AI Tutor: Solution for Chinas Disadvantaged and Under-resourced Children

Abstract

This academic paper delves into the pressing issue of educational disparities in China, particularly focusing on the challenges faced by disadvantaged and under-resourced children, including both migrant and left-behind children. The paper underscores the socioeconomic and geographical complexities that exacerbate these disparities, emphasizing the need for innovative solutions. It then introduces the transformative potential of AI tutors, leveraging recent advancements in large language models (LLMs), to bridge the educational gap. The study highlights the significant impact of migration on children's access to education, with rural-to-urban migration patterns creating hurdles for migrant children to secure enrollment in urban schools. Additionally, it sheds light on the plight of left-behind children, who face emotional challenges and limited educational resources in rural settings. The paper introduces AI tutors, particularly ChatGPT-based Khanmigo, as innovative solutions that can offer personalized educational support, generate educational materials, assist teachers, and even evaluate student work. It discusses the advantages of these AI tutors, such as cost-effectiveness and accessibility, and their potential to democratize education. However, the paper also acknowledges the limitations of AI tutors, particularly in areas requiring creativity, critical thinking, and emotional intelligence. It raises concerns about exacerbating educational inequality if high-quality human educators become exclusive to the privileged, leaving disadvantaged children reliant on AI-based solutions.