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A study of Computing doctorates in South Africa from 1978 to 2014

机译:1978年至2014年南非计算机博士学位研究

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This paper studies the output of South African universities in terms of computing-related doctorates in order to determine trends in numbers of doctorates awarded and to identify strong doctoral study research areas. Data collected from a variety of sources relating to Computing doctorates conferred since the late 1970s was used to compare the situation in Computing with that of all doctorates. The number of Computing doctorates awarded has increased considerably over the period of study. Nearly three times as many doctorates were awarded in the period 2010–2014 as in 2000–2004. The universities producing the most Computing doctorates were either previously “traditional” universities or comprehensive universities formed by amalgamating a traditional research university with a technikon. Universities of technology have not yet produced many doctorates as they do not have a strong research tradition. The analysis of topic keywords using ACM Computing classifications is preliminary but shows that professional issues are dominant in Information Systems, models are often built in Computer Science and several topics, including computing in education, are evident in both IS and CS. The relevant data is in the public domain but access is difficult as record keeping was generally inconsistent and incomplete. In addition, electronic databases at universities are not easily searchable and access to HEMIS data is limited. The database built for this paper is more inclusive in terms of discipline-related data than others.
机译:本文根据与计算相关的博士学位来研究南非大学的产出,以确定授予博士学位的趋势并确定强大的博士研究领域。自1970年代末以来,从与计算机博士学位有关的各种来源收集的数据被用于将计算机领域的状况与所有博士学位的状况进行比较。在研究期间,获得计算机博士学位的人数大大增加。 2010-2014年获得博士学位的人数几乎是2000-2004年获得博士学位的三倍。产生计算博士学位最多的大学要么是以前的“传统”大学,要么是将传统研究型大学与technikon合并而成的综合大学。理工大学尚未建立许多博士学位,因为它们没有很强的研究传统。使用ACM计算分类对主题关键字进行的分析是初步的,但表明专业问题在信息系统中占主导地位,模型通常是在计算机科学中构建的,并且在IS和CS中都明显包括教育中的计算在内的多个主题。相关数据在公共领域,但由于记录保存通常前后不一致且不完整,因此难以访问。此外,大学中的电子数据库不易搜索,访问HEMIS数据的机会受到限制。就学科相关数据而言,为本文构建的数据库比其他数据库更具包容性。

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