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COMPARING ASSESSMENT METHODS AS PREDICTORS OF STUDENT LEARNING IN UNDERGRADUATE MATHEMATICS

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Date Issued:
2008
Abstract/Description:
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.
Title: COMPARING ASSESSMENT METHODS AS PREDICTORS OF STUDENT LEARNING IN UNDERGRADUATE MATHEMATICS.
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Name(s): Shorter, Nichole, Author
Young, Cynthia, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2008
Publisher: University of Central Florida
Language(s): English
Abstract/Description: 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.
Identifier: CFE0002432 (IID), ucf:47704 (fedora)
Note(s): 2008-12-01
M.S.
Sciences, Department of Mathematics
Masters
This record was generated from author submitted information.
Subject(s): announced quizzes
assessment
continuous assessment
cumulative assessment
multiple regression
predictor
project-based learning
quizzes
stepwise regression
student learning
undergraduate mathematics
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0002432
Restrictions on Access: public
Host Institution: UCF

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