With the development and improvement of technology, live streaming systems have emerged in people's daily lives, providing new channels for agricultural product sales. This study aims to understand how to scientifically design live streaming systems for agricultural product sales based on user perceptions and preferences. We conducted an online survey, and Study 1 obtained 569 valid samples. We established a structural equation model and applied fuzzy-set qualitative comparative analysis to identify necessary conditions and configurations. In Study 2, two survey stages obtained 61 and 228 valid samples, respectively, and exploratory factor analysis was used for dimensionality reduction. The results showed that information quality and perceived interactivity can reduce social anxiety in female and male users, respectively. Information quality and perceived playfulness positively affect purchase intention. Furthermore, we identified four positive factors, including natural quality, support for domestic agriculture, transportation services, and information attractiveness, and three negative factors, including fulfillment risk, decision pressure, and inefficient consumption experience that may influence users' purchase intention. The findings provide validated design insights for live streaming systems, playing a positive role in enhancing design effectiveness and promoting agricultural product sales.

This study examines artificial intelligence in college students' painting education and their potential impact on students' continuous learning intention. In this study, two surveys were conducted. The first survey included 793 valid samples, and the second survey contained 210 valid samples. Study 1 established the path influence relationship between self-perceived creativity, flow experience, learning interest, and continuous learning intention, confirming gender and educational level as moderators. Study 2 identifies 4 positive factors and 3 negative factors to continuous learning intention through exploratory factor analysis. These findings not only provide a reference for the application of artificial intelligence to art education, but also provide new ideas and approaches for the widespread promotion and application of artificial intelligence to other disciplines of education.

This study aims to understand how interaction design can enhance the user experience of random video chats using virtual avatars (RVC–VAs). We propose a framework to explain the mechanisms underlying changes in social anxiety and flow experiences. We applied analysis of variance (ANOVA), structural equation modeling (SEM), and fuzzy set qualitative comparative analysis (fsQCA) to data collected through surveys. Our findings indicate that a second-order construct, named mysterious interaction, comprising perceived interactivity, perceived vividness, and mystery, can reduce social anxiety and positively impact flow. Novelty experience enhances flow for female users but increases social anxiety for all users. Notably, social anxiety unexpectedly showed a positive effect on flow. Based on these findings, we propose interaction design strategies that could aid in the development and optimization of RVC-VA platforms, providing specific parameters to assist designers in prioritizing and planning actionable steps. This study makes a significant contribution to the advancing of online social services and addressing users’ needs for online social interaction.