Predicting Student Success in a K-12 Online School

Given the rapid growth of K-12 online learning, research is needed in the effective identification of at-risk students so that administrators and teachers can develop appropriate supports and interventions. The purpose of this research was to determine if student success in an online course could be predicted for English Learners (EL) using identifiable student characteristics and traits. This study looked at the student traits of behavior, structure, and demographics to determine if they could be used as predictive variables for successful course completion in a K-12 online course. The behavior characteristics were measured by a survey tool and were identified in the categories of organization/self-regulation, technology skills/access, responsibility/risk-taking, and achievement/self-esteem beliefs. Structure variables were related to the course such as subject area (Subject), the reason that the student is taking the course (Reason), the student experience level in taking a course with this online school (Experience). The students’ personally identifiable characteristics such as race/ethnicity, gender, GPA, grade level, and EL status were identified as the Demographic variables. The findings demonstrated that GPA was the greatest predictor of online student success, but certain behavior, structure, and demographic variables consistently predict the final course grade which in turn could be used to support students. This study can be used as a mean to help initiate the conversation about how leaders can best support students enrolled in online schools