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The majority of articles were primarily concerned with the concept of MOOCs, discussing challenges and trends, while other themes generally appeared within only one paper except for the concept of connectivism and its implications. The themes were re-stratified into the following categories.
The articles were then individually re-considered and assigned to the categories which reflected the contents; many articles were assigned to more than one category. Table 4 shows the spread of these categories. Case Studies Across the articles classified, 21 had a case study element, and in total 13 different MOOCs were studied.
CritLit - Critical Literacies: CS1 - An introductory programming course from the University of Helsinki Finland based on an apprenticeship model. CS - An introductory computer science course, from Udacity. Future of Learning - an education course: Table 5 shows the number of articles studying each MOOC and the number of articles studying each as the single central case study.
MobiMOOC is the only other course to be considered in more than one paper. The majority of case studies have used multiple methods for data collection in line with the general practice of case study research Yin, In most case studies online surveys were used to collect data from participants in the MOOC s.
Four studies considering PLENK as a case used multiple surveys active participant survey, lurker survey, and end course survey.
Researchers also reported collecting data via email interviews, focus groups, Moodle log data, discussion forum data, blogs, and observations. Three articles reported the use of techniques based on virtual ethnography and another used narrative inquiry as their research approach.
In two of these instances the researcher was described as a learner in the MOOC, in another two as a participant, and in the remaining three as an observer.
The demarcation if one really exists between a learner and a participant in a MOOC is not clear, and may well simply be a matter of differing nomenclature.
The majority of the participants in the case study research were people who had participated in the MOOC under consideration. Two articles also included data collected from instructors. He associates courses similar to AI-Stanford predominantly with cognitive-behaviourist approaches and c-MOOCs with connectivist approaches.
By comparing multiple case studies Rodriguez claims that courses similar to AI-Stanford have a more individualist learning approach while c-MOOCs have a more social approach to learning.
He also shows the different roles played by facilitators in each type of MOOC. It is probable that both Rodriguez and Daniel are similarly classifying MOOCs but using the two different labels for the same thing: However, our systematic review has shown that there is a gap in the scholarly literature in defining these different types of MOOCs.
Limitations The aim of this study is to develop a classification of academic research relating to MOOCs, based on a systematic consideration of the existing peer reviewed MOOC literature.
Other materials such as blog posts and unpublished reports are not included in this review. Blog posts always present difficulties for authors of reviews in determining the credibility of the posts: It should be noted that the same search terms applied above used in Google Web search returned over 50, items and used in a Google Blog search resulted in results December 04,however these items are not analysed here.
Daniel includes references to such resources. Inclusion of such resources in a systematic review is contentious as they are often highly subjective and have rarely been critically reviewed by peers. The question of whether such resources should be included in a systematic review needs further methodological consideration in the literature, but at present it is unusual due to issues of credibility.
Articles published in languages other than English were not considered for this review. When searching forward references using Google Scholar, the authors came across publications that referenced articles in the review but were published in other languages such as Chinese.
Because of this, the authors believe that there could be articles that would have been included in the review were they published in English. However, most research has investigated the learner perspective, with a significant minor focus on the institutional threats and opportunities.
Inevitably this leaves out potentially useful data on Twitter, blogs, and other social media spaces. For example, Liyanagunawardena shows that there is a significant use of external communications other than the official LMS discussions to support learner groups in traditional, blended, and online distance education settings.
Despite many research studies using publicly available data from a MOOC for research purposes, only a few papers have considered the ethical aspects of such use. This may well be due to a lack of good guidance and best practice examples on the general question of the use of data from online social media and similar sources for such research Zimmer, Many studies have presented participant demographics and it was observed that a large majority of participants were from North America and Europe.
This is hardly surprising due to the possible barriers of access to online learning that can be presumed in those parts of the world, both technological and linguistic see Liyanagunawardena, for a discussion of the similar problems in the introduction of online learning in Sri Lanka.
There are two plausible reasons: It could be that the course content of the MobiMOOC mLearning is of more interest to learners from those regions or it could be that mLearning is significantly more accessible in those places.
This shows the potential for exploring the possibility of mLearning MOOC provision in the developing world, both for increasing and widening participation.MOOC (Massive Open Online Course) is a new form of education for students who want to advance their skills at any level or cannot access traditional education due to time, financial problems, geographic accessibility, disability or other caninariojana.com://caninariojana.com · Massive open online courses have been recently introduced as a modern learning method mainly due to the great progress made in the fields of Information Technology and, moreover, the ever increasing number of technologies supported by the caninariojana.com://caninariojana.com MOOC stands for a Massive Open Online Course.
It is an online course aimed at large-scale participation and open (free) access via the internet. They are similar to university courses, but do .
· The e-Transformation in higher education, in which Massive Open Online Courses (MOOCs) are playing a pivotal role, has had an impact on the modality in which behavior analysis is taught.
In this paper, we survey the history and implications of online education including MOOCs and caninariojana.com · Massive Open Online Course. The first MOOC, titled Connectivism and Connective Knowledge was created in by a Canadian team of academics (Downes , Littlejohn )caninariojana.com +Acumen, Acumen’s online learning platform and global learning community for social change leaders, has expanded to become the largest massive open online course (MOOC) provider in the social sector.
Launched in , +Acumen was designed to bring the nonprofit venture fund’s unique model and 15 years of insights from building social enterprises in the world’s [ ]caninariojana.com