This study investigates how fourth-grade primary school students’ interactions with generative artificial intelligence tools—specifically ChatGPT and Microsoft Copilot—during story-creation tasks are reflected in their native-language reading skills. Using a qualitative design embedded within an action-research process, data were gathered through semi-structured interviews, in-class observations, field notes and students’ written responses to two story-comprehension forms derived from AI-generated narratives. The data were analysed through thematic content analysis, supported by descriptive statistics. Guided by Rosenblatt’s reader-response theory, Kintsch’s construction–integration model, inference-based comprehension research and the Turkish fourth-grade language arts learning outcomes, the analysis produced five key themes: Text Comprehension, Inference-Making, Detail Awareness, Emotional Response and Connection, and Word Consciousness. Across the dataset, 132 codes were identified. Findings indicate that students demonstrate strength in fundamental text comprehension and event-focused interpretation but show limited development in abstract inference, vocabulary awareness and deeper affective engagement. AI-supported story production appears to scaffold comprehension processes by helping students recognise narrative structure, form empathetic connections with characters and draw on personal experiences while making meaning. Individual analyses of focal participants reveal a shift from surface-level recall to more reflective, value-oriented and empathy-driven reading behaviours. Overall, the results suggest that AI-supported storytelling holds promise as a pedagogical tool for enhancing native-language reading, provided it is accompanied by explicit instruction targeting inference-making, vocabulary development and critical engagement with AI-generated texts.

This study aims to examine high school teachers' perceptions of artificial intelligence (AI) technologies and how these perceptions differ based on various demographic and professional variables. The research, conducted using a quantitative research methodology, employed the "Artificial Intelligence Perception Scale" as a data collection tool. A total of 355 teachers with diverse professional experiences and demographic characteristics participated in the study.The findings indicate that high school teachers generally have a positive perception of AI technologies. While no significant difference was found in AI perceptions based on gender, variables such as school type and prior technological training were observed to influence perceptions. Teachers working in private schools demonstrated higher perceptions of AI compared to those in public schools. Moreover, teachers who had received training on AI exhibited more positive attitudes toward these technologies. The results emphasize the need for increasing training programs and improving infrastructure to enhance teachers' perceptions of AI technologies. Recommendations include strengthening technological integration, raising awareness of AI, and enhancing teachers' digital skills.