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The Effects of Item Format and Cognitive Domain on Students' Science Performance in TIMSS 2011

机译:物品格式与认知域对蒂姆斯学生科学表现的影响

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The purpose of this study was to examine eighth-grade students' science performance in terms of two test design components, item format, and cognitive domain. The portion of Taiwanese data came from the 2011 administration of the Trends in International Mathematics and Science Study (TIMSS), one of the major international large-scale assessments in science. The item difficulty analysis was initially applied to show the proportion of correct items. A regression-based cumulative link mixed modeling (CLMM) approach was further utilized to estimate the impact of item format, cognitive domain, and their interaction on the students' science scores. The results of the proportion-correct statistics showed that constructed-response items were more difficult than multiple-choice items, and that the reasoning cognitive domain items were more difficult compared to the items in the applying and knowing domains. In terms of the CLMM results, students tended to obtain higher scores when answering constructed-response items as well as items in the applying cognitive domain. When the two predictors and the interaction term were included together, the directions and magnitudes of the predictors on student science performance changed substantially. Plausible explanations for the complex nature of the effects of the two test-design predictors on student science performance are discussed. The results provide practical, empirical-based evidence for test developers, teachers, and stakeholders to be aware of the differential function of item format, cognitive domain, and their interaction in students' science performance.
机译:本研究的目的是根据两个测试设计组件,项目格式和认知域来检查八年级学生的科学表现。台湾数据的一部分来自2011年的国际数学和科学研究趋势(TIMSS),是科学的主要国际大规模评估之一。最初应用该项目难度分析以显示正确物品的比例。进一步利用基于回归的累积链路混合建模(CLMM)方法来估计物品格式,认知领域及其对学生科学分数的互动的影响。比例校正统计的结果表明,构造 - 响应项比多项选择项更困难,而且与应用和了解域中的项目相比,推理认知域项更加困难。就CLMM结果而言,学生们在回答构建的响应项目以及应用认知域中的项目时倾向于获得更高的分数。当两个预测器和交互项被包括在一起时,预测因子对学生科学性能的方向和大幅度变化大幅变化。讨论了两种测试设计预测因素对学生科学表现的复杂性质的合理解释。结果为测试开发人员,教师和利益相关者提供了实用,基于实证的证据,了解物品格式,认知领域的差异功能,以及学生科学表现的互动。

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