Analysis of the User Perception of Chatbots in Education Using A Partial Least Squares Structural Equation Modeling Approach
Project Overview
The document examines the integration of generative AI, particularly chatbots powered by Large Language Models (LLMs) such as ChatGPT and Google Bard, into the educational landscape. It emphasizes the necessity of understanding students' perceptions and acceptance of these AI technologies, identifying key factors that influence their adoption, including optimism, innovativeness, and user engagement, while also noting discomfort and insecurity as significant barriers. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM), the study explores the relationship between these factors and the intention to use chatbots in educational settings. The findings suggest that fostering a positive perception of generative AI can enhance user engagement and facilitate its acceptance in education, ultimately leading to improved learning experiences. The document concludes that effectively addressing barriers and leveraging the positive influences can promote the successful implementation of AI chatbots in educational environments, thereby transforming traditional learning methodologies and enhancing student interaction with educational content.
Key Applications
Chatbots for educational purposes
Context: Higher education, targeting graduate-level students and those considering graduate studies.
Implementation: Data was collected through a survey distributed to students, utilizing a five-point Likert scale for responses and analyzed using PLS-SEM.
Outcomes: Optimism and innovativeness positively influence perceived ease of use (PEOU) and perceived usefulness (PU) of chatbots. Interaction and engagement, accuracy, and responsiveness significantly affect the intention to use chatbots.
Challenges: Discomfort and insecurity negatively impact PEOU and PU, making it harder for users to adopt chatbots.
Implementation Barriers
Behavioral Barrier
Discomfort and insecurity among users regarding the adoption of chatbots.
Proposed Solutions: Developers should address user concerns and improve engagement strategies to mitigate discomfort and insecurity.
Project Team
Md Rabiul Hasan
Researcher
Nahian Ismail Chowdhury
Researcher
Md Hadisur Rahman
Researcher
Md Asif Bin Syed
Researcher
JuHyeong Ryu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Md Rabiul Hasan, Nahian Ismail Chowdhury, Md Hadisur Rahman, Md Asif Bin Syed, JuHyeong Ryu
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