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Analyzing Information-Seeking Behaviors in a Hakka AI Chatbot: A Cognitive-Pragmatic Study
This paper analyzes user interactions with TALKA, a generative AI chatbot designed for Hakka language learning, examining 7,077 user utterances through Bloom's Taxonomy and dialogue act categorization to understand information-seeking behaviors and cognitive processes in low-resource language learning.
With many endangered languages at risk of disappearing, efforts to preserve them now rely more than ever on using technology alongside culturally informed teaching strategies. This study examines user behaviors in TALKA, a generative AI-powered chatbot designed for Hakka language engagement, by employing a dual-layered analytical framework grounded in Bloom's Taxonomy of cognitive processes and dialogue act categorization. We analyzed 7,077 user utterances, each carefully annotated according to