同行评议的审稿人分配策略:面向自我分配中的合谋管理

Yanqing Wang, Bingyu Liu, Kun Zhang, Yu Jiang, Fu-Quan Sun
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引用次数: 2

摘要

同侪评估是一种高效的学习过程,已广泛应用于高等教育的各个领域。尽管合谋有很多好处,但它也是一个常见的挑战,使得同行评估的可靠性成为实践中主要关注的问题,特别是当自我分配策略应用于审稿人分配时。本研究旨在提出一种以协同网络作为识别合谋的手段的合谋管理模型。提出的模型作为软件模块在同行代码评审系统EduPCR中实现。EduPCR能够监控这一措施,并在识别出可疑的串通时触发教师对串通嫌疑人的查询。在某大学C编程课程中进行的验证表明,所提出的合谋管理模型是合理的,识别算法在不同的同行评估环境下是实用的。关键词:同行评议,审稿人分配,合谋,协同网络,自分配策略,EduPCR
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reviewer Assignment Strategy of Peer Assessment: Towards Managing Collusion in Self-assignment
Peer assessment is an efficient and effective learning process that has been widely used in diverse fields in the higher education. Despite of its many benefits, collusion is a common challenge that makes the reliability of peer assessment a primary concern in practices, especially when self-assignment strategy is applied in reviewer assignment. This research aims to propose a model of collusion management that applies cooccurrence network as a means to identify collusion. The proposed model is implemented as a software module in a peer code review system called EduPCR. EduPCR is able to monitor this measure and trigger instructor’s inquiries to collusion suspects when it identifies suspected collusion. A verification implemented in a university-level C Programming course shows that the proposed collusion management model is reasonable and the identification algorithm is practical in diverse peer assessment contexts. Keywords—peer assessment, reviewer assignment, collusion, cooccurrence network, self-assignment strategy, EduPCR
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