Processing of Test Matrices with Guessing Correction

TL;DR

This paper proposes a method for processing test matrices by inserting specific elements for responses and using classical and item response theory to estimate scores and probabilities.

Contribution

It introduces a novel approach combining correction elements in test matrices with classical and IRT methods for score estimation.

Findings

Effective correction of test responses improves score accuracy

IRT-based logits provide detailed item and examinee analysis

Correlation adjustments enhance test reliability

Abstract

It is suggested to insert into test matrix 1s for correct responses, 0s for response refusals, and negative corrective elements for incorrect responses. With the classical test theory approach test scores of examinees and items are calculated traditionally as sums of matrix elements, organized in rows and columns. Correlation coefficients are estimated using correction coefficients. In item response theory approach examinee and item logits are estimated using maximum likelihood method and probabilities of all matrix elements.