Over 1100 students over four semesters were given the option of taking an introductory undergraduate statistics class either by in-person attendance in lectures or by taking exactly the same class (same instructor, recorded lectures, homework, blind grading, website, etc.) without the in-person lectures. Roughly equal numbers of students chose each option. The online lectures were available to all. Attendance by online students was rare. The online students did slightly better on computer-graded exams. The causal effect of choosing only online lectures was estimated by adjusting for measured confounders, of which the incoming ACT math scores turned out to be most important, using four standard methods. The four nearly identical point estimates remained positive but were small and not statistically significant at the 95% confidence level. Sensitivity analysis indicated that unmeasured confounding was unlikely to be large but might plausibly reduce the point estimate to zero. No statistically significant differences were found in preliminary comparisons of effects on females/males, U.S./non-U.S. citizens, freshmen/non-freshman, and lower-scoring/higher-scoring math ACT groups.
翻译:在四个学期内,超过1100名学生可以选择参加初级本科统计课程,其中一组接受面对面授课,而另一组只通过相同的方式,但不接受面对面授课(相同的讲师、录制的讲座、作业、盲目评分、网站等)。几乎有相同数量的学生选择了每种选项。在线讲座对所有人都开放,但在线学生的出勤率很低。在线学生在计算机评分的考试中表现稍微更好一些。选择仅在线讲座的因果效应是通过使用四种标准方法,用经过测量的混淆因素进行调整来估计的,其中入学时的 ACT 数学成绩是最重要的。四个几乎相同的点估计保持为正,但在95%置信水平下很小并且不具有统计学意义。敏感性分析表明,未测量的混淆可能不大,但可能将点估计合理地降至零。初步比较表明,在女性/男性、美国/非美国公民、大一/非大一和较低/较高的数学 ACT 组之间,对影响没有统计学上的显著差异。