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Hajin Lim

Publications and source records attributed to Hajin Lim.

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InnerPond: Fostering Inter-Self Dialogue with a Multi-Agent Approach for Introspection

Introspection is central to identity construction and future planning, yet most digital tools approach the self as a unified entity. In contrast, Dialogical Self Theory (DST) views the self as composed of multiple internal perspectives, such as values, concerns, and aspirations, that can come into tension or dialogue with one another. Building on this view, we designed InnerPond, a research probe in the form of a multi-agent system that represents these internal perspectives as distinct LLM-based agents for introspection. Its design was shaped through iterative explorations of spatial metaphors, interaction scaffolding, and conversational orchestration, culminating in a shared spatial environment for organizing and relating multiple inner perspectives. In a user study with 17 young adults navigating career choices, participants engaged with the probe by co-creating inner voices with AI, composing relational inner landscapes, and orchestrating dialogue as observers and mediators, offering insight into how such systems could support introspection. Overall, this work offers design implications for AI-supported introspection tools that enable exploration of the self's multiplicity.

cs.HC

Actor's Note: Examining the Role of AI-Generated Questions in Character Journaling for Actor Training

Character journaling is a well-established exercise in actor training, but many actors struggle to sustain it due to cognitive burden, the blank page problem, and unclear short-term rewards. We reframe large language models not as co-authors but as maieutic partners-tools that guide reflection through context-aware questioning rather than producing text on behalf of the user. Based on this perspective, we designed Actor's Note, a journaling tool that tailors questions to the script, role, and rehearsal phase while preserving actor agency. We evaluated the system in a 14-day crossover study with 29 actors using surveys, logs, and interviews. Results indicate that the tool reduced entry barriers, supported sustained reflection, and enriched character exploration, with participants describing different benefits when AI was introduced at earlier versus later rehearsal stages. This work contributes empirical insights and design principles for creativity-support tools that sustain reflective practices while preserving artistic immersion in performance training.

cs.HC

Understanding Digital Gifting Through Messengers Across Cultures: A Comparative Study of University Students in South Korea, China, and Japan

Digital gift-giving has become a key means of maintaining social relationships, but most existing research has focused on gifting within global e-commerce or social media platforms. The emergence of messenger-based gifting in East Asia, where Korea, Japan, and China each have distinct and deeply rooted gifting traditions, remains underexplored. This study examines how in-app gifting services on the most widely used messaging platforms in South Korea (KakaoTalk), Japan (LINE), and China (WeChat) reflect and reshape culturally embedded gifting practices. Through semi-structured interviews with 26 university students, we found that KakaoTalk facilitates frequent, informal exchanges aligned with Korea's emphasis on broad social ties; LINE supports selective and carefully presented gifts, reflecting Japanese norms of formality and sincerity; and WeChat's Hongbao feature enables playful, communal monetary exchanges largely detached from traditional, obligation-driven gifting. Drawing on these findings, we propose the Channel-Oriented Gifting Cycle model, which extends classical gift-exchange theory by showing that the choice of gifting platform is not merely logistical but a culturally meaningful part of the gifting process. We conclude with design implications for culturally sensitive digital gifting services.

cs.HC

NoRe: Augmenting Journaling Experience with Generative AI for Music Creation

Journaling has long been recognized for fostering emotional awareness and self-reflection, and recent advancements in generative AI offer new opportunities to create personalized music that can enhance these practices. In this study, we explore how AI-generated music can augment the journaling experience. Through a formative study, we examined journal writers' writing patterns, purposes, emotional regulation strategies, and the design requirements for the system that augments journaling experience by journal-based AI-generated music. Based on these insights, we developed NoRe, a system that transforms journal entries into personalized music using generative AI. In a seven-day in-the-wild study (N=15), we investigated user engagement and perceived emotional effectiveness through system logs, surveys, and interviews. Our findings suggest that journal-based music generation could support emotional reflection and provide vivid reminiscence of daily experiences. Drawing from these findings, we discuss design implications for tailoring music to journal writers' emotional states and preferences.

cs.HC

Adaptive-VP: A Framework for LLM-Based Virtual Patients that Adapts to Trainees' Dialogue to Facilitate Nurse Communication Training

