Psychological Aspects of Pair Programming: A Mixed-methods Experimental Study

Marcel Valový
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Abstract

With the recent advent of artificially intelligent pairing partners in software engineering, it is interesting to renew the study of the psychology of pairing. Pair programming provides an attractive way of teaching software engineering to university students. Its study can also lead to a better understanding of the needs of professional software engineers in various programming roles and for the improvement of the concurrent pairing software. [Objective] This preliminary study aimed to gain quantitative and qualitative insights into pair programming, especially students’ attitudes towards its specific roles and what they require from the pairing partners. The research's goal is to use the findings to design further studies on pairing with artificial intelligence. [Method] Using a mixed-methods and experimental approach, we distinguished the effects of the pilot, navigator, and solo roles on (N = 35) students’ intrinsic motivation. Four experimental sessions produced a rich data corpus in two software engineering university classrooms. It was quantitatively investigated using the Shapiro-Wilk normality test and one-way analysis of variance (ANOVA) to confirm the relations and significance of variations in mean intrinsic motivation in different roles. Consequently, seven semi-structured interviews were conducted with the experiment's participants. The qualitative data excerpts were subjected to the thematic analysis method in an essentialist way. [Results] The systematic coding interview transcripts elucidated the research topic by producing seven themes for understanding the psychological aspects of pair programming and for its improvement in university classrooms. Statistical analysis of 612 self-reported intrinsic motivation inventories confirmed that students find programming in pilot-navigator roles more interesting and enjoyable than programming simultaneously. [Conclusion] The executed experimental settings are viable for inspecting the associations between students’ attitudes and the distributed cognition practice. The preliminary results illuminate the psychological aspects of the pilot-navigator roles and reveal many areas for improvement. The results also provide a strong basis for conducting further studies with the same design involving the big five personality and intrinsic motivation on using artificial intelligence in pairing and to allow comparison of those results with results of pairing with human partners.
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结对编程的心理方面:一项混合方法的实验研究
随着人工智能结对伙伴在软件工程中的出现,结对心理学的重新研究是一个有趣的问题。结对编程为大学生提供了一种极具吸引力的软件工程教学方式。它的研究还可以帮助我们更好地理解各种编程角色的专业软件工程师的需求,以及对并行结对软件的改进。【目的】本初步研究旨在定量和定性地了解结对编程,特别是学生对结对编程的具体角色的态度以及他们对结对伙伴的要求。该研究的目标是利用这些发现来设计与人工智能配对的进一步研究。[方法]采用混合方法和实验方法,区分飞行员、领航员和单人角色对(N = 35)名学生内在动机的影响。在两个软件工程大学的教室里,四次实验产生了一个丰富的数据语料库。采用Shapiro-Wilk正态检验和单因素方差分析(ANOVA)进行定量研究,以确定不同角色平均内在动机变化的相关性和显著性。因此,对实验参与者进行了七次半结构化访谈。定性数据节选采用本质主义的专题分析方法。[结果]系统的编程访谈记录通过产生七个主题来阐明研究主题,以了解结对编程的心理方面以及在大学课堂上的改进。对612份自我报告的内在动机量表的统计分析证实,学生认为在领航员角色中编程比同时编程更有趣和愉快。[结论]所设置的实验设置对于考察学生态度与分布式认知练习的关系是可行的。初步结果阐明了领航员角色的心理方面,并揭示了许多有待改进的领域。这一结果也为进一步开展涉及大五人格和内在动机的相同设计的研究提供了坚实的基础,并允许将这些结果与与人类伴侣配对的结果进行比较。
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