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ERIC Number: ED428076
Record Type: Non-Journal
Publication Date: 1999-Jan-21
Pages: 21
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
A Review of Scoring Algorithms for Multiple-Choice Tests.
Kurz, Terri Barber
Multiple-choice tests are generally scored using a conventional number right scoring method. While this method is easy to use, it has several weaknesses. These weaknesses include decreased validity due to guessing and failure to credit partial knowledge. In an attempt to address these weaknesses, psychometricians have developed various scoring algorithms. This paper provides an overview of the different scoring algorithms that correct for guessing and award credit for partial knowledge. Included in the overview is an explanation of the scoring formulas as well as a brief summary of the literature regarding the utility of each algorithm. Formula scoring methods and formula scoring with Item Response Theory are discussed. The following methods for awarding credit for partial knowledge are also reviewed: (1) confidence weighting; (2) answer-until-correct scoring; (3) option weighting; (4) elimination and inclusion scoring; and (5) multiple-answer scoring. (Contains 21 references.) (Author/SLD)
Publication Type: Reports - Descriptive; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A