目的 针对传统高校图书馆AIGC交互界面多忽略学生个性化差异,导致信任构建模糊问题。通过建立个性化高校学生信任偏好,以提升用户体验与信任度。方法 通过问卷与访谈调查本、硕、博学生对AIGC工具的信任偏好;运用层次分析法计算用户影响信任偏好需求权重,结合均值对比分析识别不同学历群体在13项子准则上的差异;以正交实验构建界面样本,建立高保真样本并邀请用户使用样本进行测试,通过用户测试与联合分析建立信任偏好与设计模式的关联模型;接着,通过数智化服务蓝图完成从量化偏好到系统架构的完整设计路径;最后,通过信任度量表,满意度调查与深度访谈验证方案可行性。结果 信任偏好呈现学历差异：本科生以能力信任为核心,硕士研究生聚焦过程信任,博士研究生呈现能力信任与情感信任融合。依据综合正交表结果,确定7项设计要素,并据此构建AIGC交互界面方案。结论 AIGC交互界面方案在用户满意度与信任度上均显著优于传统高校图书馆界面。基于学生信任偏好的AIGC界面设计方法,为未来数智化高校图书馆满足个性化需求提供了一种可行路径。
Abstract
The work aims to establish personalized trust preferences among students to address the issue that traditional AIGC interactive interface designs for university libraries often overlook students' personalized differences, leading to vague trust construction, so as to enhance user experience and trust. Through questionnaires and interviews, trust preferences of undergraduate, master's, and doctoral students toward AIGC tools were investigated. The Analytic Hierarchy Process (AHP) was used to calculate the weights of influencing factors, and mean comparison analysis was employed to identify differences among the three academic groups across 13 sub-criteria. An orthogonal experiment was conducted to construct high-fidelity interface prototypes, which were then tested by users. Conjoint analysis was applied to build a relational model between trust preferences and design patterns. Subsequently, a digital intelligence service blueprint was utilized to translate quantitative preferences into a complete system architecture. Finally, the feasibility of the solution was validated through a trust measurement scale, user satisfaction surveys, and in-depth interviews. The results revealed differentiated trust preferences by academic levels: undergraduate students prioritized competence trust, master's students focused on process trust, and doctoral students exhibited a blend of competence and emotional trust. Based on the results of a comprehensive orthogonal array, seven design factors were identified and used to construct an AIGC interactive interface prototype. In conclusion, the AIGC interactive interface significantly outperforms the traditional university library interface in terms of both user satisfaction and trust. This student trust-informed AIGC interface design approach provides a feasible pathway for future smart digital university libraries to accommodate personalized needs.
关键词
信任偏好 /
生成式人工智能（AIGC） /
用户体验 /
交互界面 /
高校图书馆
Key words
trust preference /
Artificial Intelligence Generated Content (AIGC) /
user experience /
interactive interface /
university library
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基金
谢友柏设计科学研究基金（XYB-DS-202204）; 教育部产学合作协同育人项目（230711243607244）
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