ExploreSelf: Fostering User-driven Exploration and Reflection on Personal Challenges with Adaptive Guidance by Large Language Models
arXiv:2409.09662 · doi:10.1145/3706598.3713883
Abstract
Expressing stressful experiences in words is proven to improve mental and physical health, but individuals often disengage with writing interventions as they struggle to organize their thoughts and emotions. Reflective prompts have been used to provide direction, and large language models (LLMs) have demonstrated the potential to provide tailored guidance. However, current systems often limit users' flexibility to direct their reflections. We thus present ExploreSelf, an LLM-driven application designed to empower users to control their reflective journey, providing adaptive support through dynamically generated questions. Through an exploratory study with 19 participants, we examine how participants explore and reflect on personal challenges using ExploreSelf. Our findings demonstrate that participants valued the flexible navigation of adaptive guidance to control their reflective journey, leading to deeper engagement and insight. Building on our findings, we discuss the implications of designing LLM-driven tools that facilitate user-driven and effective reflection of personal challenges.
17 pages excluding reference and appendix. Accepted at ACM CHI 2025. https://naver-ai.github.io/exploreself
References in corpus (10)
- CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities
- Cultural Bias and Cultural Alignment of Large Language Models
- A Design Space for Intelligent and Interactive Writing Assistants
- MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
- Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data
- Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health Intervention
- ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
- Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction
- Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App
- Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms