Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course
Project Overview
The document explores the use of generative AI, specifically ChatGPT, in enhancing programming education within a Python course aimed at first-year university students. It emphasizes the AI's role in facilitating debugging, generating code, and providing explanations, which collectively contribute to increased student engagement and enriched learning experiences. Over an eight-week study period, student perceptions and interactions with ChatGPT were assessed, revealing a largely positive response to its integration in the curriculum. The findings suggest that while ChatGPT can significantly enhance educational outcomes by supporting students in their programming tasks, challenges remain, such as the risk of students becoming overly reliant on AI assistance and encountering instances of incorrect information provided by the tool. The document advocates for strategies to optimize the use of generative AI in programming education while addressing these challenges, aiming to foster a balanced approach that leverages AI's capabilities without compromising critical thinking and problem-solving skills.
Key Applications
ChatGPT as a programming assistant for debugging, code generation, and explanations
Context: University-level Python programming course for first-year students
Implementation: Students used ChatGPT freely during programming exercises, homework, and projects, logging interactions for analysis.
Outcomes: Positive reception from students, who found ChatGPT helpful for correcting code, providing examples, and clarifying concepts. Increased engagement and understanding of programming concepts.
Challenges: Potential dependency on ChatGPT leading to reduced self-thinking, risks of incorrect answers, and providing solutions outside course scope.
Implementation Barriers
Cognitive Barrier
Students may become dependent on ChatGPT, reducing their ability to think independently and engage deeply with programming tasks.
Proposed Solutions: Encouraging step-by-step hints and interactive questioning to foster self-thinking and critical problem-solving.
Technical Barrier
ChatGPT may not always provide correct answers or may suggest advanced solutions that exceed the course's scope.
Proposed Solutions: Ensuring code correctness and offering multiple solutions to enhance understanding.
Project Team
["Boxaun Ma", "Li Chen", "Shin"ichi Konomi"]
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: ["Boxaun Ma", "Li Chen", "Shin"ichi Konomi"]
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai