Suppr超能文献

GenBio-MAPS 作为一个案例研究,以了解和解决低风险项目评估中考试动机的影响。

GenBio-MAPS as a Case Study to Understand and Address the Effects of Test-Taking Motivation in Low-Stakes Program Assessments.

机构信息

School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, NE 68588.

出版信息

CBE Life Sci Educ. 2021 Jun;20(2):ar20. doi: 10.1187/cbe.20-10-0243.

Abstract

The General Biology-Measuring Achievement and Progression in Science (GenBio-MAPS) assessment measures student understanding of the core concepts at the beginning, middle, and end of undergraduate biology degree programs. Assessment coordinators typically administer this instrument as a low-stakes assignment for which students receive participation credit. While these conditions can elicit high participation rates, it remains unclear how to best measure and account for potential variation in the amount of effort students give to the assessment. To better understand student test-taking motivation, we analyzed GenBio-MAPS data from more than 8000 students at 20 institutions. While the majority of students give acceptable effort, some students exhibited behaviors associated with low motivation, such as low self-reported effort, short test completion time, and high levels of rapid-selection behavior on test questions. Standard least-squares regression models revealed that students' self-reported effort predicts their observable time-based behaviors and that these motivation indices predict students' GenBio-MAPS scores. Furthermore, we observed that test-taking behaviors and performance change as students progress through the assessment. We provide recommendations for identifying and filtering out data from students with low test-taking motivation so that the filtered data set better represents student understanding.

摘要

《综合生物学-衡量科学成就与进展(GenBio-MAPS)》评估衡量了学生在本科生物学学位课程开始、中期和结束时对核心概念的理解。评估协调员通常将此工具作为一项低风险作业进行管理,学生可以获得参与学分。虽然这些条件可以产生高参与率,但仍不清楚如何最好地衡量和解释学生在评估中投入的努力的潜在差异。为了更好地了解学生的考试动机,我们分析了来自 20 个机构的 8000 多名学生的 GenBio-MAPS 数据。虽然大多数学生都付出了可接受的努力,但有些学生表现出与低动机相关的行为,例如自我报告的努力程度低、测试完成时间短以及对测试问题的快速选择行为水平高。标准最小二乘回归模型表明,学生的自我报告的努力程度预测了他们可观察到的基于时间的行为,而这些动机指标预测了学生的 GenBio-MAPS 成绩。此外,我们观察到随着学生在评估中的进展,考试行为和表现会发生变化。我们提供了识别和筛选出具有低考试动机的学生数据的建议,以便过滤后的数据更好地代表学生的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e7c/8734388/a40cd2c5b4fc/cbe-20-ar20-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验