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Enabling Interdisciplinary Instruction in Computer Science and Humanities An Innovative Teaching and Learning Model Customized for Small Liberal Arts Colleges

机译:在计算机科学和人文学科中实现跨学科教学,是为小型文艺学院定制的创新教学和学习模式

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Infiltration of data-driven computational methods of humanities research has generated mutual interests between the two communities of computer science and humanities. Larger institutions have adopted drastic structural reforms to meet the challenges to bridge the two fields. Successful examples include the integrated major programs launched at Stanford University and the collaborative workshop at Carnegie Mellon University. These types of exploratory experiments require (1) intensive resources as well as (2) strong support of faculty and administration. At a small college, both can be luxuries. We present an innovative model to carry out effective synchronized courses of computational humanities and digital humanities that pulls together efforts between two small programs and needs little additional support. This paper reviews the proposal, design, and delivery of a pair of interdisciplinary graduate courses in the small college setting. We discuss the details of our implementation and provided our observations and recommendations.
机译:数据驱动的人文研究方法的渗透在计算机科学与人文学科的两个社区之间产生了共同利益。较大的机构采用了剧烈的结构改革,以应对弥合这两个领域的挑战。成功的例子包括在斯坦福大学和卡内基梅隆大学的合作研讨会发布的综合主要方案。这些类型的探索性实验需要(1)强化资源,以及(2)教师和管理的强大支持。在一个小学,两者都可以奢侈。我们提出了一种创新模型,用于开展有效的计算人文和数字人文学课程,这些课程和数字人文学科将努力共同努力,需要几乎没有额外的支持。本文审查了小学环境中一对跨学科研究生课程的提案,设计和交付。我们讨论了我们实施的详细信息,并提供了我们的观察和建议。

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