Peer assessment methodology of open-ended assignments: Insights from a two-year case study within a university course using novel open source system

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2024-02-01 DOI:10.1016/j.compedu.2024.105001
Ljiljana Brkić , Igor Mekterović , Melita Fertalj , Darko Mekterović
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Abstract

Peer assessment is a process in which students rate their peers which has many benefits for both the assessor and the assessed. It actively engages students, increases motivation by giving a sense of ownership of the assessment process, encourages autonomy and critical analysis skills, broadens their understanding of the topic, enhances problem-solving and self-assessment abilities as well as develops soft skills. Peer assessment is also beneficial to the teachers as it reduces the strain of the repetitive grading process thus opening more resources for teaching and the development of course materials, especially in large courses with hundreds of students. Sometimes, peer assessment is the only viable option, as in MOOCs (Massive Open Online Courses). Peer assessment has long been studied at all education levels and is gaining traction in recent years, where MOOCs and even the Covid pandemic, which instigated the development of digital competencies, had a positive influence. However, peer assessment is still a demanding process to carry out, but one that can be assisted by modern Internet technology. This paper has a twofold contribution: we present the peer assessment module of our open-source automated programming assessment system Edgar which has been heavily used and developed for the last six years, while peer assessment has been used for the previous three years. Additionally, we present a methodology used and a two-year case study of peer assessment of open-ended assignments in the undergraduate Databases course where 500+ students per season had to provide an entity-relationship model for a given domain and assess their peers' submissions. We discuss our grading methodology, provide in-depth data analysis, and present the students' opinions of the process acquired through an anonymous questionnaire. We find that the process is both demanding in terms of the design of assignments and assessment questionnaires and rewarding in the assessment phase, where the students’ grades turned out to be of high quality.

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开放式作业的同行评估方法:在大学课程中使用新型开源系统进行为期两年的案例研究的启示
同伴评价是学生对同伴进行评分的过程,对评价者和被评价者都有很多好处。它能让学生积极地参与进来,通过赋予学生对评价过程的主人翁意识来提高他们的积极性,鼓励自主性和批判性分析能力,拓宽他们对主题的理解,提高解决问题和自我评价的能力,以及培养软技能。同伴互评对教师也有好处,因为它减轻了重复评分过程的压力,从而为教学和教材编写提供了更多的资源,特别是在有数百名学生的大型课程中。有时,同伴互评是唯一可行的选择,比如在 MOOC(大规模开放式在线课程)中。长期以来,各级教育机构一直在研究同行评估,近年来,MOOCs 甚至引发数字能力发展的 Covid 大流行,都对同行评估产生了积极影响。然而,同伴互评仍然是一项要求很高的工作,但现代互联网技术可以为其提供帮助。本文有两方面的贡献:我们介绍了我们的开源自动编程评估系统 Edgar 的同行评估模块,该系统在过去六年中得到了大量的使用和开发,而同行评估在过去三年中也得到了使用。此外,我们还介绍了在本科数据库课程中对开放式作业进行同行评估所使用的方法和为期两年的案例研究,在该课程中,每季度有 500 多名学生必须为给定领域提供实体关系模型,并对同行提交的作业进行评估。我们讨论了我们的评分方法,提供了深入的数据分析,并通过匿名问卷介绍了学生对这一过程的看法。我们发现,这一过程对作业和评估问卷的设计要求很高,而在评估阶段则收获颇丰,学生们的成绩都很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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