评估工程教育中AI助教的使用效果与伦理挑战
Evaluating AI-Powered Learning Assistants in Engineering Higher Education: Student Engagement, Ethical Challenges, and Policy Implications
- 通过问卷、日志和访谈,分析学生对AI助教的使用体验
- 近半数学生更愿意用AI助教而非找教师或助教求助
- 强调透明政策与教师引导对有效AI应用的关键作用
随着生成式AI逐步融入高等教育,理解学生如何与这些技术互动对负责任的推广至关重要。本研究评估了在一所大型R1公立大学的本科土木与环境工程课程中实施的教育AI枢纽(Educational AI Hub)这一AI赋能学习框架。采用混合方法设计,结合前后测问卷、系统使用日志及对学生AI交互的质性分析,研究考察了学生对信任度、伦理、可用性及学习成效的认知。结果显示,学生普遍认为该AI助教具有可及性和亲和力,近一半人表示使用它比向教师或助教求助更轻松。该工具在完成作业和理解概念方面最为有用,但对其教学质量评价褒贬不一。伦理不确定性,特别是关于机构政策和学术诚信的问题,成为全面参与的主要障碍。总体而言,学生视AI为对人类教学的补充而非替代。研究强调可用性、伦理透明度及教师指导在促进有意义的AI参与中的重要性。共71名学生参与两门课程,产生超过600次AI交互和100份问卷,提供了量化与情境化兼具的学习参与洞察。
原文摘要 · Abstract (English)
As generative AI becomes increasingly integrated into higher education, understanding how students engage with these technologies is essential for responsible adoption. This study evaluates the Educational AI Hub, an AI-powered learning framework, implemented in undergraduate civil and environmental engineering courses at a large R1 public university. Using a mixed-methods design combining pre- and post-surveys, system usage logs, and qualitative analysis of students' AI interactions, the research examines perceptions of trust, ethics, usability, and learning outcomes. Findings show that students valued the AI assistant for its accessibility and comfort, with nearly half reporting greater ease using it than seeking help from instructors or teaching assistants. The tool was most helpful for completing homework and understanding concepts, though views on its instructional quality were mixed. Ethical uncertainty, particularly around institutional policy and academic integrity, emerged as a key barrier to full engagement. Overall, students regarded AI as a supplement rather than a replacement for human instruction. The study highlights the importance of usability, ethical transparency, and faculty guidance in promoting meaningful AI engagement. A total of 71 students participated across two courses, generating over 600 AI interactions and 100 survey responses that provided both quantitative and contextual insights into learning engagement.
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