Student success and retention rates in the online classroom
Gerry Lee Bedore, Capella University, United States
Capella University . Awarded
This study is grounded in the idea that not all online learning models are the same and not all online models produce the same dropout rates. In addition, each online learning model may have different student success factors associated with the "successful student." This study centers on online programs offered by the Art Institute Online (AIO), which has extensive resources and demonstrates high levels of understanding about online learning in every area of its operation. Factor analysis was done to reduce the number of variables from 64 to 17 factors. A multiple regression analysis was done. Two factors were shown to be statistically significant. They were Factor 1, Satisfaction with Content and Facilitator, and Factor 15, Satisfaction with Prior Online Experiences. Stepwise regression analysis identified the same two factors as statistically significant. Hierarchical regression analysis showed that one factor, Satisfaction with Content and Facilitator, significantly contributed to the variation of the model. Logistical regression analysis identified these same two variables as significant.
Bedore, G.L. Student success and retention rates in the online classroom. Ph.D. thesis, Capella University.
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