A Cross-Validation of EasyCBM[R] Mathematics Cut Scores in Oregon PDF Download
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Author: Daniel Anderson Publisher: ISBN: Category : Languages : en Pages : 80
Book Description
In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in Oregon. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Oregon state test was used as the criterion. Optimal cut scores were examined for each group. Results indicate quite stable cut scores across groups. Further, the overall area under the ROC curve (AUC) was not statistically different between groups for any measurement occasion at any grade, providing strong evidence of the validity of the cut scores as optimal to predict student performance on the Oregon statewide large-scale assessment. (Contains 2 tables.).
Author: Daniel Anderson Publisher: ISBN: Category : Languages : en Pages : 80
Book Description
In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in Oregon. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Oregon state test was used as the criterion. Optimal cut scores were examined for each group. Results indicate quite stable cut scores across groups. Further, the overall area under the ROC curve (AUC) was not statistically different between groups for any measurement occasion at any grade, providing strong evidence of the validity of the cut scores as optimal to predict student performance on the Oregon statewide large-scale assessment. (Contains 2 tables.).
Author: Bitnara Jasmine Park Publisher: ISBN: Category : Languages : en Pages : 312
Book Description
This technical report presents results from a cross-validation study designed to identify optimal cut scores when using easyCBM[R] reading tests in Oregon. The cross-validation study analyzes data from the 2009-2010 academic year for easyCBM[R] reading measures. A sample of approximately 2,000 students per grade, randomly split into two groups of roughly the same size, was used for this study. Students state test performance classification (passing/not passing) on the Oregon Assessment of Knowledge and Skills (OAKS) was used as the criterion. Optimal cut scores were identified for each of the randomly split groups with a receiver operating characteristic curve (ROC) analysis. Results indicated reasonably stable cut scores between groups. Further, the overall area under the ROC curve (AUC) was not statistically different between groups for any measurement occasion at any grade, providing strong evidence for the validity of identified cut scores as optimal to predict student performance classification on the Oregon state large-scale assessment. (Contains 2 tables.).
Author: Daniel Anderson Publisher: ISBN: Category : Languages : en Pages : 78
Book Description
In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in the state of Washington. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Washington state test was used as the criterion. Optimal cut scores were examined for each group. Results indicate quite stable cut scores across groups. Further, the overall area under the ROC curve (AUC) was not statistically different between groups for any measurement occasion at any grade, providing strong evidence of the validity of the cut scores as optimal to predict student performance on the Washington statewide large-scale assessment. (Contains 2 tables.).
Author: P. Shawn Irvin Publisher: ISBN: Category : Languages : en Pages : 257
Book Description
This technical report presents results from a cross-validation study designed to identify optimal cut scores when using easyCBM[R] reading tests in Washington state. The cross-validation study analyzes data from the 2009-2010 academic year for easyCBM[R] reading measures. A sample of approximately 900 students per grade, randomly split into two groups of roughly the same size, was used for this study. Students state test performance classification (passing/not passing) on the Measurements of Student Progress (MSP) state test in Washington was used as the criterion. Optimal cut scores were identified for each of the randomly split groups with a receiver operating characteristic curve (ROC) analysis. Results indicated reasonably stable cut scores between groups. Further, the overall area under the ROC curve (AUC) was not statistically different between groups for any measurement occasion at any grade, providing strong evidence for the validity of identified cut scores as optimal to predict student performance classification on the Washington state large-scale assessment.
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Author: Daniel Anderson
Author: Bitnara Jasmine Park
Author: Daniel Anderson
Author: P. Shawn Irvin