Developing a model and applications for probabilities of student success: a case study of predictive analytics
Developing a model and applications for probabilities of student success: a case study of predictive analytics
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开发学生成功概率的模型和应用程序：预测分析的案例研究
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Carol Calvert
中科院分区：
文献类型：
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作者：
Carol Calvert
本案例研究涉及远程学习开放获取课程的学生。它演示了使用预测分析来生成学生旅程中不同点或里程碑的成功和保留概率模型。已经确定了一套核心解释变量，并确定了它们在不同里程碑的不同相对重要性。模型运行时的解释变量、里程碑和参考点在其他机构会有所不同，但这种方法可以推广到远程学习机构，更广泛地说，推广到任何高等教育机构。机构，特别是远程教育机构，不具有经常见到学生的优势，需要充分利用它们所掌握的任何记录信息，设法查明哪些学生有可能或可能离开。在不同的里程碑，不同因素的重要性，可能有助于量身定制学生支持个别学生，从而改善开放式远程教育的低保留率。
This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at different milestones identified. The explanatory variables, milestones and reference points when the model is run will be different at other institutions but the approach may be generalised to distance learning institutions and, more broadly, to any HE institution. Institutions, and especially distance education institutions which do not have the advantages of frequently seeing students, need to make full use of any recorded information they hold to try and identify students who are, or become, at potential risk of leaving. The importance of different factors, at different milestones, may help tailor student support to individual students and therefore improve low retention in open access distance education.