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A new metric for assessing quality in advanced graduate courses in computer science and engineering

机译:评估计算机科学与工程高级研究生课程质量的新指标

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In the graduate schools across the US, the teaching of graduate courses continues to constitute a significant component of graduate education. This paper presents a philosophy that underlies the design of a few advanced graduate courses at Arizona State University in the sub-disciplines of hardware description languages, communications networks, computer-aided design of digital systems, distributed systems, distributed algorithms, and modeling and simulation. From the philosophy, a new metric emerges-the extent and significance of the knowledge "discovered" by the students, towards evaluating the quality of such courses. Discovery refers to the knowledge that is brought out into the open, through logical reasoning from the first principles, by the student for himself/herself. It is significant in that it becomes an integral part of the individual who not only gains invaluable insight and confidence in the subject matter but can improvise, reason, and apply it to other areas in creative ways. The paper illustrates the application of the metric through a number of actual cases encountered during teaching at ASU. It also presents a list of the desirable attributes of the underlying educational environment to ensure success in the design and delivery of such courses.
机译:在美国的研究生院中,研究生课程的教学继续构成研究生教育的重要组成部分。本文提出了一种哲学,该哲学是亚利桑那州立大学在硬件描述语言,通信网络,数字系统的计算机辅助设计,分布式系统,分布式算法以及建模和仿真等子学科中设计一些高级研究生课程的基础。从哲学上,出现了一个新的指标-学生“发现”的知识的程度和重要性,以评估此类课程的质量。发现是指学生根据第一原理通过逻辑推理公开获得的知识。重要的是,它成为个人不可或缺的一部分,不仅可以对主题获得宝贵的见识和信心,还可以即兴创作,推理并以创造性的方式将其应用到其他领域。本文通过在ASU教学期间遇到的许多实际案例说明了该指标的应用。它还列出了基础教育环境的理想属性,以确保成功设计和交付此类课程。

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