The integration of Artificial Intelligence (AI) into education is a recent development, with chatbots emerging as a noteworthy addition to this transformative landscape. As online learning platforms rapidly advance, students need to adapt swiftly to excel in this dynamic environment. Consequently, understanding the acceptance of chatbots, particularly those employing Large Language Model (LLM) such as Chat Generative Pretrained Transformer (ChatGPT), Google Bard, and other interactive AI technologies, is of paramount importance. However, existing research on chatbots in education has overlooked key behavior-related aspects, such as Optimism, Innovativeness, Discomfort, Insecurity, Transparency, Ethics, Interaction, Engagement, and Accuracy, creating a significant literature gap. To address this gap, this study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the determinant of chatbots adoption in education among students, considering the Technology Readiness Index (TRI) and Technology Acceptance Model (TAM). Utilizing a five-point Likert scale for data collection, we gathered a total of 185 responses, which were analyzed using R-Studio software. We established 12 hypotheses to achieve its objectives. The results showed that Optimism and Innovativeness are positively associated with Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). Conversely, Discomfort and Insecurity negatively impact PEOU, with only Insecurity negatively affecting PU. These findings provide insights for future technology designers, elucidating critical user behavior factors influencing chatbots adoption and utilization in educational contexts.

翻译：人工智能（AI）融入教育是近年来的发展成果，其中聊天机器人成为这一变革性格局中值得关注的补充。随着在线学习平台的快速发展，学生需要快速适应以在动态环境中脱颖而出。因此，理解聊天机器人（特别是采用大语言模型（LLM）的Chat Generative Pretrained Transformer、Google Bard及其他交互式AI技术）的接受度至关重要。然而，现有关于教育领域聊天机器人的研究忽略了关键的行为相关方面，如乐观、创新性、不适感、不安全感、透明度、伦理、交互性、参与度及准确性，形成了显著的研究空白。为填补这一空白，本研究采用偏最小二乘结构方程模型（PLS-SEM），结合技术准备指数（TRI）与技术接受模型（TAM），探究学生教育中采用聊天机器人的决定因素。通过五级李克特量表收集数据，共获得185份有效回复，并使用R-Studio软件进行分析。为实现研究目标，我们提出了12项假设。结果表明，乐观和创新性与感知易用性（PEOU）及感知有用性（PU）呈正相关；反之，不适感和不安全感对PEOU产生负面影响，其中仅不安全感对PU产生负面效应。这些发现为未来技术设计者提供了洞见，阐明了影响教育情境下聊天机器人采用与利用的关键用户行为因素。