Massive Open Online Courses (MOOCs) play an ever more central role in open education. However, in contrast to traditional classroom settings, many aspects of learners' behaviour in MOOCs are not well researched. In this work, we focus on modelling learner behaviour in the context of continuous assessments with completion certificates, the most common assessment setup in MOOCs today. Here, learners can obtain a completion certificate once they obtain a required minimal score (typically somewhere between 50-70%) in tests distributed throughout the duration of a MOOC. In this setting, the course material or tests provided after "passing" do not contribute to earning the certificate (which is ungraded), thus potentially affecting learners' behaviour. Therefore, we explore how ``passing'' impacts MOOC learners: do learners alter their behaviour after this point? And if so how? While in traditional classroom-based learning the role of assessment and its influence on learning behaviour has been well-established, we are among the first to provide answers to these questions in the context of MOOCs.
Original languageEnglish
Title of host publicationAdjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP 2017
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages83-88
Number of pages6
ISBN (Electronic)978-1-4503-5067-9
DOIs
StatePublished - 2017
EventUMAP 2017 - Bratislava, Slovakia
Duration: 9 Jul 201712 Jul 2017
Conference number: 25

Conference

ConferenceUMAP 2017
CountrySlovakia
CityBratislava
Period9/07/1712/07/17

    Research areas

  • MOOCs, Learning Analytics, Certi€cate Achievement

ID: 33898511