Evaluating AI-Powered Learning Assistants in Engineering Higher Education: Student Engagement, Ethical Challenges, and Policy Implications
Project Overview
The document explores the integration of generative AI tools in higher education, specifically through the lens of the Educational AI Hub utilized in civil and environmental engineering courses. It outlines the advantages of AI, including personalized learning experiences and enhanced student engagement. However, it also raises important ethical considerations, such as trust issues and the necessity for well-defined institutional policies to ensure the responsible implementation of AI technologies. Key findings indicate that while students value the convenience and targeted assistance provided by AI, they harbor concerns regarding academic integrity and the potential disparity in quality between AI-generated support and traditional human assistance. Overall, the document underscores the dual nature of generative AI in education, highlighting both its transformative potential and the critical need for guidelines to address the challenges it presents.
Key Applications
AI Educational Assistance Hub
Context: Used in undergraduate civil and environmental engineering courses at a large R1 public university and vocational training for certification readiness, providing students with AI support for homework, understanding course concepts, and preparation for certifications.
Implementation: A mixed-methods approach using AI technologies for educational support, including adaptive quizzes, flashcards, and an AI chatbot for interactive assistance. The implementation involves pre- and post-surveys, system usage logs, and qualitative analysis of student interactions.
Outcomes: Students reported convenience and helpfulness of the AI tools for homework and understanding concepts, with high accuracy in preparing students for certifications. However, perceptions of instructional quality varied, and ethical concerns regarding academic misconduct were noted.
Challenges: Ethical concerns about academic misconduct and uncertainty about institutional policies limited full engagement with the AI tools.
Implementation Barriers
Ethical Concern
Students expressed concerns about being accused of academic misconduct when using AI tools.
Proposed Solutions: Clear institutional policies and guidelines about AI usage in education.
Trust Issues
Some students were unsure about the reliability of AI-generated responses.
Proposed Solutions: Building trust through transparency and faculty guidance.
Usability Concerns
Perceptions about the inferior instructional quality of AI compared to human assistance.
Proposed Solutions: Enhancing the quality of AI-generated assistance and providing better training for students.
Project Team
Ramteja Sajja
Researcher
Yusuf Sermet
Researcher
Brian Fodale
Researcher
Ibrahim Demir
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ramteja Sajja, Yusuf Sermet, Brian Fodale, Ibrahim Demir
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