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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:启用计算机科学和人文学科的跨学科教学为小型文理学院量身定制的创新教学模式

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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计算方法的渗透已在计算机科学和人文科学两个社区之间产生了共同利益。较大的机构已经进行了激烈的结构改革,以应对在这两个领域之间架起桥梁的挑战。成功的例子包括在斯坦福大学启动的综合大型课程和在卡内基梅隆大学的合作研讨会。这些类型的探索性实验需要(1)大量资源以及(2)师资力量和行政管理的大力支持。在一所小型大学中,两者都是奢侈品。我们提出了一种创新的模型来执行计算人文科学和数字人文科学的有效同步课程,该课程将两个小程序之间的努力汇集在一起​​,几乎不需要额外的支持。本文回顾了小型大学环境中一对跨学科研究生课程的建议,设计和提供。我们讨论了实施的细节,并提供了意见和建议。

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