Platform-Independent and Curriculum-Oriented Intelligent Assistant for Higher Education
Project Overview
The document presents an overview of an AI-augmented intelligent educational assistance framework utilizing GPT-3, specifically designed to bridge communication gaps between students and instructors in higher education. It emphasizes the role of chatbots as virtual teaching assistants, which facilitate immediate access to course-related information, enhance student engagement, and alleviate the workload for teaching staff. By enabling the development of course-specific intelligent assistants capable of addressing queries related to course logistics, the framework aims to significantly improve the learning experience for students. The findings suggest that the integration of generative AI in educational settings can lead to more efficient communication, foster a supportive learning environment, and ultimately contribute to better educational outcomes.
Key Applications
AI-augmented intelligent educational assistance framework using GPT-3
Context: Higher education, targeting undergraduate and graduate students
Implementation: Developed a framework that generates course-specific assistants based on syllabi; integrated into various platforms including web and messaging applications.
Outcomes: Improved access to information for students, reduced workload for instructors, enhanced learning experience, increased student engagement.
Challenges: Initial setup requires accurate syllabus input; potential for miscommunication if the knowledge base is not up-to-date.
Implementation Barriers
Communication barrier
Miscommunication and challenges in communication between students and instructors can hinder learning. Students often face insecurities that prevent them from seeking help during office hours.
Proposed Solutions: Implementing AI-powered chatbots to provide immediate assistance and support for students, and creating a virtual assistant that is available at all times to reduce reliance on traditional office hour interactions.
Project Team
Ramteja Sajja
Researcher
Yusuf Sermet
Researcher
David Cwiertny
Researcher
Ibrahim Demir
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ramteja Sajja, Yusuf Sermet, David Cwiertny, 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