announced quizzes, assessment, continuous assessment, cumulative assessment, multiple regression, predictor, project-based learning, quizzes, stepwise regression, student learning, undergraduate mathematics
This experiment was designed to determine which assessment method: continuous assessment (in the form of daily in-class quizzes), cumulative assessment (in the form of online homework), or project-based learning, best predicts student learning (dependent upon posttest grades) in an undergraduate mathematics course. Participants included 117 university-level undergraduate freshmen enrolled in a course titled "Mathematics for Calculus". Initially, a multiple regression model was formulated to model the relationship between the predictor variables (the continuous assessment, cumulative assessment, and project scores) versus the outcome variable (the posttest scores). However, due to the possibility of multicollinearity present between the cumulative assessment predictor variable and the continuous assessment predictor variable, a stepwise regression model was implemented and caused the cumulative assessment predictor variable to be forced out of the resulting model, based on the results of statistical significance and hypothesis testing. The finalized stepwise regression model included continuous assessment scores and project scores as predictor variables of students' posttest scores with a 99% confidence level. Results indicated that ultimately the continuous assessment scores best predicted students' posttest scores.
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Master of Science (M.S.)
College of Sciences
Length of Campus-only Access
Masters Thesis (Open Access)
Shorter, Nichole, "Comparing Assessment Methods As Predictors Of Student Learning In Undergraduate Mathematics" (2008). Electronic Theses and Dissertations, 2004-2019. 3688.