arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.04811cs.CYcs.HC
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社会投入与学习投入--对FutureLearn学习者的探索性研究

Social Engagement versus Learning Engagement -- An Exploratory Study of FutureLearn Learners

Lei Shi, Alexandra I. Cristea, Armando M. Toda, Wilk Oliveira

摘要:

大规模开放式在线课程(MOOC)的入学人数继续增加,但只有一小部分入学者完成了MOOC。虽然很多研究都集中在预测完成情况上,但很少有研究分析MOOC的流行与学习者明显脱离之间的表面矛盾。具体而言,重要的是不仅要从学习的角度,而且要从社会的角度来分析参与。这一点尤其重要,因为MOOC提供了越来越多的活动,这些活动可以归类为社交互动。因此,本研究特别关注学习者如何与同龄人互动,以及他们在MOOC中的学习进展。此外,与大多数主要关注学习成果的现有研究不同,本研究采用了细粒度的时间方法来探索学习者在MOOC中的进步。这项研究是在探索较少的FutureLearn平台上进行的,该平台采用社会建构主义方法,促进协作学习。初步结果表明,潜在的有趣的细粒度预测模型的学习者行为,涉及每周监测的社会,非社会行为的活跃的学生(进一步分类为完成者和非完成者)。

英文摘要:

Massive Open Online Courses (MOOCs) continue to see increasing enrolment, but only a small percent of enrolees completes the MOOCs. Whilst a lot of research has focused on predicting completion, there is little research analysing the ostensible contradiction between the MOOC's popularity and the apparent disengagement of learners. Specifically, it is important to analyse engagement not just in learning, but also from a social perspective. This is especially crucial, as MOOCs offer a growing amount of activities, which can be classified as social interactions. Thus, this study is particularly concerned with how learners interact with peers, along with their study progression in MOOCs. Additionally, unlike most existing studies that are mainly focused on learning outcomes, this study adopts a fine-grained temporal approach to exploring how learners progress within a MOOC. The study was conducted on the less explored FutureLearn platform, which employs a social constructivist approach and promotes collaborative learning. The preliminary results suggest potential interesting fine-grained predictive models for learner behaviour, involving weekly monitoring of social, non-social behaviour of active students (further classified as completers and non-completers).

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。

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