As generative AI transforms educational feedback practices, understanding students' perceptions of different feedback providers becomes crucial for effective implementation. This study addresses a critical gap by comparing undergraduate students' trust in AI-generated, human-created, and human-AI co-produced feedback, informing how institutions can adapt feedback practices in this new era. Through a within-subject experiment with 91 participants, we investigated factors predicting students' ability to distinguish between feedback types, perception of feedback quality, and potential biases to AI involvement. Findings revealed that students generally preferred AI and co-produced feedback over human feedback in terms of perceived usefulness and objectivity. Only AI feedback suffered a decline in perceived genuineness when feedback sources were revealed, while co-produced feedback maintained its positive perception. Educational AI experience improved students' ability to identify AI feedback and increased their trust in all feedback types, while general AI experience decreased perceived usefulness and credibility. Male students consistently rated all feedback types as less valuable than their female and non-binary counterparts. These insights inform evidence-based guidelines for integrating AI into higher education feedback systems while addressing trust concerns and fostering AI literacy among students.

本研究解决了在生成性人工智能变革教育反馈实践背景下，学生对不同反馈提供者的信任感问题。通过对91名本科生的实验，发现学生普遍更信赖人工智能及共同制作的反馈，而对人类反馈的信任度较低，且男性学生普遍评估所有反馈类型的价值低于女性和非二元性别的学生。这些发现为教育机构在新时期调整反馈实践提供了重要依据。

评估本科生对人工智能、人类及共同制作反馈的信任