Educational impacts of generative artificial intelligence on learning and performance of engineering students in China
Project Overview
The document examines the influence of generative AI on the educational experiences and performance of engineering students in China, revealing its benefits in enhancing learning efficiency, fostering creativity, and promoting independent thought. A survey of 148 students indicated that many experienced improved learning outcomes attributed to generative AI; however, this did not always translate into better academic performance, raising concerns about issues such as accuracy, over-reliance on AI tools, and ethical implications. To optimize the integration of generative AI in engineering education, the document offers recommendations that include establishing clear guidelines, providing training for students and educators, and tackling the ethical challenges associated with AI usage. Overall, while generative AI holds promise for enriching education, careful implementation and consideration of its limitations are crucial.
Key Applications
Generative AI tools (e.g., ChatGPT, Baidu's Wenxin Yiyan) used for academic tasks
Context: Higher education, specifically for engineering students in China
Implementation: Survey of 148 engineering students regarding their use of generative AI in their studies
Outcomes: Increased learning efficiency, improved creativity, and enhanced independent thinking reported by many students; 88.52% stated improved productivity.
Challenges: Concerns about the accuracy of AI-generated content, over-reliance on tools, and ethical issues.
Implementation Barriers
Technical
Inaccuracy of AI-generated content, especially for complex engineering tasks.
Proposed Solutions: Improving the accuracy of AI outputs and ensuring they cater to specific engineering disciplines.
Behavioral
Over-reliance on AI tools can diminish independent problem-solving skills and critical thinking.
Proposed Solutions: Establishing clear usage guidelines and promoting active engagement with learning material.
Ethical
Concerns regarding academic integrity, plagiarism, and data privacy.
Proposed Solutions: Implementing ethical training and guidelines for responsible AI use in education.
Project Team
Lei Fan
Researcher
Kunyang Deng
Researcher
Fangxue Liu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Lei Fan, Kunyang Deng, Fangxue Liu
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