Developing generative AI chatbots conceptual framework for higher education
Project Overview
The document examines the integration of generative AI chatbots in higher education, focusing on their ability to boost student engagement, offer personalized support, and aid in academic tasks. It presents the Generative AI Chatbots Acceptance Model (GAICAM), which combines various theoretical frameworks to tackle the challenges and barriers to implementing AI chatbots in educational environments. The study underscores the importance of a holistic strategy to promote the acceptance and effective utilization of these technologies within higher education institutions. Through this lens, the findings suggest that while generative AI has the potential to transform educational experiences, a structured approach is necessary to ensure these tools are embraced and utilized effectively by both students and educators. Overall, the document highlights the promising applications of generative AI in education while calling for careful consideration of the factors influencing its successful adoption.
Key Applications
Generative AI chatbots (e.g., ChatGPT, Google Bard)
Context: Higher education institutions (HEIs), targeting both lecturers and students
Implementation: Utilized for personalized academic assistance, research tasks, and administrative support.
Outcomes: Improved student engagement, streamlined educational processes, and enhanced access to academic resources.
Challenges: Negative student attitudes towards chatbots, concerns about academic integrity, and doubts about AI-generated content accuracy.
Implementation Barriers
Technological
Concerns about the reliability and security of generative AI chatbots.
Proposed Solutions: Implementing transparency measures, providing evidence of educational benefits, addressing biases.
Social
Negative attitudes from students regarding the use of AI chatbots for learning.
Proposed Solutions: Encouraging positive perceptions through training and demonstrating the value of AI chatbots.
Ethical
Risks of cheating and plagiarism due to the use of AI-generated content.
Proposed Solutions: Developing clear academic integrity policies, employing advanced plagiarism detection tools.
Project Team
Joshua Ebere Chukwuere
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Joshua Ebere Chukwuere
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