Validating Measurement of Knowledge Integration in Science Using Multiple-Choice and Explanation Items
Validating Measurement of Knowledge Integration in Science Using Multiple-Choice and Explanation Items
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使用多项选择和解释项目验证科学知识整合的测量
DOI：
10.1080/08957347.2011.554604
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发表时间：
2011
影响因子：
1.5
通讯作者：
M. Linn
中科院分区：
文献类型：
--
作者：
Hee;O. Liu;M. Linn
本研究以多项选择题和解释题探讨科学知识整合的测量。本研究采用结构效度和教学效度证据检验多项选择题和解释题在测量学生知识整合能力中的作用。对于结构效度，我们分析项目属性，如对齐，歧视，和目标范围的知识整合规模使用Rasch部分信用模型分析。教学效度，我们测试的敏感性多项选择和解释项目知识整合教学使用队列比较设计。结果表明：（1）三分之一正确的多项选择题与较高的知识整合水平相一致，而四分之三不正确的多项选择题与较低的知识整合水平相一致;（2）解释题比多项选择题更能有效区分知识整合能力高和低的学生，（3）解释题比多项选择题更能测量学生的知识整合水平;（4）解释题比多项选择题对知识整合教学更敏感。
This study explores measurement of a construct called knowledge integration in science using multiple-choice and explanation items. We use construct and instructional validity evidence to examine the role multiple-choice and explanation items plays in measuring students' knowledge integration ability. For construct validity, we analyze item properties such as alignment, discrimination, and target range on the knowledge integration scale using a Rasch Partial Credit Model analysis. For instructional validity, we test the sensitivity of multiple-choice and explanation items to knowledge integration instruction using a cohort comparison design. Results show that (1) one third of correct multiple-choice responses are aligned with higher levels of knowledge integration while three quarters of incorrect multiple-choice responses are aligned with lower levels of knowledge integration, (2) explanation items discriminate between high and low knowledge integration ability students much more effectively than multiple-choice items, (3) explanation items measure a wider range of knowledge integration levels than multiple-choice items, and (4) explanation items are more sensitive to knowledge integration instruction than multiple-choice items.