motivation, engagement, and retention in a MOOC: A structural equation modeling approach. Global Education Review, 2 (3). 23-33 Examining the Relations among Student Motivation, Engagement, and Retention in a MOOC: A Structural Equation Modeling Approach. Xiong, Y., Li, H., Kornhaber, M., L., Suen, H., K., Pursel, B., & Goins, D., D. Technical Report
abstract   bibtex   
Students who are enrolled in MOOCs tend to have different motivational patterns than fee-paying college students. A majority of MOOC students demonstrate characteristics akin more to "tourists" than formal learners. As a consequence, MOOC students' completion rate is usually very low. The current study examines the relations among student motivation, engagement, and retention using structural equation modeling and data from a Penn State University MOOC. Three distinct types of motivation are examined: intrinsic motivation, extrinsic motivation, and social motivation. Two main hypotheses are tested: (a) motivation predicts student course engagement; and (b) student engagement predicts their retention in
@techreport{
 title = {motivation, engagement, and retention in a MOOC: A structural equation modeling approach. Global Education Review, 2 (3). 23-33 Examining the Relations among Student Motivation, Engagement, and Retention in a MOOC: A Structural Equation Modeling Approach},
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 abstract = {Students who are enrolled in MOOCs tend to have different motivational patterns than fee-paying college students. A majority of MOOC students demonstrate characteristics akin more to "tourists" than formal learners. As a consequence, MOOC students' completion rate is usually very low. The current study examines the relations among student motivation, engagement, and retention using structural equation modeling and data from a Penn State University MOOC. Three distinct types of motivation are examined: intrinsic motivation, extrinsic motivation, and social motivation. Two main hypotheses are tested: (a) motivation predicts student course engagement; and (b) student engagement predicts their retention in},
 bibtype = {techreport},
 author = {Xiong, Yao and Li, Hongli and Kornhaber, Mindy L and Suen, Hoi K and Pursel, Barton and Goins, Deborah D}
}

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