arXiv subjects

Joseph Tu

Publications and source records attributed to Joseph Tu.

5 recordsLinked to original sources

arXiv2026

Theory, Experience, and Instinct: A Glimpse Into AAA Game Processes and How UX Leaders Navigate Pre-Production

Foundational decisions shape a project's long-term trajectory, a dynamic that becomes especially evident in the inherent complexity of game pre-production. However, academic frameworks often see limited uptake at this stage, as they do not readily map onto industry contexts, production constraints, and cross-functional workflows. To better understand how design decisions are made in practice, we conducted interviews with 15 UX leaders from the AAA (triple-A) games industry. Our findings show that early UX decisions emerge from a dynamic blend of theory, experience, and intuition. In cross-functional structures (such as strike and competency teams), UX leaders collaboratively align player needs, technical feasibility, and creative vision. These decision-making processes involve translating academic concepts into production-ready insights, codifying experiential knowledge into reusable practices, and relying on informed intuition amid uncertainty. We argue that meaningful impact requires academia to develop malleable conceptual tools that integrate with practitioners' highly adaptive design processes. We conclude by discussing how existing frameworks might be adapted to connect academic insights with AAA workflows. Rather than prescriptive directives, we offer these as starting points for discussion that support strike and competency teams through shared language, reusable design systems, and strategies for collaborative, context-sensitive decision-making.

cs.HC↗

arXiv2025

From Solo to Social: Exploring the Dynamics of Player Cooperation in a Co-located Cooperative Exergame

Digital games offer rich social experiences and promote valuable skills, but they fall short in addressing physical inactivity. Exergames, which combine exercise with gameplay, have the potential to tackle this issue. However, current exergames are primarily single-player or competitive. To explore the social benefits of cooperative exergaming, we designed a custom co-located cooperative exergame that features three distinct forms of cooperation: Free (baseline), Coupled, and Concurrent. We conducted a within-participants, mixed-methods study (N = 24) to evaluate these designs and their impact on players' enjoyment, motivation, and performance. Our findings reveal that cooperative play improves social experiences. It drives increased team identification and relatedness. Furthermore, our qualitative findings support cooperative exergame play. This has design implications for creating exergames that effectively address players' exercise and social needs. Our research contributes guidance for developers and researchers who want to create more socially enriching exergame experiences.

cs.HC↗

arXiv2024

The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writing

Generative AI (GenAI) use in research writing is growing fast. However, it is unclear how peer reviewers recognize or misjudge AI-augmented manuscripts. To investigate the impact of AI-augmented writing on peer reviews, we conducted a snippet-based online survey with 17 peer reviewers from top-tier HCI conferences. Our findings indicate that while AI-augmented writing improves readability, language diversity, and informativeness, it often lacks research details and reflective insights from authors. Reviewers consistently struggled to distinguish between human and AI-augmented writing but their judgements remained consistent. They noted the loss of a "human touch" and subjective expressions in AI-augmented writing. Based on our findings, we advocate for reviewer guidelines that promote impartial evaluations of submissions, regardless of any personal biases towards GenAI. The quality of the research itself should remain a priority in reviews, regardless of any preconceived notions about the tools used to create it. We emphasize that researchers must maintain their authorship and control over the writing process, even when using GenAI's assistance.

cs.CL↗

arXiv2024

Augmenting the Author: Exploring the Potential of AI Collaboration in Academic Writing

This workshop paper presents a critical examination of the integration of Generative AI (Gen AI) into the academic writing process, focusing on the use of AI as a collaborative tool. It contrasts the performance and interaction of two AI models, Gemini and ChatGPT, through a collaborative inquiry approach where researchers engage in facilitated sessions to design prompts that elicit specific AI responses for crafting research outlines. This case study highlights the importance of prompt design, output analysis, and recognizing the AI's limitations to ensure responsible and effective AI integration in scholarly work. Preliminary findings suggest that prompt variation significantly affects output quality and reveals distinct capabilities and constraints of each model. The paper contributes to the field of Human-Computer Interaction by exploring effective prompt strategies and providing a comparative analysis of Gen AI models, ultimately aiming to enhance AI-assisted academic writing and prompt a deeper dialogue within the HCI community.

cs.HC↗

arXiv2024

Sora OpenAI's Prelude: Social Media Perspectives on Sora OpenAI and the Future of AI Video Generation

The rapid advancement of Generative AI (Gen-AI) is transforming Human-Computer Interaction (HCI), with significant implications across various sectors. This study investigates the public's perception of Sora OpenAI, a pioneering Gen-AI video generation tool, via social media discussions on Reddit before its release. It centers on two main questions: the envisioned applications and the concerns related to Sora's integration. The analysis forecasts positive shifts in content creation, predicting that Sora will democratize video marketing and innovate game development by making video production more accessible and economical. Conversely, there are concerns about deepfakes and the potential for disinformation, underscoring the need for strategies to address disinformation and bias. This paper contributes to the Gen-AI discourse by fostering discussion on current and future capabilities, enriching the understanding of public expectations, and establishing a temporal benchmark for user anticipation. This research underscores the necessity for informed, ethical approaches to AI development and integration, ensuring that technological advancements align with societal values and user needs.

cs.CY↗