The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis
Kulick and Wright concluded, based on theoretical mathematical simulations of hypothetical student exam scores, that assigning exam grades to students based on the relative position of their exam performance scores within a normal curve may be unfair, given the role that randomness plays in any give...
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Georgia Southern University
2012-01-01
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Online Access: | https://digitalcommons.georgiasouthern.edu/ij-sotl/vol6/iss1/11 |
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doaj-b82a724e4a5a406abe79b96fa5f3f7082020-11-25T01:33:42ZengGeorgia Southern UniversityInternational Journal for the Scholarship of Teaching and Learning1931-47442012-01-016110.20429/ijsotl.2012.060111The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation AnalysisGary BaileyRonald SteedKulick and Wright concluded, based on theoretical mathematical simulations of hypothetical student exam scores, that assigning exam grades to students based on the relative position of their exam performance scores within a normal curve may be unfair, given the role that randomness plays in any given student’s performance on any given exam. However, their modeling predicts that academically heterogeneous students should fare much better than high achieving, academically homogenous students. We assess their conclusion indirectly using student scores from actual exams in actual university classes. We document that academically heterogeneous students do tend to perform at a similar level on different exams across a given semester: correlations among six different assessments were moderately strong and highly significant. We confirm their prediction that actual student scores for academically heterogeneous first-year students do not reveal gross random variation. We encourage similar analysis of scores for high achieving, academically homogeneous students.https://digitalcommons.georgiasouthern.edu/ij-sotl/vol6/iss1/11Normal curvesAssigning gradesGrading practicesAssessmentCurving gradesAssessing grading practices |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gary Bailey Ronald Steed |
spellingShingle |
Gary Bailey Ronald Steed The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis International Journal for the Scholarship of Teaching and Learning Normal curves Assigning grades Grading practices Assessment Curving grades Assessing grading practices |
author_facet |
Gary Bailey Ronald Steed |
author_sort |
Gary Bailey |
title |
The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis |
title_short |
The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis |
title_full |
The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis |
title_fullStr |
The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis |
title_full_unstemmed |
The Impact of Grading on a Curve: Assessing the Results of Kulick and Wright’s Simulation Analysis |
title_sort |
impact of grading on a curve: assessing the results of kulick and wright’s simulation analysis |
publisher |
Georgia Southern University |
series |
International Journal for the Scholarship of Teaching and Learning |
issn |
1931-4744 |
publishDate |
2012-01-01 |
description |
Kulick and Wright concluded, based on theoretical mathematical simulations of hypothetical student exam scores, that assigning exam grades to students based on the relative position of their exam performance scores within a normal curve may be unfair, given the role that randomness plays in any given student’s performance on any given exam. However, their modeling predicts that academically heterogeneous students should fare much better than high achieving, academically homogenous students. We assess their conclusion indirectly using student scores from actual exams in actual university classes. We document that academically heterogeneous students do tend to perform at a similar level on different exams across a given semester: correlations among six different assessments were moderately strong and highly significant. We confirm their prediction that actual student scores for academically heterogeneous first-year students do not reveal gross random variation. We encourage similar analysis of scores for high achieving, academically homogeneous students. |
topic |
Normal curves Assigning grades Grading practices Assessment Curving grades Assessing grading practices |
url |
https://digitalcommons.georgiasouthern.edu/ij-sotl/vol6/iss1/11 |
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AT garybailey theimpactofgradingonacurveassessingtheresultsofkulickandwrightssimulationanalysis AT ronaldsteed theimpactofgradingonacurveassessingtheresultsofkulickandwrightssimulationanalysis AT garybailey impactofgradingonacurveassessingtheresultsofkulickandwrightssimulationanalysis AT ronaldsteed impactofgradingonacurveassessingtheresultsofkulickandwrightssimulationanalysis |
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