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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Bibliographic Details
Main Authors: Gary Bailey, Ronald Steed
Format: Article
Language:English
Published: Georgia Southern University 2012-01-01
Series:International Journal for the Scholarship of Teaching and Learning
Subjects:
Online Access:https://digitalcommons.georgiasouthern.edu/ij-sotl/vol6/iss1/11
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spelling 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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