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Exploring Student Perception and Interaction Using ChatGPT in Programming Education

Title: Exploring Student Perception and Interaction Using ChatGPT in Programming Education
Language: English
Authors: Boxuan Ma; Li Chen; Shin’ichi Konomi
Source: International Association for Development of the Information Society. 2024.
Availability: International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
Peer Reviewed: Y
Page Count: 8
Publication Date: 2024
Document Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Descriptors: Artificial Intelligence; Computer Science Education; Programming; Computer Uses in Education; Programming Languages; Introductory Courses; Student Attitudes; Knowledge Level; Educational Benefits; Computer Attitudes; Academic Achievement; Undergraduate Students; Foreign Countries
Geographic Terms: Japan
Abstract: Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and interactions using ChatGPT in a beginner-level Python programming course through a combination of questionnaire responses and student-ChatGPT dialogue data analysis. The findings reveal a generally positive student reception toward ChatGPT, emphasizing its role in enhancing the programming education experience. Additionally, by clustering and analyzing the types of prompts students use, we identify four distinct patterns of ChatGPT usage and compare the performance outcomes associated with each pattern. This empirical research provides a deeper understanding of AI-enhanced programming education, offering valuable insights and suggesting pathways for future research and practical applications. [For the full proceedings, see ED665357.]
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED665431
Database: ERIC