Evaluating Different Scoring Methods for Multiple Response Items Providing Partial Credit

Abstract

The multiple response structure can underlie several different technology-enhanced item types. With the increased use of computer-based testing, multiple response items are becoming more common. This response type holds the potential for being scored polytomously for partial credit. However, there are several possible methods for computing raw scores. This research will evaluate several approaches found in the literature using an approach that evaluates how the inclusion of scoring related to the selection/nonselection of both relevant and irrelevant information is incorporated extending Wilson’s approach. Results indicated all methods have potential, but the plus/minus and true/false methods seemed the most promising for items using the “select all that apply” instruction set. Additionally, these methods showed a large increase in information per time unit over the dichotomous method.