Data Students’ Intention to Use Large Language Model Agents for Learning Support A Mixed-Methods Study Extending the UTAUT Model

Data collection was conducted through an online survey platform targeting Chinese university students. Potential respondents were recruited through the questionnaire link shared by university teachers and students. To ensure data authenticity, eligibility criteria required participants to have prior experience with LLM Agents. The data collection spanned 7 weeks, with intermittent reminders to enhance participation rates. A total of 326 responses were collected, and after excluding invalid entries , 306 valid questionnaires were retained, achieving a validity rate of 93.9%.

本研究通过面向中国大学生的在线调查平台开展数据采集工作。潜在受访者通过高校师生分享的问卷链接招募而来。为保障数据真实性，本次调查设置准入标准：参与者需具备大语言模型智能体（LLM Agents）的使用经验。数据采集周期共计7周，期间通过间歇性发送提醒以提升参与率。最终累计回收问卷326份，剔除无效作答后保留有效问卷306份，有效率达93.9%。