AI-Driven Literary Analysis for High School Education Using Transformer Architecture

Even though the process of integrating AI into the educational domain continues to increase, the literary analysis remains a difficult problem to automate because of the intricate and subtle character of literary works. The classic approaches do not necessarily represent the complicated literary devices, themes, and character development. In order to address the concerns, the paper uses AI based Automated Literary Analysis (AI-ALA) model which uses Generative Pretrained Transformer (GPT-4), a state of the art generative language model in order to automate literary analysis in high school literature courses. The fact that this method is interactive at the time of lesson and that the teacher works with pupils to assess literary tools such as metaphors and sarcasm as well as discuss the character and theme in a setting is revolutionary. The successful adjustment of the algorithm to a set of books with high school students is the guarantee of their adequacy and applicability in the field of education. The experiments indicate that GPT-4 is more precise and context-responsive as compared to rule-based. It is an in-depth examination of characters, themes, and literary strategies. The strategy, according to the statistics, can present teachers with an effective and scalable tool to enhance student learning. The concept simplifies the process of literary analysis through interactive interaction combined with questions and answers sessions. Literary analysis automation and personalization will break the existing boundaries and enhance literature classes teaching.

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