Lune

CSCW2023顶会

The Value of Activity Traces in Peer Evaluations: An Experimental Study

Wenxuan Wendy Shi, Sneha R. Krishna Kumaran, Hari Sundaram, Brian P. Bailey

2023年份
10被引次数
5顶会引用

摘要

Peer evaluations are a well-established tool for evaluating individual and team performance in collaborative contexts, but are susceptible to social and cognitive biases. Current peer evaluation tools have also yet to address the unique opportunities that online collaborative technologies provide for addressing these biases. In this work, we explore the potential of one such opportunity for peer evaluations: data traces automatically generated by collaborative tools, which we refer to as "activity traces". We conduct a between-subjects experiment with 101 students and MTurk workers, investigating the effects of reviewing activity traces on peer evaluations of team members in an online collaborative task. Our findings show that the usage of activity traces led participants to make more and greater revisions to their evaluations compared to a control condition. These revisions also increased the consistency and participants' perceived accuracy of the evaluations that they received. Our findings demonstrate the value of activity traces as an approach for performing more reliable and objective peer evaluations of teamwork. Based on our findings as well as qualitative analysis of free-form responses in our study, we also identify and discuss key considerations and design recommendations for incorporating activity traces into real-world peer evaluation systems.

CCS Concepts: • Human-centered computing → Computer supported cooperative work; Empirical studies in collaborative and social computing.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper5

问问它们各自怎么用它

它引用的顶会 Paper1

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