arXiv subjects

Kyrie Zhixuan Zhou

Publications and source records attributed to Kyrie Zhixuan Zhou.

At least 19 recordsLinked to original sources

arXiv2026

Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education

Generative AI is reshaping programming education, yet educators often infer students' AI-supported learning from classroom observations alone. This experience report presents a trio-ethnography involving two computing educators with different teaching philosophies and one undergraduate computer science student to examine how these interpretations evolve through dialogue. Across three conversations, the educators reflected on students' AI use, discussed changes to programming pedagogy, and revisited their assumptions after engaging with the student's lived experiences. Rather than simply confirming or contradicting the educators' perspectives, the student's narratives revealed learning processes that were largely invisible in the classroom, prompting both educators to reconsider assumptions about AI use, assessment, transparency, and programming instruction. We argue that trio-ethnography offers a valuable reflective approach for helping computing educators move beyond observable student behaviors toward a richer understanding of AI-supported learning and for informing instructional adaptation in the era of generative AI.

cs.HC↗

arXiv2025

User Negotiations of Authenticity, Ownership, and Governance on AI-Generated Video Platforms: Evidence from Sora

As AI-generated video platforms rapidly advance, ethical challenges such as copyright infringement emerge. This study examines how users make sense of AI-generated videos on OpenAI's Sora by conducting a qualitative content analysis of user comments. Through a thematic analysis, we identified four dynamics that characterize how users negotiate authenticity, authorship, and platform governance on Sora. First, users acted as critical evaluators of realism, assessing micro-details such as lighting, shadows, fluid motion, and physics to judge whether AI-generated scenes could plausibly exist. Second, users increasingly shifted from passive viewers to active creators, expressing curiosity about prompts, techniques, and creative processes. Text prompts were perceived as intellectual property, generating concerns about plagiarism and remixing norms. Third, users reported blurred boundaries between real and synthetic media, worried about misinformation, and even questioned the authenticity of other commenters, suspecting bot-generated engagement. Fourth, users contested platform governance: some perceived moderation as inconsistent or opaque, while others shared tactics for evading prompt censorship through misspellings, alternative phrasing, emojis, or other languages. Despite this, many users also enforced ethical norms by discouraging the misuse of real people's images or disrespectful content. Together, these patterns highlighted how AI-mediated platforms complicate notions of reality, creativity, and rule-making in emerging digital ecosystems. Based on the findings, we discuss governance challenges in Sora and how user negotiations inform future platform governance.

cs.HC↗

arXiv2025

"Everyone Else Does It": The Rise of Preprinting Culture in Computing Disciplines

Preprinting has become a norm in fast-paced computing fields such as artificial intelligence (AI) and human-computer interaction (HCI). In this paper, we conducted semistructured interviews with 15 academics in these fields to reveal their motivations and perceptions of preprinting. The results found a close relationship between preprinting and characteristics of the fields, including the huge number of papers, competitiveness in career advancement, prevalence of scooping, and imperfect peer review system - preprinting comes to the rescue in one way or another for the participants. Based on the results, we reflect on the role of preprinting in subverting the traditional publication mode and outline possibilities of a better publication ecosystem. Our study contributes by inspecting the community aspects of preprinting practices through talking to academics.

cs.HC↗

arXiv2025

WHEN TO ACT, WHEN TO WAIT: Modeling the Intent-Action Alignment Problem in Dialogue

Dialogue systems often fail when user utterances are semantically complete yet lack the clarity and completeness required for appropriate system action. This mismatch arises because users frequently do not fully understand their own needs, while systems require precise intent definitions. This highlights the critical Intent-Action Alignment Problem: determining when an expression is not just understood, but truly ready for a system to act upon. We present STORM, a framework modeling asymmetric information dynamics through conversations between UserLLM (full internal access) and AgentLLM (observable behavior only). STORM produces annotated corpora capturing trajectories of expression phrasing and latent cognitive transitions, enabling systematic analysis of how collaborative understanding develops. Our contributions include: (1) formalizing asymmetric information processing in dialogue systems; (2) modeling intent formation tracking collaborative understanding evolution; and (3) evaluation metrics measuring internal cognitive improvements alongside task performance. Experiments across four language models reveal that moderate uncertainty (40-60%) can outperform complete transparency in certain scenarios, with model-specific patterns suggesting reconsideration of optimal information completeness in human-AI collaboration. These findings contribute to understanding asymmetric reasoning dynamics and inform uncertainty-calibrated dialogue system design.

