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
发表日期
2020/7/7
期刊
arXiv preprint arXiv:2007.03704
简介
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 …
引用总数
2019202020212022202320241121
学术搜索中的文章
R Alur, R Baraniuk, R Bodik, A Drobnis, S Gulwani… - arXiv preprint arXiv:2007.03704, 2020