TY - GEN
T1 - A comparison and classification of grading approaches used in engineering education
AU - Carberry, A. R.
AU - Atwood, S. A.
AU - Siniawski, M. T.
AU - Diefes-Dux, H. A.
N1 - Funding Information:
This work was made possible by a grant from the National Science Foundation (NSF DUE-1503794). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
Publisher Copyright:
© 2020 SEFI 47th Annual Conference: Varietas Delectat... Complexity is the New Normality, Proceedings. All rights reserved.
PY - 2020
Y1 - 2020
N2 - Grades are intended to communicate achievement associated with a learning experience. Engineering educators in higher education often default to a particular grading approach without considering how the approach impacts student achievement. This work proposes a model for comparing and classifying commonly used grading systems in engineering higher education. Examples from the engineering education literature revealed five general categories of grading: 1) normative, score-based grading, 2) summative grading, 3) standards-based grading, 4) mastery-based grading, and 5) adaptive grading. (Note: variations in naming conventions were observed.) Each grading system was examined to determine key characteristics of the system and how student performance was ultimately assessed. A continuum of grading approaches was created after discovering that each system ranged in its intention to select and/or develop talent. The most widely adopted approaches to grading in engineering higher education, norm-based grading, were classified using purely selective processes (e.g., letter grades). Alternative, learning outcomes-based grading approaches differentiate themselves by the level in which they attempt to develop talent. This was determined by examining differences in how the grading system impacted sequencing of content, course pace, number of attempts to demonstrate achievement, scale and weight of performance, feedback provided, and basis for a final grade. The resulting continuum provides a tool for engineering educators to compare and discuss grading approaches in order to select an appropriate system for their course or program. Informed decisions on grading can have a critical impact in student retention and program improvement.
AB - Grades are intended to communicate achievement associated with a learning experience. Engineering educators in higher education often default to a particular grading approach without considering how the approach impacts student achievement. This work proposes a model for comparing and classifying commonly used grading systems in engineering higher education. Examples from the engineering education literature revealed five general categories of grading: 1) normative, score-based grading, 2) summative grading, 3) standards-based grading, 4) mastery-based grading, and 5) adaptive grading. (Note: variations in naming conventions were observed.) Each grading system was examined to determine key characteristics of the system and how student performance was ultimately assessed. A continuum of grading approaches was created after discovering that each system ranged in its intention to select and/or develop talent. The most widely adopted approaches to grading in engineering higher education, norm-based grading, were classified using purely selective processes (e.g., letter grades). Alternative, learning outcomes-based grading approaches differentiate themselves by the level in which they attempt to develop talent. This was determined by examining differences in how the grading system impacted sequencing of content, course pace, number of attempts to demonstrate achievement, scale and weight of performance, feedback provided, and basis for a final grade. The resulting continuum provides a tool for engineering educators to compare and discuss grading approaches in order to select an appropriate system for their course or program. Informed decisions on grading can have a critical impact in student retention and program improvement.
KW - Assessment
KW - Engineering higher education
KW - Grading systems
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M3 - Conference contribution
AN - SCOPUS:85077821079
T3 - SEFI 47th Annual Conference: Varietas Delectat... Complexity is the New Normality, Proceedings
SP - 216
EP - 225
BT - SEFI 47th Annual Conference
A2 - Nagy, Balazs Vince
A2 - Murphy, Mike
A2 - Jarvinen, Hannu-Matti
A2 - Kalman, Aniko
PB - European Society for Engineering Education (SEFI)
T2 - 47th SEFI Annual Conference 2019 - Varietas Delectat: Complexity is the New Normality
Y2 - 16 September 2019 through 19 September 2019
ER -