ChatGPT in Programming Education

An Empirical Study on Its Impact on Student Performance, Creativity, and Teamwork

Bibliographic Data

ID22044580
AuthorsDiana Stoyanova (0000-0003-3001-7893, Plovdiv University, corresponding author), Silviya Stoyanova-Petrova (0000-0003-3366-0235, Plovdiv University), Snezha Shotarova (0009-0006-1598-2301, Plovdiv University), Slavi Lyubomirov (0000-0002-0843-9312, Plovdiv University), Nevena Mileva (0000-0002-5157-6611, Plovdiv University)
Year2025
Volume16
Issue1
Pages19
Publication date2025-12-23
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci16010019
OpenAlexW7117117410
LanguageEN
Citations received1
References cited45

This study employs a two-part research design to explore the impact of ChatGPT on programming education for engineering undergraduates. Study 1 involved 56 third-year students who completed a questionnaire examining the frequency and purposes of ChatGPT use in text-based programming. While no statistically significant association was found between ChatGPT usage frequency and final grades, high-achieving students tended to use the tool less frequently, whereas lower-performing students relied on it more for support. Study 2 employed a counterbalanced repeated-measures design with nine first-year students divided into two groups, who developed desktop applications with and without ChatGPT. Project assessments and focus-group interviews were used to examine the effects of ChatGPT on creativity, confidence, effectiveness, and teamwork in visual programming. The results indicate that ChatGPT use was associated with reduced task completion time and increased coding efficiency; however, it was also linked to decreased creativity, greater reliance on ready-made solutions, and diminished code readability and collaborative engagement. These results highlight the need for teaching strategies that balance AI integration in programming education. The study recommends incorporating tasks based on the Reverse Bloom’s Taxonomy and activities that allow students to work with and without ChatGPT to encourage critical reflection and responsible AI use

Empirical research · Group work · Readability · Task Analysis · Teaching method · Teamwork · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Teaching and Learning Programming

Tools

Open DOIOpen Access