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THE SUBSET SELECTION TECHNIQUE FOR MULTIPLE‐CHOICE TESTS: AN EMPIRICAL INQUIRY
Author(s) -
JARADAT DERAR,
SAWAGED SARI
Publication year - 1986
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1986.tb00256.x
Subject(s) - reliability (semiconductor) , selection (genetic algorithm) , test (biology) , multiple choice , set (abstract data type) , psychology , short forms , statistics , computer science , mathematics , artificial intelligence , clinical psychology , significant difference , paleontology , power (physics) , physics , quantum mechanics , biology , programming language
The impact of the Subset Selection Technique (SST) for administering and scoring multiple‐choice items on certain properties of a test was compared with that of the two other commonly used methods, the Number Right (NR) and the Correction for Guessing Formula (CFG). Under SST, examinees are instructed to select any number of response alternatives, the objective being to include the correct answer in the chosen set. The effects of each scoring method on the psychometric properties of a test and on the performance of examinees with different achievement levels and/or risk‐taking propensities were investigated. Results indicated that SST outperformed the other two methods, producing not only higher reliability and validity coefficients for the test, but doing so without favoring high risk takers. The superiority of SST may be attributed to two interrelated factors: the efficiency of the technique in controlling for guessing and the encouragement provided examinees to use their partial knowledge in responding.