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Comparing and assessing department-level instructional workloads: a study in data management
Journal of Higher Education Policy and Management ( IF 2.553 ) Pub Date : 2021-02-23 , DOI: 10.1080/1360080x.2021.1889448
Richard L. Goerwitz 1
Affiliation  

ABSTRACT

Hiring academic staff into departments and supporting them remains the single costliest activity that most institutions of higher learning engage in and requires careful, long-term, data-driven planning. This study identifies widely available (but seldom actually used) variables needed for this process: available instructional workload units and student credits. While doing so, this study also walks through best practices in extracting such variables from administrative systems in repeatable, auditable ways using stock database design tools and methods. Finally, this study (literally) illustrates, in practice, how surfacing such variables in readily interpretable tables, pictures, and interactive dashboards can facilitate their application and use, by providing administrators with ways of presenting these data to peers and oversight boards in transparent, ideologically neutral, but yet actionable, formats. Although this study brings considerable quantitative data to bear, it is, at its core, a practical study in how academic administrators should be managing their data—the ‘new gold’. 



中文翻译:

比较和评估部门级教学工作量:数据管理研究

摘要

聘请学术人员到院系并为他们提供支持仍然是大多数高等教育机构从事的一项成本最高的活动,需要仔细、长期、数据驱动的规划。这项研究确定了此过程所需的广泛可用(但很少实际使用)的变量:可用的教学工作量单位和学生学分。在这样做的同时,本研究还介绍了使用库存数据库设计工具和方法以可重复、可审计的方式从管理系统中提取此类变量的最佳实践。最后,这项研究(字面意思)说明,在实践中,如何在易于解释的表格、图片和交互式仪表板中显示这些变量可以促进它们的应用和使用,通过为管理员提供以透明、意识形态中立但可操作的格式向同行和监督委员会呈现这些数据的方式。尽管这项研究带来了大量的定量数据,但它的核心是关于学术管理者应该如何管理他们的数据——“新黄金”——的实用研究。 

更新日期:2021-02-23
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