当前位置: X-MOL 学术Learning and Individual Differences › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Process data from electronic textbooks indicate students' classroom engagement
Learning and Individual Differences ( IF 3.8 ) Pub Date : 2020-09-29 , DOI: 10.1016/j.lindif.2020.101934
Frank Reinhold , Anselm Strohmaier , Stefan Hoch , Kristina Reiss , Ricardo Böheim , Tina Seidel

Electronic learning environments used in mathematics lessons offer new ways to assess and analyze students' classroom engagement during authentic learning settings. In this study, we investigated students' electronic textbook-use as a measure for their individual engagement during mathematics instruction. To this end, we combined quantity measures (i.e., time on task, text length) and quality measures (i.e., on topic, mathematically valid, mathematical language used). Cluster analysis based on process data of 253 six-graders—who worked on three writing-to-learn exercises during fraction instruction—revealed four different clusters that we ordered hierarchically in terms of engagement, revealing gender differences in favor of girls. Analyses showed negligible differences in prior knowledge between the clusters, yet significant achievement differences in a posttest—with higher engaged clusters reaching higher outcomes. Our approach offers a viable way to unobtrusively measure students' classroom engagement utilizing process data from electronic textbooks.



中文翻译:

电子教科书的过程数据表明学生的课堂参与度

数学课程中使用的电子学习环境提供了评估和分析学生在真实学习环境中课堂参与度的新方法。在这项研究中,我们调查了学生的电子教科书使用情况,以此作为他们在数学教学中个人参与度的一种度量。为此,我们将数量度量(即,工作时间,文本长度)和质量度量(即,主题,数学上有效的数学语言)结合在一起。基于253个六年级学生的过程数据进行聚类分析,他们在分数教学中进行了三项写作到学习的练习,揭示了四个不同的聚类,我们根据参与度对这些聚类进行了分层排序,揭示了性别差异,有利于女孩。分析表明,集群之间的先验知识差异可忽略不计,事后测试中的成就差异很大-参与度更高的群体达到更高的结果。我们的方法提供了一种可行的方法,可以利用电子教科书中的过程数据来客观地衡量学生的课堂参与度。

更新日期:2020-09-29
down
wechat
bug