STEM领域的人才短缺日益严重，大学和学院都在竭力满足这一需求。以计算机科学为例，参加入门课程的美国学生人数在过去10年增长了3倍。最近，作为缓解这种压力的一种方式，大规模在线开放课程（MOOCs）得到了推广，这提供了受教育的机会。然而，更大的挑战在于学生的不同背景、学生黏性以及提供反馈和评估的问题。依靠计算工具的个性化教育可以应对这一挑战。
尽管自动化辅导在不同时段和不同社区被研究，但计算机和教育技术的最新进展为改变学生的学习方式提供了令人振奋的机会。尤其，至少有三个趋势具有重大意义。首先，随着逻辑推理、数据分析和自然语言处理技术的发展，自动评估、个性化教学（包括目标反馈）和适应多种学科的内容生成的辅导工具应运而生。其次，学习科学和人机交互的研究有助于更好地理解不同的学生如何学习，什么时间和什么类型的干预对不同的教学目标是有效的，以及如何衡量教育工具的成功。最后，最近学术界和产业界出现的在线教育平台为共享基础设施的发展带来了新的机遇。这次CCC研讨会聚集了开发基于逻辑推理和机器学习等技术教育工具的研究人员和教育、人机交互和认知心理学的研究人员。
原文标题：Computer-Aided Personalized Education
原文：The shortage of people trained in STEM fields is becoming acute, and universities and colleges are straining to satisfy this demand. In the case of computer science, for instance, the number of US students taking introductory courses has grown three-fold in the past decade. Recently, massive open online courses (MOOCs) have been promoted as a way to ease this strain. This at best provides access to education. The bigger challenge though is coping with heterogeneous backgrounds of different students, retention, providing feedback, and assessment. Personalized education relying on computational tools can address this challenge.
While automated tutoring has been studied at different times in different communities, recent advances in computing and education technology offer exciting opportunities to transform the manner in which students learn. In particular, at least three trends are significant. First, progress in logical reasoning, data analytics, and natural language processing has led to tutoring tools for automatic assessment, personalized instruction including targeted feedback, and adaptive content generation for a variety of subjects. Second, research in the science of learning and human-computer interaction is leading to a better understanding of how different students learn, when and what types of interventions are effective for different instructional goals, and how to measure the success of educational tools. Finally, the recent emergence of online education platforms, both in academia and industry, is leading to new opportunities for the development of a shared infrastructure. This CCC workshop brought together researchers developing educational tools based on technologies such as logical reasoning and machine learning with researchers in education, human-computer interaction, and cognitive psychology.
原文作者：Rajeev Alur, Richard Baraniuk, Rastislav Bodik, Ann Drobnis, Sumit Gulwani, Bjoern Hartmann, Yasmin Kafai, Jeff Karpicke, Ran Libeskind-Hadas, Debra Richardson, Armando Solar-Lezama, Candace Thille, Moshe Vardi
原文地址：https://arxiv.org/abs/2007.03704
计算机辅助的个性化教育（CS CY）.pdf