What Can We Learn from Exam Grade Distributions?
A course with good learning outcomes is one in which most of the enrolled students achieve the mastery specified in the predefined learning objectives. Since the enrolment is invariably a mix of students with heterogeneous capabilities, the class average grade is a poor indicator of how the class is...
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Georgia Southern University
2021
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oai:doaj.org-article:47598e3dacec4950a73ac0a87bdb3e942021-12-02T18:48:36ZWhat Can We Learn from Exam Grade Distributions?1931-474410.20429/ijsotl.2021.150207https://doaj.org/article/47598e3dacec4950a73ac0a87bdb3e942021-11-01T00:00:00Zhttps://digitalcommons.georgiasouthern.edu/ij-sotl/vol15/iss2/7https://doaj.org/toc/1931-4744A course with good learning outcomes is one in which most of the enrolled students achieve the mastery specified in the predefined learning objectives. Since the enrolment is invariably a mix of students with heterogeneous capabilities, the class average grade is a poor indicator of how the class is divided into at least two groups, of high- and low-performers. Clearly, achieving the desired outcomes implies increasing the proportion of high-performing students and their mean grade by providing appropriately designed teaching protocols. In this paper, the actual class grade distribution is approximated by a bimodal probability distribution function, whose parameters enable the proportions and average performance of these two groups to be quantified. This paper describes the methodology to achieve this and demonstrates its usage to diagnose example exam grade distributions, as well as to provide quantification of the impact of pedagogic changes on the degree of achieving teaching objectives.Daniel LewinGeorgia Southern Universityarticleassessmentbimodal distributionsoutcomesTheory and practice of educationLB5-3640ENInternational Journal for the Scholarship of Teaching and Learning, Vol 15, Iss 2 (2021) |
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assessment bimodal distributions outcomes Theory and practice of education LB5-3640 Daniel Lewin What Can We Learn from Exam Grade Distributions? |
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A course with good learning outcomes is one in which most of the enrolled students achieve the mastery specified in the predefined learning objectives. Since the enrolment is invariably a mix of students with heterogeneous capabilities, the class average grade is a poor indicator of how the class is divided into at least two groups, of high- and low-performers. Clearly, achieving the desired outcomes implies increasing the proportion of high-performing students and their mean grade by providing appropriately designed teaching protocols. In this paper, the actual class grade distribution is approximated by a bimodal probability distribution function, whose parameters enable the proportions and average performance of these two groups to be quantified. This paper describes the methodology to achieve this and demonstrates its usage to diagnose example exam grade distributions, as well as to provide quantification of the impact of pedagogic changes on the degree of achieving teaching objectives. |
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article |
author |
Daniel Lewin |
author_facet |
Daniel Lewin |
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Daniel Lewin |
title |
What Can We Learn from Exam Grade Distributions? |
title_short |
What Can We Learn from Exam Grade Distributions? |
title_full |
What Can We Learn from Exam Grade Distributions? |
title_fullStr |
What Can We Learn from Exam Grade Distributions? |
title_full_unstemmed |
What Can We Learn from Exam Grade Distributions? |
title_sort |
what can we learn from exam grade distributions? |
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Georgia Southern University |
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2021 |
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https://doaj.org/article/47598e3dacec4950a73ac0a87bdb3e94 |
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AT daniellewin whatcanwelearnfromexamgradedistributions |
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