人工智能在高等教育中的感知与干预：学生对学习影响、情感反应和伦理优先事项的看法
AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities
AI总结：
本研究探讨了人工智能在高等教育中的感知与干预对学生学习影响、情感反应及伦理优先事项的影响，发现学生更偏好系统生成的提示而非教师帮助，并强调自主性和隐私的伦理优先级。
摘要：
人工智能技术通过感知学生注意力和情绪来实现更个性化的教学干预正日益推广，但引发了关于学生学习、福祉和伦理的紧迫问题。特别是，学生对人工智能感知-干预在学习中的观点往往被忽视。我们与澳大利亚大学学生（N=132）进行了在线混合方法实验，呈现了不同是否使用感知（使用中 vs. 不使用）、感知方式（基于目光的注意力检测 vs. 基于面部的情绪检测）和干预（通过数字设备 vs. 教师）的视频场景。参与者还完成了配对排名任务以优先考虑六个核心伦理问题。研究发现，学生重视有针对性的干预，但对AI监控的反应消极，无论感知方法如何。学生更倾向于系统生成的提示而非教师发起的帮助， citing 学习自主性和社交尴尬的担忧。学生在伦理考虑上优先考虑自主性和隐私，随后是透明度、准确性、公平性和学习利他性。我们呼吁设计可定制、社会敏感、非侵入性的系统，以保护学生控制、自主性和福祉。
英文摘要：
AI technologies that sense student attention and emotions to enable more personalised teaching interventions are increasingly promoted, but raise pressing questions about student learning, well-being, and ethics. In particular, students' perspectives about AI sensing-intervention in learning are often overlooked. We conducted an online mixed-method experiment with Australian university students (N=132), presenting video scenarios varying by whether sensing was used (in-use vs. not-in-use), sensing modality (gaze-based attention detection vs. facial-based emotion detection), and intervention (by digital device vs. teacher). Participants also completed pairwise ranking tasks to prioritise six core ethical concerns. Findings revealed that students valued targeted intervention but responded negatively to AI monitoring, regardless of sensing methods. Students preferred system-generated hints over teacher-initiated assistance, citing learning agency and social embarrassment concerns. Students' ethical considerations prioritised autonomy and privacy, followed by transparency, accuracy, fairness, and learning beneficence. We advocate designing customisable, social-sensitive, non-intrusive systems that preserve student control, agency, and well-being.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
