Predictors of Retention and Achievement in a Massive Open Online Course

Datos Bibliográficos

ID8222811
AutoresJeffrey A Greene (0000-0003-4145-1847, University of North Carolina at Chapel Hill, autor de correspondencia), C Oswald (0000-0001-8291-9544, University of North Carolina at Chapel Hill), Christopher A Oswald (University of North Carolina at Chapel Hill), Jeffrey Pomerantz (0000-0003-1056-3627, University of North Carolina at Chapel Hill)
Año2015
Volumen52
Número5
Páginas925-955
Fecha de publicación2015-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaAmerican Educational Research Journal (JOURNAL)
Identificadores de la revistaISSN: 0002-8312 • E-ISSN: 1935-1011
EditorialAmerican Educational Research Association (AERA) (PUBLISHER)
DOI10.3102/0002831215584621
OpenAlexW1896083716
IdiomaEN
Citas recibidas29
Referencias citadas32

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 learners’ 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

Academic achievement · Certificate · Massive open online course · Mathematics education · Online course · Political science · Relevance (law · Student achievement · Computer Science · Online and Blended Learning · Online Learning and Analytics · Psychological and Educational Research Studies · Psychology