Effective communication training is essential to preparing nurses for high-quality patient care. While standardized patient (SP) simulations provide valuable experiential learning, they are often costly and inflexible. Virtual patient (VP) systems offer a scalable alternative, but most fail to adapt to the varying communication skills of trainees. In particular, when trainees respond ineffectively, VPs should escalate in hostility or become uncooperative--yet this level of adaptive interaction remains largely unsupported. To address this gap, we introduce Adaptive-VP, a VP dialogue generation framework that leverages large language models (LLMs) to dynamically adapt VP behavior based on trainee input. The framework features a pipeline for constructing clinically grounded yet flexible VP scenarios and a modular system for assessing trainee communication and adjusting VP responses in real time, while ensuring learner safety. We validated Adaptive-VP by simulating challenging patient conversations. Automated evaluation using a corpus from practicing nurses showed that our communication skill evaluation mechanism reflected real-world proficiency levels. Expert nurses further confirmed that Adaptive-VP produced more natural and realistic interactions than existing approaches, demonstrating its potential as a scalable and effective tool for nursing communication training.

cs.CL

Letters from Future Self: Augmenting the Letter-Exchange Exercise with LLM-based Agents to Enhance Young Adults' Career Exploration

Young adults often encounter challenges in career exploration. Self-guided interventions, such as the letter-exchange exercise, where participants envision and adopt the perspective of their future selves by exchanging letters with their envisioned future selves, can support career development. However, the broader adoption of such interventions may be limited without structured guidance. To address this, we integrated Large Language Model (LLM)-based agents that simulate participants' future selves into the letter-exchange exercise and evaluated their effectiveness. A one-week experiment (N=36) compared three conditions: (1) participants manually writing replies to themselves from the perspective of their future selves (baseline), (2) future-self agents generating letters to participants, and (3) future-self agents engaging in chat conversations with participants. Results indicated that exchanging letters with future-self agents enhanced participants' engagement during the exercise, while overall benefits of the intervention on future orientation, career self-concept, and psychological support remained comparable across conditions. We discuss design implications for AI-augmented interventions for supporting young adults' career exploration.

cs.HC

Exploring K-12 Physical Education Teachers' Perspectives on Opportunities and Challenges of AI Integration Through Ideation Workshops

While AI's potential in education and professional sports is widely recognized, its application in K-12 physical education (PE) remains underexplored with significant opportunities for innovation. This study aims to address this gap by engaging 17 in-service secondary school PE teachers in group ideation workshops to explore potential AI applications and challenges in PE classes. Participants envisioned AI playing multidimensional roles, such as an operational assistant, personal trainer, group coach, and evaluator, as solutions to address unique instructional and operational challenges in K-12 PE classes. These roles reflected participants' perspectives on how AI could enhance class management, deliver personalized feedback, promote balanced team activities, and streamline performance assessments. Participants also highlighted critical considerations for AI integration, including the need to ensure robust student data security and privacy measures, minimize the risk of over-reliance on AI for instructional decisions, and accommodate the varying levels of technological proficiency among PE teachers. Our findings provide valuable insights and practical guidance for AI developers, educators, and policymakers, offering a foundation for the effective integration of AI into K-12 PE curricula to enhance teaching practices and student outcomes.

cs.HC

I Stan Alien Idols and Also the People Behind Them: Understanding How Seams Between Virtual and Real Identities Engage VTuber Fans -- A Case Study of PLAVE

Virtual YouTubers (VTubers) have recently gained popularity as streamers using computer-generated avatars and real-time motion capture to create distinct virtual identities. While prior research has explored how VTubers construct virtual personas and engage audiences, little attention has been given to viewers' reactions when virtual and real identities blur-what we refer to as "seams." To address this gap, we conducted a case study on PLAVE, a popular Korean VTuber Kpop idol group, interviewing 24 of their fans. Our findings identified two main sources of seams: technical glitches and identity collapses, where VTubers act inconsistently with their virtual personas, revealing aspects of their real selves. These seams played a pivotal role in shaping diverse fan engagements, with some valuing authenticity linked to real identities, while others prioritized the coherence of virtual personas. Overall, our findings underscore the importance of seams in shaping viewer experiences.

cs.HC

SPeCtrum: A Grounded Framework for Multidimensional Identity Representation in LLM-Based Agent

