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.

翻译：随着人工智能编程伙伴在软件工程领域的近期兴起，重新审视编程结对心理层面的研究显得尤为重要。结对编程为向大学生教授软件工程提供了一种颇具吸引力的方式。该研究亦有助于更深入地理解专业软件工程师在不同编程角色中的需求，并促进并发结对软件的改进。目标：本初步研究旨在获取关于结对编程的定量与定性洞察，尤其是学生对特定角色的态度及其对结对伙伴的要求。研究目的在于利用这些发现来设计进一步关于与人工智能结对的研究。方法：采用混合方法与实验途径，我们区分了领航员、导航员及单人角色对（N=35）学生内在动机的影响。四次实验课程在两个软件工程大学课堂中产生了丰富的数据语料。我们运用夏皮罗-威尔克正态性检验与单因素方差分析进行定量调查，以确认不同角色下内在动机均值变化的关联性与显著性。随后，对实验参与者进行了七次半结构化访谈。定性数据摘录采用本质主义方式进行主题分析。结果：系统化的访谈转录编码通过生成七个主题，揭示了理解结对编程心理层面的研究主题，并为大学课堂的改进提供了依据。对612份自报告内在动机量表的统计分析确认，学生在领航员-导航员角色下的编程比同时编程更具趣味性与愉悦性。