Assessing Learning Analytics Impact on Coding Competence Growth

David Boulanger, Jeremie Seanosky, Rébecca Guillot, Isabelle Guillot, Claudia Guillot, Shawn N. Fraser, Vivekanandan S. Kumar, Kinshuk Kinshuk
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Abstract

The literature reveals that the effectiveness of learning analytics (LA) tools is best evaluated with a mixed-method approach and not only with summative measurements such as grades. A recent study on the impact of an LA tool over academic performance did not substantiate its effect in improving grades for coding tasks despite qualitative comments of experimental group participants indicating that the tool was effective in improving coding competences in Java. In analyzing this viewpoint, this paper describes the impact of LA formative feedback on the growth of students' coding competences.
评估学习分析对编码能力成长的影响
文献表明,学习分析(LA)工具的有效性是最好的评估与混合方法的方法,而不仅仅是总结性测量,如成绩。最近一项关于LA工具对学习成绩影响的研究并没有证实它对提高编码任务成绩的影响,尽管实验组参与者的定性评论表明该工具在提高Java编码能力方面是有效的。在分析这一观点的基础上,本文描述了LA形成性反馈对学生编码能力成长的影响。
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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