What Is Best for Students, Numerical Scores or Letter Grades?
What Is Best for Students, Numerical Scores or Letter Grades?
Evi Micha, Shreyas Sekar, Nisarg Shah
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Main Track. Pages 2949-2957.
https://doi.org/10.24963/ijcai.2024/327
We study letter grading schemes, which are routinely employed for evaluating student performance. Typically, a numerical score obtained via one or more evaluations is converted into a letter grade (e.g., A+, B-, etc.) by associating a disjoint interval of numerical scores to each letter grade.
We propose the first model for studying the (de)motivational effects of such grading on the students and, consequently, on their performance in future evaluations. We use the model to compare uniform letter grading schemes, in which the range of scores is divided into equal-length parts that are mapped to the letter grades, to numerical scoring, in which the score is not converted to any letter grade (equivalently, every score is its own letter grade).
Theoretically, we identify realistic conditions under which numerical scoring is better than any uniform letter grading scheme. Our experiments confirm that this holds under even weaker conditions, but also find cases where the converse occurs.
Keywords:
Game Theory and Economic Paradigms: GTEP: Computational social choice