Marcel Valový

dblp:320/7096 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2023
0000-0001-7074-0918ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 first-author · 2 since 2021
YearPublicationVenuePosition
2023 Psychological Aspects of Pair Programming: A Mixed-methods Experimental Study
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.
Marcel Valový
EASE1
2023 The Psychological Effects of AI-Assisted Programming on Students and Professionals
abstract
Artificial intelligence (AI) tools have become integral to the coding workflow, facilitating productivity through auto-completion, code suggestions, and chat dialogues. More than ever, the psychological relationship between software engineers and AI partners requires further exploration, mirroring the need to understand the psychological aspects of pilot-navigator roles these tools partly simulate, as highlighted in earlier studies. [Goal] The presented research aims to investigate the programmer behavior change and psychological effects of AI-assisted programming on professionals and undergraduates. [Methods] The authors performed a series of seven experimental programming sessions on the undergraduate student sample, subjecting them to programming in solo, pair, and AI-assisted settings. Following the experimental sessions, five semi-structured interviews were conducted with the experimental participants from the academic realm and another five with experienced users of AI programming tools from the professional realm. The interviews were analyzed using thematic analysis in an essentialist way, allowing for a comprehensive understanding of the participants’ experiences, feelings, and attitudes toward AI-assisted programming. [Results] A total of ten themes were identified, half shared across the two realms, with 51 constituent codes selected from the professional and 35 from the student interview transcripts. The realm-agnostic themes were: "Effectance", "Intrinsic Motivation", "Perceived AI Personality", "Dynamics of Human and AI Pairing," and "Paradigm Shifts". The realm-specific themes included: "Personal Growth and Development", "Prospects", "Ethical Considerations", "Safety", and "Effects on Learning Processes". [Conclusion] The presented research illuminates the profound potential of using AI as a programming partner in simulated pilot-navigator roles in both professional and academic realms. It underscores the importance of understanding its effects on psychological well-being and human experience. Incorporating the revealed psychological aspects of human-AI interaction, its benefits, limitations, and dynamics will be pivotal for successful AI implementation and continued evolution in software engineering contexts.
Marcel Valový, Alena Buchalcevová
ICSME1