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Combating Procrastination on Massive Online Open Courses via Optimal Calls to Action

机译:通过最佳呼叫采取措施对大规模的在线开放课程进行拖延

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Massive online open courses (MOOCs) are a booming phenomenon in the digital era, having attracted millions of users around the world to date. At the same time, educational delivery via MOOCs comes with distinct difficulties for students and instructors because the online nature of MOOCs creates every opportunity for digital distraction and procrastination. In this work, we consider that the digital nature of MOOCs and online learning management systems (LMSs) may also offer unique opportunities to counteract procrastination. Building on the temporal motivation theory, this study examines a number of calls to action (CTAs) pertaining to the completion and submission of course assignments, with an eye toward combating student procrastination on MOOCs. We report on the results of a randomized field experiment on a leading MOOC platform in China. By randomly treating MOOC users with different CTAs related to active course assignments, we seek to examine the impacts of alternative informational interventions on students' time to completion and probability of on-time assignment submission. We consider multiple types of CTAs: a simple CTA, a deadline reminder, descriptive norm interventions (communicating peer assignment completion rates), and a simple CTA combined with a financial incentive. We find that descriptive norms lead to higher probabilities of assignment completion and a shorter time to completion. In contrast, we find that the deadline reminder has a surprisingly counterproductive effect. Subsequently, exploring heterogeneity in the response to our different interventions-considering factors such as course load, education level, and user tenure on the MOOC platform-we find evidence that the deadline reminder in particular can backfire if students' active course load is low. This result suggests that students with low course loads may perceive the deadline to be distant, which reduces their sense of urgency and leads to complacency. We discuss the implications of our findings for both research and practice.
机译:大规模的在线开放课程(MOOCS)是数字时代的蓬勃发展现象,吸引了全球数百万用户迄今为止。与此同时,通过Moocs的教育送货对学生和教练具有不同的困难,因为Moocs的在线性质为数字分心和拖延创造了每一个机会。在这项工作中,我们认为MOOCS和在线学习管理系统(LMSS)的数字性质也可能提供独特的机会来抵消拖延。建立在时间动机理论上,本研究审查了一些与完成和提交课程任务的行动(CTA)的呼叫,以致力于将学生拖延对MOOCS进行打击。我们报告了中国领先的MoOC平台上的随机现场实验结果。通过随机处理具有与有效课程任务相关的不同CTA的MooC用户,我们寻求检查替代信息干预对学生完成和准时分配概率的概率的影响。我们考虑多种类型的CTA:简单的CTA,截止日期提醒,描述性规范干预(传送对等分配完成率),以及简单的CTA与财务激励相结合。我们发现描述性规范导致较高的分配完成概率以及缩短完成时间。相比之下,我们发现截止日期提醒令人惊讶的反驳效果。随后,考虑到课程负荷,教育水平和用户权限等因素,探讨异质性 - 考虑到MooC平台上的课程负荷,教育水平和用户权限 - 我们发现截止日期提醒,特别是如果学生的有效课程负荷低,则可以反向。这一结果表明,课程负荷低的学生可能会感知到遥远的截止日期,这降低了他们的紧迫感并导致自满。我们讨论了我们对研究和实践的研究所的影响。

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