Data files for Automated tailored feedback does not help university students overcome mathematics misconceptions

Contains the main data file, Rmd script, and html output of the Rmd script. Also contains the figures from the manuscript.Article abstract:Background: Programming automated tailored feedback to help students overcome mathematical errors is time-consuming, and given the mixed results of the feedback literature might not be worth the effort.Aims: We conducted an experiment to test whether automated tailored feedback helped students overcome a well-known misconception involving calculating the area bounded by a curve and the x-axis.Sample: Participants were 461 university students drawn from three continents.Methods: Participants were randomly assigned to receive no feedback, or accuracy feedback, or accuracy with elaborated feedback. The experiment involved a pre-test for participants to revise and practise integral calculus techniques, priming items to cue the misconception, intervention items that provided feedback or none according to condition, and post-test items similar to the intervention items.Results: Counter to our expectations, the vast majority of participants scored 0 in the post-test. Participants in the accuracy with elaborated feedback condition scored more highly than those in the accuracy feedback condition, who scored more highly than those in the no feedback condition, but these differences were not significant. In addition, participants in the accuracy with elaborated feedback condition gave fewer misconception responses than those in the accuracy feedback condition, who gave fewer misconception responses than those in the no feedback condition, but again these differences were not significant.Conclusions: Programming automated tailored feedback that responds to common mathematics misconceptions in university mathematics may not be worth the effort.

本数据集包含主要数据文件、Rmd脚本及其生成的html输出，以及来自论文的图表。摘要：背景：编程以自动化、定制化的反馈来帮助学生克服数学错误是一项耗时的工作，鉴于反馈文献结果的参差不齐，可能不值得投入如此努力。目标：我们进行了一项实验，旨在检验自动化、定制化的反馈是否有助于学生克服涉及计算曲线与x轴所围成的面积这一著名误解。样本：参与者为来自三大洲的461名大学生。方法：参与者被随机分配接受无反馈、准确性反馈或带有详细解释的准确性反馈。实验包括对参与者进行的前测，以修订和练习积分计算技巧，提示项以引导误解，干预项根据条件提供反馈或无反馈，以及与干预项相似的测试项。结果：与我们的预期相反，绝大多数参与者在后测中得分均为0。在带有详细解释的准确性反馈条件下，参与者的得分高于准确性反馈条件下的参与者，而后者又高于无反馈条件下的参与者，但这些差异并不显著。此外，在带有详细解释的准确性反馈条件下，参与者的误解反应少于准确性反馈条件下的参与者，而后者又少于无反馈条件下的参与者，但这些差异同样并不显著。结论：针对大学数学中常见的数学误解编程自动化、定制化的反馈可能不值得投入如此努力。