EduPal 无教授落伍：通过同伴驱动的推荐系统支持教师
EduPal leaves no professor behind: Supporting faculty via a peer-powered recommender system
AI总结：
EduPal通过同伴驱动的推荐系统为教师提供个性化教学支持，解决知识蒸馏问题，并通过众包和反馈提升教育实践质量。
摘要：
新冠疫情后高等教育的迅速变革揭示了教师在教学支持方面的不足。我们提出一个智能、基于知识的聊天机器人，解决知识蒸馏问题，并为教师提供个性化推荐。我们的协作系统通过众包获取有用的教育实践，并根据理论和用户反馈持续过滤推荐，从而提升后续同行的体验。我们为本地STEM教师构建了原型作为证明概念，并获得积极反馈，鼓励我们扩展开发和推广，特别是针对资源匮乏的教师。
英文摘要：
The swift transitions in higher education after the COVID-19 outbreak identified a gap in the pedagogical support available to faculty. We propose a smart, knowledge-based chatbot that addresses issues of knowledge distillation and provides faculty with personalized recommendations. Our collaborative system crowdsources useful pedagogical practices and continuously filters recommendations based on theory and user feedback, thus enhancing the experiences of subsequent peers. We build a prototype for our local STEM faculty as a proof concept and receive favorable feedback that encourages us to extend our development and outreach, especially to underresourced faculty.
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。
