An Empirical Study of Students’ Perceptions on the Setup and Grading of Group Programming Assignments

Efthimia Aivaloglou, A. V. D. Meulen
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引用次数: 7

Abstract

Courses in computer science curricula often involve group programming assignments. Instructors are required to take several decisions on assignment setup and monitoring, team formation policies, and grading systems. Group programming projects provide unique monitoring opportunities due to the availability of both product and process data, as well as challenges in team composition, with students of varying levels of prior programming experience. To gain insights into the experiences and perceptions of students about the assignment setup and grading policies in group programming projects, we interviewed 20 computer science students from four universities. The thematic analysis highlighted factors in group composition that are considered important, as well as advantages and disadvantages of the self-selection of the teams. It also indicated three grading strategies experienced by the students, namely, being assigned the same group grade, individual grades distributed by the instructor, and grade distribution determined by the team, with perceptions about them varying greatly. Several practices for monitoring team contributions were identified. Checking the source code repositories was considered useful in recognizing slacking members, but automated metrics are not always representative of the work distribution. The analysis also uncovered student perceptions on the grading factors for programming assignments, including coding efficiency and skill.
学生对小组规划作业设置与评分认知的实证研究
计算机科学课程中的课程通常涉及小组编程作业。教师需要在作业设置和监督、团队组建政策和评分系统方面做出若干决定。由于产品和过程数据的可用性,以及团队组成的挑战,小组编程项目提供了独特的监控机会,因为学生的编程经验水平各不相同。为了深入了解学生对小组编程项目的作业设置和评分政策的经验和看法,我们采访了来自四所大学的20名计算机科学专业的学生。专题分析突出了小组组成中被认为重要的因素,以及小组自我选择的优点和缺点。学生经历了三种评分策略,分别是相同的小组分数、导师分配的个人分数和团队决定的分数分配,对这三种评分策略的认知差异很大。确定了监测小组贡献的几种做法。检查源代码存储库被认为有助于识别偷懒的成员,但是自动化度量并不总是代表工作分布。分析还揭示了学生对编程作业评分因素的看法,包括编码效率和技能。
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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