当前位置: X-MOL 学术Large-scale Assessments in Education › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Using process data to understand problem-solving strategies and processes for drag-and-drop items in a large-scale mathematics assessment
Large-scale Assessments in Education Pub Date : 2021-02-24 , DOI: 10.1186/s40536-021-00095-4
Yang Jiang , Tao Gong , Luis E. Saldivia , Gabrielle Cayton-Hodges , Christopher Agard

In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to study the cognitive and behavioral processes that underlie test-takers’ performances in ways that are not otherwise possible with the response data alone. In this exploratory study, we investigated the problem-solving processes and strategies applied by the nation’s fourth and eighth graders by analyzing the process data collected during their interactions with two technology-enhanced drag-and-drop items (one item for each grade) included in the first digital operational administration of the NAEP’s mathematics assessments. Results from this research revealed how test-takers who achieved different levels of accuracy on the items engaged in various cognitive and metacognitive processes (e.g., in terms of their time allocation, answer change behaviors, and problem-solving strategies), providing insights into the common mathematical misconceptions that fourth- and eighth-grade students held and the steps where they may have struggled during their solution process. Implications of the findings for educational assessment design and limitations of this research are also discussed.



中文翻译:

使用过程数据来理解大规模数学评估中拖放项目的问题解决策略和过程

2017年,作为国家教育进步评估(NAEP)计划一部分的数学评估经历了转变,将行政管理从纸笔形式转变为基于数字的评估(DBA)。这种转变引入了新的交互式项目类型,这些类型带来了丰富的过程数据,并且为以应试者的表现为基​​础的认知和行为过程研究提供了巨大的机会,而这是单独使用响应数据所无法实现的。在这项探索性研究中,我们分析了美国四年级和八年级学生采用的解决问题的过程和策略,方法是分析他们与第一台数字操作设备中包含的两个技术增强的拖放项(每个年级一个)交互期间收集的过程数据NAEP数学评估的管理。这项研究的结果表明,考生如何在参与各种认知和元认知过程的项目上达到不同水平的准确性(例如,在时间分配,回答变化行为和解决问题的策略方面),从而提供了对四年级和八年级学生的常见数学误解以及他们在解决过程中可能遇到的困难。

更新日期:2021-03-17
down
wechat
bug