ScholarWorks@성균관대학교

초록

Human-AI collaborative systems are increasingly explored as tools for promoting mental well-being and supporting personal development. We present POCKET-MIND, a personalized digital journaling system powered by a Large Language Model (LLM) that facilitates both emotional exploration and goal pursuit through a novel Dual-Prompt Framework. Unlike traditional journaling apps that treat emotional reflection and goal tracking as separate tasks, POCKET-MIND integrates these dimensions by generating adaptive prompts that help users meaningfully connect their feelings with their personal aspirations. In a one-week exploratory study with 30 young adults, preliminary findings suggest that POCKET-MIND may support emotional articulation, self-reflection, and goal-directed behaviors. While the study had a relatively small sample size, the findings highlight the potential of Human-AI collaborative journaling for personal mental health support. This work contributes to Human-Computer Interaction (HCI) by offering early design insights into adaptive conversational systems that personalize reflective practices and foster user growth through interactive experiences.

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