Would ChatGPT-facilitated programming mode impact college students’ programming behaviors, performances, and perceptions? An empirical study

ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing learners with opportunities to better understand the principles of programming. However, limited empirical studies have explored the impact of C...

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Vydané v:International Journal of Educational Technology in Higher Education Ročník 21; číslo 1; s. 14 - 22
Hlavní autori: Sun, Dan, Boudouaia, Azzeddine, Zhu, Chengcong, Li, Yan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cham Springer International Publishing 01.12.2024
Springer Nature B.V
SpringerOpen
Predmet:
Academic achievement
Artificial intelligence
Behavior
Behavioral analysis
Chatbots
ChatGPT
College student
College students
Colleges & universities
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Copying
Data analysis
Debugging
Design of experiments
Educational programs
Educational Technology
Empirical analysis
Feedback
Higher Education
Human-computer interaction
Humanities
Information Systems Applications (incl.Internet)
Instructional design
Law
Messages
Multidimensional data
Multidimensional methods
New advances in artificial intelligence applications in higher education
Perception
Perceptions
Programming
Programming learning
Quasi-experimental methods
Quasiexperimental Design
Research Article
Research design
Statistics for Social Sciences
Students
Troubleshooting
Usefulness
User experience
Programming learning
College student
Perception
ChatGPT
Behavioral analysis
ISSN:2365-9440, 2365-9440
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Shrnutí:ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing learners with opportunities to better understand the principles of programming. However, limited empirical studies have explored the impact of ChatGPT on learners’ programming processes. This study employed a quasi-experimental design to explore the possible impact of ChatGPT-facilitated programming mode on college students’ programming behaviors, performances, and perceptions. 82 college students were randomly divided into two classes. One class employed ChatGPT-facilitated programming (CFP) practice and the other class utilized self-directed programming (SDP) mode. Mixed methods were utilized to collect multidimensional data. Data analysis uncovered some intriguing results. Firstly, students in the CFP mode had more frequent behaviors of debugging and receiving error messages, as well as pasting console messages on the website and reading feedback. At the same time, students in the CFP mode had more frequent behaviors of copying and pasting codes from ChatGPT and debugging, as well as pasting codes to ChatGPT and reading feedback from ChatGPT. Secondly, CFP practice would improve college students’ programming performance, while the results indicated that there was no statistically significant difference between the students in CFP mode and the SDP mode. Thirdly, student interviews revealed three highly concerned themes from students' user experience about ChatGPT: the services offered by ChatGPT, the stages of ChatGPT usage, and experience with ChatGPT. Finally, college students’ perceptions toward ChatGPT significantly changed after CFP practice, including its perceived usefulness, perceived ease of use, and intention to use. Based on these findings, the study proposes implications for future instructional design and the development of AI-powered tools like ChatGPT.
Bibliografia:ObjectType-Article-1
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ISSN:2365-9440
2365-9440
DOI:10.1186/s41239-024-00446-5