评估学生准备的课前指标与学生入门统计表现之间的关联：基于模拟的推理与基于非模拟的推理的早期数据的结果
Assessing the association between pre-course metrics of student preparation and student performance in introductory statistics: Results from early data on simulation-based inference vs. nonsimulation based inference
摘要：
最近在基于代数的入门统计课程（统计101）的基于模拟的推理（SBI）运动提供了改善学生的概念理解和保留的初步证据。然而，很少有人知道这些积极的影响是否优先分布在进入课程的学生类型。我们认为两个指标的统计101学生准备（概念库存和数学ACT成绩的课前表现）可能会或可能不会与课程结束时的学生表现的概念库存。所有准备水平的学生倾向于在统计101中显示出进步，但在SBI课程的早期版本中，所有学生准备水平都有更多的进步。此外，无论学生在入学时准备得多还是少，学生的收获都是相似的。最近对使用当前版本SBI课程的学生进行的抽样数据显示了类似的结果，但无法与非SBI学生进行直接比较。总体而言，我们的分析提供了额外的证据表明，SBI课程是有效的，无论学生准备提高学生的概念理解的统计思想课程后。需要进一步的工作，以更好地了解基于其他学生的人口统计数据，以前的课程，以及教师和机构变量的学生改进的细微差别。
英文摘要：
The recent simulation-based inference (SBI) movement in algebra-based introductory statistics courses (Stat 101) has provided preliminary evidence of improved student conceptual understanding and retention. However, little is known about whether these positive effects are preferentially distributed across types of students entering the course. We consider how two metrics of Stat 101 student preparation (pre-course performance on concept inventory and math ACT score) may or may not be associated with end of course student performance on conceptual inventories. Students across all preparation levels tended to show improvement in Stat 101, but more improvement was observed across all student preparation levels in early versions of a SBI course. Furthermore, students' gains tended to be similar regardless of whether students entered the course with more preparation or less. Recent data on a sample of students using a current version of an SBI course showed similar results, though direct comparison with non-SBI students was not possible. Overall, our analysis provides additional evidence that SBI curricula are effective at improving students' conceptual understanding of statistical ideas post-course regardless student preparation. Further work is needed to better understand nuances of student improvement based on other student demographics, prior coursework, as well as instructor and institutional variables.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
