Measures of Partial Knowledge and Unexpected Responses in Multiple-Choice Tests

Abstract

This study investigates differences in the partial scoring performance of examinees in elimination testing and conventional dichotomous scoring of multiple-choice tests implemented on a computer-based system. Elimination testing that uses the same set of multiple-choice items rewards examinees with partial knowledge over those who are simply guessing. This study provides a computer-based test and item analysis system to reduce the difficulty of grading and item analysis following elimination tests. The Rasch model, based on item response theory for dichotomous scoring, and the partial credit model, based on graded item response for elimination testing, are the kernel of the test-diagnosis subsystem to estimate examinee ability and itemdifficulty parameters. This study draws the following conclusions: (1) examinees taking computer-based tests (CBTs) have the same performance as those taking paper-and-pencil tests (PPTs); (2) conventional scoring does not measure the same knowledge as partial scoring; (3) the partial scoring of multiple choice lowers the number of unexpected responses from examinees; and (4) the different question topics and types do not influence the performance of examinees in either PPTs or CBTs.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 33 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.