cs.AI↗

arXiv2025

Toward Designing Accessible and Meaningful Software for Cancer Survivors

Cancer survivors experience a wide range of impairments arising from cancer or its treatment, such as chemo brain, visual impairments, and physical impairments. These impairments degrade their quality of life and potentially make software use more challenging for them. However, there has been limited research on designing accessible software for cancer survivors. To bridge this research gap, we conducted a formative study including a survey (n=46), semi-structured interviews (n=20), and a diary study (n=10) with cancer survivors. Our results revealed a wide range of impairments experienced by cancer survivors, including chemo brain, neuropathy, and visual impairments. Cancer survivors heavily relied on software for socialization, health purposes, and cancer advocacy, but their impairments made software use more challenging for them. Based on the results, we offer a set of accessibility guidelines that software designers can utilize when creating applications for cancer survivors. Further, we suggest design features for inclusion, such as health resources, socialization tools, and games, tailored to the needs of cancer survivors. This research aims to spotlight cancer survivors' software accessibility challenges and software needs and invite more research in this important yet under-investigated domain.

cs.HC↗

arXiv2025

Global Public Sentiment on Decentralized Finance: A Spatiotemporal Analysis of Geo-tagged Tweets from 150 Countries

Blockchain technology and decentralized finance (DeFi) are reshaping global financial systems. Despite their impact, the spatial distribution of public sentiment and its economic and geopolitical determinants are often overlooked. This study analyzes over 150 million geo-tagged, DeFi-related tweets from 2012 to 2022, sourced from a larger dataset of 7.4 billion tweets. Using sentiment scores from a BERT-based multilingual classification model, we integrated these tweets with economic and geopolitical data to create a multimodal dataset. Employing techniques like sentiment analysis, spatial econometrics, clustering, and topic modeling, we uncovered significant global variations in DeFi engagement and sentiment. Our findings indicate that economic development significantly influences DeFi engagement, particularly after 2015. Geographically weighted regression analysis revealed GDP per capita as a key predictor of DeFi tweet proportions, with its impact growing following major increases in cryptocurrency values such as bitcoin. While wealthier nations are more actively engaged in DeFi discourse, the lowest-income countries often discuss DeFi in terms of financial security and sudden wealth. Conversely, middle-income countries relate DeFi to social and religious themes, whereas high-income countries view it mainly as a speculative instrument or entertainment. This research advances interdisciplinary studies in computational social science and finance and supports open science by making our dataset and code available on GitHub, and providing a non-code workflow on the KNIME platform. These contributions enable a broad range of scholars to explore DeFi adoption and sentiment, aiding policymakers, regulators, and developers in promoting financial inclusion and responsible DeFi engagement globally.

econ.GN↗

arXiv2024

Understanding the concerns and choices of public when using large language models for healthcare

Large language models (LLMs) have shown their potential in biomedical fields. However, how the public uses them for healthcare purposes such as medical Q\&A, self-diagnosis, and daily healthcare information seeking is under-investigated. This paper adopts a mixed-methods approach, including surveys (N=214) and interviews (N=17) to investigate how and why the public uses LLMs for healthcare. We found that participants generally believed LLMs as a healthcare tool have gained popularity, and are often used in combination with other information channels such as search engines and online health communities to optimize information quality. Based on the findings, we reflect on the ethical and effective use of LLMs for healthcare and propose future research directions.

cs.CY↗

arXiv2024

Accessible Adventures: Teaching Accessibility to High School Students Through Games

Accessibility education has been rarely incorporated into the high school curricula. This is a missed opportunity to equip next-generation software designers and decision-makers with knowledge, awareness, and empathy regarding accessibility and disabilities. We taught accessibility to students (N=93) in a midwestern high school through empathy-driven games and interviewed three Computer Science high school teachers and one librarian who taught programming. Accessibility education is currently insufficient in high school, facing challenges such as teachers' knowledge and conflicted curriculum goals. The students exhibited increased knowledge and awareness of accessibility and empathy for people with disabilities after playing the games. With this education outreach, we aim to provide insights into teaching next-generation software designers about accessibility by leveraging games.

cs.HC↗

arXiv2024

"Sora is Incredible and Scary": Emerging Governance Challenges of Text-to-Video Generative AI Models

