关于学生在线学习成功21项发现的复制研究

Replicating 21 Findings on Student Success in Online Learning

过去几年,研究者围绕影响学生在线课程学习成功的因素开展了大量研究,包括获得学分的课程和开放课程。然而,在不同课程内开展学生成功研究发现的复制研究相对有限。本文将提供一个框架来促进复制研究,从ed X大规模开放在线课程(MOOC)中获取数据,以原始形式或稍加修改的形式自动搜索,并测试一系列研究结论的适用性。我们在已发表的MOOCs完成率研究论文中选定21项研究发现,将它们呈现在本文体系结构中。之后选择一门MOOC课程并验证此体系结构,采用事后比较方法控制多项对比。研究发现,在当前的数据集中,其中9项已有研究发现得以成功复制,两项研究发现出现了相互矛盾的结果。这项工作标志着我们正朝大规模自动复制相关研究成果的方向迈进。

There has been a considerable amount of research over the last few years devoted towards studying what factors lead to student success in online courses,whether for-credit or open.However,there has been relatively limited work towards formally studying which findings replicate across courses.In this paper,we present an architecture to facilitate replication of this type of research,which can ingest data from an edX Massively Open Online Course（MOOC） and test whether a range of findings apply,in their original form or slightly modified using an automated search process.We identify 21 findings from previously published studies on completion in MOOCs,render them into production rules within our architecture,and test them in the case of a single MOOC,using a post-hoc method to control for multiple comparisons.We find that nine of these previously published results replicate successfully in the current data set and that contradictory results are found in two cases.This work represents a step towards automated replication of correlational research findings at large scale.