Predictors of high school student success in online courses
Mark S. Grubb, University of Houston, United States
University of Houston . Awarded
As the use of online learning in high schools continues to increase, more research needs to be conducted on how students with different skills, abilities, and attributes perform in online courses. Not all students are successful at online learning, and they should be reviewed on an individual basis to see what strengths and weaknesses these students possess before enrolling them into online courses. This study identifies critical characteristics shared by successful online high school students using quantitative historical data collected from a large urban district's summer school program in 2010.
Student responses to an online pre-course evaluation instrument were compared to their course grades at the end of the semester. A multiple linear regression model using the stepwise method was calculated using 119 responses to predict the students' final grades in their online courses based on their Individual Attributes, Learning Styles, Technical Competency, Technical Knowledge, Reading Rate, Reading Recall, Typing Speed, and Typing Accuracy as reported by the constructs of an online evaluation instrument. Based on the results, Typing Speed and Reading Recall were found to contribute with statistical significance as predictive constructs to the final grade earned by the students. A significant regression equation was found (F (2,116) = 14.039, p < .001), with an adjusted R2 of .181. Research suggests that high school students given pre-course evaluative instruments before taking online courses can tell us more about online learning predictors, and how to better improve implementation of online learning for all high school students.
Grubb, M.S. Predictors of high school student success in online courses. Ph.D. thesis, University of Houston.
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