Hybrid Intelligence as a Tool for Textual Decoding: Integrating the Literary Detective Framework in Higher Education

Abstract

This paper explores the transformative integration of Hybrid Intelligence (HI) within the landscape of higher philological education, specifically operationalized through the innovative 'Literary Detective' pedagogical framework. Amidst the shifting cognitive baselines of the digital era, this study addresses the crisis of sustained deep attention by proposing a synergistic model of textual archaeology. The research focuses on the intricate process of multidimensional decoding, wherein human cultural intuition collaborates with the computational power of Large Language Models (LLMs) to excavate latent intertextual layers across a diverse literary corpus.The study provides a comparative analysis of foundational and modern texts, demonstrating how a structured Decoding Matrix facilitates the identification of complex cultural codes in the cosmological epics of Vaja-Pshavela, the impressionistic prose of Niko Lortkipanidze, and the tragic war poetry of Mirza Gelovani, alongside the works of Homer, Margaret Atwood, and Ana Kalandadze. The findings reveal that Artificial Intelligence, when utilized as a cognitive scaffold rather than a replacement for authorial voice, significantly amplifies the student's capacity to navigate intertextual networks and resolve “artificial hallucinations” through intuitive filtering. Empirical evidence suggests that this hybrid approach not only increases the efficiency of thematic identification by approximately 38% but also fosters advanced critical thinking and digital literacy. Ultimately, the paper argues for a paradigm shift in the humanities, positioning the student as an active investigator in an AI-augmented hermeneutic environment, ensuring the continued relevance of philological rigor in a post-digital academic world.