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Van Hecke, Tanja – Teaching Mathematics and Its Applications, 2015
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 right scoring, the initial correction (IC) and…
Descriptors: Multiple Choice Tests, Error Correction, Grading, Evaluation Methods
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Merrel, Jeremy D.; Cirillo, Pier F.; Schwartz, Pauline M.; Webb, Jeffrey A. – Higher Education Studies, 2015
Multiple choice testing is a common but often ineffective method for evaluating learning. A newer approach, however, using Immediate Feedback Assessment Technique (IF AT®, Epstein Educational Enterprise, Inc.) forms, offers several advantages. In particular, a student learns immediately if his or her answer is correct and, in the case of an…
Descriptors: Multiple Choice Tests, Feedback (Response), Evaluation Methods, Guessing (Tests)
Tollefson, Nona; Chung, Jing-Mei – 1986
Procedures for correcting for guessing and for assessing partial knowledge (correction-for-guessing, three-decision scoring, elimination/inclusion scoring, and confidence or probabilistic scoring) are discussed. Mean scores and internal consistency reliability estimates were compared across three administration and scoring procedures for…
Descriptors: Achievement Tests, Comparative Analysis, Evaluation Methods, Graduate Students
Smith, Richard M. – 1982
There have been many attempts to formulate a procedure for extracting information from incorrect responses to multiple choice items, i.e., the assessment of partial knowledge. The results of these attempts can be described as inconsistent at best. It is hypothesized that these inconsistencies arise from three methodological problems: the…
Descriptors: Difficulty Level, Evaluation Methods, Goodness of Fit, Guessing (Tests)