposive sampling to ensure a diverse range of perspectives. Interviews were transcribed and subjected to thematic analysis to identify key themes and patterns in the data. Three main themes emerged from the analysis: implementation challenges, the impact on students, and teacher experiences. Teachers reported significant technical difficulties, inadequate training, and limited administrative support as major challenges. Despite these issues, AI tools had a positive impact on student engagement, motivation, learning outcomes, social interaction, and behavioral changes. Teachers experienced a range of emotions, from initial skepticism to eventual acceptance, and highlighted the importance of peer support and professional growth. The study underscores the transformative potential of AI in special education, while also identifying critical areas that need attention for successful implementation. The integration of AI-based learning tools in special education offers significant benefits for students with severe disabilities, including enhanced engagement, improved learning outcomes, and better social interactions. However, successful implementation requires addressing technical issues, providing comprehensive training, securing administrative support, and fostering a culture of feedback and reflection. Future research should focus on long-term impacts, comparative effectiveness of different AI tools, and the development of effective training programs. Educational institutions must prioritize these areas to maximize the positive impact of AI technologies in special education.