<![CDATA[This study aims to analyze ChatGPT usage behavior in the context of learning using B.F. Skinner's operant conditioning theory and information systems theory on technology adoption. The main focus is to understand how AI literacy affects users' perceptions of ChatGPT responses and their intention to use it, as well as how the quality of ChatGPT responses plays a role in shaping learning behavior when using AI applications as tools. The type of research used is quantitative. Data processing uses Partial Least Square (PLS)-based Structural Equation Modeling (SEM), and data is collected through online questionnaires. This study involved 82 student respondents and was analyzed using SmartPLS through three stages: (1) testing the validity and reliability of the instruments, (2) testing the relationship between variables in the structural model, and (3) testing multiple groups (MGA) to compare respondent groups based on the frequency of ChatGPT use per day. The analysis results show that the AI Literacy variable has a significant effect on ChatGPT Response Perception, as does ChatGPT Response Perception on ChatGPT Usage Intention, while the effect of AI Literacy on ChatGPT Usage Intention shows a positive but weak result. When an in-depth analysis was conducted, it was found that the results of grouping respondents based on the frequency of ChatGPT usage showed that low users (1-2 times a day) had negative values, while the medium (3-5) and high (above 5) frequency groups had positive results. The findings of this study indicate that based on operant conditioning theory and technology adoption, the role of AI literacy and the reinforcement of response perception in achieving the intention to use technology in the learning process is very important.]]>
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