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Cited by 23Teaching and Learning ProgrammingSoftware Engineering Techniques and PracticesSoftware Engineering Research

The Psychological Effects of AI-Assisted Programming on Students and Professionals

Valový, Marcel, Buchalcevova, Alena·2023·2023 IEEE International Conference on Software Maintenance and Evolution (ICSME)
DOI 10.1109/icsme58846.2023.00050
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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 Motivati…

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  • As LLMs increasingly automate routine and syntactic coding tasks, educators face the challenge of preserving essential programming competencies such as algorithmic thinking, debugging, and independent problem-solving.

    “As LLMs increasingly automate routine and syntactic coding tasks, educators face the challenge of preserving essential programming competencies, such as algorithmic thinking, debugging, and independent problem-solving (Valový & Buchalcevova, 2023;Bull & Kharrufa, 2024;French et al., 2023).”

    From Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI Errors (2025) · cites this paper as Valový & Buchalcevova, 2023

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Authors
Valový, M., & Buchalcevova, A.
Affiliations
  • Prague University of Economics and Business (CZ)
  • Prague University of Economics and Business,Department of Information Technologies,Prague,Czech Republic
ORCID
Valový, Marcel
Venue
2023 IEEE International Conference on Software Maintenance and Evolution (ICSME)
Publisher
IEEE
Published
2023-10-01
Pages
385-390
ISSN
1063-6773 (ISSN-L)
DOI
10.1109/icsme58846.2023.00050
OpenAlex
W4389544212
Cited by
23
References
4
Citations by year
2026: 6 · 2025: 14 · 2024: 3
FWCI
6.95
Type
conference paper
Language
en
Open access
closed
Licence
Locations
IEEE International Conference on Software Maintenance (ICSM) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Research
Keywords
AI-assisted programming, human-AI interaction, psychological impact, intrinsic motivation, paradigm shift, ethical considerations, safety, programming education, psychological well-being

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