
handle: 1887/47088
Massive Open Online Courses (MOOCs) as a new approach to distance education, which originated from the open education resources (OER) movement, are becoming widespread throughout the world. Over time, early versions of cMOOCs have undergone changes in terms of use, name and structure. In their short life, MOOCs have been categorized into different taxonomies depending on, for example, their types, pedagogies, orientations, target participants, resources and content. This article proposes a new taxonomy to position MOOCs on two dimensions: massiveness and openness, which brings a fresh perspective for understanding varieties of MOOCs based on the two definitional elements. The dimensions of massiveness and openness are identified and discussed. Based on these, we conclude two dimensional matrix with four categories: (i) small scale and less open, (ii) small scale and more open, (iii) large scale and less open, (iv) large scale and more open. This classification provides a comprehensive description of different types of MOOCs which could be helpful to answer the necessities of MOOC providers, educators, students, and researchers.
Massive open online courses;MOOCs;Open learning;Distance education;Online courses;Taxonomy of MOOCs
Massive open online courses;MOOCs;Open learning;Distance education;Online courses;Taxonomy of MOOCs
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 49 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