Text-to-video generative AI models such as Sora OpenAI have the potential to disrupt multiple industries. In this paper, we report a qualitative social media analysis aiming to uncover people's perceived impact of and concerns about Sora's integration. We collected and analyzed comments (N=292) under popular posts about Sora-generated videos, comparison between Sora videos and Midjourney images, and artists' complaints about copyright infringement by Generative AI. We found that people were most concerned about Sora's impact on content creation-related industries. Emerging governance challenges included the for-profit nature of OpenAI, the blurred boundaries between real and fake content, human autonomy, data privacy, copyright issues, and environmental impact. Potential regulatory solutions proposed by people included law-enforced labeling of AI content and AI literacy education for the public. Based on the findings, we discuss the importance of gauging people's tech perceptions early and propose policy recommendations to regulate Sora before its public release.

cs.CY↗

arXiv2024

User Privacy Harms and Risks in Conversational AI: A Proposed Framework

This study presents a unique framework that applies and extends Solove (2006)'s taxonomy to address privacy concerns in interactions with text-based AI chatbots. As chatbot prevalence grows, concerns about user privacy have heightened. While existing literature highlights design elements compromising privacy, a comprehensive framework is lacking. Through semi-structured interviews with 13 participants interacting with two AI chatbots, this study identifies 9 privacy harms and 9 privacy risks in text-based interactions. Using a grounded theory approach for interview and chatlog analysis, the framework examines privacy implications at various interaction stages. The aim is to offer developers, policymakers, and researchers a tool for responsible and secure implementation of conversational AI, filling the existing gap in addressing privacy issues associated with text-based AI chatbots.

cs.HC↗

arXiv2024

Revitalizing Sex Education for Chinese Children: A Formative Study

Sex education helps children obtain knowledge and awareness of sexuality, and protects them against sexually transmitted diseases, pregnancy, and sexual abuse. Sex education is not well taught to children in China -- both school-based education and parental communication on this topic are limited. To interrogate the status quo of sex education in China and explore suitable interventions, we conducted a series of formative studies including interviews and social media analysis. Multiple stakeholders such as children, parents, education practitioners, and the general public were engaged for an in-depth understanding of their unique needs regarding teaching and learning sex education. We found that school-based sex education for Chinese children was currently insufficient and restrictive. Involving parents in sex education posed several challenges, such as a lack of sexuality and pedagogy knowledge, and embarrassment in initiating sex education conversations. Culture and politics were major hurdles to effective sex education. Based on the findings, we reflect on the complex interactions between culture, politics, education policy, and pedagogy, and discuss situated design of sex education in broader cultural and social contexts.

cs.CY↗

arXiv2024

"The teachers are confused as well": A Multiple-Stakeholder Ethics Discussion on Large Language Models in Computing Education

Large Language Models (LLMs) are advancing quickly and impacting people's lives for better or worse. In higher education, concerns have emerged such as students' misuse of LLMs and degraded education outcomes. To unpack the ethical concerns of LLMs for higher education, we conducted a case study consisting of stakeholder interviews (n=20) in higher education computer science. We found that students use several distinct mental models to interact with LLMs - LLMs serve as a tool for (a) writing, (b) coding, and (c) information retrieval, which differ somewhat in ethical considerations. Students and teachers brought up ethical issues that directly impact them, such as inaccurate LLM responses, hallucinations, biases, privacy leakage, and academic integrity issues. Participants emphasized the necessity of guidance and rules for the use of LLMs in higher education, including teaching digital literacy, rethinking education, and having cautious and contextual policies. We reflect on the ethical challenges and propose solutions.

cs.CY↗

arXiv2024

Exploring the Diversity of Music Experiences for Deaf and Hard of Hearing People

Sensory substitution or enhancement techniques have been proposed to enable deaf or hard of hearing (DHH) people to listen to and even compose music. However, little is known about how such techniques enhance DHH people's music experience. Since deafness is a spectrum -- as are DHH people's preferences and perceptions of music -- a more situated understanding of their interaction with music is needed. To understand the music experience of this population, we conducted social media analyses, both qualitatively and quantitatively, in the deaf and hard of hearing Reddit communities. Our content analysis revealed that DHH people leveraged sign language and visual/haptic cues to feel the music and preferred familiar, non-lyrical, instrument-heavy, and loud music. In addition, hearing aids were not customized for music, and the visual/haptic techniques developed were not widely adopted by DHH people, leading to their suboptimal music experiences. The DHH community embodied mutual support among music lovers, evidenced by active information sharing and Q&A around music and hearing loss. We reflect on design justice for DHH people's music experience and propose practical design implications to create a more accessible music experience for them.

cs.HC↗

arXiv2023

Uncovering Gender Stereotypes in Video Game Character Designs: A Multi-Modal Analysis of Honor of Kings

