Predictors of Retention and Achievement in a Massive Open Online Course

Jeffrey A. Greene, Christopher A. Oswald, Jeffrey Pomerantz
<span title="">2015</span> <i title="American Educational Research Association (AERA)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tkrb35zt7rh3ljk23kykum4gsi" style="color: black;">The American Educational Research Journal</a> </i> &nbsp;
Massive open online courses (MOOCs) have been heralded as an education revolution, but they suffer from low retention, calling into question their viability as a means of promoting education for all. In addition, numerous gaps remain in the research literature, particularly concerning predictors of retention and achievement. In this study, we used survival analysis to examine the degree to which student characteristics, relevance, prior experience with MOOCs, self-reported commitment, and
more &raquo; ... rs' implicit theory of intelligence predicted retention and achievement. We found that learners' expected investment, including level of commitment, expected number of hours devoted to the MOOC, and intention to obtain a certificate, related to retention likelihood. Prior level of schooling and expected hours devoted to the MOOC predicted achievement.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3102/0002831215584621">doi:10.3102/0002831215584621</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yko3gkgcarbvdapqmuc7pa4n5q">fatcat:yko3gkgcarbvdapqmuc7pa4n5q</a> </span>
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