AI-ENHANCED CULTURAL HERITAGE LEARNING PLATFORMS

Abstract [English]

AI-Enhanced Cultural Heritage Learning Platforms can be viewed as a paradigm shift in the convergence of the artificial intelligence, digital humanities, and technology-supported learning. With the growing digitization of collections in museums, archives, and culture institutions, the problem becomes not about gaining access to the collections, but about having meaningful interaction that further learning, interpretation, and cultural continuity. The proposed research suggests a combined platform architecture that uses multimodal AI, using natural language processing, computer vision, 3D object cognition, and graphic reasoning to provide custom learning experiences that are contextually rich and full of emotions. The platform starts with the mass multimodal content acquisition of textual records, high-resolution images, scans in 3D, audio narrative, and oral histories. Annotating, classifying and tying cultural objects Semantic enrichment provides an AI-based pipeline of processing to perform annotation and classification on cultural artifacts and connect them based on heritage-specific ontologies. Personalized learning engine is customized to the profile of learners, their interests and behavioral patterns whereas the conversational storytelling module allows interactive exploration through the dialogue of the narrative, answering questions and learning through scenarios. The model uses affective computing that identifies the emotions of the learner and tailors help strategies to improve motivation and thinking. The study constitutes a methodological procedure of assembling a narrowed down dataset of cultural archives and museum depositories, educating NLP, vision, and graph networks through artifact perception, context inference, and recommendation. Experimental findings indicate that the model has a high level of model performance in terms of accuracy, interpretability, and mitigation of bias, and that users and heritage specialists have a positive user experience.