Reflections on Different Learning Analytics Indicators for Supporting Study Success

Dirk Ifenthaler, J. Yau
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引用次数: 15

Abstract

Common factors, which are related to study success include students’ sociodemographic factors, cognitive capacity, or prior academic performance, and individual attributes as well as course related factors such as active learning and attention or environmental factors related to supportive academic and social embeddedness. In addition, there are various stages of a learner’s learning journey from the beginning when commencing learning until its completion, as well as different indicators or variables that can be examined to gauge or predict how successfully that journey can or will be at different points during that journey, or how successful learners may complete the study and thereby acquiring the intended learning outcomes. The aim of this research is to gain a deeper understanding of not only if learning analytics can support study success, but which aspects of a learner’s learning journey can benefit from the utilisation of learning analytics. We, therefore, examined different learning analytics indicators to show which aspect of the learning journey they were successfully supporting. Key indicators may include GPA, learning history, and clickstream data. Depending on the type of higher education institution, and the mode of education (face-to-face and/or distance), the chosen indicators may be different due to them having different importance in predicting the learning outcomes and study success.
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对支持学习成功的不同学习分析指标的思考
与学习成功相关的常见因素包括学生的社会人口学因素、认知能力或先前的学习成绩、个人属性以及与课程相关的因素,如主动学习和注意力,或与支持性学术和社会嵌入相关的环境因素。此外,从开始学习到完成学习,学习者的学习之旅有不同的阶段,也有不同的指标或变量,可以用来衡量或预测这段旅程在不同阶段的成功程度,或者学习者完成学习的成功程度,从而获得预期的学习成果。本研究的目的是更深入地了解学习分析是否可以支持学习成功,以及学习者学习过程的哪些方面可以从学习分析的使用中受益。因此,我们检查了不同的学习分析指标,以显示他们成功地支持了学习旅程的哪个方面。关键指标可能包括GPA、学习历史和点击流数据。根据高等教育机构的类型和教育模式(面对面和/或远程),所选择的指标可能会有所不同,因为它们在预测学习成果和学习成功方面具有不同的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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