درخت حوزه‌های تخصصی

This study aimed to evaluate the effectiveness of Interpersonal Reconstructive Therapy (IRT) in enhancing empathy and conflict resolution skills among parents of autistic children. This randomized controlled trial included 30 parents of autistic children, divided into an intervention group (n = 15) receiving IRT and a control group (n = 15) receiving no intervention. Participants were assessed at baseline, post-intervention, and four months post-intervention using the Interpersonal Reactivity Index (IRI) and Conflict Resolution Styles Inventory (CRSI). Data analysis involved repeated measures ANOVA and Bonferroni post-hoc tests, conducted using SPSS-27. The intervention group showed significant improvements in empathy and conflict resolution scores. Empathy scores increased from 54.78 (SD = 5.32) at baseline to 67.32 (SD = 5.67) post-intervention and were maintained at 65.91 (SD = 5.42) at follow-up. Conflict resolution scores rose from 62.14 (SD = 6.23) to 74.89 (SD = 5.47) post-intervention, with scores at follow-up being 73.28 (SD = 5.63). ANOVA results indicated significant main effects for Time (empathy: F(2, 56) = 45.67, p < 0.001, η² = 0.62; conflict resolution: F(2, 56) = 49.18, p < 0.001, η² = 0.64), Group (empathy: F(1, 28) = 32.78, p < 0.001, η² = 0.54; conflict resolution: F(1, 28) = 35.91, p < 0.001, η² = 0.57), and Time × Group interactions (empathy: F(2, 56) = 41.23, p < 0.001, η² = 0.59; conflict resolution: F(2, 56) = 43.89, p < 0.001, η² = 0.60). Bonferroni post-hoc tests confirmed significant improvements from baseline to post-intervention and baseline to follow-up. IRT significantly enhances empathy and conflict resolution skills in parents of autistic children, with improvements maintained over a four-month period. These findings highlight the potential of IRT as an effective intervention to support parents in managing the challenges of raising children with autism.

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.