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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Veröffentlicht in:International Journal of Educational Technology in Higher Education Jg. 21; H. 1; S. 14 - 22
Hauptverfasser: Sun, Dan, Boudouaia, Azzeddine, Zhu, Chengcong, Li, Yan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.12.2024
Springer Nature B.V
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ISSN:2365-9440, 2365-9440
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Abstract 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.
AbstractList 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.
Abstract 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.
ArticleNumber 14
Author Sun, Dan
Zhu, Chengcong
Boudouaia, Azzeddine
Li, Yan
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  organization: Chinese Education Modernization Research Institute, Hangzhou Normal University
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  fullname: Boudouaia, Azzeddine
  organization: Zhejiang University, College of Education
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  givenname: Chengcong
  surname: Zhu
  fullname: Zhu, Chengcong
  organization: Xiaoshan High School
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  givenname: Yan
  orcidid: 0000-0002-0640-1783
  surname: Li
  fullname: Li, Yan
  email: yanli@zju.edu.cn
  organization: Zhejiang University, College of Education
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Keywords Programming learning
College student
Perception
ChatGPT
Behavioral analysis
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Snippet ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing...
Abstract ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by...
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SubjectTerms 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
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Title Would ChatGPT-facilitated programming mode impact college students’ programming behaviors, performances, and perceptions? An empirical study
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Volume 21
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