In this paper, we conduct a comprehensive analysis of gender stereotypes in the character design of Honor of Kings, a popular multiplayer online battle arena (MOBA) game in China. We probe gender stereotypes through the lens of role assignments, visual designs, spoken lines, and background stories, combining qualitative analysis and text mining based on the moral foundation theory. Male heroes are commonly designed as masculine fighters with power and female heroes as feminine "ornaments" with ideal looks. We contribute with a culture-aware and multi-modal understanding of gender stereotypes in games, leveraging text-, visual-, and role-based evidence.

cs.HC↗

arXiv2023

"Centralized or Decentralized?": Concerns and Value Judgments of Stakeholders in the Non-Fungible Tokens (NFTs) Market

Non-fungible tokens (NFTs) are decentralized digital tokens to represent the unique ownership of items. Recently, NFTs have been gaining popularity and at the same time bringing up issues, such as scams, racism, and sexism. Decentralization, a key attribute of NFT, contributes to some of the issues that are easier to regulate under centralized schemes, which are intentionally left out of the NFT marketplace. In this work, we delved into this centralization-decentralization dilemma in the NFT space through mixed quantitative and qualitative methods. Centralization-decentralization dilemma is the dilemma caused by the conflict between the slogan of decentralization and the interests of stakeholders. We first analyzed over 30,000 NFT-related tweets to obtain a high-level understanding of stakeholders' concerns in the NFT space. We then interviewed 15 NFT stakeholders (both creators and collectors) to obtain their in-depth insights into these concerns and potential solutions. Our findings identify concerning issues among users: financial scams, counterfeit NFTs, hacking, and unethical NFTs. We further reflected on the centralization-decentralization dilemma drawing upon the perspectives of the stakeholders in the interviews. Finally, we gave some inferences to solve the centralization-decentralization dilemma in the NFT market and thought about the future of NFT and decentralization.

cs.CY↗

arXiv2023

More Than a Wife and a Mom: A Study of Mom Vlogging Practices in China

Mom vloggers are stay-at-home moms who record and share their daily life through short videos. In this exploratory study, we aspire to understand mom vloggers' motivations, practices, and challenges. Our mixed-methods inspection contained interviews with 4 mom vloggers in China and a content analysis of mom vlogs of 5 other mom vloggers. Mom vloggers' primary motivations are to make money, record daily life, and seek their individual identities and values, well meeting their financial and social needs after leaving their paid employment. When creating vlog content, mom bloggers encounter various challenges, such as a lack of video visibility, being stretched by both intensive motherhood and heavy digital work, privacy and self-presentation concerns, and so on. Based on the findings, we propose design implications toward resolving these challenges and benefiting mom vloggers' experiences.

cs.HC↗

arXiv2023

Public Perceptions of Gender Bias in Large Language Models: Cases of ChatGPT and Ernie

Large language models are quickly gaining momentum, yet are found to demonstrate gender bias in their responses. In this paper, we conducted a content analysis of social media discussions to gauge public perceptions of gender bias in LLMs which are trained in different cultural contexts, i.e., ChatGPT, a US-based LLM, or Ernie, a China-based LLM. People shared both observations of gender bias in their personal use and scientific findings about gender bias in LLMs. A difference between the two LLMs was seen -- ChatGPT was more often found to carry implicit gender bias, e.g., associating men and women with different profession titles, while explicit gender bias was found in Ernie's responses, e.g., overly promoting women's pursuit of marriage over career. Based on the findings, we reflect on the impact of culture on gender bias and propose governance recommendations to regulate gender bias in LLMs.

cs.AI↗

arXiv2023

How NFT Collectors Experience Online NFT Communities: A Case Study of Bored Ape

Non-fungible tokens (NFTs) are unique cryptographic assets representing the ownership of digital media. NFTs have soared in popularity and trading prices. However, there exists a large gap in the literature regarding NFTs, especially regarding the stakeholders and online communities that have formed around NFT projects. Bored Ape Yacht Club (BAYC) is one of the most influential NFT projects. Through an observational study of online BAYC communities across social media platforms and semi-structured interviews with four participants who owned BAYC NFTs, we explored the experiences of NFT collectors within the online NFT community. Positive community experiences, i.e., personal expression and identity, mutual support among BAYC holders, and exclusive access to online and offline events, were expressed. Encountered challenges included scams and "cash grab" NFT projects as well as trolling. The results of this study point towards the welcoming, positive nature of the NFT community, which is a possible causation factor of the initial rise in popularity of NFTs. Demotivators, on the other hand, countered the established trustworthiness of NFT technology among its consumers.

cs.HC↗