论文标题
互动和迭代的同伴评估
Interactive and Iterative Peer Assessment
论文作者
论文摘要
迭代性同行分级活动可能会使学生在课堂项目演示过程中参与其中。收集和汇总同行评估数据的有效方法至关重要。学生倾向于对项目进行分级。因此，在要求学生提高数字成绩是一种常见的方法时，它通常会导致所有项目的成绩膨胀，从而导致高级成绩有许多联系。此外，学生可以从战略上为他人的项目分配较低的成绩，以便他们的项目大放异彩。另外，要求学生将由于人类认知能力的限制而对所有最佳项目的所有项目进行排名。为了解决这些问题，我们提出了一个新颖的同行评分模型，该模型由（a）算法组成，旨在引发学生评估，以及（b）基于中位数的投票方案，用于将成绩汇总到单个排名订单中，以降低关系。在大学课程中部署和测试了基于我们模型的应用程序，表明替代方案之间的联系较少，并且学生的认知和沟通负担大大减少。
Iterative peer grading activities may keep students engaged during in-class project presentations. Effective methods for collecting and aggregating peer assessment data are essential. Students tend to grade projects favorably. So, while asking students for numeric grades is a common approach, it often leads to inflated grades across all projects, resulting in numerous ties for the top grades. Additionally, students may strategically assign lower grades to others' projects so that their projects will shine. Alternatively, requesting students to rank all projects from best to worst presents challenges due to limitations in human cognitive capacity. To address these issues, we propose a novel peer grading model consisting of (a) an algorithm designed to elicit student evaluations and (b) a median-based voting protocol for aggregating grades to a single ranked order that reduces ties. An application based on our model was deployed and tested in a university course, demonstrating fewer ties between alternatives and a significant decrease in students' cognitive and communication burdens.
