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A Unified Approach to Quantitatively Measure the Similarity of Computer Science Units in Australia

机译:统一衡量澳大利亚计算机科学单位相似性的统一方法

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Research Full paper - Computer Science (CS) education is increasingly becoming popular across the globe. With the increased popularity of CS and Information and Communications Technology (ICT) courses, the ability to measure the similarity/distance between units can aid the decision-making process of education providers during learning path recommendations, evaluating unit exemptions/advanced standings, etc. The ability to quantitatively measure the similarity of two units will assist decision-making processes which are otherwise likely to be tedious and time-consuming. Therefore, in this work, we explore how to quantitatively measure the similarity/distance between two CS/ICT units, in an Australian setting. In this study, we utilize data from multiple CS/ICT courses offered by two Australian education providers. The data is generated as a result of the Australian Computer Society’s (ACS) course accreditation process during which each unit of a course is mapped into multiple knowledge areas. We measured the similarity between units in terms of their coverage of the knowledge areas using multiple distance measures. Our work is novel in examining a quantitative measure of unit similarity, by introducing a unified approach across education providers that follow the ACS course accreditation process.
机译:研究全文 - 计算机科学(CS)教育越来越受全球流行。随着CS和信息和通信技术(ICT)课程的普及,衡量单位之间相似性/距离的能力可以帮助教育提供者在学习路径建议期间的决策过程,评估单位豁免/高级分配等。定量测量两个单位相似性的能力将有助于决策过程,否则可能会乏味且耗时。因此,在这项工作中,我们探讨如何在澳大利亚环境中定量测量两个CS / ICT单元之间的相似性/距离。在本研究中,我们利用两个澳大利亚教育提供者提供的多个CS / ICT课程的数据。由于澳大利亚计算机协会(ACS)课程认证过程的结果产生了数据,在此期间课程的每个单位映射到多个知识区域。我们在使用多个距离措施的知识区域的覆盖范围内测量了单位之间的相似性。我们的作品是在研究单位相似性的定量衡量标准的小说,通过在遵循ACS课程认证过程的教育提供者介绍统一的方法。

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