Optimal assessment tools should measure in a limited time the knowledge of students in a correct and unbiased way. A method for automating the scoring is multiple choice scoring. This article compares scoring methods from a probabilistic point of view by modelling the probability to pass: the number righy scoring, the initial correctin (IC) and the negative marking (NM) method. We will compare the probabilities for students to pass when their assessment is translated into a score by means of the NM and the IC method, Moreover, given a knowledge level of the sutdent, the variance of this probablility will be discussed for both methods.
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