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ABSTRACT
Present research has devoted attention to a long-standing problem: how to better serve students who take K-12 online mathematics courses by investigating learner subgroups based on their semester-long learning trajectories. Mixture growth modeling was used to examine month-by-month scores students earned by completing assignments. The best-fitting model suggested four distinct subgroups representing (1) nearly linear growth, (2) exponential growth, (3) hardly any growth, (4) and early rapid growth. Follow-up analyses demonstrated that two different types of successful trajectories were more likely associated with advanced level courses, such as AP or Calculus courses, and foundation courses, such as Algebra and Geometry, were with the unpromising trajectory. Given those results, implications for practitioners and researchers were discussed from the perspective of self-regulated online learning and evidence-based mathematics instructional practices.
