ChatISA: A Prompt-Engineered, In-House Multi-Modal Generative AI Chatbot for Information Systems Education
Project Overview
The document explores the creation and application of ChatISA, a multi-modal generative AI chatbot tailored for Information Systems and Analytics education, reflecting the increasing necessity for educators to equip students for AI-enhanced professional settings. ChatISA comprises four distinct modules—Coding Companion, Project Coach, Exam Ally, and Interview Mentor—each designed to improve specific aspects of the educational experience. The implementation of generative AI in education is shown to yield significant benefits, including enhanced task performance and greater student engagement. However, the document also raises important concerns regarding the ethical use of AI, the preservation of academic integrity, and the challenges posed by unequal access to technology. Overall, the use of generative AI like ChatISA represents a transformative approach to education, offering innovative solutions while necessitating careful consideration of its implications.
Key Applications
AI Learning Assistant
Context: Various educational contexts including undergraduate Information Systems and Analytics courses, focusing on coding inquiries, project management, exam preparation, and job interview readiness.
Implementation: Developed using design science research methodology and interactive AI technologies, these tools provide personalized assistance tailored to students' academic needs and tasks. They utilize a combination of AI chatbot frameworks and content generation algorithms to support students in coding, project management, exam preparation, and interview practices.
Outcomes: ['Enhanced student learning experiences and engagement.', 'Fosters personalized learning and improves coding skills.', 'Supports structured learning and project management capabilities.', 'Facilitates continuous self-assessment and understanding of course material.', 'Prepares students for job interviews with realistic scenarios.']
Challenges: ['Concerns over academic integrity and over-reliance on AI for task completion.', 'Ensuring student engagement without diminishing critical thinking.', 'Quality of generated content dependent on the accuracy of input materials.', 'Risk of students becoming overly reliant on AI-generated questions during interview preparations.']
Implementation Barriers
Ethical
Concerns about academic integrity and potential misuse of AI tools for dishonest assignments.
Proposed Solutions: Establish clear ethical guidelines, emphasize the role of AI as a supplementary tool, and promote academic honesty.
Access
Disparities in access to advanced AI technologies can hinder learning opportunities, particularly for underprivileged groups.
Proposed Solutions: Develop in-house generative AI solutions that are cost-effective and accessible to all students.
Technical
Challenges related to the integration of AI tools into existing curricula and pedagogical practices.
Proposed Solutions: Encourage faculty to adapt teaching strategies to incorporate AI tools systematically.
Project Team
Fadel M. Megahed
Researcher
Ying-Ju Chen
Researcher
Joshua A. Ferris
Researcher
Cameron Resatar
Researcher
Kaitlyn Ross
Researcher
Younghwa Lee
Researcher
L. Allison Jones-Farmer
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Fadel M. Megahed, Ying-Ju Chen, Joshua A. Ferris, Cameron Resatar, Kaitlyn Ross, Younghwa Lee, L. Allison Jones-Farmer
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