Existing methods for simulating individual identities often oversimplify human complexity, which may lead to incomplete or flattened representations. To address this, we introduce SPeCtrum, a grounded framework for constructing authentic LLM agent personas by incorporating an individual's multidimensional self-concept. SPeCtrum integrates three core components: Social Identity (S), Personal Identity (P), and Personal Life Context (C), each contributing distinct yet interconnected aspects of identity. To evaluate SPeCtrum's effectiveness in identity representation, we conducted automated and human evaluations. Automated evaluations using popular drama characters showed that Personal Life Context (C)-derived from short essays on preferences and daily routines-modeled characters' identities more effectively than Social Identity (S) and Personal Identity (P) alone and performed comparably to the full SPC combination. In contrast, human evaluations involving real-world individuals found that the full SPC combination provided a more comprehensive self-concept representation than C alone. Our findings suggest that while C alone may suffice for basic identity simulation, integrating S, P, and C enhances the authenticity and accuracy of real-world identity representation. Overall, SPeCtrum offers a structured approach for simulating individuals in LLM agents, enabling more personalized human-AI interactions and improving the realism of simulation-based behavioral studies.

cs.CL

EmoBridge: Bridging the Communication Gap between Students with Disabilities and Peer Note-Takers Utilizing Emojis and Real-Time Sharing

Students with disabilities (SWDs) often struggle with note-taking during lectures. Therefore, many higher education institutions have implemented peer note-taking programs (PNTPs), where peer note-takers (PNTs) assist SWDs in taking lecture notes. To better understand the experiences of SWDs and PNTs, we conducted semi-structured interviews with eight SWDs and eight PNTs. We found that the interaction between SWDs and PNTs was predominantly unidirectional, highlighting specific needs and challenges. In response, we developed EmoBridge, a collaborative note-taking platform that facilitates real-time collaboration and communication between PNT-SWD pairs using emojis. We evaluated EmoBridge through an in-the-wild study with seven PNT-SWD pairs. The results showed improved class participation for SWDs and a reduced sense of sole responsibility for PNTs. Based on these insights, we discuss design implications for collaborative note-taking systems aimed at enhancing PNTPs and fostering more effective and inclusive educational experiences for SWDs.

cs.HC

SMART-TBI: Design and Evaluation of the Social Media Accessibility and Rehabilitation Toolkit for Users with Traumatic Brain Injury

Traumatic brain injury (TBI) can cause a range of cognitive and communication challenges that negatively affect social participation in both face-to-face interactions and computer-mediated communication. In particular, individuals with TBI report barriers that limit access to participation on social media platforms. To improve access to and use of social media for users with TBI, we introduce the Social Media Accessibility and Rehabilitation Toolkit (\textbf{SMART-TBI}). The toolkit includes five aids (Writing Aid, Interpretation Aid, Filter Mode, Focus Mode, and Facebook Customization) designed to address the cognitive and communicative needs of individuals with TBI. We asked eight users with moderate-severe TBI and five TBI rehabilitation experts to evaluate each aid. Our findings revealed potential benefits of aids and areas for improvement, including the need for psychological safety, privacy control, and balancing business and accessibility needs; and overall mixed reactions among the participants to AI-based aids.

cs.HC

Investigating the Day-to-Day Experiences of Users with Traumatic Brain Injury with Conversational Agents

Traumatic brain injury (TBI) can cause cognitive, communication, and psychological challenges that profoundly limit independence in everyday life. Conversational Agents (CAs) can provide individuals with TBI with cognitive and communication support, although little is known about how they make use of CAs to address injury-related needs. In this study, we gave nine adults with TBI an at-home CA for four weeks to investigate use patterns, challenges, and design requirements, focusing particularly on injury-related use. The findings revealed significant gaps between the current capabilities of CAs and accessibility challenges faced by TBI users. We also identified 14 TBI-related activities that participants engaged in with CAs. We categorized those activities into four groups: mental health, cognitive activities, healthcare and rehabilitation, and routine activities. Design implications focus on accessibility improvements and functional designs of CAs that can better support the day-to-day needs of people with TBI.

cs.HC

So, I Can Feel Normal: Participatory Design for Accessible Social Media Sites for Individuals with Traumatic Brain Injury

Traumatic brain injury (TBI) can result in chronic sensorimotor, cognitive, psychosocial, and communication challenges that can limit social participation. Social media can be a useful outlet for social participation for individuals with TBI, but there are barriers to access. While research has drawn attention to the nature of access barriers, few studies have investigated technological solutions to address these barriers, particularly considering the perspectives of individuals with TBI. To address this gap in knowledge, we used a participatory approach to engage 10 adults with TBI in conceptualizing tools to address their challenges accessing Facebook. Participants described multifaceted challenges in using social media, including interface overload, social comparisons, and anxiety over self-presentation and communication after injury. They discussed their needs and preferences and generated ideas for design solutions. Our work contributes to designing assistive and accessibility technology to facilitate an equal access to the benefits of social media for individuals with TBI.

cs.HC