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TYPES OF PARTICIPANTS' BEHAVIORS IN A MASSIVE OPEN ONLINE COURSE

机译:大规模开放在线课程中参与者行为的类型

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In recent years, there has been a proliferation of Massive Open Online Courses (MOOCs). Initiatives like Coursera, edX and Udacity provide platforms for higher education institutions to develop and deliver online courses to the general public. These courses are usually offered free of charge, with no preconditions or commitment, and attract massive numbers of registrants from around the world. Yet, a central criticism about MOOCs refers to the relatively low completion rates of participants, with 10% or less of the course registrants earning a statement of accomplishment. Ho et al. (2014) argued that certification rates are a misleading representation of the diverse ways in which registrants are engaging with MOOCs. Kizilcec et al. (2013) argued that the categorization of MOOCs learners into those who pass the class, and everyone else, makes no allowances for learners who choose to stay engaged with the course and participate in some aspects of it, without earning a certificate. Subsequently, the purpose of this study was to gain more insights into different types of participants' behaviors in MOOCs, by analyzing non-certificate earners' and certificate earners' behaviors. The study examined the different types of participants' behaviors in one MOOC, based on the participants' activity in the main learning resources of the course. The research questions were: 1 What are the types of engagement in the course? 2 What are the types of behaviors in regard to the course video lectures, discussion forums, and assessments? The study examined a MOOC on plant biology, which was offered by Tel Aviv University in Coursera. The course began on October 2013 and lasted 7 weeks. Each week, a different topic was covered via the course learning resources, which consisted of: professor announcements, reading recommendations, 50 short video lectures, around 40 interactive in-video questions, 7 discussion forums, 6 quizzes, and a final exam. 32,007 people registered for the course, and 68.4% of the registrants (21,889) started it. 10.6% of the participants who started the course (2,319) completed it and received a certificate. The study was conducted using a data mining methodology. The data mining was applied on a data set that documented the participants' actions during the course. The data was received from Coursera in database tables. Using MySQL queries, a set of variables were computed for each participant, displaying their use of the course components. Using a Two-Step cluster analysis, the course participants were then classified into clusters, based on their activity in the main learning resources of the course. The following 8 variables were chosen for the analysis: unique video lectures viewed online, unique video lectures downloaded, unique in-video questions answered; total threads views, total threads opened, total comments; unique quizzes submitted, and Final exam submitted. The cluster analysis was applied separately for the non-certificate earners and for the certificate earners groups. This separation was essential in order to gain better insights into the different behaviors between the groups and within each group. The analyses revealed 8 clusters in total; 4 clusters per group. The clusters are presented and discussed in detail in the paper. The different types of engagement and behaviors that emerged in the clusters were analyzed. Five major types of engagement in the course were identified: Tasters, Keepers, Partially Persisting, Committed participants and Completers. With reference to criticism regarding relatively low completion rates in MOOCs, significant numbers of non certificate earners who demonstrated some level of engagement, ranging from the Moderately Persisting participants to the highly committed participants, were identified. Regarding video usage, three types of behaviors were identified: online, offline, and combined. These types may indicate different participant preferences for watching the videos and may have significant implications on the learning process, as they facilitate different pedagogies. Regarding the discussion forums, two prominent types of behaviors were identified: passive and active participation. Consistent with the literature, the vast majority of discussion participants were found to be passive, whereas only a small group, consisting mostly of certificate earners, held the on-going discussions. These findings raise questions regarding the extent to which the social learning potential of MOOCs is realized. Finally, three levels of participation in the assessments were identified: negligible, moderate, and extensive. This study was conducted on one MOOC. More research is required on other MOOCs, in varied disciplines, target audiences, and structures.
机译:近年来,大规模的在线公开课程(MOOC)激增。 Coursera,edX和Udacity等计划为高等教育机构提供了平台,以开发和向公众提供在线课程。这些课程通常是免费提供的,没有任何先决条件或承诺,并且会吸引来自世界各地的大量注册人。但是,对MOOC的主要批评是参与者的完成率相对较低,只有10%或更少的课程注册者获得成就声明。 Ho等。 (2014年)认为,认证率误导了注册人与MOOC互动的多种方式。 Kizilcec等。 (2013年)认为,将MOOC的学习者归类为通过课程的人和其他所有人,对于选择不参与课程并参与课程某些方面而没有获得证书的学习者来说,是没有任何余地的。随后,本研究的目的是通过分析非证书赚取者和证书赚取者的行为来获得对MOOC中不同类型参与者行为的更多见解。该研究根据课程主要学习资源中参与者的活动,研究了一种MOOC中参与者的不同类型的行为。研究问题是:1课程参与的类型是什么? 2关于课程视频讲座,讨论论坛和评估的行为类型是什么?这项研究检查了由特拉维夫大学(Coursera)提供的关于植物生物学的MOOC。该课程于2013年10月开始,历时7周。每周,课程学习资源都会涵盖一个不同的主题,包括:教授公告,阅读建议,50个简短的视频讲座,大约40个交互式视频内问题,7个讨论论坛,6个测验和期末考试。有32,007人注册了该课程,其中68.4%的注册人(21,889)启动了该课程。参加该课程的参与者(2,319)的10.6%完成了课程并获得了证书。该研究是使用数据挖掘方法进行的。数据挖掘应用于记录了学员在课程中的操作的数据集。数据是从Coursera的数据库表中接收的。使用MySQL查询,为每个参与者计算了一组变量,显示了他们对课程组件的使用。使用两步聚类分析,然后根据他们在课程主要学习资源中的活动将课程参与者分类为聚类。选择了以下8个变量进行分析:在线观看独特的视频讲座,下载独特的视频讲座,回答独特的视频中问题;总线程视图,打开的总线程,总注释;提交了独特的测验,并提交了期末考试。聚类分析分别适用于非证书收入者和证书收入者组。为了更好地了解组之间以及每个组内的不同行为,这种分离是必不可少的。分析显示总共有8个簇。每组4个群集。本文对集群进行了详细介绍和讨论。分析了集群中出现的不同类型的参与和行为。确定了课程的五种主要参与类型:品酒师,老板,部分坚持,忠实参与者和完成者。关于对MOOC相对较低的完成率的批评,确定了显示出一定程度的敬业度的大量非证书赚取者,从中等持久性参与者到高度忠诚的参与者。关于视频使用情况,确定了三种类型的行为:在线,离线和组合行为。这些类型可能表明参与者观看视频的偏好不同,并且由于它们促进了不同的教学方法,因此可能对学习过程产生重大影响。关于讨论论坛,确定了两种突出的行为类型:被动和主动参与。与文献一致的是,绝大多数的讨论参与者被认为是被动的,而只有一小部分人(主要由获得证书的人组成)进行了持续的讨论。这些发现提出了关于在多大程度上实现MOOC的社会学习潜力的问题。最后,确定了参与评估的三个级别:可以忽略不计,中等和广泛。这项研究是在一个MOOC上进行的。在其他学科,目标受众和结构方面,还需要对其他MOOC进行更多研究。

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