AI-DRIVEN ADAPTIVE FEEDBACK TOOL: IMPACTS ON STUDENT LEARNING OUTCOMES AND TEACHERS' PERCEPTIONS ACROSS EDUCATIONAL CONTEXTS

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

This study investigates the impact of an AI-driven adaptive feedback tool on student learning outcomes and teachers’ perceptions across primary, secondary, and tertiary education in both rural and urban contexts. Adopting a quasi-experimental mixed-methods design, the research engaged 60 students and 12 teachers across six institutions, integrating ChatGPT into English and Science classroom tasks to provide real-time adaptive feedback. Quantitative findings revealed significant improvements in students’ post-test performance at all levels, with particularly strong gains at the university level. Comparative analyses indicated that while rural students lagged behind urban peers in absolute performance, the relative benefits of utilizing AI tool were consistent across contexts. Teacher surveys and interviews highlighted positive perceptions in terms of its usefulness and pedagogical value, though self-efficacy and ease of use were lower in rural settings due to infrastructural and digital literacy challenges. Thematic insights emphasized AI tool’s role in supporting instruction, while also pointing to the evolving role of teachers as facilitators who guide students in critically engaging with AI tool. The findings affirm constructivist and sociocultural learning perspectives, while also supporting the Technology Acceptance Model in explaining adoption. The study concludes that AI holds promise as an equitable and effective feedback tool, provided contextual barriers and teacher preparedness are systematically addressed.

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