Exploring the Impact of ChatGPT on Student Interactions in Computer-Supported Collaborative Learning
Project Overview
The document explores the role of generative AI, particularly ChatGPT, in enhancing educational experiences within computer-supported collaborative learning (CSCL). It emphasizes how ChatGPT can personalize learning and serve as a virtual assistant, offering valuable support to students. The analysis centers on a graduate-level product engineering course, investigating ChatGPT's impact on student creativity and interaction during group brainstorming sessions. Initial findings reveal a paradoxical effect: while ChatGPT facilitates some interactions by providing immediate assistance, it also appears to diminish direct student-to-student engagement, potentially undermining the collaborative nature of learning. The study raises important considerations regarding the balance between leveraging AI technology for individualized support and maintaining academic integrity and effective teamwork in educational settings. Overall, the findings call for further exploration of how generative AI can be integrated effectively into educational frameworks to optimize learning outcomes while fostering collaboration among students.
Key Applications
ChatGPT as a question-answering agent in CSCL
Context: Graduate-level product engineering course with students engaging in asynchronous group brainstorming
Implementation: ChatGPT was integrated into the chat system used by one group of cohorts (Type A), allowing them to tag ChatGPT for responses during discussions.
Outcomes: Increased active learning interactions directed towards ChatGPT, but a decrease in student-student interactions.
Challenges: Concerns regarding the decreased level of collaboration among students and the potential for ChatGPT to dominate interactions.
Implementation Barriers
Technological
Issues of factual accuracy and hallucination of responses from ChatGPT.
Proposed Solutions: Further analysis and improvements to AI systems to enhance reliability and reduce hallucination effects.
Pedagogical
Concerns about academic integrity and the impact of AI on traditional assessment methods.
Proposed Solutions: Re-evaluating assessment strategies to incorporate AI tools while maintaining integrity.
Project Team
Han Kyul Kim
Researcher
Shriniwas Nayak
Researcher
Aleyeh Roknaldin
Researcher
Xiaoci Zhang
Researcher
Marlon Twyman
Researcher
Stephen Lu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Han Kyul Kim, Shriniwas Nayak, Aleyeh Roknaldin, Xiaoci Zhang, Marlon Twyman, Stephen Lu
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