AI-driven recommender systems are often perceived as personalization black boxes, limiting users' ability to understand how their data shapes content (information asymmetry) or to influence system behavior meaningfully (power asymmetry). This study explores how design can strengthen user agency by integrating transparency with actionable control. We developed a provotype that introduces new interface features for managing data use, discovering varied content, and configuring context-based recommending modes. The walkthroughs and interviews with 19 participants show how these features help users interpret personalization signals, understand how their actions influence outcomes, address concerns from unwanted inference to narrow feeds (e.g., filter bubbles), and build trust in the system. We also identify strategies for promoting adoption and awareness of agency-enhancing features. Overall, our findings reaffirm users' desire for active influence over personalization and contribute concrete interface mechanisms with empirical insights for designing recommender systems that foreground user autonomy and fairness in AI-driven content delivery.

Mobile games are becoming a vital medium for social interaction, offering a platform that transcends geographical boundaries.An increasing number of visually impaired individuals are engaging in mobile gaming to connect, collaborate, compete, and build friendships.In China, visually impaired communities face significant social challenges in offline settings, making mobile games a crucial avenue for socialization.However, the design of mobile games and their mapping to real-world environments significantly shape their social gaming experiences.This study explores how visually impaired players in China navigate socialization and integrate into gaming communities.Through interviews with 30 visually impaired players, we found that while mobile games fulfill many of their social needs, technological barriers and insufficient accessibility features, and internal community divisions present significant challenges to their participation.This research sheds light on their social experiences and offers insights for designing more inclusive and accessible mobile games.

Recommender systems have emerged as powerful tools for providing personalized recommendations, often employed by online platforms to suggest products or media content based on user behavior. The design of these systems significantly influences and shapes user experience, as they guide users through vast amounts of information and help them make decisions more efficiently. In this study, we conducted an online experiment (N = 268) to test how different framings of source (human-oriented vs. machine-oriented vs. proxy-oriented vs. none) in recommendation explanations induced users’ attribution of human vs. machine agency in the recommendation process, thus impacting trusting beliefs and trusting behavioral intentions. Results revealed that subtle wording variations could lead participants to orient to different recommendation sources and then attribute human or machine agencies differently, regardless of their understanding of the true technical mechanism. Participants who attributed greater human agency to the recommendations exhibited higher confidence in making choices based on the system’s suggestions and a greater willingness to disclose personal information for continued use, mediated by the competence and integrity dimensions of trust, respectively. By evaluating both wine and vacuum recommendations, we also explored the contextual differences between hedonic and utilitarian product types in the recommendation process. The findings of this study provide implications for the trust-building and ethical communication design of recommender systems.

Providing preparatory information is a pretraining intervention method suitable for high cognitive loads and high-pressure training environments and can significantly improve training effects. In this study, we investigated the impact of the media immersion level and pretraining intervention on cardiopulmonary resuscitation (CPR) training. We conducted a 2 [immersive embodied virtual reality (IEVR) vs. video] by 2 [pretraining intervention vs. no pretraining intervention] between-subject randomised experiment in Yixin, China. The results demonstrated that regardless of the media immersion level, embodied training combined with body movements is effective in improving self-efficacy, knowledge retention, and skill transfer. Although the subjects’ self-efficacy and CPR knowledge were significantly improved after training, the media level did not significantly improve knowledge retention and self-efficacy. Our study suggested that the media immersion level and pretraining intervention strategy have a significant interaction effect on the level of skill transfer. Moreover, the pretraining intervention promoted skills transfer in IEVR training but did not have a similar effect on video embodied training. These results indicate that incorporating a pretraining intervention by providing preparatory information can enhance the learning outcomes in IEVR training.